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Objective: The study aims to explore Resveratrol (RES) as a potential therapeutic agent for Glioblastoma multiforme (GBM), a challenging brain cancer. RES, a polyphenolic compound with known benefits in various diseases including cancer, has shown promise in inhibiting glioma progression through its effects on the AKT signaling pathways. However, its limited ability to cross the blood-brain barrier restricts its clinical application in GBM treatment. This study seeks to enhance efficacy of RES by developing RES-loaded nanoparticles designed to improve penetration into glioma cells and potentially overcome the blood-brain barrier, thereby enhancing therapeutic outcomes., Methods: Albumin nanoparticles were prepared and characterized using FT-IR, X-RD, and SEM to determine particle size. In vitro experiments were conducted using the C6 glioma cell line, employing MTT assays, Immunofluorescence, DC-FDA staining, and western blot analysis. Molecular docking studies were also performed to assess ability of RES to inhibit the AKT/GSK-3β/NF-kB pathway., Results: In vitro results demonstrated that RES-loaded nanoparticles induced apoptosis and reduced proliferation of C6 glioma cells compared to controls. Molecular docking studies confirmed RES's potential as an inhibitor targeting the AKT/GSK-3β/NF-kB pathway. Western blot analysis revealed downregulation of AKT and GSK-3β expression in cells treated with RES-loaded nanoparticles, accompanied by increased caspase 1 levels and decreased bcl2 expression, indicative of apoptosis., Conclusion: The findings suggest that RES effectively targets the AKT/GSK-3β/NF-kB signaling pathway in glioma cells. Furthermore, RES-loaded albumin nanoparticles significantly enhance therapeutic efficacy by improving cellular penetration, highlighting their potential in advancing GBM treatment strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Background: While protein-protein docking is fundamental to our understanding of how proteins interact, scoring protein-protein complex conformations is a critical component of successful docking programs. Without accurate and efficient scoring functions to differentiate between native and non-native binding complexes, the accuracy of current docking tools cannot be guaranteed. Although many innovative scoring functions have been proposed, a good scoring function for docking remains elusive. Deep learning models offer alternatives to using explicit empirical or mathematical functions for scoring protein-protein complexes., Results: In this study, we perform a comprehensive survey of the state-of-the-art scoring functions by considering the most popular and highly performant approaches, both classical and deep learning-based, for scoring protein-protein complexes. The methods were also compared based on their runtime as it directly impacts their use in large-scale docking applications., Conclusions: We evaluate the strengths and weaknesses of classical and deep learning-based approaches across seven public and popular datasets to aid researchers in understanding the progress made in this field., Competing Interests: Declarations. Ethics approval and consent to participate: The authors agreed on roles and responsibilities prior to the research, and all capacity-building plans were thoroughly discussed. All data utilized in this research were derived from publicly available sources or generated through computational methods, ensuring compliance with ethical standards in scientific research. Competing interests: The authors declare that they have no Conflict of interest., (© 2025. The Author(s).)

Glaucoma, a prevalent eye ailment causing irreversible vision loss, affects over 295 million individuals globally, necessitating the exploration of novel therapeutic avenues. Despite extensive research on targets like the phosphodiesterase enzyme and rho kinase, the potential of MAP4K4 in glaucoma remains untapped. This study aims to identify potent MAP4K4 inhibitors to counteract retinal cell apoptosis and oxidative stress associated with glaucoma. Using HTVS and XP docking, 911,059 compounds were screened. The MMGBSA calculation and pharmacokinetics analysis were used to shortlist the compounds. After performing 75 molecular dynamics simulations, further meta-dynamics were employed to calculate dissociation-free energy and find potential MAP4K4 inhibitors. Findings indicated that ZINC06717217 and ZINC38836256 exhibited remarkable promise, with docking scores of -9.57 and -11.12 and MMGBSA binding energies of -91.07 kcal/mol and -87.52 kcal/mol, respectively. Comparative analysis with the reference compound Q27453723 underscored their superior stability, requiring dissociation-free energies of -15.11 kcal/mol and -12.46 kcal/mol to disengage from the docked complex. This underscored their robust binding affinity. ZINC06717217 and ZINC38836256 show promising stability and strong binding to the MAP4K4 protein. Hence, these findings are promising in inhibiting MAP4K4 for glaucoma treatment, potentially leading to more effective treatment and curing blindness. KEY MESSAGES: First to incorporate the dissociation-free energy for identifying compounds for glaucoma treatment. In-silico analysis showed that ZINC06717217 and ZINC38836256 are promising compounds for targeting MAP4K4., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The available literature indicates that amino acids can stabilize proteins. Our experimental data demonstrated that lysine and glutamic acid can stabilize recombinant human erythropoietin (rhEPO) at 40°C for at least 1 month, as measured by RP-UPLC. Studies with different excipient concentrations demonstrated optimal concentrations of these amino acids within 10-12 mM. The results suggest that a lower concentration of amino acids may not be sufficient to stabilize formulations, while a higher concentration of amino acids can lead lower stability. In silico studies highlighted the importance of the FA4G4S4 model in experimental glycosylation determination, particularly in glycoprotein analysis. We obtained insights into the interactions between the glycosylated ligands of rhEPO and amino acids, as well as their impact on protein behavior and stability. We observed different interactions between the amino acids glycine, glutamic acid, and lysine and the rhEPO protein using this model in docking experiments. They also made it easier to find specific interaction areas by analyzing ligand‒protein interaction fingerprints (PLIFs). This demonstrated how the ligands bind to the proteins or remain outside their vicinity. Furthermore, this study revealed specific places where ligands and rhEPO residues can interact, which helps us learn more about how they stabilize rhEPO., Competing Interests: Declarations. Competing interests: Víctor Pérez Medina Martínez, Carlos E. Espinosa-de la Garza, and Néstor O. Pérez are employees of Probiomed S.A. de C.V., who develop, manufacture and market biologics. The other authors declare that they have no competing interests., (© 2024. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Background: Alzheimer's disease is a neurodegenerative disorder that affects learning, memory and behavioral turbulence in elderly patients. Acetylcholinesterase (AChE) inhibitors act as anti-Alzheimer's agents. Phenothiazine derivatives are considered momentous anti-Alzheimer's agents because of their AChE inhibitory activity. The elevated levels and increased expression of this protein have been associated with Alzheimer's disease. Coumarin-fused phenothiazines have emerged as significant anti-Alzheimer's agents due to their notable receptor inhibitory activity., Objective: Some unique phenothiazine analogs were designed, and computational studies were conducted to explore their inhibitory activity against the AChE enzyme (PDB id: 4EY7) by using the Schrodinger suite-2019-4., Methods: Docking studies were conducted by using the Glide module; binding free energies were calculated by means of the Prime MM-GBSA module, and Molecular dynamics (MD) simulation was performed by using the Desmond module of the Schrodinger suite. Glide scores were used to find out the binding affinity of the ligands with the target 4EY7., Results: The compounds exhibited enhanced hydrophobic interactions and formed hydrogen bonds, effectively impeding Acetylcholinesterase. The Glide scores for the compounds ranged from -13.4237 to -8.43439, surpassing the standard (Donepezil) with a score of -16.9898. Interestingly, a positive value was obtained for the MM-GBSA binding of the potent inhibitor. To gain insights into the dynamic behavior of the protein A8, molecular dynamics (MD) simulations were employed., Conclusion: Based on the results, the study concludes that phenothiazine derivatives show promise as acetylcholinesterase inhibitors. Compounds with notable Glide scores are poised to exhibit significant anti-Alzheimer's activity, suggesting their potential therapeutic efficacy. Further in vitro and in vivo investigations are warranted to validate and explore the therapeutic potentials of these compounds., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Aim: The purpose of the current study was to explore the virtual library for the screening against Monoamine oxidase (MAO) isoforms. An in-house library of natural based ligands was docked within the active sites of MAO isoforms and their in vitro study was also conducted., Objective: The prime objective of the current study was to screen and validate the natural-based derivatives for MAO inhibitory action with the least adverse effects and get molecular aspects about further structural modifications on the most active leads., Background: The importance of MAOs in controlling the activity of the central nervous system has been extensively studied. Our goal in this work is to identify a prospective natural lead molecule that has a stronger affinity for the MAO enzyme in order to produce a more effective natural candidate for a neurological agent., Methods and Results: In order to get insight into how different categories of natural compounds interact with the targeted protein, we virtually screened the numerous natural compound categories in the current study. Rhamnetin, quercetin, piperine, eugenol, and umbelliferone showed the highest dock scores in the case of MAO-B, with scores of -10.57, -9.938, -9.445, and 7.821, respectively. For MAO-A, umbelliferone, curcumin, caffeic acid, and quercetin, the corresponding dock scores were -8.001, -7.941, -7.357, and -6.658. Additionally, an in vitro MAO inhibitory experiment was utilized to assess the top-ranked compounds with the best docking scores. The most potent Human Monoamine oxidase (hMAO-A) inhibitor, with an IC 50 of 10.98±0.006 M and a selectivity index (SI) of 0.607, was discovered to be the compound umbelliferone. Rhamnetin, the lead chemical, has demonstrated hMAO-B activity with a value of 10.32±0.044 M (SI value of 3.096)., Conclusion: These natural potential ligands have been found remarkable to the standard compounds against MAO-A and MAO-B, and they could be used as a lead chemical in the development of novel therapeutic candidates. The in silico screening results and in vitro hMAO inhibitory efficacy exhibited strong correlations., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Glycyrrhetinic acid (GA) possesses various pharmacological effects, including anti-inflammatory, anti-tumor, and anti-viral properties. However, its clinical application is limited by poor solubility and low oral bioavailability. Polymers play a crucial role in pharmaceutical formulations, particularly as matrices in excipients to enhance the solubility, bioavailability, and stability of active pharmaceutical ingredients. The amorphous solid dispersions (ASDs) of GA were prepared with three different polymers (i.e., GA-S-ASD, GA-VA64-ASD, and GA-K30-ASD). The ASDs were characterized by differential scanning calorimetry (DSC), powder X-ray diffractometry (PXRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR spectroscopy), molecular docking, and contact angle measurement. Pharmacokinetics were evaluated in Beagle dogs, and long-term stability was examined. The solubility of GA increased with the rising weight of the polymer, and the optimal drug-to-carrier ratio was 1:5. In all ASDs, GA was amorphous, thus suggesting that a hydrogen bonding must have formed between GA and the polymers. The molecular docking showed that the binding energy was the highest and the hydrogen bonding was the strongest between GA and Soluplus. The dissolution of the ASDs was primarily driven by carrier-controlled dissolution, and there was minor influence from diffusion-limited release in the case of GA-S-ASD. The three ASDs significantly improved the bioavailability of GA. However, only GA-S-ASD passed the accelerated stability test. In the case of GA-VA64-ASD and GA-K30-ASD, due to serious moisture absorption, the originally fluffy ASDs became gels, and recrystallization occurred. Overall, GA-S-ASD presents promising potential for pharmaceutical applications due to its superior solubility, bioavailability, and stability., Competing Interests: Declarations. Ethics Statement: The animal study was reviewed and approved by Animal Ethics Committee of Chengde Medical University. (Approval No. CDMULAC-20190502–019). Conflicts of Interest: The authors declare no conflict of interest., (© 2024. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Unfractionated heparin (UFH) is commonly used as an anticoagulant in sepsis treatment and has recently been found to have non-anticoagulant effects, but underlying mechanisms remain unclear. This retrospective clinical data showed that UFH has significant protective effects in sepsis compared to low-molecular-weight heparin and enoxaparin, indicating potential benefits of its non-anticoagulant properties. Recombinant protein chip screening, surface plasmon resonance, and molecular docking data demonstrated that UFH specifically bound to the cytoplasmic Drp1 protein through its zone 2 non-anticoagulant segment. In-vitro experiments verified that UFH's specific binding to Drp1 suppressed Drp1 translocation to mitochondria following "sepsis" challenge, thereby improving mitochondrial morphology, function and metabolism in vascular endothelial cells. Consequently, UHF comprehensively protected mitochondrial quality, thus reducing vascular leakage and improving prognosis in a sepsis rat model. These findings highlight the potential of UFH as a sepsis treatment strategy targeting non-anticoagulation mechanism., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Background: The current study aimed to evaluate the anti-inflammatory, anti-oxidant, and pronounced gastro-protective activities of β- Citronellol using in vitro, in vivo assays and in silico approaches., Methods: In vitro assays, denaturation of bovine serum albumin, egg protein, and human Red Blood Cells (RBCs) membrane stabilization were performed, using Piroxicam as standard. For in vivo assessment, Histamine (0.1 ml from 1% w/v) and Formaldehyde (0.1 ml from 2% v/v) were used to mediate inflammation. In silico molecular docking and network pharmacology were employed to probe the possible target genes mediating gastroprotective effect of β-Citronellol at 25, 50, and 100 mg/kg, using indomethacin-induced (25 mg/kg i.p) gastric ulcer in rats. Moreover, Gastric tissues were evaluated for morphological, histopathological, and bio-chemical analysis of PGE 2, COX-I, COX-II, 5-LOX, eNOS, ICAM-1, oxygen-free radical scavengers (SOD, CAT), and oxidative stress marker (MDA)., Results: β-Citronellol prevented denaturation of proteins and RBCs membrane stabilization with maximum effect observed at 6,400 µg/mL. Citronellol decreased rat's paw edema. Network pharmacology and docking studies revealed gastro-protective potential of Citronellol possibly mediated through arachidonic acid pathways by targeting COX-I, COX-II, PGE 2 , and 5-LOX. Citronellol reduced the ulcer indices, and histopathological changes. Further, β-Citronellol (50 and 100 mg/kg) increased gastric PGE 2, COX-1, and eNOS; while suppressing COX-2, 5-LOX and ICAM-1. Citronellol markedly enhanced the oxidative balance in isolated rat stomach tissues., Conclusions: The anti-inflammatory, anti-oxidant, and gastro-protective effects of β-Citronellol against indomethacin-induced gastric ulcer model in rats through mediating COX-I, COX-II, PGE 2, 5-LOX, eNOS, and ICAM-1 inflammatory markers., (© 2024. The Author(s).)

Gaultheria trichophylla Royle is a traditional treatment for inflammatory conditions including arthritis. The objective was to evaluate the anti-arthritic activity of the extracts and salicylate-rich fractions through adjuvant-induced arthritis, histopathological analysis, radiological imaging, hematological, biochemical parameters along with using bioinformatic tools. In vivo anti-arthritic efficacy of the extract and SRF (at 100, 200, 300, and 150 mg/kg doses) was assessed using healthy albino rats. Molecular docking of identified compounds along with network pharmacology analysis helped to determine the route of action of drug. Both the extract and SRF showed dose-dependent anti-arthritic activity by decreasing the joint diameter, increase in pain threshold and body weight compared with negative control group. Along with SRF (150 mg/kg), EEGT (300 and 200 mg/kg) shows significant (P < 0.01) anti-arthritic activity by lowering levels of WBC, platelets, serum C-reactive protein (CRP), and rheumatoid factor (RF) and raising levels of RBC and Hb. The modified biochemical measures (AST, ALT, ALP, and total protein level) further supported the anti-arthritic action. Histopathology and radiology study showed that EEGT (300 and 200 mg/kg), SRF (150 mg/kg) and diclofenac (10 mg/kg) inhibited joint destruction. GCMS analysis showed the presence of methyl salicylate, sitosterol, calcifediol, and ergosta-5,22-dien-3-ol, acetate as important bioactive constituents. Moreover, as the significant node in the pharmacology network and docking against TNF-α, a classical therapeutic target in RA showed potential of G. trichophylla in treatment of RA. The results showed that G. trichophylla have effectively reduced the inflammation of the joints., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Parkinson's disease (PD) is the second most common neurodegenerative disease, but treatment options for PD are limited, and drug development has reached a bottleneck. With the progress of the aging population, the number of PD patients in China is increasing day by day, imposing a heavy burden on patients and society. Therefore, it is urgent to explore targeted medicine based on the pathogenesis of PD and disease targets. Ancient physicians have used the traditional Chinese medicine formula SiJunZi decoction (SJZD) to treat PD. However, it is less commonly used clinically now, and its pharmacological mechanism still needs to be further elucidated. In this study, based on network pharmacology research and molecular docking technology, the mechanism of SJZD in treating PD was revealed, showing that the extract of SJZD acts on cell microdomain membranes and lipid rafts, affecting ubiquitin-protein ligase binding and ubiquitin-like protein ligase binding processes, and plays a role in neurogenesis. Molecular docking results showed that Ellipticine and Hederagenin in SJZD exhibited significant effects on targets: CASP3, BCL2, and PTGS2. The effect of SJZD reversing MPP + -induced SH-SY5Y cells injury was verified by experiments, concentrations ranging from 5ug/mL to 0.1ug/mL showed significant cell protection at 24 h., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This study was funding by The Specialized Medical Training Project in Foshan's 14th Five-Year Plan (FSPY145228) and Project of Administration of Traditional Chinese Medicine of Guangdong Province of China (No. 20231135)., (Copyright © 2024. Published by Elsevier B.V.)

Alzheimer's disease (AD) and related dementias are among the primary neurological disorders and call for the urgent need for early-stage diagnosis to gain an upper edge in therapeutic intervention and increase the overall success rate. Choline acetyltransferase (ChAT) is the key acetylcholine (ACh) biosynthesizing enzyme and a legitimate target for the development of biomarkers for early-stage diagnosis and monitoring of therapeutic responses. It is also a theranostic target for tackling colon and lung cancers, where overexpression of non-neuronal ChAT leads to the production of acetylcholine, which acts as an autocrine growth factor for cancer cells. Theranostics is a hybrid of diagnostics and therapeutics that can be used to locate cancer cells using radiotracers and kill them without affecting other healthy tissues. Traditional virtual screening protocols have a lot of limitations; given the current rate of chemical database expansion exceeding billions, much faster screening protocols are required. Deep docking (DD) is one such platform that leverages the power of deep neural network (DNN)-based virtual screening, empowering researchers to dock billions of molecules in a speedy, yet explicit manner. Here, we have screened 1.3 billion compounds library from the ZINC20 database, identifying the best-performing hits. With each iteration run where the first iteration gave ∼116 million hits, the second iteration gave ∼3.7 million hits, and the final third iteration gave 168,447 hits from which further refinement gave us the top 5 compounds as potential ChAT inhibitors. The discovery of novel ChAT inhibitors will enable researchers to develop new probes that can be used as novel theranostic agents against cancer and as early-stage diagnostics for the onset of AD, for timely therapeutic intervention to halt the further progression of AD.

Oxybutynin (Ditropan), a widely distributed muscarinic antagonist for treating the overactive bladder, has been awaiting a definitive crystal structure for ≈50 years due to the sample and technique limitations. Past reports used powder X-ray diffraction (PXRD) to shed light on the possible packing of the molecule however their model showed some inconsistencies when compared with the 2D chemical structure. These are largely attributed to X-ray-induced photoreduction. Here microcrystal electron diffraction (MicroED) is used to successfully unveil the experimental 3D structure of oxybutynin hydrochloride showing marked improvement over the reported PXRD structure. Using the improved model, molecular docking is applied to investigate the binding mechanism between M 3 muscarinic receptor (M 3 R) and (R)-oxybutynin, revealing essential contacts/residues and conformational changes within the protein pocket. A possible universal conformation is proposed for M 3 R antagonists, which is valuable for future drug development and optimization. This study underscores the immense potential of MicroED as a complementary technique for elucidating unknown pharmaceutical structures, as well as for protein-drug interactions., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Generative molecular models generate novel molecules with desired properties by searching chemical space. Traditional combinatorial optimization methods, such as genetic algorithms, have demonstrated superior performance in various molecular optimization tasks. However, these methods do not utilize docking simulation to inform the design process, and heavy dependence on the quality and quantity of available data, as well as require additional structural optimization to become candidate drugs. To address this limitation, we propose a novel model named DockingGA that combines Transformer neural networks and genetic algorithms to generate molecules with better binding affinity for specific targets. In order to generate high quality molecules, we chose the Self-referencing Chemical Structure Strings to represent the molecule and optimize the binding affinity of the molecules to different targets. Compared to other baseline models, DockingGA proves to be the optimal model in all docking results for the top 1, 10 and 100 molecules, while maintaining 100% novelty. Furthermore, the distribution of physicochemical properties demonstrates the ability of DockingGA to generate molecules with favorable and appropriate properties. This innovation creates new opportunities for the application of generative models in practical drug discovery., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Overactive bladder (OAB) is a usual medical syndrome that affects the bladder, and Mirabegron (MBG) is preferred medicine for its control. Currently, available marketed formulations (MYRBETRIQ® granules and MYRBETRIQ® ER tablets) suffer from low bioavailability (29-35%) hampering their therapeutic effectiveness and compromising patient compliance. By creating MBG nanostructured lipid carriers (MBG-NLCs) for improved systemic availability and drug release, specifically in oral administration of OAB treatment, this study aimed to address these issues. MBG-NLCs were fabricated using a hot-melt ultrasonication technique. MBG-GMS; MBG-oleic acid interaction was assessed by in silico molecular docking. QbD relied on the concentration of Span 80 (X1) and homogenizer speed (X2) as critical material attribute (CMA) and critical process parameter (CPP) respectively, while critical quality attributes (CQA) such as particle size (Y1) and cumulative drug release at 24 h (Y2) were estimated as dependent variables. 32 factorial design was utilized to investigate the interconnection in variables that are dependent and independents. Optimized MBG-NLCs with a particle size of 194.4 ± 2.25 nm were suitable for lymphatic uptake. A PDI score of 0.275 ± 0.02 and zeta potential of -36.2 ± 0.721 mV indicated a uniform monodisperse system with stable dispersion properties. MBG-NLCs exhibited entrapment efficiency of 77.3 ± 1.17% and a sustained release in SIF of 94.75 ± 1.60% for 24 h. MBG-NLCs exhibited the Higuchi model with diffusion as a release mechanism. A pharmacokinetic study in Wistar rats exhibited a 1.67-fold higher bioavailability as compared to MBG suspension. Hence, MBG-NLCs hold promise for treating OAB by improving MBG's oral bio absorption., (© 2024. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

This study utilized network pharmacology and docking analyses to explore a groundbreaking therapeutic approach for managing the neuropathic pain and depressive disorder (NP/DD) comorbidity. Schisandra chinensis (SC), a common Chinese medicine, has demonstrated numerous beneficial effects in treating neuropsychological disorders. The main objective of this study was to identify potential bioactive components of SC and investigate their interactions with relevant target genes associated with NP/DD. To gain insights into the underlying molecular mechanisms, GO and KEGG analyses were conducted. Furthermore, molecular docking analysis was employed to validate the therapeutic relevance of SC's active ingredients. Seven bioactive components of SC, namely Longikaurin A, Deoxyharringtonine, Angeloylgomisin O, Schisandrin B, Gomisin A, Gomisin G, and Gomisin R, exhibited effectiveness in the treatment of NP/DD. From this list, the first five components were selected for further analysis. The analyses revealed a complex network of interactions between the targets of SC and NP/DD, providing valuable information about the molecular mechanisms involved in the treatment of NP/DD with SC. SC components demonstrated the ability to regulate pathways involving tumor necrosis factor (TNF), vascular endothelial growth factor (VEGF), and other growth hormones (GH). Overall, this study contributes to our understanding of the molecular mechanisms underlying the effects of SC in treating NP/DD. Further investigation is necessary to explore the therapeutic potential of SC as a viable strategy for NP/DD comorbidity. These findings lay a solid foundation for future research endeavors in this field, holding potential implications for the development of novel therapeutic interventions targeting NP/DD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 IBRO. Published by Elsevier Inc. All rights reserved.)

We here introduce Ensemble Optimizer (EnOpt), a machine-learning tool to improve the accuracy and interpretability of ensemble virtual screening (VS). Ensemble VS is an established method for predicting protein/small-molecule (ligand) binding. Unlike traditional VS, which focuses on a single protein conformation, ensemble VS better accounts for protein flexibility by predicting binding to multiple protein conformations. Each compound is thus associated with a spectrum of scores (one score per protein conformation) rather than a single score. To effectively rank and prioritize the molecules for further evaluation (including experimental testing), researchers must select which protein conformations to consider and how best to map each compound's spectrum of scores to a single value, decisions that are system-specific. EnOpt uses machine learning to address these challenges. We perform benchmark VS to show that for many systems, EnOpt ranking distinguishes active compounds from inactive or decoy molecules more effectively than traditional ensemble VS methods. To encourage broad adoption, we release EnOpt free of charge under the terms of the MIT license., (© 2024. The Author(s).)

Objectives: Neurological disorders represent a significant global health challenge, necessitating the exploration of novel therapeutic agents. Apigenin, a natural flavonoid abundantly found in various plants, has garnered attention for its potential neuroprotective properties. In this study, we employed molecular docking simulations to investigate the interaction between apigenin and key molecular targets associated with neurological disorders., Methods: The molecular docking analysis focused on receptors implicated in neuroinflammation, oxidative stress, and neurotransmission regulation., Results: Our results reveal a high binding affinity of apigenin towards critical targets, including GABA, mACh, nACh, NMDA, 5HTA, AMPA, insulin, and dopamine receptors. The findings suggest that apigenin may exert its neuroprotective effects through multifaceted mechanisms, including anti-inflammatory, antioxidant, and neurotransmission regulatory pathways. Additionally, the absence of adverse binding poses emphasizes the safety profile of apigenin., Conclusions: This molecular docking study provides valuable insights into the potential therapeutic role of apigenin in mitigating molecular pathways implicated in neurological disorders. Further in vitro and in vivo investigations are warranted to validate and elucidate the neuroprotective mechanisms of apigenin, paving the way for its development as a promising treatment option for various neurological conditions., Competing Interests: Conflicts of Interest and Source of Funding: The authors have no conflicts of interest to declare., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Introduction: Methicillin-resistant Staphylococcus aureus (MRSA)-caused infections greatly threaten public health. The discovery of natural-product-based anti-MRSA agents for treating infectious diseases has become one of the current research focuses., Objectives: This study aims to identify promising anti-MRSA agents with a clear mechanism based on natural norharmane modified by quaternization or dimerization., Methods: A total of 32 norharmane analogues were prepared and characterized. Their antibacterial activities and resistance development propensity were tested by the broth double-dilution method. Cell counting kit-8 and hemolysis experiments were used to assess their biosafety. The plasma stability, bactericidal mode, and biofilm disruption effects were examined by colony counting and crystal violet staining assays. Fluorescence microscopy, metabolomic analysis, docking simulation and spectra titration revealed its anti-MRSA mechanisms. The mouse skin infection model was used to investigate the in vivo efficacy., Results: Compound 5a was selected as a potential anti-MRSA agent, which exhibited potent anti-MRSA activity in vitro and in vivo, low cytotoxicity and hemolysis under an effective dose. Moreover, compound 5a showed good stability in 50% plasma, a low tendency of resistance development and capabilities to disrupt bacterial biofilms. The mechanism studies revealed that compound 5a could inhibit the biosynthesis of bacteria cell walls, damage the membrane, disturb energy metabolism and amino acid metabolism pathways, and interfere with protein synthesis and nucleic acid function., Conclusions: These results suggested that compound 5a is a promising candidate for combating MRSA infections, providing valuable information for further exploiting a new generation of therapeutic antibiotics., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Production and hosting by Elsevier B.V.)

Background: Delirium and Alzheimer's disease (AD) are common causes of cognitive dysfunction among older adults. These neurodegenerative diseases share a common and complex relationship, and can occur individually or concurrently, increasing the chance of permanent mental dysfunction. However, the common molecular pathophysiology, key proteomic biomarkers, and functional pathways are largely unknown, whereby delirium is superimposed on AD and dementia., Methods: We employed an integrated bioinformatics and system biology analysis approach to decipher such common key proteomic signatures, pathophysiological links between delirium and AD by analyzing the gene expression data of AD-affected human brain samples and comparing them with delirium-associated proteins. The present study identified the common drug target hub-proteins examining the protein-protein interaction (PPI) and gene regulatory network analysis. The functional enrichment and pathway analysis was conducted to reveal the common pathophysiological relationship. Finally, the molecular docking and dynamic simulation was used to computationally identify and validate the potential drug target and repurposable drugs for delirium and AD., Results: We detected 99 shared differentially expressed genes (sDEGs) associated with AD and delirium. The sDEGs-set enrichment analysis detected the transmission across chemical synapses, neurodegeneration pathways, neuroinflammation and glutamatergic signaling pathway, oxidative stress, and BDNF signaling pathway as the most significant signaling pathways shared by delirium and AD. The disease-sDEGs interaction analysis highlighted the other disease risk factors with delirium and AD development and progression. Among the sDEGs of delirium and AD, the top 10 hub-proteins including ALB, APP, BDNF, CREB1, DLG4, GAD1, GAD2, GFAP, GRIN2B and GRIN2A were found by the PPI network analysis. Based on the maximum molecular docking binding affinities and molecular dynamic simulation (100 ns) results, the ALB and GAD2 were found as prominent drug target proteins when tacrine and donepezil were identified as potential drug candidates for delirium and AD., Conclusion: The study outlined the common key biomolecules and biological pathways shared by delirium and AD. The computationally reported potential drug molecules need a deeper investigation including clinical trials to validate their effectiveness. The outcomes from this study will help to understand the typical pathophysiological relationship between delirium and AD and flag future therapeutic development research for delirium., (© 2024. The Author(s).)

The misfolding and aggregation of beta-amyloid (Aβ) peptides have been implicated as key pathogenic events in the early stages of Alzheimer's disease (AD). Inhibiting Aβ aggregation represents a potential disease-modifying therapeutic approach to AD treatment. Previous studies have identified various molecules that inhibit Aβ aggregation, some of which share common chemical substructures (fragments) that may be key to their inhibitory activity. Employing fragment-based drug discovery (FBDD) methods may facilitate the identification of these fragments, which can subsequently be used to screen new inhibitors and provide leads for further drug development. In this study, we used an in silico FBDD approach to identify 17 fragment clusters that are significantly enriched among Aβ aggregation inhibitors. These fragments were then used to screen anti-infective agents, a promising drug class for repurposing against amyloid aggregation. This screening process identified 16 anti-infective drugs, 5 of which were chosen for further investigation. Among the 5 candidates, anidulafungin, an antifungal compound, showed high efficacy in inhibiting Aβ aggregation in vitro. Kinetic analysis revealed that anidulafungin selectively blocks the primary nucleation step of Aβ aggregation, substantially delaying Aβ fibril formation. Cell viability assays demonstrated that anidulafungin can reduce the toxicity of oligomeric Aβ on BV2 microglia cells. Molecular docking simulations predicted that anidulafungin interacted with various Aβ species, including monomers, oligomers, and fibrils, potentially explaining its activity against Aβ aggregation and toxicity. This study suggests that anidulafungin is a potential drug to be repurposed for AD, and FBDD is a promising approach for discovering drugs to combat Aβ aggregation.

Alzheimer's disease is characterized by a progressive deterioration of cognitive function and memory loss, and it is closely associated with the dysregulation of cholinergic neurotransmission. Since acetylcholinesterase (AChE) is a critical enzyme in the nervous system, responsible for breaking down the neurotransmitter acetylcholine, its inhibition holds a significant interest in the treatment of various neurological disorders. Therefore, it is crucial to develop efficient AChE inhibitors capable of increasing acetylcholine levels, ultimately leading to improved cholinergic neurotransmission. The results reported here represent a step forward in the development of novel thiazoloindazole-based compounds that have the potential to serve as effective AChE inhibitors. Molecular docking studies revealed that certain of the evaluated nitroindazole-based compounds outperformed donepezil, a well-known AChE inhibitor used in Alzheimer's disease treatment. Sustained by these findings, two series of compounds were synthesized. One series included a triazole moiety ( Tl45a-c ), while the other incorporated a carbazole moiety ( Tl58a-c ). These compounds were isolated in yields ranging from 66 to 87% through nucleophilic substitution and Cu(I)-catalyzed azide-alkyne 1,3-dipolar cycloaddition (CuAAC) reactions. Among the synthesized compounds, the thiazoloindazole-based 6b core derivatives emerged as selective AChE inhibitors, exhibiting remarkable IC 50 values of less than 1.0 μM. Notably, derivative Tl45b displays superior performance as an AChE inhibitor, boasting the lowest IC 50 (0.071 ± 0.014 μM). Structure-activity relationship (SAR) analysis indicated that derivatives containing the bis(trifluoromethyl)phenyl-triazolyl group demonstrated the most promising activity against AChE, when compared to more rigid substituents such as carbazolyl moiety. The combination of molecular docking and experimental synthesis provides a suitable and promising strategy for the development of new efficient thiazoloindazole-based AChE inhibitors.

Background: Lianhuaqingwen (LHQW) has been used in the treatment of chronic bronchitis, but the precise mechanism through which LHQW exhibits its anti-inflammatory effects in this context is not yet fully understood. The aim of this study was to investigate the active ingredients and signaling pathways responsible for LHQW's effectiveness in managing chronic bronchitis., Methods: The research leveraged the TCMSP database to determine the active compounds and drug targets of LHQW. In parallel, the GeneCards, DrugBank, and PharmGkb databases were used to uncover targets pertinent to chronic bronchitis. To discern the potential mechanisms by which LHQW's active ingredients might treat chronic bronchitis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. Network pharmacology facilitated the construction of a drug-active ingredient-disease target network, aiding in forecasting the core targets for chronic bronchitis treatment by LHQW. Subsequently, molecular docking techniques alongside in vitro experiments were applied to confirm the interactions between the active ingredients and the primary targets., Results: A total of 157 active ingredients, 225 potential drug targets, and 594 bronchitis-related targets were derived from various databases. Following this, 76 potential gene targets were pinpointed by integrating drug and related targets. GO and KEGG enrichment analyses were employed to identify key pathways involved in LHQW's mechanism for treating chronic bronchitis. By constructing a protein-protein interaction (PPI) network for the 76 potential gene targets, four core targets (TNF, IL6, IFNG, and STAT3) were identified as primarily involved in responses to lipopolysaccharide, the TNF pathway, and the JAK-STAT pathway. Molecular docking results revealed a favorable affinity between multiple active ingredients of LHQW and the four core targets, suggesting that the therapeutic effects are mediated through the inhibition of inflammatory responses and signaling pathways. Interestingly, quercetin, an active ingredient of LHQW, was observed to bind to all four core targets simultaneously. Furthermore, cell experiment and western blot analysis indicated that both LHQW and quercetin exhibit anti-inflammatory effects by targeting the four core proteins and the JAK-STAT pathways., Conclusion: This research emphasizes the diverse active ingredients, targets, channels, and pathways of LHQW in the treatment of chronic bronchitis, providing important perspectives for the creation of novel therapeutic drugs and clinical uses., (© 2024. The Author(s).)

Recent studies have sparked renewed interest in the therapeutic potential of psychedelics for treating depression and other mental health conditions. Simultaneously, the novel psychoactive substances (NPS) phenomenon, with a huge number of NPS emerging constantly, has changed remarkably the illicit drug market, being their scientific evaluation an urgent need. Thus, this study aims to elucidate the impact of amino-terminal modifications to the 5-MeO-DMT molecule on its interactions with serotonin receptors and transporters, as well as its psychoactive and thermoregulatory properties. Our findings demonstrated, using radioligand binding methodologies, that all examined 5-MeO-tryptamines exhibited selectivity for 5-HT1AR over 5-HT2AR. In fact, computational docking analyses predicted a better interaction in the 5-HT1AR binding pocket compared to 5-HT2AR. Our investigation also proved the interaction of these compounds with SERT, revealing that the molecular size of the amino group significantly influenced their affinity. Subsequent experiments involving serotonin uptake, electrophysiology, and superfusion release assays confirmed 5-MeO-pyr-T as the most potent partial 5-HT releaser tested. All tested tryptamines elicited, to some degree, the head twitch response (HTR) in mice, indicative of a potential hallucinogenic effect and mainly mediated by 5-HT2AR activation. However, 5-HT1AR was also shown to be implicated in the hallucinogenic effect, and its activation attenuated the HTR. In fact, tryptamines that produced a higher hypothermic response, mediated by 5-HT1AR, tended to exhibit a lower hallucinogenic effect, highlighting the opposite role of both 5-HT receptors. Moreover, although some 5-MeO-tryptamines elicited very low HTR, they still act as potent 5-HT2AR agonists. In summary, this research offers a comprehensive understanding of the psychopharmacological profile of various amino-substituted 5-MeO-tryptamines, keeping structural aspects in focus and accumulating valuable data in the frame of NPS. Moreover, the unique characteristics of some 5-MeO-tryptamines render them intriguing molecules as mixed-action drugs and provide insight within the search of non-hallucinogenic but 5-HT2AR ligands as therapeutical agents., (© 2024. The Author(s).)

Introduction: Traditional Chinese medicinal plant, safflower, shows effective for treating pulmonary arterial hypertension (PAH), yet the underlying mechanisms remain largely unexplored. This study is aimed at exploring the potential molecular mechanisms of safflower in the treatment of PAH., Methods: Network pharmacology approach and molecular docking were applied to identify the core active compounds, therapeutic targets, and potential signaling pathways of safflower against PAH. Meanwhile, high-performance liquid chromatography (HPLC) assay was performed to determine the core compounds from safflower. Further, the mechanism of action of safflower on PAH was verified by in vivo and in vitro experiments., Results: A total of 15 active compounds and 177 targets were screened from safflower against PAH. Enrichment analysis indicated that these therapeutic targets were mainly involved in multiple key pathways, such as TNF signaling pathway and Th17 cell differentiation. Notably, molecular docking revealed that quercetin (core compound in safflower) displayed highest binding capacity with NLRP3. In vivo, safflower exerted therapeutic effects on PAH by inhibiting right ventricular hypertrophy, inflammatory factor release, and pulmonary vascular remodeling. Mechanistically, it significantly reduced the expression of proangiogenesis-related factors (MMP-2, MMP-9, Collagen 1, and Collagen 3) and NLRP3 inflammasome components (NLRP3, ASC, and Caspase-1) in PAH model. Similarly, these results were observed in vitro. Besides, we further confirmed that NLRP3 inhibitor had the same therapeutic effect as safflower in vitro., Conclusion: Our findings suggest that safflower mitigates PAH primarily by inhibiting NLRP3 inflammasome activation. This provides novel insights into the potential use of safflower as an alternative therapeutic approach for PAH., (© 2024 The Author(s). The Clinical Respiratory Journal published by John Wiley & Sons Ltd.)

The interpretation of cryo-EM maps often includes the docking of known or predicted structures of the components, which is particularly useful when the map resolution is worse than 4 Å. Although it can be effective to search the entire map to find the best placement of a component, the process can be slow when the maps are large. However, frequently there is a well-founded hypothesis about where particular components are located. In such cases, a local search using a map subvolume will be much faster because the search volume is smaller, and more sensitive because optimizing the search volume for the rotation-search step enhances the signal to noise. A Fourier-space likelihood-based local search approach, based on the previously published em&#95;placement software, has been implemented in the new emplace&#95;local program. Tests confirm that the local search approach enhances the speed and sensitivity of the computations. An interactive graphical interface in the ChimeraX molecular-graphics program provides a convenient way to set up and evaluate docking calculations, particularly in defining the part of the map into which the components should be placed., (open access.)

An immunologic system attacking the body's own tissues is a hallmark of autoimmune disorders, which encompass a wide range of unique conditions. Numerous essential biologic functions, including the regulation of the immune system, inflammation, cell division, and tissue repair, are carried out by cytokines. Natural compounds are an effective treatment for autoimmune illnesses by modulation of inflammatory cytokines and infiltration of leukocytes into the inflamed tissue. Here, anti-arthritic study was carried out using oral administration of Azelaic acid (AzA) for 28 days with doses (20, 40, and 80 mg/kg) in Complete Freund's Adjuvant (CFA) induced arthritis model. AzA ameliorated the adjuvant-induced arthritis by decreasing arthritic score, paw volume, improved body-weight alterations and serum levels of PGE2, 5-LOX and anti-ccp. AzA showed significant down regulation of NF-κB, COX-II, TNF-α, IL-17, IL-1β, IL-6, and up regulation of IL4 and IL10. Hemoglobin and RBCs count remarkably increased and ESR, CRP, platelets, WBCs levels markedly reduced in post treatment. In addition, the weakened SOD (superoxide dismutase), Catalase (CAT), Glutathione (GSH) activity and the increased levels of malondialdehyde (MDA) were all reversed by AzA treatment. And showed improved radiographical and histologic alterations in the structure of the joints. Molecular docking studies targeting COX-II, iNOS, TNF-α, 5-LOX, IL4, IL10, IL-6, and IL-17 establish a correlation between theoretical and experimental results. Results showed that AzA inhibit pro-inflammatory cytokines (COX-II, TNF-α, 5-LOX, IL-17, NF-κB, IL-1β, and IL-6) and increase anti-inflammatory cytokines, which supported the anti-arthritic and immunomodulatory potential of AzA., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Arbutin, a naturally soluble glycosylated phenol has antioxidant, antimicrobial, antitumor and anti-inflammatory properties. The current exploration appraises the treatment of arthritis by use of Arbutin (25, 50 and 100 mg/kg) orally in CFA-induced rat arthritis model. Body weight changes, paw size, and joint diameter were recorded till the 28th day in the arthritic-induced rats. Hematological, biochemical, oxidative and inflammatory biomarkers were measured through the blood samples of anesthetized rats. Arbutin markedly decreased paw volume, PGE-2, anti-CCP and 5-LOX levels, however, maintained metabolic and hematological balance and prevented weight loss. Radiology and histology changes improved significantly in the ankle joints of rats. Moreover, Arbutin increased gene pointers such as IL-10 and IL-4 while significantly reducing the levels of CRP and WBCs, whereas Hb, platelets and RBCs count markedly raised in post-treatments. Antioxidant levels of SOD, CAT and GSH were improved and MDA level was reduced in treated groups. Rt-PCR investigation showed a significant reduction of the interleukin-1β, TNF-α, interleukin-6, cyclooxygenase-2, NF-κB and IL-17 and increased expression of gene pointers like IL-4, and IL-10 in treated groups. Assessment of molecular docking revealed a strong binding interaction of Arbutin against 5-LOX, IL-17, TNF-alpha and interleukin-6, cyclooxygenase-2, nuclear factor-κB, IL-4 and iNOS providing a strong association between experimental and theoretical results. As a result, Arbutin has significantly reduced CFA-induced arthritis by modulation of anti-inflammatory cytokines, i.e., IL-10 and IL-4, the pro-inflammatory cytokines panel such as NF-κB, TNF-alpha, IL-1β, IL-6, PGE-2, 5-LOX and COX-2 and oxidative biomarkers., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Quinone-containing compounds have risen as promising anti-inflammatory targets; however, very little research has been directed to investigate their potentials. Accordingly, the current study aimed to design and synthesize group of quinones bearing different substituents to investigate the effect of these functionalities on the anti-inflammatory activities of this important scaffold. The choice of these substituents was carefully done, varying from a directly attached heterocyclic ring to different aromatic moieties linked through a nitrogen spacer. Both in vitro and in vivo anti-inflammatory activities of the synthesized compounds were assessed relative to the positive standards: celecoxib and indomethacin. The in vitro enzymatic and transcription inhibitory actions of all the synthesized compounds were tested against cyclooxygenase-2 (COX-2), cyclooxygenase-1 (COX-1), and 5-lipoxygenase (LOX) and the in vivo gene expression of Interleukin-1, interleukin 10, and Tumor Necrosis Factor-α (TNF-α) were determined. The IC 50 against COX-1 and COX-2 enzymes obtained by the immunoassay test revealed promising activities of sixteen compounds with selectivity indices higher than 100-fold COX-2 selectivity. Out of those, four compounds revealed selectivity indices comparable to celecoxib as a reference drug. Furthermore, all the tested compounds inhibited LOX with an IC 50 in the range of 1.59-3.11 µM superior to that of the reference drug used; zileuton (IC 50  = 3.50 µM). Consequently, these results highlight the promising LOX inhibitory activity of the tested compounds. The obtained in vivo paw edema results showed high inhibitory percentage for the compounds 9a, 9b, and 11a with the significant lower TNF-α relative mRNA expression for compounds 5a, 5d, 9a, 9b, 12d, and 12e. Finally, in silico docking of the most active compounds (5b, 5d, 9a, 9b) against COX2 enzymes presented an acceptable justification of the obtained in vitro inhibitory activities. As a conclusion, Compounds 5b, 5d, 9a, 9b, and 11b showed promising results and thus deserves further investigation., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study introduces (S)-Opto-prop-2, a second-generation photoswitchable ligand designed for precise modulation of β 2 -adrenoceptor (β 2 AR). Synthesised by incorporating an azobenzene moiety with propranolol, (S)-Opto-prop-2 exhibited a high PSS cis (photostationary state for cis isomer) percentage (∼90 %) and a favourable half-life (>10 days), facilitating diverse bioassay measurements. In vitro, the cis-isomer displayed substantially higher β 2 AR binding affinity than the trans-isomer (1000-fold), making (S)-Opto-prop-2 one of the best photoswitchable GPCR (G protein-coupled receptor) ligands reported so far. Molecular docking of (S)-Opto-prop-2 in the X-ray structure of propranolol-bound β 2 AR followed by site-directed mutagenesis studies, identified D113 3.32 , N312 7.39 and F289 6.51 as crucial residues that contribute to ligand-receptor interactions at the molecular level. In vivo efficacy was assessed using a rabbit ocular hypertension model, revealing that the cis isomer mimicked propranolol's effects in reducing intraocular pressure, while the trans isomer was inactive. Dynamic optical modulation of β 2 AR by (S)-Opto-prop-2 was demonstrated in two different cAMP bioassays and using live-cell confocal imaging, indicating reversible and dynamic control of β 2 AR activity using the new photopharmacology tool. In conclusion, (S)-Opto-prop-2 emerges as a promising photoswitchable ligand for precise and reversible β 2 AR modulation with light. The new tool shows superior cis-on binding affinity, one of the largest reported differences in affinity (1000-fold) between its two configurations, in vivo efficacy, and dynamic modulation. This study contributes valuable insights into the evolving field of photopharmacology, offering a potential avenue for targeted therapy in β 2 AR-associated pathologies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Nanomaterials excel in mimicking the structure and function of natural enzymes while being far more interesting in terms of structural stability, functional versatility, recyclability, and large-scale preparation. Herein, the story assembles hemin, histidine analogs, and G-quadruplex DNA in a catalytically competent supramolecular assembly referred to as assembly-activated hemin enzyme (AA-heminzyme). The catalytic properties of AA-heminzyme are investigated both in silico (by molecular docking and quantum chemical calculations) and in vitro (notably through a systematic comparison with its natural counterpart horseradish peroxidase, HRP). It is found that this artificial system is not only as efficient as HRP to oxidize various substrates (with a turnover number k cat of 115 s -1 ) but also more practically convenient (displaying better thermal stability, recoverability, and editability) and more economically viable, with a catalytic cost amounting to <10% of that of HRP. The strategic interest of AA-heminzyme is further demonstrated for both industrial wastewater remediation and biomarker detection (notably glutathione, for which the cost is decreased by 98% as compared to commercial kits)., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Renal cell carcinoma is a highly vascular tumor associated with vascular endothelial growth factor (VEGF) expression. The Vascular Endothelial Growth Factor -2 (VEGF-2) and its receptor was identified as a potential anti-cancer target, and it plays a crucial role in physiology as well as pathology. Inhibition of angiogenesis via blocking the signaling pathway is considered an attractive target. In the present study, 150 FDA-approved drugs have been screened using the concept of drug repurposing against VEGFR-2 by employing the molecular docking, molecular dynamics, grouping data with Machine Learning algorithms, and density functional theory (DFT) approaches. The identified compounds such as Pazopanib, Atogepant, Drosperinone, Revefenacin and Zanubrutinib shown the binding energy - 7.0 to - 9.5 kcal/mol against VEGF receptor in the molecular docking studies and have been observed as stable in the molecular dynamic simulations performed for the period of 500 ns. The MM/GBSA analysis shows that the value ranging from - 44.816 to - 82.582 kcal/mol. Harnessing the machine learning approaches revealed that clustering with K = 10 exhibits the relevance through high binding energy and satisfactory logP values, setting them apart from compounds in distinct clusters. Therefore, the identified compounds are found to be potential to inhibit the VEGFR-2 and the present study will be a benchmark to validate the compounds experimentally., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Lutein (Lut) is a recognized nutritional supplement known for its antioxidative and anti-inflammatory properties, crucial in mitigating ocular disease. However, enhancements to Lut stability and solubility remain challenges to be addressed in the healthcare industry. Herein, we fabricated and evaluated a food-grade highly porous β-cyclodextrin metal-organic framework (β-CD-MOF) for its ability to encapsulate Lut. Lut stability considerably improved when loaded into β-CD-MOF to form a Lut@β-CD-MOF complex, which exhibited better stability than Lut loaded into the γ-cyclodextrin metal-organic framework (Lut@γ-CD-MOF), Lut@β-CD, and commercial product (Blackmores™) at 40°C, 60°C, and 70°C, respectively. The solubility of Lut@β-CD-MOF in water increased by 26.8-fold compared to raw Lut at 37°C. Lut@β-CD-MOF exhibited greater hydrophilicity, as determined by measuring the water contact angle. Molecular docking and other characterizations of Fourier transform infrared spectroscopy and powder X-ray diffraction confirmed that Lut was successfully encapsulated in the chamber formed by the three cyclodextrins in β-CD-MOF. Thermogravimetric analysis and Raman spectroscopy demonstrated that Lut distributed in the β-CD-MOF cavity deeply improved Lut stability and solubility. In conclusion, our findings underscored the function of β-CD-MOF in enhancing Lut stability and solubility for formulation applications., (© 2024. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

Background: COVID-19 is an infectious disease caused by SARS-CoV-2, a close relative of SARS-CoV. Several studies have searched for COVID-19 therapies. The topics of these works ranged from vaccine discovery to natural products targeting the SARS-CoV-2 main protease (M pro ), a potential therapeutic target due to its essential role in replication and conserved sequences. However, published research on this target is limited, presenting an opportunity for drug discovery and development., Method: This study aims to repurpose 10692 drugs in DrugBank by using ligand-based virtual screening (LBVS) machine learning (ML) with Konstanz Information Miner (KNIME) to seek potential therapeutics based on M pro inhibitors. The top candidate compounds, the native ligand (GC-376) of the M pro inhibitor, and the positive control boceprevir were then subjected to absorption, distribution, metabolism, excretion, and toxicity (ADMET) characterization, drug-likeness prediction, and molecular docking (MD). Protein-protein interaction (PPI) network analysis was added to provide accurate information about the M pro regulatory network., Results: This study identified 3,166 compound candidates inhibiting M pro . The random forest (RF) molecular access system ML model provided the highest confidence score of 0.95 (bromo-7-nitroindazole) and identified the top 22 candidate compounds. Subjecting the 22 candidate compounds, the native ligand GC-376, and boceprevir to further ADMET property characterization and drug-likeness predictions revealed that one compound had two violations of Lipinski's rule. Additional MD results showed that only five compounds had more negative binding energies than the native ligand (- 12.25 kcal/mol). Among these compounds, CCX-140 exhibited the lowest score of - 13.64 kcal/mol. Through literature analysis, six compound classes with potential activity for M pro were discovered. They included benzopyrazole, azole, pyrazolopyrimidine, carboxylic acids and derivatives, benzene and substituted derivatives, and diazine. Four pathologies were also discovered on the basis of the M pro PPI network., Conclusion: Results demonstrated the efficiency of LBVS combined with MD. This combined strategy provided positive evidence showing that the top screened drugs, including CCX-140, which had the lowest MD score, can be reasonably advanced to the in vitro phase. This combined method may accelerate the discovery of therapies for novel or orphan diseases from existing drugs., (© 2023. The Author(s), under exclusive licence to Tehran University of Medical Sciences.)

Eugenol (Eug) holds potential as a treatment for bacterial rhinosinusitis by nasal powder drug delivery. To stabilization and solidification of volatile Eug, herein, nasal inhalable γ-cyclodextrin metal-organic framework (γ-CD-MOF) was investigated as a carrier by gas-solid adsorption method. The results showed that the particle size of Eug loaded by γ-CD-MOF (Eug@γ-CD-MOF) distributed in the range of 10-150 μm well. In comparison to γ-CD and β-CD-MOF, γ-CD-MOF has higher thermal stability to Eug. And the intermolecular interactions between Eug and the carriers were verified by characterizations and molecular docking. Based on the bionic human nasal cavity model, Eug@γ-CD-MOF had a high deposition distribution (90.07 ± 1.58%). Compared with free Eug, the retention time Eug@γ-CD-MOF in the nasal cavity was prolonged from 5 min to 60 min. In addition, the cell viability showed that Eug@γ-CD-MOF (Eug content range 3.125-200 µg/mL) was non-cytotoxic. And the encapsulation of γ-CD-MOF could not reduce the bacteriostatic effect of Eug. Therefore, the biocompatible γ-CD-MOF could be a potential and valuable carrier for nasal drug delivery to realize solidification and nasal therapeutic effects of volatile oils., (© 2024. The Author(s), under exclusive licence to American Association of Pharmaceutical Scientists.)

In silico modeling was applied to study the efficiency of two ligands, namely, UCB-J and UCB-F , to bind to isoforms of the synaptic vesicle glycoprotein 2 (SV2) that are involved in the regulation of synaptic function in the nerve terminals, with the ultimate goal to understand the selectivity of the interaction between UCB-J and UCB-F to different isoforms of SV2. Docking and large-scale molecular dynamics simulations were carried out to unravel various binding patterns, types of interactions, and binding free energies, covering hydrogen bonding and nonspecific hydrophobic interactions, water bridge, π-π, and cation-π interactions. The overall preference for bonding types of UCB-J and UCB-F with particular residues in the protein pockets can be disclosed in detail. A unique interaction fingerprint, namely, hydrogen bonding with additional cation-π interaction with the pyridine moiety of UCB-J , could be established as an explanation for its high selectivity over the SV2 isoform A (SV2A). Other molecular details, primarily referring to the presence of π-π interactions and hydrogen bonding, could also be analyzed as sources of selectivity of the UCB-F tracer for the three isoforms. The simulations provide atomic details to support future development of new selective tracers targeting synaptic vesicle glycoproteins and their associated diseases.

Anti-SARS-CoV-2 drugs are urgently needed to prevent the pandemic and for immunization. Their protease inhibitor treatment for COVID-19 has been used in clinical trials. In Calu-3 and THP1 cells, 3CL SARS-CoV-2 Mpro protease is required for viral expression, replication, and the activation of the cytokines IL-1, IL-6, and TNF-. The Mpro structure was chosen for this investigation because of its activity as a chymotrypsin-like enzyme and the presence of a cysteine-containing catalytic domain. Thienopyridine derivatives increase the release of nitric oxide from coronary endothelial cells, which is an important cell signaling molecule with antibacterial activity against bacteria, protozoa, and some viruses. Using DFT calculations, global descriptors are computed from HOMO-LUMO orbitals; the molecular reactivity sites are analyzed from an electrostatic potential map. NLO properties are calculated, and topological analysis is also part of the QTAIM studies. Both compounds 1 and 2 were designed from the precursor molecule pyrimidine and exhibited binding energies (-14.6708 kcal/mol and -16.4521 kcal/mol). The binding mechanisms of molecule 1 towards SARS-COV-2 3CL Mpro exhibited strong hydrogen bonding as well as Vdw interaction. In contrast, derivative 2 was bound to the active site protein's active studied that several residues and positions, including (His41, Cys44, Asp48, Met49, Pro52, Tyr54, Phe140, Leu141, Ser144, His163, Ser144, Cys145, His164, Met165, Glu166, Leu167, Asp187, Gln189, Thr190, and GLn192) are critical for the maintenance of inhibitors inside the active pocket. Molecular docking and 100 ns MD simulation analysis revealed that Both compounds 1 and 2 with higher binding affinity and stability toward the SARS-COV-2 3CL Mpro protein. Binding free energy calculations and other MD parameters support the finding.Communicated by Ramaswamy H. Sarma.

The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells to learn the properties of drug compounds in the DrugBank, aiming to obtain a new and virtual screening compounds database with drug-like properties. Ultimately, a compounds database consisting of 26,316 compounds is obtained by this method. To evaluate the potential of this compounds database, a series of tests are performed, including chemical space, ADME properties, compound fragmentation, and synthesizability analysis. As a result, it is proved that the database is equipped with good drug-like properties and a relatively new backbone, its potential in virtual screening is further tested. Finally, a series of seedling compounds with completely new backbones are obtained through docking and binding free energy calculations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The development of new molecules for the treatment of calmodulin related cardiovascular or neurodegenerative diseases is an interesting goal. In this work, we introduce a novel strategy with four main steps: (1) chemical synthesis of target molecules, (2) Förster Resonance Energy Transfer (FRET) biosensor development and in vitro biological assay of new derivatives, (3) Cheminformatics models development and in vivo activity prediction, and (4) Docking studies. This strategy is illustrated with a case study. Firstly, a series of 4-substituted Riluzole derivatives 1-3 were synthetized through a strategy that involves the construction of the 4-bromoriluzole framework and its further functionalization via palladium catalysis or organolithium chemistry. Next, a FRET biosensor for monitoring Ca 2+ -dependent CaM-ligands interactions has been developed and used for the in vitro assay of Riluzole derivatives. In particular, the best inhibition (80%) was observed for 4-methoxyphenylriluzole 2b. Besides, we trained and validated a new Networks Invariant, Information Fusion, Perturbation Theory, and Machine Learning (NIFPTML) model for predicting probability profiles of in vivo biological activity parameters in different regions of the brain. Next, we used this model to predict the in vivo activity of the compounds experimentally studied in vitro. Last, docking study conducted on Riluzole and its derivatives has provided valuable insights into their binding conformations with the target protein, involving calmodulin and the SK4 channel. This new combined strategy may be useful to reduce assay costs (animals, materials, time, and human resources) in the drug discovery process of calmodulin inhibitors., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.)

Since 2019 the SARS-CoV-2 and its variants caused COVID-19, such incidents brought the world in pandemic situation. This happened due to furious mutations in SARS-CoV-2, in which some variants had high transmissibility and infective, this led the virus emerged as virulent and worsened the COVID-19 situation. Among the variants, P323L is one of the important mutants of RdRp in SARS-CoV-2. To inhibit the erroneous function of this mutated RdRp, we have screened 943 molecules against the P323L mutated RdRp with the criteria that the molecules with 90% similar to the structure of remdesivir (control drug) resulted nine molecules. Further, these molecules were evaluated by induced fit docking (IFD) identified two molecules (M2 & M4) which are forming strong intermolecular interactions with the key residues of mutated RdRp and has high binding affinity. Docking score of the M2 and M4 molecules with mutated RdRp are -9.24 and -11.87 kcal/mol, respectively. Further, to understand the intermolecular interactions, conformational stability, the molecular dynamics simulation and binding free energy calculations were performed. The binding free energy values of M2 and M4 molecules with the P323L mutated RdRp complexes are -81.60 and -83.07 kcal/mol, respectively. The results of this in silico study confirm that M4 is a potential molecule; hence, it may be considered as the potential inhibitor of P323L mutated RdRp to treat COVID-19 after clinical investigation.Communicated by Ramaswamy H. Sarma.

Neurodegenerative diseases (NDs) are one of the prominent health challenges facing contemporary society, and many efforts have been made to overcome and (or) control it. In this research paper, we described a practical one-pot two-step three-component reaction between 3,4-dihydronaphthalen-1(2 H )-one ( 1 ), aryl(or heteroaryl)glyoxal monohydrates ( 2a - h ), and hydrazine monohydrate (NH 2 NH 2 •H 2 O) for the regioselective preparation of some 3-aryl(or heteroaryl)-5,6-dihydrobenzo[ h ]cinnoline derivatives ( 3a - h ). After synthesis and characterization of the mentioned cinnolines ( 3a - h ), the in silico multi-targeting inhibitory properties of these heterocyclic scaffolds have been investigated upon various Homo sapiens -type enzymes, including h MAO-A, h MAO-B, h AChE, h BChE, h BACE-1, h BACE-2, h NQO-1, h NQO-2, h nNOS, h iNOS, h PARP-1, h PARP-2, h LRRK-2 (G2019S) , h GSK-3β, h p38α MAPK, h JNK-3, h OGA, h NMDA receptor, h nSMase-2, h IDO-1, h COMT, h LIMK-1, h LIMK-2, h RIPK-1, h UCH-L1, h PARK-7, and h DHODH, which have confirmed their functions and roles in the neurodegenerative diseases (NDs), based on molecular docking studies, and the obtained results were compared with a wide range of approved drugs and well-known (with IC 50 , EC 50 , etc.) compounds. In addition, in silico ADMET prediction analysis was performed to examine the prospective drug properties of the synthesized heterocyclic compounds ( 3a - h ). The obtained results from the molecular docking studies and ADMET-related data demonstrated that these series of 3-aryl(or heteroaryl)-5,6-dihydrobenzo[ h ]cinnolines ( 3a - h ), especially hit ones, can really be turned into the potent core of new drugs for the treatment of neurodegenerative diseases (NDs), and/or due to the having some reactionable locations, they are able to have further organic reactions (such as cross-coupling reactions), and expansion of these compounds (for example, with using other types of aryl(or heteroaryl)glyoxal monohydrates) makes a new avenue for designing novel and efficient drugs for this purpose.

Androgen receptor (AR) antagonists are widely used for the treatment of prostate cancer (PCa), but their therapeutic efficacy is usually compromised by the rapid emergence of drug resistance. However, the lack of the detailed interaction between AR and its antagonists poses a major obstacle to the design of novel AR antagonists. Here, funnel metadynamics is employed to elucidate the inherent regulation mechanisms of three AR antagonists (hydroxyflutamide, enzalutamide, and darolutamide) on AR. For the first time it is observed that the binding of antagonists significantly disturbed the C-terminus of AR helix-11, thereby disrupting the specific internal hydrophobic contacts of AR-LBD and correspondingly the communication between AR ligand binding pocket (AR-LBP), activation function 2 (AF2), and binding function 3 (BF3). The subsequent bioassays verified the necessity of the hydrophobic contacts for AR function. Furthermore, it is found that darolutamide, a newly approved AR antagonist capable of fighting almost all reported drug resistant AR mutants, can induce antagonistic binding structure. Subsequently, docking-based virtual screening toward the dominant binding conformation of AR for darolutamide is conducted, and three novel AR antagonists with favorable binding affinity and strong capability to combat drug resistance are identified by in vitro bioassays. This work provides a novel rational strategy for the development of anti-resistant AR antagonists., (© 2024 The Authors. Advanced Science published by Wiley‐VCH GmbH.)

Despite the recent advances in the determination of high-resolution membrane protein (MP) structures, the structural and functional characterization of MPs remains extremely challenging, mainly due to the hydrophobic nature, low abundance, poor expression, purification, and crystallization difficulties associated with MPs. Whereby the major challenges/hurdles for MP structure determination are associated with the expression, purification, and crystallization procedures. Although there have been significant advances in the experimental determination of MP structures, only a limited number of MP structures (approximately less than 1% of all) are available in the Protein Data Bank (PDB). Therefore, the structures of a large number of MPs still remain unresolved, which leads to the availability of widely unplumbed structural and functional information related to MPs. As a result, recent developments in the drug discovery realm and the significant biological contemplation have led to the development of several novel, low-cost, and time-efficient computational methods that overcome the limitations of experimental approaches, supplement experiments, and provide alternatives for the characterization of MPs. Whereby the fine tuning and optimizations of these computational approaches remains an ongoing endeavor.Computational methods offer a potential way for the elucidation of structural features and the augmentation of currently available MP information. However, the use of computational modeling can be extremely challenging for MPs mainly due to insufficient knowledge of (or gaps in) atomic structures of MPs. Despite the availability of numerous in silico methods for 3D structure determination the applicability of these methods to MPs remains relatively low since all methods are not well-suited or adequate for MPs. However, sophisticated methods for MP structure predictions are constantly being developed and updated to integrate the modifications required for MPs. Currently, different computational methods for (1) MP structure prediction, (2) stability analysis of MPs through molecular dynamics simulations, (3) modeling of MP complexes through docking, (4) prediction of interactions between MPs, and (5) MP interactions with its soluble partner are extensively used. Towards this end, MP docking is widely used. It is notable that the MP docking methods yet few in number might show greater potential in terms of filling the knowledge gap. In this chapter, MP docking methods and associated challenges have been reviewed to improve the applicability, accuracy, and the ability to model macromolecular complexes., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

The interactions of G-protein-coupled receptors (GPCRs) with other proteins are critical in several cellular processes but resolving their structural dynamics remains challenging. An increasing number of GPCR complexes have been experimentally resolved but others including receptor variants are yet to be characterized, necessitating computational predictions of their interactions. Although integrative approaches with multi-scale simulations would provide rigorous estimates of their conformational dynamics, protein-protein docking remains a first tool of choice of many researchers due to the availability of open-source programs and easy to use web servers with reasonable predictive power. Protein-protein docking algorithms have limited ability to consider protein flexibility, environment effects, and entropy contributions and are usually a first step towards more integrative approaches. The two critical steps of docking: the sampling and scoring algorithms have improved considerably and their performance has been validated against experimental data. In this chapter, we provide an overview and generalized protocol of a few docking protocols using GPCRs as test cases. In particular, we demonstrate the interactions of GPCRs with extracellular protein ligands and an intracellular protein effectors (G-protein) predicted from docking approaches and test their limitations. The current chapter will help researchers critically assess docking protocols and predict experimentally testable structures of GPCR complexes., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Terpenes are a diverse class of natural products which have long been sought after for their chemical properties as medicine, perfumes, and for food flavoring. Computational docking studies of terpene mechanisms have been a challenge due to the lack of strong directing groups which many docking programs rely on. In this chapter, we dive into our computational method Terdockin (Terpene-Docking) as a successful methodology in modeling terpene synthase mechanisms. This method could also be used as inspiration for any multi-ligand docking project., (Copyright © 2024. Published by Elsevier Inc.)

Intrinsically disordered proteins (IDPs) are a novel class of proteins that have established a significant importance and attention within a very short period of time. These proteins are essentially characterized by their inherent structural disorder, encoded mainly by their amino acid sequences. The profound abundance of IDPs and intrinsically disordered regions (IDRs) in the biological world delineates their deep-rooted functionality. IDPs and IDRs convey such extensive functionality through their unique dynamic nature, which enables them to carry out huge number of multifaceted biomolecular interactions and make them "interaction hub" of the cellular systems. Additionally, with such widespread functions, their misfunctioning is also intimately associated with multiple diseases. Thus, understanding the dynamic heterogeneity of various IDPs along with their interactions with respective binding partners is an important field with immense potentials in biomolecular research. In this context, molecular docking-based computational approaches have proven to be remarkable in case of ordered proteins. Molecular docking methods essentially model the biomolecular interactions in both structural and energetic terms and use this information to characterize the putative interactions between the two participant molecules. However, direct applications of the conventional docking methods to study IDPs are largely limited by their structural heterogeneity and demands for unique IDP-centric strategies. Thus, in this chapter, we have presented an overview of current methodologies for successful docking operations involving IDPs and IDRs. These specialized methods majorly include the ensemble-based and fragment-based approaches with their own benefits and limitations. More recently, artificial intelligence and machine learning-assisted approaches are also used to significantly reduce the complexity and computational burden associated with various docking applications. Thus, this chapter aims to provide a comprehensive summary of major challenges and recent advancements of molecular docking approaches in the IDP field for their better utilization and greater applicability.Asp (D)., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

Protein-protein interactions between SH2 domains and segments of proteins that include a post-translationally phosphorylated tyrosine residue (pY) underpin numerous signal transduction cascades that allow cells to respond to their environment. Dysregulation of the writing, erasing, and reading of these posttranslational modifications is a hallmark of human disease, notably cancer. Elucidating the precise role of the SH2 domain-containing adaptor proteins Crk and CrkL in tumor cell migration and invasion is challenging because there are no specific and potent antagonists available. Crk and CrkL SH2s interact with a region of the docking protein p130Cas containing 15 potential pY-containing tetrapeptide motifs. This chapter summarizes recent efforts toward peptide antagonists for this Crk/CrkL-p130Cas interaction. We describe our protocol for recombinant expression and purification of Crk and CrkL SH2s for functional assays and our procedure to determine the consensus binding motif from the p130Cas sequence. To develop a more potent antagonist, we employ methods often associated with structure-based drug design. Computational docking using Rosetta FlexPepDock, which accounts for peptides having a greater number of conformational degrees of freedom than small organic molecules that typically constitute libraries, provides quantitative docking metrics to prioritize candidate peptides for experimental testing. A battery of biophysical assays, including fluorescence polarization, differential scanning fluorimetry and saturation transfer difference nuclear magnetic resonance spectroscopy, were employed to assess the candidates. In parallel, GST pulldown competition assays characterized protein-protein binding in vitro. Taken together, our methodology yields peptide antagonists of the Crk/CrkL-p130Cas axis that will be used to validate targets, assess druggability, foster in vitro assay development, and potentially serve as lead compounds for therapeutic intervention., (Copyright © 2024. Published by Elsevier Inc.)

Anshen Dingzhi prescription (ADP) is a classic prescription of traditional Chinese medicine, which has been used in the treatment of neuropsychiatric diseases. However, its treatment of breast cancer-related post-traumatic stress disorder (BC-PTSD) lacks clinical research evidence and its mechanism is not clear. The present study investigated the efficacy and action mechanism of ADP against BC-PTSD. The results of the clinical trial showed that after 4 weeks of treatment, both groups showed reduced post-traumatic stress disorder checklist-civilian version (PCL-C), Pittsburgh sleep quality index (PSQI), self-rating depression scale (SDS) and self-rating anxiety scale (SAS) scores, and increased functional assessment of cancer therapy-breast (FACT-B) scores. The serum cortisol (CORT), tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β) levels were decreased and brain-derived neurotrophic factor (BDNF) level were increased, and the improvement of serum TNF-α, IL-1β, and BDNF in treatment group was better than that of the control group. The overall treatment efficacy in the treatment group (43.90%) was superior to that in the control group (23.81%), and the overall incidence of adverse effects was lower than that in the control group. The results of network analysis and molecular docking showed that ADP blood components could act on IL1B, TNF, and BDNF. ADP contributes to the treatment of BC-PTSD symptoms, with a mechanism possibly related to its regulatory effect on TNF-α, IL-1β, and BDNF levels.Trial registration: Chinese Clinical Trial Registry, http://www.chictr.org.cn,ChiCTR2300077801., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: Alkaloids are important phytoconstituents obtained from various plant sources. The study's primary goal is to assess the anti-Alzheimer potential of alkaloids using a molecular docking study. Alzheimer's disease (AD) is considered a gradual decline in memory, reasoning, decision-making, orientation to one's physical surroundings, and language., Materials and Methods: The main target i.e. acetylcholinesterase proteins was selected for the molecular docking study., Results: The structures of various alkaloids were drawn using Chem Draw Software, PDB was retrieved from the RCSB PDB database, and molecular docking study was performed on Molergo Virtual Docker. The potential alkaloids were identified with anti-Alzheimer potency., Conclusion: Reserpine, vinblastine, ergotamine, and tubocurarine were found to exhibit potential anti-Alzheimer potency., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Proteins are the fundamental organic macromolecules in living systems that play a key role in a variety of biological functions including immunological detection, intracellular trafficking, and signal transduction. The docking of proteins has greatly advanced during recent decades and has become a crucial complement to experimental methods. Protein-protein docking is a helpful method for simulating protein complexes whose structures have not yet been solved experimentally. This chapter focuses on major search tactics along with various docking programs used in protein-protein docking algorithms, which include: direct search, exhaustive global search, local shape feature matching, randomized search, and broad category of post-docking approaches. As backbone flexibility predictions and interactions in high-resolution protein-protein docking remain important issues in the overall optimization context, we have put forward several methods and solutions used to handle backbone flexibility. In addition, various docking methods that are utilized for flexible backbone docking, including ATTRACT, FlexDock, FLIPDock, HADDOCK, RosettaDock, FiberDock, etc., along with their scoring functions, algorithms, advantages, and limitations are discussed. Moreover, what progress in search technology is expected, including not only the creation of new search algorithms but also the enhancement of existing ones, has been debated. As conformational flexibility is one of the most crucial factors affecting docking success, more work should be put into evaluating the conformational flexibility upon binding for a particular case in addition to developing new algorithms to replace the rigid body docking and scoring approach., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)