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The Tyr-Pro (YP) dipeptide can serve as an adiponectin receptor 1 (AdipoR1) agonist. We thus investigated the AdipoR1-agonistic potential of YP-related tripeptides in the soybean protein sequence. Among the 17 soybean candidate tripeptides, those elongated at the C-terminus of YP (0.1 μM YPG, 140 ± 16%; 0.1 μM YPE, 141 ± 22%; 0.1 μM YPP, 145 ± 19%; 0.1 μM YPQ, 143 ± 20%; p < 0.05) significantly promoted glucose uptake by L6 muscle myotubes, comparable to the effect of 0.1 μM AdipoRon (163 ± 52%, p < 0.05). The knockdown of AdipoR1 expression in L6 cells abrogated this effect of YPG and YPP, indicating that the two tripeptides had an AdipoR1 agonistic effect. CHARMM-GUI-aided molecular dynamics simulation in a virtual phospholipid membrane revealed that YPG and YPP were stably positioned at the binding pockets of AdipoR1 (binding free energy < −10 kcal/mol). These findings demonstrate that the tripeptides YPG and YPP, with AdipoR1 agonistic YP sequences, have alternative adiponectin-like potential via their preferential binding to AdipoR1.

Hi, I have uploaded the input data for MD simulation undertaken for the IFD pose of compound 77 bound to AR, using 1T7R pdb structure of AR.

The ability to engineer synthetic polymers with the same structural precision as biomacromolecules is crucial to enable the de novo design of robust nanomaterials with biomimetic function. Peptoids, poly(N-substituted) glycines, are a highly controllable bio-inspired polymer family that can assemble into a variety of functional, crystalline nanostructures over a wide range of sequences. Extensive investigation on the molecular packing in these lattices has been reported; however, many key atomic-level details of the molecular structure remain underexplored. Here, we use cryo-TEM 3D reconstruction to directly visualize the conformation of an individual polymer chain within a peptoid nanofiber lattice in real space at 3.6 Å resolution. The backbone in the N-decylglycine hydrophobic core is shown to clearly adopt an extended, all-cis-sigma strand conformation, as previously suggested in many peptoid lattice models. We also show that packing interactions (covalent and noncovalent) at the solvent-exposed N-termini have a dominant impact on the local chain ordering and hence the ability of the chains to pack into well-ordered lattices. Peptoids in pure water form fibers with limited growth in the a direction (

The COVID-19 is still pandemic due to emerging of the various variant of concern of SARS-CoV2. Hence it is devastating the world, causing significant economic as well as social chaos. This needs great effort to search and develop effective alternatives along with vaccination. Therefore to continue drug discovery endeavors, we used chalcone derivatives to find an effective drug candidate against SARS-CoV2. Chalcone is a common simple scaffold that exists in many diets as well as in traditional medicine. Natural as well as synthetic chalcones have shown numerous interesting biological activities and are also effective in fighting various diseases. Hence various computational methods were applied to find out potential inhibitors of 3CLPro using a library of 3000 compounds of chalcones. Firstly the screening by structure-based pharmacophore model yielded 84 hits that were subjected to molecular docking. The top 10 docked compounds were characterized for stability by using 100 nanoseconds (ns) molecular dynamic (MD) simulation approach. Further, the binding free energy calculation by MMPBSA showed that four compounds bind to 3CLPro enzyme with high affinity i.e., -87.962(KJ/mol), -66.125 (KJ/mol), -59.589(KJ/mol), and -66.728(KJ/mol) respectively. Since chalcone is a common simple scaffold that is present in many diets as well as in traditional medicine, we suggest that screened compounds may emerge as promising drug candidates for SARS-CoV-2. These compounds may be investigated in vitro to evaluate the efficacy againstSARS-CoV-2.

The“RAS-RAF-MEK-ERK” pathway is an important signaling pathway in melanoma. BRAFV600E(70–90%) is the most common mutation in this pathway. BRAF inhibitors have four types of conformers: type I (aC-IN/DFG-IN), type II (aC-IN/DFG-OUT), type I1/2(aC-OUT/DFG-IN), and type I/II (aC-OUT/DFG-OUT). First-and second-generation BRAF inhibitors show resistance to BRAFV600Eand are ineffective against malignancies induced by dimer BRAF mutants causing ‘paradoxical’ activation. In the present study, we performed molecular modeling of pyrimidine–sulfonamide hybrids inhibitors using 3D-QSAR, molecular docking, and molecular dynamics simulations. Previous reports reveal the importance of pyrimidine and sulfonamide moieties in the development of BRAFV600E inhibitors. Analysis of 3D-QSAR models provided novel pyrimidine sulfonamide hybrid BRAFV600E inhibitors. The designed compounds share similarities with several structural moieties present in first- and second-generation BRAF inhibitors. A total library of 88 designed compounds was generated and molecular docking studies were performed with them. Four molecules (T109, T183, T160, and T126) were identified as hits and selected for detailed studies. Molecular dynamics simulations were performed at 900 ns and binding was calculated. Based on molecular docking and simulation studies, it was found that the designed compounds have better interactions with the core active site [the nucleotide (ADP or ATP) binding site, DFG motif, and the phospho-acceptor site (activation segment) of BRAFV600E protein than previous inhibitors. Similar to the FDA-approved BRAFV600E inhibitors the developed compounds have [aC-OUT/DFG-IN] conformation. Compounds T126, T160 and T183 interacted with DIF (Leu505), making them potentially useful against BRAFV600E resistance and malignancies induced by dimer BRAF mutants. The synthesis and biological evaluation of the designed molecules is in progress, which may lead to some potent BRAFV600E selective inhibitors.

Peptide separations by reversed-phase liquid chromatography (RPLC) are an integral part of bottom-up proteomics. These separations typically employ C18 columns with water/acetonitrile gradient elution in the presence of formic acid. Despite the widespread use of such workflows, the exact nature of peptide interactions with the stationary and mobile phases are poorly understood. Here we employ microsecond molecular dynamics (MD) simulations to uncover details of peptide RPLC. We examined two tryptic peptides, a hydrophobic and a hydrophilic species, in a slit pore lined with C18 chains that were grafted onto SiO2 support. Our simulations explored peptide trapping, followed by desorption and elution. Trapping in an aqueous mobile phase was initiated by C18 contacts with Lys butyl moieties. This was followed by extensive anchoring of nonpolar side chains (Leu/Ile/Val) in the C18 layer. Exposure to water/acetonitrile triggered peptide desorption in a stepwise fashion; charged sites close to the termini were the first to lift off, followed by the other residues. During water/acetonitrile elution, both peptides preferentially resided close to the pore center. The hydrophilic peptide exhibited no contacts with the stationary phase under these conditions. In contrast, the hydrophobic species underwent multiple transient Leu/Ile/Val binding interactions with C18 chains. These nonpolar interactions represent the foundation of differential peptide retention, in agreement with the experimental elution behavior of the two peptides. Extensive peptide/formate ion pairing was observed in water/acetonitrile, particularly at N-terminal sites. Overall, this work uncovers an unprecedented level of RPLC molecular details, paving the way for MD simulations as a future tool for improving retention prediction algorithms, and for the design of novel column materials.

Files needed for molecular simulation using GROMACS (top, gro, itp files) of polyethylene glycol (PEG200) Bash and python scripts to analyze obtained simulation trajectories

New pseudonucleosides containing cyclic sulfamide moiety and sulfamoyl β-D-glucosamine derivative are described. These pseudonucleosides are synthesized in good yields starting from chlorosulfonyl isocyanate and β-D-glucosamine hydrochloride in five steps; (protection, acetylation, removal of the Boc group, sulfamoylation, and cyclization). Further, novel glycosylated sulfamoyloxazolidin-2-one is prepared in three steps; carbamoylation, sulfamoylation, and intramolecular cyclization. The structures of the synthesized compounds were confirmed by usual spectroscopic and spectrometric methods NMR, IR, MS, and EA. Interesting molecular docking of the prepared pseudonucleosides and (Beclabuvir, Remdesivir) drugs with SARS-CoV-2/Mpro (PDB:5R80) was conducted using the same parameters for a fair comparison. A low binding affinity of the synthesized compounds compared to the Beclabuvir and other analysis showed that pseudonucleosides have the ability to inhibit SARS-CoV-2. After the motivating results of molecular docking study, the complex between the SARS-CoV-2 Mpro and compound 7 was subjected to 100 ns molecular dynamics (MD) simulation using Desmond module of Schrodinger suite, during which the receptor-ligand complex showed substantial stability after 10 ns of MD simulation. Also, we studied the prediction of absorption, distribution, properties of metabolism, excretion, and toxicity (ADMET) of the synthesized compounds. Communicated by Ramaswamy H. Sarma

In numerous studies the application of the molecular dynamics scheme based on reactive force field (ReaxFF) method has been proven effective in modeling catalytic behavior of metallic- organic compounds [1]. Recently, the method has been successfully applied for MOx (M=Cu, Fe, Mn, Ni) transition-metal oxides [2]. Yet, the problem arose during this analysis, since not all the force field parameters were available at the time. To bridge this gap, the force field for modeling mixed metal oxides had to be developed. For Mn-Fe bond, this was done within the work presented in a recent conference [3]. Here we establish the remaining two needed force field parameter sets (namely, Cu-Mn and Ni-Mn) and apply them to the problem of toluene adsorption on such catalyst mixed metal-oxide surfaces in order to verify their validity. The training set consisted of at least 10 crystal structures containing at minimum Ni-Mn-O or Cu-Mn-O atoms obtained from the Material project database [4]. The parameter training has been done using the in-home compiled version of the ReaxFF code. After training the force fields for geometry reproduction, the parameters were refined using the optimization by atom charges, comparing the ReaxFF values to those obtained for the respective structures using periodic crystal DFT codes implemented in Quantum Espresso [5] and Abinit [6]. [1] T. P. Senftle et al, npj Comput Mater, 2 15011 (2016). [2] M. Duplančić, V. Gomzi, A. Pintar, S. Kurajica, V. Tomašić, Ceramics Int. 47(3), 3108- 3121 (2021). [3] V. Gomzi, M. Duplančić, V. Tomašić Reactive force field optimization and MnFeO3 catalyst theoretical investigation, 18th Ruzicka Days, September 16–18, 2020 / Vukovar, Croatia. [4] (a) A. Jain, S.P. Ong et al, APL Materials, 1(1), 011002 (2013). (b) S. P. Ong et al, Comp. Mat. Sci., 68, 314–319 (2013). [5] (a) P. Giannozzi et. al., J.Phys.:Condens.Matter 21, 395502 (2009) (b) P Giannozzi et al, J.Phys.:Condens.Matter 29, 465901 (2017) (c) P. Giannozzi et al, J. Chem. Phys. 152, 154105 (2020). [6] X. Gonze et al, Comput. Phys. Commun. 248, 107042 (2020).

The volume of tailings in the world has increased rapidly in recent years, which poses a substantial ecological threat. With the objective of reducing negative impacts on environment and reuse the abandoned slate tailings, the possibility of making eco-friendly unburned bricks by using slate tailings from Shaanxi Province of China was investigated. Raw materials included slate tailings, fly ash and cement, and bricks were produced through the process of mixing, molding, and curing. The optimal compressive strength of the product was found at the slate tailings: fly ash: cement = 5:2:3 (wt.%) with 7-day curing at room temperature and 1-day curing in oven, and the forming water content is 15 wt.%. Under these conditions, the compressive strength and water absorption rate were 26 MPa and 14.32% respectively. Other physical properties and durability conform to the Chinese GB/T4111-2013 standard for test methods for concrete blocks and bricks and the Chinese JC/T422-2007 standard for unfired bricks made of tailings. In addition, a variety of methods were combined to explore the formation mechanism. The phase composition, chemical structure and microstructure of the brick are analyzed by XRD, SEM and AFM. Finally, molecular dynamics (MD) was used to simulate main cementation component, the hydrated calcium silicate (C–S–H) gel, to advance the understanding of mechanical properties of brick at the nanoscale. The results show that the C–S–H gel formed in the curing process acted as the main adhesive component, and the slate tailings are mainly worked as aggregate skeleton to provide support strength for unburned bricks.

Graphical abstract COVID-19, the disease caused by SARS-CoV-2, has been declared as a global pandemic. Traditional medicinal plants have long history to treat viral infections. Our in silico approach suggested that unique phytocompounds such as emodin, thymol and carvacrol, and artemisinin could physically bind SARS-CoV-2 spike glycoproteins (6VXX and 6VYB), SARS-CoV-2 B.1.351 South Africa variant of Spike glycoprotein (7NXA), and even with ACE2 and prevent the SARS-CoV-2 binding to the host ACE2, TMPRSS2 and neutrapilin-1 receptors. Since Chloroquine has been looked as potential therapy against COVID-19, we also compared the binding of chloroquine and artemisinin for its interaction with spike proteins (6VXX, 6VYB) and its variant 7NXA, respectively. Molecular docking study of phytocompounds and SARS-CoV-2 spike protein was performed by using AutoDock/Vina software. Molecular dynamics (MD) simulation was performed for 50ns. Among all the phytocompounds, molecular docking studies revealed lowest binding energy of artemisinin with 6VXX and 6VYB, with Etotal −10.5 KJ mol−1 and −10.3 KJ mol−1 respectively. Emodin showed the best binding affinity with 6VYB with Etotal −8.8 KJ mol−1and SARS-CoV-2 B.1.351 variant (7NXA) with binding energy of −6.4KJ mol−1. Emodin showed best interactions with TMPRSS 2 and ACE2 with Etotal of −7.1 and −7.3 KJ mol−1 respectively, whereas artemisinin interacts with TMPRSS 2 and ACE2 with Etotal of −6.9 and −7.4 KJ mol−1 respectively. All the phytocompounds were non-toxic and non-carcinogenic. MD simulation showed that artemisinin has more stable interaction with 6VYB as compared to 6VXX, and hence proposed as potential phytochemical to prevent SARS-CoV-2 interaction with ACE-2 receptor. Supplementary Information The online version contains supplementary material available at 10.1007/s40495-021-00259-4.

Surfaces with microscale roughness can entail dual-scale hierarchical structures such as the recently reported nano/microstructured surfaces produced in the laboratory (Wang et al. Nature2020, 582, 55−5732494077). However, how the dual-scale hierarchical structured surface affects the apparent wetting/dewetting states of a water droplet, and the transitions between the states are still largely unexplored. Here, we report a systematic large-scale molecular dynamics (MD) simulation study on the wetting/dewetting states of water droplets on various dual-scale nano/near-submicrometer structured surfaces. To this end, we devise slab-water/slab-substrate model systems with a variety of dual-scale surface structures and with different degrees of intrinsic wettability (as measured based on the counterpart smooth surface). The dual-scale hierarchical structure can be described as “nanotexture-on-near-submicrometer-hill”. Depending on three prototypical nanotextures, our MD simulations reveal five possible wetting/dewetting states for a water droplet: (i) Cassie state; (ii) infiltrated upper-valley state; (iii) immersed nanotexture-on-hill state; (iv) infiltrated valley state; and (v) Wenzel state. The transitions between these wetting/dewetting states are strongly dependent on the intrinsic wettability (Ein), the initial location of the water droplet, the height of the nanotextures (H1), and the spacing between nanotextures (W1). Notably, Ein–H1 and Ein–W1 diagrams show that regions of rich wetting/dewetting states can be identified, including regions where between one to five states can coexist.

Despite the intense research work since the beginning of the pandemic, the pathogenesis of COVID-19 is not yet clearly understood. The previous mechanism of COVID-19, based on ACE2 tropism and explained through a single receptor, is insufficient to explain the pathogenesis due to the absence of angiotensin-converting enzyme 2 (ACE2) receptors in most of the affected organs. In the current study, we used the PatchDock server to run a molecular docking study of both the gonadotropin-releasing hormone receptor (GnRHR) and G-protein-coupled-receptor (GPCR) with the SARS-CoV-2 spike protein. Molecular Dynamics (MD) simulations were run to analyze the stability of the complexes using the GROMACS package. The docking results showed a high affinity between the spike protein with the GnRHR (−1424.9 kcal/mol) and GPCR (−1451.8 kcal/mol). The results of the MD simulations revealed the significant stability of the spike protein with the GnRHR and GPCR up to 100 ns. The SARS-CoV-2 spike protein had strong binding interactions with the GPCRs and GnRHRs, which are highly expressed in the brain, endocrine organs, and olfactory neurons. This study paves the way towards understanding the complex mechanism of neuroendocrine involvement and peripheral organ involvement, may explain the changing symptoms in patients due to new variants, and may lead to the discovery of new drug targets for COVID-19. In vitro studies involving genetic engineering or gene knockdown of the GPCRs and GnRHRs are needed to further investigate the role of these receptors in COVID-19 pathogenesis.

During the past two decades, the world has witnessed the emergence of various SARS-CoV-2 variants with distinct mutational profiles influencing the global health, economy, and clinical aspects of the COVID-19 pandemic. These variants or mutants have raised major concerns regarding the protection provided by neutralizing monoclonal antibodies and vaccination, rates of virus transmission, and/or the risk of reinfection. The newly emerged Omicron, a genetically distinct lineage of SARS-CoV-2, continues its spread in the face of rising vaccine-induced immunity while maintaining its replication fitness. Efforts have been made to improve the therapeutic interventions and the FDA has issued Emergency Use Authorization for a few monoclonal antibodies and drug treatments for COVID-19. However, the current situation of rapidly spreading Omicron and its lineages demands the need for effective therapeutic interventions to reduce the COVID-19 pandemic. Several experimental studies have indicated that the FDA-approved monoclonal antibodies are less effective than antiviral drugs against the Omicron variant. Thus, in this study, we aim to identify antiviral compounds against the Spike protein of Omicron, which binds to the human angiotensin-converting enzyme 2 (ACE2) receptor and facilitates virus invasion. Initially, docking-based virtual screening of the in-house database was performed to extract the potential hit compounds against the Spike protein. The obtained hits were optimized by DFT calculations to determine the electronic properties and molecular reactivity of the compounds. Further, MD simulation studies were carried out to evaluate the dynamics of protein–ligand interactions at an atomistic level in a time-dependent manner. Collectively, five compounds (AKS-01, AKS-02, AKS-03, AKS-04, and AKS-05) with diverse scaffolds were identified as potential hits against the Spike protein of Omicron. Our study paves the way for further in vitro and in vivo studies.

Punicalagin is the most bioactive pomegranate polyphenol with high antioxidant and free-radical scavenging activity and can potentially cure different ailments related to the cardiovascular system. The current research work was envisioned to predict the targeting efficiency of punicalagin (PG) nanoparticles to the macrophages, more specifically to bone marrow macrophages. For this, we selected mannose-decorated PLGA-punicalagin nanoparticles (Mn-PLGA-PG), and before formulating this nanocarrier in laboratory settings, we predicted the targeting efficiency of this nanocarrier by in silico analysis. The analysis proceeded with macrophage mannose receptors to be acquainted with the binding affinity and punicalagin-based nanocarrier interactions with this receptor. In silico docking studies of macrophage mannose receptors and punicalagin showed binding interactions on its surface. PG interacted with hydrogen bonds to the charged residue ASP668 and GLY666 and polar residue GLN760 of the Mn receptor. Mannose with a docking score of −5.811 Kcal/mol interacted with four hydrogen bonds and the mannose receptor of macrophage, and in PLGA, it showed a −4.334 Kcal/mol docking score. Further, the analysis proceeded with density functional theory analysis (DFT) and HOMO–LUMO analysis, followed by an extensive 100 ns molecular dynamics simulation to analyse the trajectories showing the slightest deviation and fluctuation. While analysing the ligand and protein interaction, a wonderful interaction was found among the atoms of the ligand and protein residues. This computational study confirms that this nanocarrier could be a promising lead molecule to regulate the incidence of drug-induced neutropenia. Furthermore, experimental validation is required before this can be stated with complete confidence or before human use.

The novel corona virus (Covid-19) has become a great challenge worldwide since 2019, as no drug has been reported yet. Different clinical trials are still under way. Among them is Ivermectin (IVM), an FDA approved drug which was recently reported as a successful candidate to reduce SARS-CoV-2 viral load by inhibiting Importin-α1 (IMP-α1) protein which subsequently affects nuclear transport of viral proteins but its basic binding mode and inhibitory mechanism is unknown. Therefore, we aimed to explore the inhibitory mechanism and binding mode of IVM with IMP-α1 via different computational methods. Initially, comparative docking of IVM was performed against two different binding sites (Nuclear Localization Signal (NLS) major and minor sites) of IMP-α1 to predict the probable binding mode of IVM. Then, classical MD simulation was performed (IVM/NLS-Major site and IVM/NLS-Minor site), to predict its comparative stability dynamics and probable inhibitory mechanism. The stability dynamics and biophysical analysis of both sites highlighted the stable binding of IVM within NLS-Minor site by establishing and maintaining more hydrophobic contacts with crucial residues, required for IMP-α1 inhibition which were not observed in NLS-major site. Altogether, these results recommended the worth of IVM as a possible drug to limit the SARS-CoV-2 viral load and consequently reduces its progression. Communicated by Ramaswamy H. Sarma

Quinoline-3-carboxamides are an essential class of drug-like small molecules that are known to inhibit the phosphatidylinositol 3-kinase-related kinases (PIKK) family kinases. The quinoline nitrogen is shown to bind to the hinge region of the kinases, making them competitive inhibitors of adenosine triphosphate (ATP). We have previously designed and synthesized quinoline-3-carboxamides as potential ataxia telangiectasia mutated (ATM) kinase inhibitors to function as an adjuvant treatment with DNA damaging agents. This article discusses the molecular docking studies performed with these derivatives with the DNA damage and response (DDR) kinases-ATM, ataxia telangiectasia and rad3 related (ATR), and DNA dependent protein kinase catalytic subunit (DNA-PKcs) and highlights their selectivity towards ATM kinase. Docking studies were also performed with mTOR and PI3Kγ, which are close homologs of the DDR kinases. Molecular dynamics simulations were performed for one of the inhibitors against all the enzymes to establish the stability of the interactions involved. Finally, the absorption, distribution, metabolism, and excretion (ADME) properties of the inhibitors were predicted using the QikProp manual in Maestro. In conclusion, the molecules synthesized showed high selectivity towards the ATM kinase in comparison with the other kinases, though the sequence similarity between them was relatively high.

Zika virus caused of the emerging infections characterized by fever, Guillain-Barré syndrome (GBS) for adults. In the current work, we aimed to study the binding orientation of 1,5-benzothiazepine compounds as new potential agent against Zika virus inhibitor through molecular docking and molecular dynamic simulation. Since, 1-5-Benzothiazepines are particular interest for drug discovery and they also has some biological activities. However, their antiviral activities and in silico studies of the binding to their biological targets have not been extensively investigated. Molecular docking study of 1,5-benzothiazepine chalcone derivatives compounds with protein target 5GJB (PDB ID) and this protein was taken from the crystallographic structure. In this study, twelve 1,5-benzothiazepine chalcone derivative compounds were docked to the protein with the grid box along x, y and z radius of 26.85, 28.17 and 24.43 Å, respectively. Suramin was used as positive control. Thus, it can be used as a reference for design new inhibitors for Zika virus helicase. Based on the docking results, it is observed that compounds MA3 and MA8 are estimated to have activity as inhibitors for Zika virus helicase with binding free energy values of -4.6490 and -4.9291 kcal/mol, respectively. MA3 and MA8 were also stable during the MD simulations with the hydrogen bonding are still maintained before and after MD simulation. Furthermore, both of these compounds can be used an early stage for drug design and drug delivery process.

In the current era, our experience is full of pandemic infectious agents that no longer threaten the major local source but the whole globe. One such infectious agent is HPV, a sexually transmitted disease that can cause various clinical disorders, including benign lesions and cervical cancer. Since available vaccines still need further improvements in order to enhance efficacy, our goal was to design a chimeric vaccine against HPV using an immunoinformatics approach. For designing the vaccine, the sequence of HPV was retrieved, and then phylogenetic analysis was performed. Several CTL epitopes, HTL epitopes, and LBL epitopes were all predicted using bioinformatics tools. After checking the antigenicity, allergenicity, and toxicity scores, the best epitopes were selected for vaccine construction, and then physicochemical and immunological properties were analyzed. Subsequently, vaccine 3D structure prediction, refinement, and validation were performed. Molecular docking and dynamics simulation techniques were used to explore the interactions between the Toll-like receptor 2 and the modeled vaccine construct. To ensure the vaccine protein was expressed at a higher level, the construct was computationally cloned into the pET28a (+) plasmid. The molecular docking and simulation results showed that our designed vaccine is stable, of immunogenic quality, and has considerable solubility. Through in silico immune simulation, it was predicted that the designed polypeptide vaccine construct would trigger both humoral and cellular immune responses. The developed vaccine showed significant affinity for the TLR2 receptor molecule. However, additional laboratory research is required to evaluate its safety and efficacy.

The disordered nature of Intrinsically Disordered Proteins (IDPs) makes their structural ensembles particularly susceptible to changes in chemical environmental conditions, often leading to an alteration of their normal functions. A Radial Distribution Function (RDF) is considered a standard method for characterizing the chemical environment surrounding particles during atomistic simulations, commonly averaged over an entire or part of a trajectory. Given their high structural variability, such averaged information might not be reliable for IDPs. We introduce the Time-Resolved Radial Distribution Function (TRRDF), implemented in our open-source Python package SPEADI, which is able to characterize dynamic environments around IDPs. We use SPEADI to characterize the dynamic distribution of ions around the IDPs Alpha-Synuclein (AS) and Humanin (HN) from Molecular Dynamics (MD) simulations, and some of their selected mutants, showing that local ion–residue interactions play an important role in the structures and behaviors of IDPs.

Pseudomonas aeruginosa is an opportunistic Gram-negative bacterium implicated in acute and chronic nosocomial infections and a leading cause of patient mortality. Pseudomonas aeruginosa infections are frequently associated with the development of biofilms, which give the bacteria additional drug resistance and increase their virulence. The goal of this study was to find strong compounds that block the Anthranilate-CoA ligase enzyme made by the pqsA gene. This would stop the P. aeruginosa quorum signaling system. This enzyme plays a crucial role in the pathogenicity of P. aeruginosa by producing autoinducers for cell-to-cell communication that lead to the production of biofilms. Pharmacophore-based virtual screening was carried out utilizing a library of commercially accessible enzyme inhibitors. The most promising hits obtained during virtual screening were put through molecular docking with the help of MOE. The virtual screening yielded 7/160 and 10/249 hits (ZINC and Chembridge). Finally, 2/7 ZINC hits and 2/10 ChemBridge hits were selected as potent lead compounds employing diverse scaffolds due to their high pqsA enzyme binding affinity. The results of the pharmacophore-based virtual screening were subsequently verified using a molecular dynamic simulation-based study (MDS). Using MDS and post-MDS, the stability of the complexes was evaluated. The most promising lead compounds exhibited a high binding affinity towards protein-binding pocket and interacted with the catalytic dyad. At least one of the scaffolds selected will possibly prove useful for future research. However, further scientific confirmation in the form of preclinical and clinical research is required before implementation.

Class A serine β-lactamases (SBLs) have a conserved non-active site structural domain called the omega loop (Ω-loop), in which a glutamic acid residue is believed to be directly involved in the hydrolysis of β-lactam antibiotics by providing a water molecule during catalysis. We aimed to design and characterise potential pentapeptides to mask the function of the Ω-loop of β-lactamases and reduce their efficacy, along with potentiating the β-lactam antibiotics and eventually decreasing β-lactam resistance. Considering the Ω-loop sequence as a template, a group of pentapeptide models were designed, validated through docking, and synthesised using solid-phase peptide synthesis (SPPS). To check whether the β-lactamases (BLAs) were inhibited, we expressed specific BLAs (TEM-1 and SHV-14) and evaluated the trans-expression through a broth dilution method and an agar dilution method (HT-SPOTi). To further support our claim, we conducted a kinetic analysis of BLAs with the peptides and employed molecular dynamics (MD) simulations of peptides. The individual presence of six histidine-based peptides (TSHLH, ETHIH, ESRLH, ESHIH, ESRIH, and TYHLH) reduced β-lactam resistance in the strains harbouring BLAs. Subsequently, we found that the combinational effect of these peptides and β-lactams sensitised the bacteria towards the β-lactam drugs. We hypothesize that the antimicrobial peptides obtained might be considered among the novel inhibitors that can be used specifically against the Ω-loop of the β-lactamases.

The pandemic outbreak of human coronavirus is a global health concern that affects people of all ages and genders, but there is currently still no effective, approved and potential drug against human coronavirus, as many other coronavirus vaccines have serious side effects while the development of small antiviral inhibitors has gained tremendous attention. For this research, HE was used as a therapeutic target, as the spike protein displays a high binding affinity for both host ACE2 and viral HE glycoprotein. Molecular docking, pharmacophore modelling and virtual screening of 38,000 natural compounds were employed to find out the best natural inhibitor against human coronaviruses with more efficiency and fewer side effects and further evaluated via MD simulation, PCA, DCCR and MMGBSA. The lead compound ‘Calceolarioside B’ was identified on the basis of pharmacophoric features which depict favorable binding (ΔGbind −37.6799 kcal/mol) with the HE(5N11) receptor that describes positive correlation movements in active site residues with better stability, a robust H-bond network, compactness and reliable ADMET properties. The Fraxinus sieboldiana Blume plant containing the Calceolarioside B compound could be used as a potential inhibitor that shows a higher efficacy and potency with fewer side effects. This research work will aid investigators in the testing and identification of chemicals that are effective and useful against human coronavirus.

Coronavirus disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused a global pandemic. RNA-dependent RNA polymerase (RdRp) is the key component of the replication or transcription machinery of coronavirus. Therefore SARS-CoV-2-RdRp has been chosen as an important target for the development of antiviral drug(s). During the early pandemic of the COVID-19, chloroquine and hydroxychloroquine were suggested by the researchers for the prevention or treatment of SARS-CoV-2. In our study, the antimalarial compounds have been screened and docked against SARS-CoV-2-RdRp (PDB ID: 7BTF), and it was observed that the antimalarials chloroquine, hydroxychloroquine, and amodiaquine exhibit good affinity. Since the crystal structure of SARS-CoV-2-RdRp with its substrate is not available, poliovirus-RdRp crystal structure co-crystallized with its substrate ATP (PDB ID: 2ILY) was used as a reference structure. The superimposition of SARS-CoV-2-RdRp and poliovirus-RdRp structures showed that the active sites of both of the RdRps superimposed very well. The amino acid residues involved in the binding of ATP in the case of poliovirus-RdRp and residues involved in binding with the antimalarial compounds with SARS-CoV-2-RdRp were compared. In both cases, the conserved residues were found to be involved in establishing the interactions. The MMGBSA and molecular dynamic simulation studies were performed to strengthen our docking results. Further residues involved in binding of antimalarials with SARS-CoV-2-RdRp were compared with the residues involved in the SARS-CoV-2-RdRp complexed with remdesivir [PDB ID: 7BV2]. It was observed that co-crystallized remdesivir and docked antimalarials bind in the same pocket of SARS-CoV-2 -RdRp. Communicated by Ramaswamy H. Sarma

Main protease (Mpro) of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) intervenes in the replication and transcription processes of the virus. Hence, it is a lucrative target for anti-viral drug development. In this study, molecular modeling analyses were performed on the structure activity data of recently reported diverse SARS-CoV-2 Mpro inhibitors to understand the structural requirements for higher inhibitory activity. The classification-based quantitative structure–activity relationship (QSAR) models were generated between SARS-CoV-2 Mpro inhibitory activities and different descriptors. Identification of structural fingerprints to increase or decrease in the inhibitory activity was mapped for possible inclusion/exclusion of these fingerprints in the lead optimization process. Challenges in ADME properties of protease inhibitors were also discussed to overcome the problems of oral bioavailability. Further, depending on the modeling results, we have proposed novel as well as potent SARS-CoV-2 Mpro inhibitors. Graphic Abstract Electronic supplementary material The online version of this article (10.1007/s11030-020-10166-3) contains supplementary material, which is available to authorized users.

The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure–activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.

Direct inhibitors of glycogen synthase kinase 3β (GSK3β) have been investigated and reported for the past 20 years. In the search for novel scaffold inhibitors, 3000 compounds were selected through structure-based virtual screening (SBVS), and then high-throughput enzyme screening was performed. Among the active hit compounds, pyrazolo [1,5-a]pyrimidin-7-amine derivatives showed strong inhibitory potencies on the GSK3β enzyme and markedly activated Wnt signaling. The result of the molecular dynamics (MD) simulation, enhanced by the upper-wall restraint, was used as an advanced structural query for the SBVS. In this study, strong inhibitors designed to inhibit the GSK3β enzyme were discovered through SBVS. Our study provides structural insights into the binding mode of the inhibitors for further lead optimization.

The structural stability of DNA is important because of its biological activity. DNAs due to their inherent chemical properties are not stable in an aqueous solution, therefore, a long period of storage of DNA at the ambient condition in bioscience is of importance. Ionic liquids (ILs) as interesting alternatives compared to organic solvents and water due to their considerable properties can be used as new agents to increase the stability of DNA for a long period of storage. In this article, molecular dynamics (MD) simulations and quantum chemistry calculations were applied to investigate the effects of amino acid ionic liquids ([BMIM][Ala], [BMIM][Gly], [BMIM][Val], [BMIM][Pro] and [BMIM][Leu]) on the dynamical behavior and the structural stability of calf thymus DNA. Based on the obtained MD results ILs enter into the solvation shell of the DNA and push away the water molecules from the DNA surface. Structural analysis shows that [BMIM]+ cations can occupy the DNA minor groove without disturbing the double-helical structure of DNA. ILs due to strong electrostatic and van der Waals (vdW) interactions with the DNA structure contribute to the stability of the double-helical structure. Quantum chemistry calculations indicate that the interactions between the [BMIM]+ cation and DNA structure has an electrostatic character. Moreover, this cation forms a more stable complex with the CGCG region of the DNA in comparison with AATT base pairs. Overall, the results of this study can provide new insight into the application of ILs for maintaining DNA stability during long-term storage. Communicated by Ramaswamy H. Sarma Theoretical methods reveal that amino acid ionic liquids can be good candidates for increasing the stability of DNA in long-term storage.

Vitamin E acetate, which is used as a diluent of tetrahydrocannabinol (THC), has been reported as the primary causative agent of e-cigarette, or vaping, product use-associated lung injury (EVALI). Here, we employ in vitro assays, docking, and molecular dynamics (MD) computer simulations to investigate the interaction of vitamin E with the membrane-bound cannabinoid 2 receptor (CB2R), and its role in modulating the binding affinity of THC to CB2R. From the MD simulations, we determined that vitamin E interacts with both CB2R and membrane phospholipids. Notably, the synchronized effect of these interactions likely facilitates vitamin E acting as a lipid modulator for the cannabinoid system. Furthermore, MD simulation and trajectory analysis show that when THC binds to CB2R in the presence of vitamin E, the binding cavity widens, facilitating the entry of water molecules into it, leading to a reduced interaction of THC with CB2R. Additionally, the interaction between THC and vitamin E in solution is stabilized by several H bonds, which can directly limit the interaction of free THCs with CB2R. Overall, both the MD simulations and the in vitro dissociation assay results indicate that THC binding to CB2R is reduced in the presence of vitamin E. Our study discusses the role of vitamin E in limiting the effect of THCs and its implications on the reported pathology of EVALI.

This work aimed at evaluating the inhibitory effect of ten natural bioactive compounds (1–10) as potential inhibitors of SARS-CoV-2-3CL main protease (PDB ID: 6LU7) and SARS-CoV main proteases (PDB IDs: 2GTB and 3TNT) by molecular docking analysis. The inhibitory effect of all studied compounds was studied with compared to some proposed antiviral drugs which currently used in COVID-19 treatment such as chloroquine, hydroxychloroquine, azithromycin, remdesivir, baloxvir, lopinavir, and favipiravir. Homology modeling and sequence alignment was computed to evaluate the similarity between the SARS-CoV-2-3CL main protease and other SARS-CoV receptors. ADMET properties of all studied compounds were computed and reported. Also, molecular dynamic (MD) simulation was performed on the compound which has the highest binding affinity inside 6LU7 obtained from molecular docking analysis to study it is stability inside receptor in explicit water solvent. Based on molecular docking analysis, we found that caulerpin has the highest binding affinity inside all studied receptors compared to other bioactive compounds and studied drugs. Our homology modeling and sequence alignment showed that SARS-CoV main protease (PDB ID: 3TNT) shares high similarity with 3CLpro (96.00%). Also, ADMET properties confirmed that caulerpin obeys Lipinski’s rule and passes ADMET property, which make it a promising compound to act as a new safe natural drug against SARS-CoV-2-3CL main protease. Finally, MD simulation confirmed that the complex formed between caulerpin and 3CLpro is stable in water explicit and had no major effect on the flexibility of the protein throughout the simulations and provided a suitable basis for our study. Also, binding free energy between caulerpin and 6LU7 confirmed the efficacy of the caulerpin molecule against SARS-CoV-2 main protease. So, this study suggested that caulerpin could be used as a potential candidate in COVID-19 treatment.

Coronavirus disease 2019 (COVID-19) has affected almost every country in the world by causing a global pandemic with a high mortality rate. Lack of an effective vaccine and/or antiviral drugs against SARS-CoV-2, the causative agent, has severely hampered the response to this novel coronavirus. Natural products have long been used in traditional medicines to treat various diseases, and purified phytochemicals from medicinal plants provide a valuable scaffold for the discovery of new drug leads. In the present study, we performed a computational screening of an in-house database composed of ~1000 phytochemicals derived from traditional Saudi medicinal plants with recognised antiviral activity. Structure-based virtual screening was carried out against three druggable SARS-CoV-2 targets, viral RNAdependent RNA polymerase (RdRp), 3-chymotrypsin-like cysteine protease (3CLpro) and papain like protease (PLpro) to identify putative inhibitors that could facilitate the development of potential anti-COVID-19 drug candidates. Computational analyses identified three compounds inhibiting each target, with binding affinity scores ranging from-9.9 to -6.5 kcal/mol. Among these, luteolin 7-rutinoside, chrysophanol 8-(6-galloylglucoside) and kaempferol 7-(6’’-galloylglucoside) bound efficiently to RdRp, while chrysophanol 8-(6galloylglucoside), 3,4,5-tri-O-galloylquinic acid and mulberrofuran G interacted strongly with 3CLpro, and withanolide A, isocodonocarpine and calonysterone bound tightly to PLpro. These potential drug candidates will be subjected to further in vitro and in vivo studies and may assist the development of effective anti-COVID-19 drugs.

The recent outbreak of the SARS-CoV-2 virus leading to the disease COVID 19 has become a global pandemic that is spreading rapidly and has caused a global health emergency. Hence, there is an urgent need of the hour to discover effective drugs to control the pandemic caused by this virus. Under such conditions, it would be imperative to repurpose already known drugs which could be a quick and effective alternative to discovering new drugs. The main protease (Mpro) of SARS-COV-2 is an attractive drug target because of its essential role in the processing of the majority of the non-structural proteins which are translated from viral RNA. Herein, we report the high-throughput virtual screening and molecular docking studies to search for the best potential inhibitors against Mpro from FDA approved drugs available in the ZINC database as well as the natural compounds from the Specs database. Our studies have identified six potential inhibitors of Mpro enzyme, out of which four are commercially available FDA approved drugs (Cobicistat, Iopromide, Cangrelor, and Fortovase) and two are from Specs database of natural compounds (Hopeaphenol and Cyclosieversiodide-A). While Cobicistat and Fortovase are known as HIV drugs, Iopromide is a contrast agent and Cangrelor is an anti-platelet drug. Furthermore, molecular dynamic (MD) simulations using GROMACS were performed to calculate the stability of the top-ranked compounds in the active site of Mpro. After extensive computational studies, we propose that Cobicistat and Hopeaphenol show potential to be excellent drugs that can form the basis of treating COVID-19 disease. Communicated by Ramaswamy H. Sarma

The heating process for CuAlNi nanoclusters with cuboctahedral structure was studied by molecular dynamics simulation with the embedded atom method. A diffusionless martensitic transformation from the cuboctahedral (CO) to the icosahedral (ICO) structure before the melting point was found in some CuAlNi nanoclusters. The effects of element composition and cluster size on the thermodynamic stability and structural transformation of trimetallic nanoclusters were investigated. The results show that the CO–ICO transformation temperature was size-dependent and occurred only for small clusters. It was also observed that the CO–ICO transformation temperature firstly dropped and then raised as Al concentration increased, which may be strongly related to the release of excess energy. Furthermore, the surface segregation phenomenon was also observed that the lower surface energy components, such as Al and Cu atoms, segregated to the surface of CuAlNi nanoclusters. The changes in the melting points of CuAlNi nanoclusters with different alloy compositions and cluster sizes were also studied. And furthermore, the physical basis of structural transition of CuAlNi nanoclusters was discussed.

Newly emerged SARS-CoV-2 made recent pandemic situations across the globe is accountable for countless unwanted death and insufferable panic associated with co-morbidities among mass people. The scarcity of appropriate medical treatment and no effective vaccine or medicine against SARS-CoV-2 has turned the situation worst. Therefore, in this study, we made a deep literature review to enlist plant-derived natural compounds and considered their binding mechanism with the main protease of SARS-CoV-2 through combinatorial bioinformatics approaches. Among all, a total of 14 compounds were filtered where Carinol, Albanin, Myricetin were had better binding profile than the rest of the compounds with having binding energy of –8.476, –8.036, –8.439 kcal/mol, respectively. Furthermore, MM-GBSA calculations were also considered in this selection process to support docking studies. Besides, 100 ns molecular dynamics simulation endorsed the rigid nature, less conformational variation and binding stiffness. As this study, represents a perfect model for SARS-CoV-2 main protease inhibition through bioinformatics study, these potential drug candidates may assist the researchers to find a superior and effective solution against COVID-19 after future experiments. Communicated by Ramaswamy Sarma

In the present study, we have explored the interaction of the active components from 10 different medicinal plants of Indian origin that are commonly used for treating cold and respiratory-related disorders, through molecular docking analysis. In the current scenario, COVID-19 patients experience severe respiratory syndromes, hence it is envisaged from our study that these traditional medicines are very likely to provide a favourable effect on COVID-19 infections. The active ingredients identified from these natural products are previously reported for antiviral activities against large group of viruses. Totally 47 bioactives identified from the medicinal plants were investigated against the structural targets of SARS-CoV-2 (Mpro and spike protein) and human ACE2 receptor. The top leads were identified based on interaction energies, number of hydrogen bond and other parameters that explain their potency to inhibit SARS-CoV-2. The bioactive ligands such as Cucurbitacin E, Orientin, Bis-andrographolide, Cucurbitacin B, Isocucurbitacin B, Vitexin, Berberine, Bryonolic acid, Piperine and Magnoflorine targeted the hotspot residues of SARS-CoV-2 main protease. In fact, this protease enzyme has an essential role in mediating the viral replication and therefore compounds targeting this key enzyme are expected to block the viral replication and transcription. The top scoring conformations identified through docking analysis were further demonstrated with molecular dynamics simulation. Besides, the stability of the conformation was studied in detail by investigating the binding free energy using MM-PBSA method. Overall, the study emphasized that the proposed hit Cucurbitacin E and orientin could serve as a promising scaffold for developing anti-COVID-19 drug. Communicated by Ramaswamy H. Sarma

In December 2019, COVID-19 epidemic was described in Wuhan, China, and the infection has spread widely affecting hundreds of thousands. Herein, an effort was made to identify commercially available drugs in order to repurpose them against coronavirus by the means of structure-based virtual screening. In addition, ZINC15 library was used to identify novel leads against main proteases. Human TMPRSS2 3D structure was first generated using homology modeling approach. Our molecular docking study showed four potential inhibitors against Mpro enzyme, two available drugs (Talampicillin and Lurasidone) and two novel drug-like compounds (ZINC000000702323 and ZINC000012481889). Moreover, four promising inhibitors were identified against TMPRSS2; Rubitecan and Loprazolam drugs, and compounds ZINC000015988935 and ZINC000103558522. ADMET profile showed that the hits from our study are safe and drug-like compounds. Furthermore, molecular dynamic (MD) simulation and binding free energy calculation using the MM-PBSA method was performed to calculate the interaction energy of the top-ranked drugs. Communicated by Ramaswamy H. Sarma Keywords

The biological role of biomolecules is intimately linked to their structural dynamics. Experimental or computational techniques alone are often insufficient to determine accurate structural ensembles in atomic detail. We use all-atom molecular dynamics (MD) simulations and couple it to small-angle X-ray scattering (SAXS) experiments to resolve the structural dynamics of RNA molecules. To accomplish this task, we utilize a set of re-weighting and biasing techniques tailored for RNA molecules. To showcase our approach, we study two RNA molecules: a riboswitch that shows structural variations upon ligand binding, and a two-way junction RNA that displays structural heterogeneity and sensitivity to salt conditions. Integration of MD simulations and experiments allows the accurate construction of conformational ensembles of RNA molecules. We observe a dynamic change of the SAM-I riboswitch conformations depending on its binding partners. The binding of SAM and Mg2+ cations stabilizes the compact state. The absence of Mg2+ or SAM leads to the loss of tertiary contacts, resulting in a dramatic expansion of the riboswitch conformations. The sensitivity of RNA structures to the ionic strength demonstrates itself in the helix junction helix (HJH). The HJH shows non-monotonic compaction as the ionic strength increases. The physics-based picture derived from the experimentally guided MD simulations allows biophysical characterization of RNA molecules. All in all, SAXS-guided MD simulations offer great prospects for studying RNA structural dynamics.

The cross-linking structure of the Ethylene-propylene-diene monomer (EPDM) is made up of a number of cross-linking types, including carbon atoms from the main chain or monomer and ether crosslinks formed during degradation. Through molecular dynamic simulations, the contribution of each type of cross-linked structure to the dynamics and mechanical properties of EPDM, the study’s focus, were investigated. Cross-linking between the tertiary carbons of two main chains, cross-linking at the monomer’s unsaturated position, ether cross-linking after oxidation, and other combinations of target cross-linked carbon atoms from different positions, totaling eight types of cross-linked types, were mixed with EPDM free chains in a 1:1 ratio to form eight types of cross-linked EPDMs. These varieties of cross-linked EPDMs were then compared to an uncross-linked EPDM in terms of density, radius of gyration, free volume, mean square displacement, and uniaxial tensile stress-strain curves. It was found that the cross-linking was always proven to have a favorable influence on mechanical characteristics; however, the relaxation inhibition effect varied. The cross-linking between the diene monomer at the C9 position resulted in a more flexible molecular shape and was more than double the free volume of the uncross-linked EPDM, resulting in an improved diffusion ability. The ether cross-linking produced by the oxidation of the side chain cross-linking improved the positive contribution to stiffness and enhanced the inhibitory impact on diffusion properties, whereas the main chain cross-linking had the opposite effect. The research presented in this study leads to a better knowledge of the microscopic aspects underlying EPDM performance. Published version

Binding of cell surface glycoprotein CD44 to hyaluronic acid (HA) is a key event for mediating cell adhesion, motility, metastasis, inflammatory responses and tumor development, but the regulation mechanism and its molecular basis under diverse mechanical constraints remain unclear. We herein investigated interaction of CD44 HABD (HA binding site domain) to HA through free and steered molecular dynamics (MD) simulations as well as atomic force microscope (AFM) measurement using different constraints on HA. The middle, two ends or both of the constrained HA chains were fixed for MD simulations, while one and two biotin–avidin linkage or physical absorption were used to immobilize HA on substrates for AFM experiments, to model HA chains with low, moderate and high HA flexibilities, respectively. We found that binding of CD44 to moderate fixed HA was possessed of a better thermo-stability, a lower mechanical strength and a higher dissociation probability, while higher adhesive frequency, smaller rupture force and shorter lifetime were assigned to CD44 on the two biotin-immobilized HA rather than one biotin-immobilized or physically absorbed HA on substrates, suggesting a moderate HA flexibility requirement in favor of association and force-induced dissociation of CD44-HA complex. Tensile-induced convex conformation of HA chain was responsible for reduction of complex mechano-stability and did inversely a shrunken CD44 HABD under stretching; transition from catch bond to slip bond governed CD44-HA interaction. This study uncovered the regulation mechanism and its molecular basis for CD44-HA affinity under diverse mechano-microenvironments and provided a new insight into CD44-HA interaction-mediated cell inflammatory responses and tumor development.

The emergence of the Coronavirus Disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to over 6 million deaths. The 3C-like protease (3CLpro) enzyme of the SARS-CoV-2 virus is an attractive druggable target for exploring therapeutic drug candidates to combat COVID-19 due to its key function in viral replication. Marine natural products (MNPs) have attracted considerable attention as alternative sources of antiviral drug candidates. In looking for potential 3CLpro inhibitors, the MNP database (>14,000 molecules) was virtually screened against 3CLpro with the assistance of molecular docking computations. The performance of AutoDock and OEDocking software in anticipating the ligand-3CLpro binding mode was first validated according to the available experimental data. Based on the docking scores, the most potent MNPs were further subjected to molecular dynamics (MD) simulations, and the binding affinities of those molecules were computed using the MM-GBSA approach. According to MM-GBSA//200 ns MD simulations, chetomin (UMHMNP1403367) exhibited a higher binding affinity against 3CLpro than XF7, with ΔGbinding values of −55.5 and −43.7 kcal/mol, respectively. The steadiness and tightness of chetomin with 3CLpro were evaluated, revealing the high stabilization of chetomin (UMHMNP1403367) inside the binding pocket of 3CLpro throughout 200 ns MD simulations. The physicochemical and pharmacokinetic features of chetomin were also predicted, and the oral bioavailability of chetomin was demonstrated. Furthermore, the potentiality of chetomin analogues –namely, chetomin A-D– as 3CLpro inhibitors was investigated. These results warrant further in vivo and in vitro assays of chetomin (UMHMNP1403367) as a promising anti-COVID-19 drug candidate.

Heme is located in the active site of proteins and has diverse and important biological functions, such as electron transfer and oxygen transport and/or storage. The distortion of heme porphyrin is considered an important factor for the diverse functions of heme because it correlates with the physical properties of heme, such as oxygen affinity and redox potential. Therefore, clarification of the relationship between heme distortion and the protein environment is crucial in protein science. Here, we analyzed the fluctuation in heme distortion in the protein environment for hemoglobin and myoglobin using molecular dynamics (MD) simulations and quantum mechanical (QM) calculations. We also investigated the protein structures of hemoglobin and myoglobin stored in Protein Data Bank and found that heme is distorted along the doming mode, which correlates with its oxygen affinity, more prominently in the protein environment than in the isolated state, and the magnitude of distortion is different between hemoglobin and myoglobin. This tendency was also observed in the results of MD simulations and QM calculations. These results suggest that heme distortion is affected by its protein environment and fluctuates around its fitted conformation, leading to physical properties that are appropriate for protein functions.

In baker’s yeast (Saccharomyces cerevisiae), Trk1, a member of the superfamily of K-transporters (SKT), is the main K+ uptake system under conditions when its concentration in the environment is low. Structurally, Trk1 is made up of four domains, each similar and homologous to a K-channel α subunit. Because most K-channels are proteins containing four channel-building α subunits, Trk1 could be functional as a monomer. However, related SKT proteins TrkH and KtrB were crystallised as dimers, and for Trk1, a tetrameric arrangement has been proposed based on molecular modelling. Here, based on Bimolecular Fluorescence Complementation experiments and single-molecule fluorescence microscopy combined with molecular modelling; we provide evidence that Trk1 can exist in the yeast plasma membrane as a monomer as well as a dimer. The association of monomers to dimers is regulated by the K+ concentration.

Ovarian cancer is the third leading cause of cancer-related deaths in India. Epigenetics mechanisms seemingly plays an important role in ovarian cancer. This paper highlights the crucial epigenetic changes that occur in POTEE that get hypomethylated in ovarian cancer. We utilized the POTEE paralog mRNA sequence to identify major motifs and also performed its enrichment analysis. We identified 6 motifs of varying lengths, out of which only three motifs, including CTTCCAGCAGATGTGGATCA, GGAACTGCC, and CGCCACATGCAGGC were most likely to be present in the nucleotide sequence of POTEE. By enrichment and occurrences identification analyses, we rectified the best match motif as CTTCCAGCAGATGT. Since there is no experimentally verified structure of POTEE paralog, thus, we predicted the POTEE structure using an automated workflow for template-based modeling using the power of a deep neural network. Additionally, to validate our predicted model we used AlphaFold predicted POTEE structure and observed that the residual stretch starting from 237-958 had a very high confidence per residue. Furthermore, POTEE predicted model stability was evaluated using replica exchange molecular dynamic simulation for 50 ns. Our network-based epigenetic analysis discerns only 10 highly significant, direct, and physical associators of POTEE. Our finding aims to provide new insights about the POTEE paralog.

Overexpression and frequent mutations in FMS-like tyrosine kinase-3 (FLT3) are considered risk factors for severe acute myeloid leukemia (AML). Hyperactive FLT3 induces premature activation of multiple intracellular signaling pathways, resulting in cell proliferation and anti-apoptosis. We conducted the computational modeling studies of 40 pyrimidine-4,6-diamine-based compounds by integrating docking, molecular dynamics, and three-dimensional structure–activity relationship (3D-QSAR). Molecular docking showed that K644, C694, F691, E692, N701, D829, and F830 are critical residues for the binding of ligands at the hydrophobic active site. Molecular dynamics (MD), together with Molecular Mechanics Poison–Boltzmann/Generalized Born Surface Area, i.e., MM-PB(GB)SA, and linear interaction energy (LIE) estimation, provided critical information on the stability and binding affinity of the selected docked compounds. The MD study suggested that the mutation in the gatekeeper residue F691 exhibited a lower binding affinity to the ligand. Although, the mutation in D835 in the activation loop did not exhibit any significant change in the binding energy to the most active compound. We developed the ligand-based comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) models. CoMFA (q2 = 0.802, r2 = 0.983, and QF32 = 0.698) and CoMSIA (q2 = 0.725, r2 = 0.965 and QF32 = 0.668) established the structure–activity relationship (SAR) and showed a reasonable external predictive power. The contour maps from the CoMFA and CoMSIA models could explain valuable information about the favorable and unfavorable positions for chemical group substitution, which can increase or decrease the inhibitory activity of the compounds. In addition, we designed 30 novel compounds, and their predicted pIC50 values were assessed with the CoMSIA model, followed by the assessment of their physicochemical properties, bioavailability, and free energy calculation. The overall outcome could provide valuable information for designing and synthesizing more potent FLT3 inhibitors.

Pearlite is an important structure in carbon steel; however, the influence mechanism of carbides in pearlite on its mechanical properties and microstructure evolution has not yet been fully elucidated. In this work, a ferrite–carbide composite model with various carbide types was constructed to investigate the influence of carbide types via a uniaxial compression deformation using classical molecular dynamics simulations. It was found that the carbide type had little effect on the compressive elastic modulus, but a more obvious effect on the yield strain, yield stress, and flow stress. The maximum compressive elastic modulus was in the Fe2C model, with 300.32 GPa, while the minimum was found in the Fe4C model at 285.16 GPa; the error was 5.32%. There were significant differences in the yield stress, yield strain, and flow stress of the ferrite–carbide model according to the stress–strain curve. Secondly, the type of carbide used affected its elastic constant, especially the bulk modulus and Cauchy pressure. The maximum bulk modulus of the Fe4C model was 199.01 GPa, the minimum value of the Fe3C model was 146.03 GPa, and the difference was 52.98 GPa. The Cauchy pressure calculation results were consistent with the yield strain trend. Additionally, the effective elastic moduli of the composite system were used to verify the accuracy of the calculation results of this work. Thirdly, ferrite–carbide interfaces could act as a resource for dislocation emission. The initial stacking fault forms at ferrite–carbide interfaces and expands into ferrite. The dislocation type and segment in the ferrite–carbide model were significantly different due to the type of carbide used.

Acute myeloid leukemia (AML) is a heterogeneous hematopoietic malignancy whose prognosis is globally poor. In more than 60% of AML patients, the PI3K/AKTs/mTOR signaling pathway is aberrantly activated because of oncogenic driver alterations and further enhanced by chemotherapy as a mechanism of drug resistance. Against this backdrop, very recently we have started a multidisciplinary research project focused on AKT1 as a pharmacological target to identify novel anti-AML agents. Indeed, the serendipitous finding of the in-house compound T187 as an AKT1 inhibitor has paved the way to the rational identification of new active small molecules, among which T126 has emerged as the most interesting compound with IC50 = 1.99 ± 0.11 μM, ligand efficiency of 0.35, and a clear effect at low micromolar concentrations on growth inhibition and induction of apoptosis in AML cells. The collected results together with preliminary SAR data strongly indicate that the 5,6,7,8-tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidin-4(3H)-one derivative T126 is worthy of future biological experiments and medicinal chemistry efforts aimed at developing a novel chemical class of AKT1 inhibitors as anti-AML agents.

The performance of a desalination membrane depends on a specific pore size suitable for both water permeability and salt rejection. To increase membrane permeability, the applied pressure should be increased, which creates the need to improve membrane stability. In this research article, a molecular dynamics (MD) simulation was performed using ReaxFF module from Amsterdam Modeling suite (AMS) software to simulate water desalination efficiency using a single and multi-layer graphene membrane. The graphene membrane with different pore sizes and a multi-layer graphene membrane with descending pore size in each layer were designed and studied under different pressures. The stability of the membrane was checked using Material Studio 2019 by studying the dynamics summary. The single-layer graphene membrane was evaluated under pressures ranging from 100 to 500 MPa, with the salt rejection ranging from 95% to 82% with a water permeability of 0.347 × 10−9 to 2.94 × 10−9 (mm.g.cm−2s−1.bar−1), respectively. Almost 100% salt rejection was achieved for the multi-layer graphene membrane. This study successfully demonstrated the design and optimization of graphene membrane performance without functionalization.

Rhipicephalus (Boophilus) microplus is one of the most widespread ticks causing a massive loss to livestock production. The long-term use of acaracides rapidly develops acaracide resistance. In R. microplus, enhancing the metabolic activity of glutathione S-transferase (RmGST) is one of the mechanisms underlying acaracide resistance. RmGST catalyzes the conjugation of glutathione (GSH) to insecticides causing an easy-to-excrete conjugate. The active RmGST dimer contains two active sites (hydrophobic co-substrate binding site (H-site) and GSH binding site (G-site)) in each monomer. To preserve the insecticide efficacy, s-hexyl glutathione (GTX), a GST inhibitor, has been used as a synergist. To date, no molecular information on the RmGST-GSH/GTX complex is available. The insight is important for developing a novel RmGST inhibitor. Therefore, in this work, molecular dynamics simulations (MD) were performed to explore the binding of GTX and GSH to RmGST. GSH binds tighter and sits rigidly inside the G-site, while flexible GTX occupies both active sites. In GSH, the backbone mainly interacts with W8, R43, W46, K50, N59, L60, Q72, and S73, while its thiol group directs to Y7. In contrast, the aliphatic hexyl of GTX protrudes into the H-site and allows a flexible peptide core to form various interactions. Such high GTX flexibility and the protrusion of its hexyl moiety to the H-site suggest the dual role of GTX in preventing the conjugation reaction and the binding of acaracide. This insight can provide a better understanding of an important insecticide-resistance mechanism, which may in turn facilitate the development of novel approaches to tick control.

Data Availability Statement: All data are available in the main text. Copyright: © 2022 by the authors Prenucleation refers to the phenomenon of substrate-induced atomic ordering in the liquid adjacent to the liquid/substrate interface at temperatures above the nucleation temperature. We investigated the effects of the physical and chemical properties of the substrate on prenucleation, using the classical molecular dynamics (MD) and ab initio MD simulations. We found that the physical origin of prenucleation is structural templating, which is affected significantly by the lattice misfit between the solid and the substrate, chemical interaction between the solid and the substrate, and the substrate surface roughness at the atomic level. Prenucleation ultimately determines the nucleation potency of a substrate and provides a precursor for heterogeneous nucleation at the nucleation temperature. In this paper, we provide an overview of the recent advances in the understanding of prenucleation made by the LiME Research Hub. After a brief review of the historical research on atomic ordering at the liquid/substrate interface in the literature, we present an overview of the recent advances in understanding prenucleation, covering the concept of prenucleation, the effect of temperature, lattice misfit and substrate chemistry, and substrate surface roughness at the atomic level. Our discussions will be focused on the effect of prenucleation on heterogeneous nucleation and its consequences on grain refinement. EPSRC of the UKRI under the grant number EP/N007638/1

Chagas disease is a tropical ailment indigenous to South America and caused by the protozoan parasite Trypanosoma cruzi, which has serious health consequences globally. Insect vectors transmit the parasite and, due to the lack of vaccine availability and limited treatment options, we implemented an integrated core proteomics analysis to design a reverse vaccine candidate based on immune epitopes for disease control. Firstly, T. cruzi core proteomics was used to identify immunodominant epitopes. Therefore, we designed the vaccine sequence to be non-allergic, antigenic, immunogenic, and to have better solubility. After predicting the tertiary structure, docking and molecular dynamics simulation (MDS) were performed with TLR4, MHC-I, and MHC-II receptors to discover the binding affinities. The final vaccine design demonstrated significant hydrogen bond interactions upon docking with TLR4, MHC-I, and MHC-II receptors. This indicated the efficacy of the vaccine candidate. A server-based immune simulation approach was generated to predict the efficacy. Significant structural compactness and binding stability were found based on MDS. Finally, by optimizing codons on Escherichia coli K12, a high GC content and CAI value were obtained, which were then incorporated into the cloning vector pET2+ (a). Thus, the developed vaccine sequence may be a viable therapy option for Chagas disease.