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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.

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.

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.

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.

Here, we develop an empirical energy function based on quantum mechanical data for the interaction between methane and benzene that captures the contribution from CH-π interactions. Such interactions are frequently observed in protein-ligand crystal structures, particularly for carbohydrate ligands, but have been hard to quantify due to the absence of a model for CH-π interactions in typical molecular mechanical force fields or docking scoring functions. The CH-π term was added to the AutoDock Vina (AD VINA) scoring function enabling its performance to be evaluated against a cohort of more than 1600 occurrences in 496 experimental structures of protein-ligand complexes. By employing a conformational grid search algorithm, inclusion of the CH-π term was shown to improve the prediction of the preferred orientation of flexible ligands in protein-binding sites and to enhance the detection of carbohydrate-binding sites that display CH-π interactions. Last but not least, this term was also shown to improve docking performance for the CASF-2016 benchmark set and a carbohydrate set.

It was previously shown that human platelet 12 S -lipoxygenase (h12-LOX) exists as a dimer; however, the specific structure is unknown. In this study, we create a model of the dimer through a combination of computational methods, experimental mutagenesis, and hydrogen-deuterium exchange (HDX) investigations. Initially, Leu183 and Leu187 were replaced by negatively charged glutamate residues and neighboring aromatic residues were replaced with alanine residues (F174A/W176A/L183E/L187E/Y191A). This quintuple mutant disrupted both the hydrophobic and π-π interactions, generating an h12-LOX monomer. To refine the determinants for dimer formation further, the L183E/L187E mutant was generated and the equilibrium shifted mostly toward the monomer. We then submitted the predicted monomeric structure to protein-protein docking to create a model of the dimeric complex. A total of nine of the top 10 most energetically favorable docking conformations predict a TOP-to-TOP dimeric arrangement of h12-LOX, with the α-helices containing a Leu-rich region (L172, L183, L187, and L194), corroborating our experimental results showing the importance of these hydrophobic interactions for dimerization. This model was supported by HDX investigations that demonstrated the stabilization of four, non-overlapping peptides within helix α2 of the TOP subdomain for wt-h12-LOX, consistent with the dimer interface. Most importantly, our data reveal that the dimer and monomer of h12-LOX have distinct biochemical properties, suggesting that the structural changes due to dimerization have allosteric effects on active site catalysis and inhibitor binding.

Though pharmaceutical polymers were widely used in inhibiting drug recrystallization via strong intermolecular hydrogen and ionic bonds, the improved drug stability was achieved at the cost of the drug release rate or amount in the drug-in-adhesive transdermal patch. To overcame the difficulty, this study aimed to increase drug loading utilizing a novel drug-ionic liquid (drug-IL) strategy and illustrate the underlying molecular mechanism. Here, naproxen (NPX) and triamylamine (TAA) were chosen as the model drug and corresponding counterion, respectively. In addiiton, carboxylic pressure-sensitive adhesive (PSA) was chosen as the model polymer. The drug-IL (NPX-TAA) was synthesized and characterized by differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FT-IR), and proton nuclear magnetic resonance. The miscibility between NPX-TAA and PSA was assessed using microscopy study, X-ray diffraction, fluorescence spectroscopy, and solubility parameter calculation. In addition, molecular mechanisms of crystallization inhibition were revealed by FT-IR, Raman spectroscopy, DSC, X-ray photoelectron spectroscopy (XPS), and molecular docking. Finally, the release pattern of the high load patch of NPX-TAA was evaluated using in vitro drug release and verified by a skin permeation experiment. The results showed that drug loading in PSA was increased by 5.0 times, which was caused by the synergistic effect of strong ionic hydrogen bonding (the decreased intensity and blue shift of the O-H peak of COOH in PSA) formed between NPX-TAA and PSA-COO - and normal hydrogen bonding (red shift of the C═O peak in PSA) formed between NPX-TAA and the carbonyl group of PSA. In addition, -NH + of TAA was confirmed as the molecular basis of ionic hydrogen bonding through new peak appearance (binding energy: 400.0 eV) in XPS spectra. Moreover, high drug release percent (80.8 ± 1.8%) was achieved even at high drug loading compared with the control group (72.4 ± 2.2%). Thus, this study introduced an effective drug-IL method to enhance drug loading capacity and illustrated the brand-new action mechanism, which provided a powerful instrument for the development of a high drug loading-high release patch.

Glycosaminoglycans (GAGs) such as heparan sulfate and chondroitin sulfate decorate all mammalian cell surfaces. These mucopolysaccharides act as coreceptors for extracellular ligands, regulating cell signaling, growth, proliferation, and adhesion. In glioblastoma, the most common type of primary malignant brain tumor, dysregulated GAG biosynthesis results in altered chain length, sulfation patterns, and the ratio of contributing monosaccharides. These events contribute to the loss of normal cellular function, initiating and sustaining malignant growth. Disruption of the aberrant cell surface GAGs with small molecule inhibitors of GAG biosynthetic enzymes is a potential therapeutic approach to blocking the rogue signaling and proliferation in glioma, including glioblastoma. Previously, 4-azido-xylose-α-UDP sugar inhibited both xylosyltransferase (XYLT-1) and β-1,4-galactosyltransferase-7 (β-GALT-7)-the first and second enzymes of GAG biosynthesis-when microinjected into a cell. In another study, 4-deoxy-4-fluoro-β-xylosides inhibited β-GALT-7 at 1 mM concentration in vitro . In this work, we seek to solve the enduring problem of drug delivery to human glioma cells at low concentrations. We developed a library of hydrophobic, presumed prodrugs 4-deoxy-4-fluoro-2,3-dibenzoyl-(α- or β-) xylosides and their corresponding hydrophilic inhibitors of XYLT-1 and β-GALT-7 enzymes. The prodrugs were designed to be activatable by carboxylesterase enzymes overexpressed in glioblastoma. Using a colorimetric MTT assay in human glioblastoma cell lines, we identified a prodrug-drug pair (4-nitrophenyl-α-xylosides) as lead drug candidates. The candidates arrest U251 cell growth at an IC 50 = 380 nM (prodrug), 122 μM (drug), and U87 cells at IC 50 = 10.57 μM (prodrug). Molecular docking studies were consistent with preferred binding of the α- versus β-nitro xyloside conformer to XYLT-1 and β-GALT-7 enzymes.

Cyclin-dependent kinase 9 (CDK9), which regulates transcriptional elongation, is an attractive therapeutic target for many cancers, especially for cancers driven by transcriptional dysregulation. In particular, CDK9 promotes RNA polymerase II pause/release, a rate-limiting step in normal transcriptional regulation that is frequently dysregulated in cancers. Emerging evidence indicates that selective CDK9 inhibition or degradation may provide a therapeutic benefit against certain cancers. Indeed, the development of CDK9 modulators (inhibitors and degraders) has attracted great attention, with several molecules currently under clinical development. This review provides an overview of recent advances in CDK9 modulators in general, with special emphasis on compounds under clinical evaluation and new emerging strategies, such as proteolysis targeting chimeras (PROTACs).

Leber's hereditary optic neuropathy (LHON) is a rare genetic mitochondrial disease and the primary cause of chronic visual impairment for at least 1 in 10 000 individuals in the U.K. Treatment options remain limited, with only a few drug candidates and therapeutic approaches, either approved or in development. Recently, idebenone has been investigated as drug therapy in the treatment of LHON, although evidence for the efficacy of idebenone is limited in the literature. NAD(P)H:quinone oxidoreductase 1 (NQO1) and mitochondrial complex III were identified as the major enzymes involved in idebenone activity. Based on this mode of action, computer-aided techniques and structure-activity relationship (SAR) optimization studies led to the discovery of a series naphthoquinone-related small molecules, with comparable adenosine 5'-triphosphate (ATP) rescue activity to idebenone. Among these, three compounds showed activity in the nanomolar range and one, 2-((4-fluoro-3-(trifluoromethyl)phenyl)amino)-3-(methylthio)naphthalene-1,3-dione ( 1 ), demonstrated significantly higher potency ex vivo, and significantly lower cytotoxicity, than idebenone.

Klebsiella pneumoniae is one of the most critical opportunistic pathogens. TA systems are promising drug targets because they are related to the survival of bacterial pathogens. However, structural information on TA systems in K. pneumoniae remains lacking; therefore, it is necessary to explore this information for the development of antibacterial agents. Here, we present the first crystal structure of the VapBC complex from K. pneumoniae at a resolution of 2.00 Å. We determined the toxin inhibitory mechanism of the VapB antitoxin through an Mg 2+ switch, in which Mg 2+ is displaced by R79 of VapB. This inhibitory mechanism of the active site is a novel finding and the first to be identified in a bacterial TA system. Furthermore, inhibitors, including peptides and small molecules, that activate the VapC toxin were discovered and investigated. These inhibitors can act as antimicrobial agents by disrupting the VapBC complex and activating VapC. Our comprehensive investigation of the K. pneumoniae VapBC system will help elucidate an unsolved conundrum in VapBC systems and develop potential antimicrobial agents.

Protein therapeutics typically require a concentrated protein formulation, which can lead to self-association and/or high viscosity due to protein-protein interaction (PPI). Excipients are often added to improve stability, bioavailability, and manufacturability of the protein therapeutics, but the selection of excipients often relies on trial and error. Therefore, understanding the excipient-protein interaction and its effect on non-specific PPI is important for rational selection of formulation development. In this study, we validate a general workflow based on the site identification by ligand competitive saturation (SILCS) technology, termed SILCS-Biologics, that can be applied to protein therapeutics for rational excipient selection. The National Institute of Standards and Technology monoclonal antibody (NISTmAb) reference along with the CNTO607 mAb is used as model antibody proteins to examine PPIs, and NISTmAb was used to further examine excipient-protein interactions, in silico. Metrics from SILCS include the distribution and predicted affinity of excipients, buffer interactions with the NISTmAb Fab, and the relation of the interactions to predicted PPI. Comparison with a range of experimental data showed multiple SILCS metrics to be predictive. Specifically, the number of favorable sites to which an excipient binds and the number of sites to which an excipient binds that are involved in predicted PPIs correlate with the experimentally determined viscosity. In addition, a combination of the number of binding sites and the predicted binding affinity is indicated to be predictive of relative protein stability. Comparison of arginine, trehalose, and sucrose, all of which give the highest viscosity in combination with analysis of B 22 and k D and the SILCS metrics, indicates that higher viscosities are associated with a low number of predicted binding sites, with lower binding affinity of arginine leading to its anomalously high impact on viscosity. The present study indicates the potential for the SILCS-Biologics approach to be of utility in the rational design of excipients during biologics formulation.

Sialin, encoded by the SLC17A5 gene, is a lysosomal sialic acid transporter defective in Salla disease, a rare inherited leukodystrophy. It also enables metabolic incorporation of exogenous sialic acids, leading to autoantibodies against N -glycolylneuraminic acid in humans. Here, we identified a novel class of human sialin ligands by virtual screening and structure-activity relationship studies. The ligand scaffold is characterized by an amino acid backbone with a free carboxylate, an N -linked aromatic or heteroaromatic substituent, and a hydrophobic side chain. The most potent compound, 45 (LSP12-3129), inhibited N -acetylneuraminic acid 1 (Neu5Ac) transport in a non-competitive manner with IC 50 ≈ 2.5 μM, a value 400-fold lower than the K M for Neu5Ac. In vitro and molecular docking studies attributed the non-competitive character to selective inhibitor binding to the Neu5Ac site in a cytosol-facing conformation. Moreover, compound 45 rescued the trafficking defect of the pathogenic mutant (R39C) causing Salla disease. This new class of cell-permeant inhibitors provides tools to investigate the physiological roles of sialin and help develop pharmacological chaperones for Salla disease.

The glycosylation of small hydrophobic compounds is catalyzed by uridine diphosphate glycosyltransferases (UGTs). Because glycosylation is an invaluable tool for improving the stability and water solubility of hydrophobic compounds, UGTs have attracted attention for their application in the food, cosmetics, and pharmaceutical industries. However, the ability of UGTs to accept and glycosylate a wide range of substrates is not clearly understood due to the existence of a large number of UGTs. Pa GT2, a UGT from Phytolacca americana , can regioselectively glycosylate piceatannol but has low activity toward other stilbenoids. To elucidate the substrate specificity and catalytic mechanism, we determined the crystal structures of Pa GT2 with and without substrates and performed molecular docking studies. The structures have revealed key residues involved in substrate recognition and suggest the presence of a nonconserved catalytic residue (His81) in addition to the highly conserved catalytic histidine in UGTs (His18). The role of the identified residues in substrate recognition and catalysis is elucidated with the mutational assay. Additionally, the structure-guided mutation of Cys142 to other residues, Ala, Phe, and Gln, allows Pa GT2 to glycosylate resveratrol with high regioselectivity, which is negligibly glycosylated by the wild-type enzyme. These results provide a basis for tailoring an efficient glycosyltransferase.

Chiral sugar derivatives are potential cyclitol surrogates of the Ca 2+ -mobilizing intracellular messenger d- myo -inositol 1,4,5-trisphosphate [Ins(1,4,5)P 3 ]. Six novel polyphosphorylated analogues derived from both d- and l-glucose were synthesized. Binding to Ins(1,4,5)P 3 receptors [Ins(1,4,5)P 3 R] and the ability to release Ca 2+ from intracellular stores via type 1 Ins(1,4,5)P 3 Rs were investigated. β-d-Glucopyranosyl 1,3,4-tris-phosphate, with similar phosphate regiochemistry and stereochemistry to Ins(1,4,5)P 3 , and α-d-glucopyranosyl 1,3,4-tris-phosphate are full agonists, being equipotent and 23-fold less potent than Ins(1,4,5)P 3 , respectively, in Ca 2+ -release assays and similar to Ins(1,4,5)P 3 and 15-fold weaker in binding assays. They can be viewed as truncated analogues of adenophostin A and refine understanding of structure-activity relationships for this Ins(1,4,5)P 3 R agonist. l-Glucose-derived ligands, methyl α-l-glucopyranoside 2,3,6-trisphosphate and methyl α-l-glucopyranoside 2,4,6-trisphosphate, are also active, while their corresponding d-enantiomers, methyl α-d-glucopyranoside 2,3,6-trisphosphate and methyl α-d-glucopyranoside 2,4,6-trisphosphate, are inactive. Interestingly, both l-glucose-derived ligands are partial agonists: they are among the least efficacious agonists of Ins(1,4,5)P 3 R yet identified, providing new leads for antagonist development.

SIS3 is a specific inhibitor of Smad3 that inhibits the TGFβ1-induced phosphorylation of Smad3. In this article, a variety of SIS3 derivatives were designed and synthesized to discover potential inhibitors against P-glycoprotein-mediated multidrug resistance aided by late-stage functionalization of a 2-(4-(pyridin-2-yl)phenoxy)pyridine analogue. A novel class of potent P-gp reversal agents were investigated, and a lead compound 37 was identified as a potent P-gp reversal agent with strong bioactivity and outstanding affinity for P-gp.

ERK1 and ERK5 are proposed to have pivotal roles in several types of cancer. Under some circumstance, ERK5 may provide a common bypass route, which rescues proliferation upon abrogation of ERK1 signaling. Thus, we accurately classified the tumor types from The Cancer Genome Atlas (TCGA) based on the expression levels of ERK1 and ERK5. We proposed a novel therapeutic strategy to overcome the above-mentioned compensatory mechanism in specific tumor types by co-targeting both ERK1 and ERK5. On the basis of the idea of overcoming ERK5 compensation mechanism, 22ac (ADTL-EI1712) as the first selective dual-target inhibitor of ERK1 and ERK5 was discovered to have potent antitumor effects in vitro and in vivo . Interestingly, this compound was found to induce regulated cell death accompanied by autophagy in MKN-74 cells. Taken together, our results warrant the potential of this dual-target inhibitor as a new candidate drug that conquers compensatory mechanism in certain tumor types.

Muscarinic M 3 receptor antagonists and inverse agonists displaying high affinity and subtype selectivity over the antitarget M 2 are valuable pharmacological tools and may enable improved treatment of chronic obstructive pulmonary disease (COPD), asthma, or urinary incontinence. On the basis of known M 3 antagonists comprising a piperidine or quinuclidine unit attached to a biphenyl carbamate, 5-fluoro substitution was responsible for M 3 subtype selectivity over M 2 , while 3'-chloro substitution substantially increased affinity through a σ-hole interaction. Resultantly, two piperidinyl- and two quinuclidinium-substituted biphenyl carbamates OFH243 ( 13n ), OFH244 ( 13m ), OFH3911 ( 14n ), and OFH3912 ( 14m ) were discovered, which display two-digit picomolar affinities with K i values from 0.069 to 0.084 nM, as well as high selectivity over the M 2 subtype (46- to 68-fold). While weak inverse agonistic properties were determined for the biphenyl carbamates 13m and 13n , neutral antagonism was observed for 14m and 14n and tiotropium under identical assay conditions.

Heparanase cleaves polymeric heparan sulfate (HS) molecules into smaller oligosaccharides, allowing for release of angiogenic growth factors promoting tumor development and autoreactive immune cells to reach the insulin-producing β cells. Interaction of heparanase with HS chains is regulated by specific substrate sulfation sequences. We have synthesized 11 trisaccharides that are highly tunable in structure and sulfation pattern, allowing us to determine how heparanase recognizes HS substrate and selects a favorable cleavage site. Our study shows that (1) N -SO 3 - at +1 subsite and 6- O -SO 3 - at -2 subsite of trisaccharides are critical for heparanase recognition, (2) addition of 2- O -SO 3 - at the -1 subsite and of 3- O -SO 3 - to GlcN unit is not advantageous, and (3) the anomeric configuration (α or β) at the reducing end is crucial in controlling heparanase activity. Our study also illustrates that the α-trisaccharide having N - and 6- O -SO 3 - at -2 and +1 subsites inhibited heparanase and was resistant toward hydrolysis.

In the search for new drug-like selective G-quadruplex binders, a bioinspired design focused on the use of nucleobases as synthons in a multicomponent reaction was herein proved to be viable and successful. Hence, a new class of multifunctionalized imidazo[2,1- i ]purine derivatives, easily synthesized with a convergent approach, allowed for the identification of the first dual BCL2 / c-MYC gene promoter G-quadruplex ligand. Biophysical studies involving circular dichroism melting experiments, microscale thermophoresis measurements, NMR titrations, and computational docking calculations, as well as biological investigations including cytotoxicity and apoptotic assays, and quantitative polymerase chain reaction and Western blot analyses, were performed to assess the potency and to characterize the binding mode of the newly identified lead compound. The absence of toxicity toward normal cells, together with the small molecular weight (≅500 Da), the water solubility, the ease of functionalization, and the selectivity profile, are promising and desirable features to develop G-quadruplex binders as safe and effective anticancer agents.

Protein amyloidosis is related to many neurological disorders. Nanoparticles (NPs) due to their small size can regulate both the polypeptide monomers/oligomers assembly into amyloid fibrils/plaques and the disintegration of the existent plaques. Herein, we have synthesized ZnO nanoflowers and polyol-coated ZnO NPs of relatively small size (40 nm) with cylindrical shape, through solvothermal and microwave-assisted routes, respectively. The effect of the different morphology of nanostructures on the fibrillation/antifibrillation process was monitored in bovine serum albumin (BSA) and human insulin (HI) by fluorescence Thioflavin T (ThT) measurements. Although both nanomaterials affected the amyloid formation mechanism as well as their disaggregation, ZnO nanoflowers with their sharp edges exhibited the greatest amyloid degradation rate in both model proteins (73% and 35%, respectively) and inhibited the most the insulin fibril growth, while restrained also the fibrillation process in the case of albumin solution. In silico molecular docking simulations on the crystal structure of BSA and HI were performed to analyze further the observed in vitro activity of ZnO nanostructures. The binding energy of ZnO NPs was found lower for BSA (-5.44), highlighting their ability to act as catalysts in the fibrillation process of albumin monomers.

Structure-based virtual screening is highly used in the early stages of drug discovery to identify new putative lead compounds for a given target. However, when a small molecule elicits a biological effect, but its target is unknown, or the side effects it causes arise from its undesired interaction with unknown counterparts, the identification of its interacting targets represents an indispensable task. The computational procedure named inverse virtual screening, which relies on docking a molecule (or a small set of compounds) against panels of target proteins to select the most promising complexes, could be useful to overcome these issues. Panels can contain thousands of proteins, and they must be correctly prepared to assure the best docking performance. Therefore, the preparation of panels of proteins collected in the Protein Data Bank ( www.rcsb.org ), if manually performed, may be costly in terms of time and efforts, and this can limit the applicability of this approach in high-throughput virtual screening workflows. We here show an automated workflow to speed up panel preparation and development, and to test its performance, this protocol was initially applied to a panel of 628 viral proteins and, afterward, to a panel of transferase proteins (2789 entries) to perform a large inverse virtual screening study, testing a small set of compounds synthesized in our laboratory. Tankyrase 2 (PARP 5b) was selected as their preferred target of interaction, and the predicted binding was validated by means of surface plasmon resonance experiments. This protocol is useful for the rapid identification of the interacting target for a bioactive compound; accordingly, it facilitates the re-evaluation of the pharmacological activity of known active compounds, addressing the repurposing and the polypharmacology concepts.

Protein misfolding and its deviant self-assembly to converge into amyloid fibrils is associated with the perturbation of cellular functions and thus with debilitating neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, etc. A great deal of research has already been carried out to discover a potential amyloid inhibitor that can slow down, prevent, or remodel toxic amyloids. In the present study with the help of a combination of biophysical, imaging, and computational techniques, we investigated the mechanism of interaction of cholic acid (CA), a primary bile acid, with human insulin and Aβ-42 and found CA to be effective in inhibiting amyloid formation. From ThT data, we inferred that CA encumbers amyloid fibrillation up to 90% chiefly by targeting elongation of fibrils with an insignificant effect on lag time, while in the case of Aβ-42, CA stabilizes the peptide in its native state preventing its fibrillation. Strikingly upon adding initially at the secondary nucleation stage, CA also detained the progression/growth of insulin fibrils. CA is unable to prevent the conformational changes completely during fibrillation but tends to resist and maintain an α helical structure up to a significant extent at a primary nucleation stage while reducing the β sheet rich content at the secondary nucleation stage. Moreover, CA treated samples exhibited reduced cytotoxicity and different morphology. Furthermore, the results obtained after molecular docking indicated that CA is interacting with insulin via hydrogen bonds. For future research, this study can be considered as preliminary research for the development of CA, a metabolite of our body, as a potential therapeutic agent against Alzheimer's disease without even stimulating the immunological responses.

In this study natural-based complex polyphenols, obtained through a smart synthetic approach, have been evaluated for their ability to inhibit the formation of Aβ 42 oligomers, the most toxic species causing synaptic dysfunction, neuroinflammation, and neuronal death leading to the onset and progression of Alzheimer's disease. In vitro neurotoxicity tests on primary hippocampal neurons have been employed to select nontoxic candidates. Solution NMR and molecular docking studies have been performed to clarify the interaction mechanism of Aβ 42 with the synthesized polyphenol derivatives, and highlight the sterical and chemical requirements important for their antiaggregating activity. NMR results indicated that the selected polyphenolic compounds target Aβ 42 oligomeric species. Combined NMR and docking studies indicated that the Aβ 42 central hydrophobic core, namely, the 17-31 region, is the main interaction site. The length of the peptidomimetic scaffold and the presence of a guaiacol moiety were identified as important requirements for the antiaggregating activity. In vivo experiments on an Aβ 42 oligomer-induced acute mouse model highlighted that the most promising polyphenolic derivative (PP04) inhibits detrimental effects of Aβ 42 oligomers on memory and glial cell activation. NMR kinetic studies showed that PP04 is endowed with the chemical features of true inhibitors, strongly affecting both the Aβ 42 nucleation and growth rates, thus representing a promising candidate to be further developed into an effective drug against neurodegenerative diseases of the amyloid type.

Tosedostat is an inhibitor of aminopeptidases currently in phase II clinical trials for the treatment of blood-related cancers. In our laboratories, we have discovered that it possesses analgesic properties. Extensive in vivo pharmacological studies for the determination of antinociceptive effects of tosedostat are presented here. These studies have indicated that the observed analgesic effect of tosedostat stems from its action on the peripheral nervous system with minimal contribution from the central nervous system. Additionally, when given in combination with morphine, tosedostat exerts a synergistic analgesic effect resulting in a reduction of effective dosages required to achieve the same analgesic effect. With broad implications in addressing the opioid addiction crisis, these revelations attest to tosedostat being a highly valuable drug candidate with diverse pharmacological functions.

Tertiary EGFR C797S mutation induced resistance against osimertinib ( 1 ) is an emerging "unmet clinical need" for non-small-cell lung cancer (NSCLC) patients. A series of 5-methylpyrimidopyridone derivatives were designed and synthesized as new selective EGFR L858R/T790M/C797S inhibitors. A representative compound, 8r-B , exhibited an IC 50 of 27.5 nM against the EGFR L858R/T790M/C797S mutant, while being a significantly less potent for EGFR WT (IC 50 > 1.0 μM). Cocrystallographic structure determination and computational investigation were conducted to elucidate its target selectivity.

Polypharmacology is a promising paradigm in modern drug discovery. Herein, we have discovered a series of novel PI3K and HDAC dual inhibitors in which the hydroxamic acid moiety as the zinc binding functional group was introduced to a quinazoline-based PI3K pharmacophore through an appropriate linker. Systematic structure-activity relationship studies resulted in lead compounds 23 and 36 that simultaneously inhibited PI3K and HDAC with nanomolar potencies and demonstrated favorable antiproliferative activities. Compounds 23 and 36 efficiently modulated the expression of p-AKT and Ac-H3, arrested the cell cycle, and induced apoptosis in HCT116 cancer cells. Following pharmacokinetic studies, 23 was further evaluated in HCT116 and HGC-27 xenograft models to show significant in vivo anticancer efficacies with tumor growth inhibitions of 45.8% (po, 150 mg/kg) and 62.6% (ip, 30 mg/kg), respectively. Overall, this work shows promise in discovering new anticancer therapeutics by the approach of simultaneously targeting PI3K and HDAC pathways with a single molecule.

Reports of successful applications of machine learning (ML) methods in structure-based virtual screening (SBVS) are increasing. ML methods such as convolutional neural networks show promising results and often outperform traditional methods such as empirical scoring functions in retrospective validation. However, trained ML models are often treated as black boxes and are not straightforwardly interpretable. In most cases, it is unknown which features in the data are decisive and whether a model's predictions are right for the right reason. Hence, we re-evaluated three widely used benchmark data sets in the context of ML methods and came to the conclusion that not every benchmark data set is suitable. Moreover, we demonstrate on two examples from current literature that bias is learned implicitly and unnoticed from standard benchmarks. On the basis of these results, we conclude that there is a need for eligible validation experiments and benchmark data sets suited to ML for more bias-controlled validation in ML-based SBVS. Therefore, we provide guidelines for setting up validation experiments and give a perspective on how new data sets could be generated.

The metabotropic glutamate 7 (mGlu 7 ) receptor belongs to the group III of mGlu receptors. Since the mGlu 7 receptor can control excitatory neurotransmission in the hippocampus and cortex, modulation of the receptor may have therapeutic benefit in several CNS diseases. However, mGlu 7 remains relatively unexplored among the eight known mGlu receptors partly because of the limited availability of tool compounds to interrogate its potential therapeutic utility. Here we report the discovery of a new class of mGlu 7 allosteric agonists. Hits originating from virtual screening were followed up with further analogue searching and screening, leading to a novel series of mGlu 7 allosteric agonists. Guided by docking into a structural model of the mGlu 7 receptor the initial hit 5 was successfully optimized to analogues with comparable potencies and more attractive drug-like attributes than AMN082.

Human melanocortin-4 receptor (hMC4R) mutations have been implicated as the cause for about 6-8% of all severe obesity cases. Drug-like molecules that are able to rescue the functional activity of mutated receptors are highly desirable to combat genetic obesity among this population of patients. One such molecule is the selective MC4R agonist RM-493 (setmelanotide). While this molecule has been shown to activate mutated receptors with 20-fold higher potency over the endogenous agonist, little is known about its binding mode and how it effectively interacts with hMC4R despite the presence of mutations. In this study, a MC4R homology model was constructed based on the X-ray crystal structure of the adenosine A2A receptor in the active state. Four MC4R mutations commonly found in genetically obese patients and known to effect ligand binding in vitro were introduced into the constructed model. RM-493 was then docked into the wild-type and mutated models in order to better elucidate the possible binding modes for this promising drug candidate and assess how it may be interacting with MC4R to effectively activate receptor polymorphisms. The results reflected the orthosteric interactions of both the endogenous and synthetic ligands with the MC4R, which is supported by the site-directed mutagenesis studies. Meanwhile it helped explain the decremental affinity and potency of these ligands with the receptor polymorphisms. More significantly, our findings indicated that the structural characteristics of RM-493 may allow for enhanced receptor-ligand interactions, particularly through those with the putative allosteric binding sites, which facilitated the ligand to stabilize the active state of native and mutant MC4Rs to maintain reasonably high affinity and potency.

Alzheimer's disease is likely to be caused by copathogenic factors including aggregation of Aβ peptides into oligomers and fibrils, neuroinflammation, and oxidative stress. To date, no effective treatments are available, and because of the multifactorial nature of the disease, it emerges the need to act on different and simultaneous fronts. Despite the multiple biological activities ascribed to curcumin as neuroprotector, its poor bioavailability and toxicity limit the success in clinical outcomes. To tackle Alzheimer's disease on these aspects, the curcumin template was suitably modified and a small set of analogues was attained. In particular, derivative 1 turned out to be less toxic than curcumin. As evidenced by capillary electrophoresis and transmission electron microscopy studies, 1 proved to inhibit the formation of large toxic Aβ oligomers, by shifting the equilibrium toward smaller nontoxic assemblies and to limit the formation of insoluble fibrils. These findings were supported by molecular docking and steered molecular dynamics simulations which confirmed the superior capacity of 1 to bind Aβ structures of different complexity. Remarkably, 1 also showed in vitro anti-inflammatory and antioxidant properties. In summary, the curcumin-based analogue 1 emerged as multipotent compound worthy to be further investigated and exploited in the Alzheimer's disease multitarget context.

Engineering of assembly line polyketide synthases (PKSs) to produce novel bioactive compounds has been a goal for over 20 years. The apparent modularity of PKSs has inspired many engineering attempts in which entire modules or single domains were exchanged. In recent years, it has become evident that certain domain-domain interactions are evolutionarily optimized and, if disrupted, cause a decrease of the overall turnover rate of the chimeric PKS. In this study, we compared different types of chimeric PKSs in order to define the least invasive interface and to expand the toolbox for PKS engineering. We generated bimodular chimeric PKSs in which entire modules were exchanged, while either retaining a covalent linker between heterologous modules or introducing a noncovalent docking domain, or SYNZIP domain, mediated interface. These chimeric systems exhibited non-native domain-domain interactions during intermodular polyketide chain translocation. They were compared to otherwise equivalent bimodular PKSs in which a noncovalent interface was introduced between the condensing and processing parts of a module, resulting in non-native domain interactions during the extender unit acylation and polyketide chain elongation steps of their catalytic cycles. We show that the natural PKS docking domains can be efficiently substituted with SYNZIP domains and that the newly introduced noncovalent interface between the condensing and processing parts of a module can be harnessed for PKS engineering. Additionally, we established SYNZIP domains as a new tool for engineering PKSs by efficiently bridging non-native interfaces without perturbing PKS activity.

Glycogen synthase kinase-3β (GSK-3β) is a key enzyme in hyperphosphorylation of tau proteins and is a promising therapeutic target in Alzheimer's disease (AD). Here, we reported, for the first time, that the stereoisomers of Schisandrin B (Sch B), (+)-1, (-)-1, (+)-2, and (-)-2, were potent GSK-3β inhibitors. They were demonstrated to selectively target GSK-3β in an orthosteric binding mode, with IC 50 values of 340, 290, 80, and 70 nM, respectively. Further study showed that these stereoisomers can significantly increase the expression of p-GSK-3β (Ser9) and decrease the expressions of p-GSK-3β (Tyr216) and p-GSK-3β (Tyr279). Finally, these compounds can alleviate the cell injury induced by Aβ, and the cognitive disorders in AD mice, especially (+)-2 and (-)-2. Collectively, the stereoisomers of Sch B, especially (+)-2 and (-)-2, were found to be potential selective ATP-competitive GSK-3β inhibitors, which further affected their anti-AD effects. These promising findings explained the biological target of Sch B in AD, and bring a new understanding in the stereochemistry and bioactivities of Sch B.

Neuroinflammation underlies many neuro-degenerative diseases. In this paper, we report the identification of a new pterocarpan-type anti-inflammatory compound named sophotokin isolated from Sophora tonkinensis. S. tonkinensis has been used traditionally for treatment of conditions related to inflammation. Our initial screening showed that sophotokin dose-dependently inhibits lipopolysaccharide (LPS)-stimulated production of NO, TNF-α, PGE2, and IL-1β in microglial cells. This antineuroinflammatory effect was associated with sophotokin's blockade of LPS-induced production of the inflammatory mediators iNOS and COX-2. Western blot and qPCR analysis demonstrated that sophotokin inhibits both the p38-MAPK and NF-κB signal pathways. Further studies revealed that sophotokin also suppresses the expression of cluster differentiation 14 (CD14) in the toll-like receptor 4 (TLR4) signaling pathway. Following down-regulation of MyD88 and TRAF6, sophotokin inhibits the activation of the NF-κB and MAPK signal pathways in LPS-induced BV-2 cells. In silico studies suggested that sophotokin could interact with PU.1-DNA complex through hydrogen binding at sites 1 and 2 of the complex, blocking the DNA binding. This suggests that PU.1 may be a potential target of sophotokin. Taken together, these results suggest that sophotokin may have therapeutic potential for diseases related to neuroinflammation. The mechanism of antineuroinflammatory effects involves inhibition of the TLR4 signal pathway at the sites of NF-κB and MAPK with PU.1 as a likely upstream target.

Treating Alzheimer's disease (AD) is a major challenge at the moment with no new drugs available to cure this devastating neurodegenerative disorder. In this regard, drug repurposing, which aims to determine novel therapeutic usage for drugs already approved by the regulatory agencies, is a pragmatic approach to discover novel treatment strategies. Selective serotonin reuptake inhibitors (SSRIs) are a known class of United States Food and Drug Administration approved drugs used in the treatment of depression. We investigated the ability of SSRIs fluvoxamine, fluoxetine, paroxetine, sertraline, and escitalopram on Aβ42 aggregation and fibrillogenesis. Remarkably, the aggregation kinetic experiments carried out demonstrate the anti-Aβ42 aggregation activity of SSRIs fluoxetine, paroxetine, and sertraline at all the tested concentrations (1, 10, 50, and 100 μM). Both fluoxetine and paroxetine were identified as the most promising SSRIs, showing 74.8 and 76% inhibition of Aβ42 aggregation at 100 μM. The transmission electron microscopy experiments and dot-blot study also demonstrate the ability of fluoxetine and paroxetine to prevent Aβ42 aggregation and fibrillogenesis, providing further evidence. Investigating the binding interactions of fluoxetine and paroxetine in the Aβ42 oligomer and fibril models derived from the solid-state NMR structure suggests that these SSRIs interact at a region close to the N-terminal (Lys16-Glu22) in the S-shaped cross-β-strand assembly and reduce Aβ42 fibrillogenesis. On the basis of this study, a pharmacophore model is proposed which shows that the minimum structural requirements to design novel Aβ42 aggregation inhibitors include the presence of one ionizable group, one hydrophobic group, two aromatic rings, and two hydrogen bond donor groups. These studies demonstrate that SSRIs have the potential to prevent Aβ42 aggregation by direct binding and could be beneficial to AD patients on SSRIs.

In this paper, we describe the latest results involving molecular modeling and pharmacodynamic studies of the selected highly lipophilic compounds acting by human GABA transporter 1 (hGAT1) inhibition. The chemical interaction of 17 GABA analogues with a model of hGAT1 is described using the molecular docking method. The biological role of GAT1 is related to the regulation of GABA level in the central nervous system and GAT1 inhibition plays an important role in the control of seizure threshold. To confirm that GAT1 can be also a molecular target for drugs used to treat other neurological and psychiatric diseases (e.g., pain and anxiety), in the in vivo part of this study, potential antinociceptive and anxiolytic-like properties of tiagabine, a selective GAT1 inhibitor, are described.

The discovery of extended catalytic versatilities is of great importance in both the chemistry and biotechnology fields. Fatty acid amide hydrolase (FAAH) belongs to the amidase signature superfamily and is a major endocannabinoid inactivating enzyme using an atypical catalytic mechanism involving hydrolysis of amide and occasionally ester bonds. FAAH inhibitors are efficacious in experimental models of neuropathic pain, inflammation, and anxiety, among others. We report a new multitarget drug, AGN220653, containing a carboxyamide-4-oxazole moiety and endowed with efficacious analgesic and anti-inflammatory activities, which are partly due to its capability of achieving inhibition of FAAH, and subsequently increasing the tissue concentrations of the endocannabinoid anandamide. This inhibitor behaves as a noncompetitive, slowly reversible inhibitor. Autoradiography of purified FAAH incubated with AGN220653, opportunely radiolabeled, indicated covalent binding followed by fragmentation of the molecule. Molecular docking suggested a possible nucleophilic attack by FAAH-Ser241 on the carbonyl group of the carboxyamide-4-oxazole moiety, resulting in the cleavage of the C-C bond between the oxazole and the carboxyamide moieties, instead of either of the two available amide bonds. MRM-MS analyses only detected the Ser241-assisted formation of the carbamate intermediate, thus confirming the cleavage of the aforementioned C-C bond. Quantum mechanics calculations were fully consistent with this mechanism. The study exemplifies how FAAH structural features and mechanism of action may override the binding and reactivity propensities of substrates. This unpredicted mechanism could pave the way to the future development of a completely new class of amidase inhibitors, of potential use against pain, inflammation, and mood disorders.

A series of dual-target AChE/PDE9A inhibitor compounds were designed, synthesized, and evaluated as anti-Alzheimer's Disease (AD) agents. Among these target compounds, 11a (AChE: IC 50 = 0.048 μM; PDE9A: IC 50 = 0.530 μM) and 11b (AChE: IC 50 = 0.223 μM; PDE9A: IC 50 = 0.285 μM) exhibited excellent and balanced dual-target AChE/PDE9A inhibitory activities. Meanwhile, those two compounds possess good blood-brain barrier (BBB) penetrability and low neurotoxicity. Especially, 11a and 11b could ameliorate learning deficits induced by scopolamine (Scop). Moreover, 11a could also improve cognitive and spatial memory in Aβ 25-35 -induced cognitive deficit mice in the Morris water-maze test. In summary, our research developed a series of potential dual-target AChE/PDE9A inhibitors, and the data indicated that 11a was a promising candidate drug for the treatment of AD.

Increased interest in covalent drug discovery led to the development of computer programs predicting binding mode and affinity of covalent inhibitors. Here we compare the performance of six covalent docking tools, AutoDock4, CovDock, FITTED, GOLD, ICM-Pro, and MOE, for reproducing experimental binding modes in an unprecedently large and diverse set of covalent complexes. It was found that 40-60% of the top scoring ligand poses are within 2.0 Å RMSD from the experimental binding mode. This rate showed program dependent increase and achieved 50-90% when the best RMSD among the top ten scoring poses was considered. This performance is comparable to that of noncovalent docking tools and therefore suggests that anchoring the ligand does not necessarily improve the accuracy of the prediction. The effect of various ligand and protein features on the docking performance was investigated. At the level of warhead chemistry, higher success rate was found for Michael additions, nucleophilic additions and nucleophilic substitutions than for ring opening reactions and disulfide formation. Increasing ligand size and flexibility generally affects pose predictions unfavorably, although AutoDock4, FITTED, and ICM-Pro were found to be less sensitive up to 35 heavy atoms. Increasing the accessibility of the target cysteine tends to result in improved binding mode predictions. Docking programs show protein dependent performance suggesting a target-dependent choice of the optimal docking tool. It was found that noncovalent docking into Cys/Ala mutated proteins by ICM-Pro and Glide reproduced experimental binding modes with only slightly lower performance and at a significantly lower computational expense than covalent docking did. Overall, our results highlight the key factors influencing the docking performance of the investigated tools and they give guidelines for selecting the optimal combination of warheads, ligands, and tools for the system investigated. Results also identify the most important aspects to be considered for developing improved protocols for docking and virtual screening of covalent ligands.

Bacterial exopolymer Levan (β-(2,6) polyfructan) synthesized by levansucrase has attracted interest for various applications due to its low intrinsic viscosity compared with other polysaccharides. We report a novel levansucrase (Lsc) isolated from Sphingobium chunbukense DJ77 and verify its biochemical characteristics by comparative analysis of molecular docking analysis (MOE) and catalytic residue analysis. The complete sequence of the Lsc encoding gene ( lsc) was cloned under the direction of the T7 promoter and purified in an Escherichia coli BL21 (DE3) protein expression system. The enzyme activity analysis and ligand docking MOE study of S. chungbukense DJ77 Lsc revealed that Arg 77, Ser112, Arg 195, Asp196, Glu257, and Gln275 were involved in the sucrose binding and splitting as well as transfructosylation activity. A catalytic comparison of Lsc of S. chungbukense DJ77 with the results of site-directed mutational analysis indicated that Gln275 may coordinate a favorable substrate binding environment, offering broad pH resistance in the range of 5-10. The results suggest that the recombinant E. coli carrying S. chungbukense DJ77 Lsc might produce levan under the regular growth conditions with less need for pH manipulation.

Modulation of multiple biological targets with a single drug can lead to synergistic therapeutic effects and has been demonstrated to be essential for efficient treatment of CNS disorders. However, rational design of compounds that interact with several targets is very challenging. Here, we demonstrate that structure-based virtual screening can guide the discovery of multi-target ligands of unrelated proteins relevant for Parkinson's disease. A library with 5.4 million molecules was docked to crystal structures of the A 2A adenosine receptor (A 2A AR) and monoamine oxidase B (MAO-B). Twenty-four compounds that were among the highest ranked for both binding sites were evaluated experimentally, resulting in the discovery of four dual-target ligands. The most potent compound was an A 2A AR antagonist with nanomolar affinity ( K i = 19 nM) and inhibited MAO-B with an IC 50 of 100 nM. Optimization guided by the predicted binding modes led to the identification of a second potent dual-target scaffold. The two discovered scaffolds were shown to counteract 6-hydroxydopamine-induced neurotoxicity in dopaminergic neuronal-like SH-SY5Y cells. Structure-based screening can hence be used to identify ligands with specific polypharmacological profiles, providing new avenues for drug development against complex diseases.

Metabotropic glutamate receptor 5 (mGlu 5 ) plays a key role in synaptic information storage and memory, which is a well-known target for a variety of psychiatric and neurodegenerative disorders. In recent years, the increasing efforts have been focused on the design of allosteric modulators, and the negative allosteric modulators (NAMs) are the front-runners. Recently, the architecture of the transmembrane (TM) domain of mGlu 5 receptor has been determined by crystallographic experiment. However, it has been not well understood how the pharmacophores of NAMs accommodated into the allosteric binding site. In this study, molecular dynamics (MD) simulations were performed on mGlu 5 receptor bound with NAMs in preclinical or clinical development to shed light on this issue. In order to identify the key residues, the binding free energies as well as per-residue contributions for NAMs binding to mGlu 5 receptor were calculated. Subsequently, the in silico site-directed mutagenesis of the key residues was performed to verify the accuracy of simulation models. As a result, the shared common features of the studied 5 clinically important NAMs (mavoglurant, dipraglurant, basimglurant, STX107, and fenobam) interacting with 11 residues in allosteric site were obtained. This comprehensive study presented a better understanding of mGlu 5 receptor NAMs binding mechanism, which would be further used as a useful framework to assess and discover novel lead scaffolds for NAMs.

The multitarget approach is a promising paradigm in drug discovery, potentially leading to new treatment options for complex disorders, such as Alzheimer's disease. Herein, we present the discovery of a unique series of 1-benzylamino-2-hydroxyalkyl derivatives combining inhibitory activity against butyrylcholinesterase, β-secretase, β-amyloid, and tau protein aggregation, all related to mechanisms which underpin Alzheimer's disease. Notably, diphenylpropylamine derivative 10 showed balanced activity against both disease-modifying targets, inhibition of β-secretase (IC 50  hBACE-1 = 41.60 μM), inhibition of amyloid β aggregation (IC 50 Aβ = 3.09 μM), inhibition of tau aggregation (55% at 10 μM); as well as against symptomatic targets, butyrylcholinesterase inhibition (IC 50  hBuChE = 7.22 μM). It might represent an encouraging starting point for development of multifunctional disease-modifying anti-Alzheimer's agents.

Fragment-based drug discovery (FBDD) has become a mainstream approach in drug design because it allows the reduction of the chemical space and screening libraries while identifying fragments with high protein-ligand efficiency interactions that can later be grown into drug-like leads. In this work, we leverage high-throughput molecular dynamics (MD) simulations to screen a library of 129 fragments for a total of 5.85 ms against the CXCL12 monomer, a chemokine involved in inflammation and diseases such as cancer. Our in silico binding assay was able to recover binding poses, affinities, and kinetics for the selected library and was able to predict 8 mM-affinity fragments with ligand efficiencies higher than 0.3. All of the fragment hits present a similar chemical structure, with a hydrophobic core and a positively charged group, and bind to either sY7 or H1S68 pockets, where they share pharmacophoric properties with experimentally resolved natural binders. This work presents a large-scale screening assay using an exclusive combination of thousands of short MD adaptive simulations analyzed with a Markov state model (MSM) framework.

We recently generalized the formerly alignment-dependent multivariate image analysis applied to quantitative structure-activity relationships (MIA-QSAR) method through the application of the discrete Fourier transform (DFT), allowing for its application to noncongruent and structurally diverse chemical compound data sets. Here we report the first practical application of this method in the screening of molecular entities of therapeutic interest, with human aromatase inhibitory activity as the case study. We developed an ensemble classification model based on the two-dimensional (2D) DFT MIA-QSAR descriptors, with which we screened the NCI Diversity Set V (1593 compounds) and obtained 34 chemical compounds with possible aromatase inhibitory activity. These compounds were docked into the aromatase active site, and the 10 most promising compounds were selected for in vitro experimental validation. Of these compounds, 7419 (nonsteroidal) and 89 201 (steroidal) demonstrated satisfactory antiproliferative and aromatase inhibitory activities. The obtained results suggest that the 2D-DFT MIA-QSAR method may be useful in ligand-based virtual screening of new molecular entities of therapeutic utility.

The present investigation was aimed to prepare inclusion complexes of a therapeutically important nonsteroidal anti-inflammatory drug, etodolac (ETD) with hydroxypropyl-beta-cyclodextrin (HP-β-CD) and to study the effect of l-arginine (l-Arg) as an auxiliary agent on the complexation efficiency of HP-β-CD to improve aqueous solubility and the dissolution property of ETD. The binary and ternary complexes were prepared by physical mixing, coevaporation, and spray drying methods. The complexes were characterized using differential scanning colorimetry (DSC), Fourier transform-infrared spectroscopy (FT-IR), and powder X-ray diffraction (PXRD) studies. The mechanism of inclusion interaction of guest and host was established through 1 H NMR, molecular docking, and molecular dynamics studies. On the basis of preliminary screening studies, l-Arg was found to be the most efficient auxiliary agent for the present research problem. The change in crystallinity of ETD was evident from DSC and PXRD studies which indicated the formation of new solid forms. A remarkable increase in apparent stability constant (K c ) and complexation efficiency (CE) of HP-β-CD was observed in the presence of l-Arg in ternary complexes with improvement in solubility and dissolution of ETD than binary complexes. However, inclusion complexes of ETD obtained by computational studies is in good correlation with the results obtained through experimental methods. More stable complex formation with l-Arg was confirmed by molecular simulation studies too. Thus, the present study led to the conclusion that the ternary complex of ETD-HP-β-CD-l-Arg could be an innovative approach to augment the solubility and dissolution behavior of ETD.

In this work, we propose a deep learning approach to improve docking-based virtual screening. The deep neural network that is introduced, DeepVS, uses the output of a docking program and learns how to extract relevant features from basic data such as atom and residues types obtained from protein-ligand complexes. Our approach introduces the use of atom and amino acid embeddings and implements an effective way of creating distributed vector representations of protein-ligand complexes by modeling the compound as a set of atom contexts that is further processed by a convolutional layer. One of the main advantages of the proposed method is that it does not require feature engineering. We evaluate DeepVS on the Directory of Useful Decoys (DUD), using the output of two docking programs: Autodock Vina1.1.2 and Dock 6.6. Using a strict evaluation with leave-one-out cross-validation, DeepVS outperforms the docking programs, with regard to both AUC ROC and enrichment factor. Moreover, using the output of Autodock Vina1.1.2, DeepVS achieves an AUC ROC of 0.81, which, to the best of our knowledge, is the best AUC reported so far for virtual screening using the 40 receptors from the DUD.