In silico analysis reveals α-amylase inhibitory potential of Taraxerol (Coccinia indica) and Epoxywithanolide-1 (Withania coagulans): a possible way to control postprandial hyperglycemia-induced endothelial dysfunction and cardiovascular events.

Postprandial hyperglycemia (PPG) exacerbates endothelial dysfunction and impairs vascular function in diabetes as well in healthy people. Though synthetic drugs are available to regulate PPG, the severe gastrointestinal side effects of those medications have prompted the search for alternative treatments. Recently, some phytochemicals captured the attention because of their inhibitory effects on α-amylase to control diabetes. The aim of this study was to investigate and identify potential alpha-amylase inhibitors in C. indica and W. coagulans. This study also aims to understand one of the possible mechanisms of action of plants for their anti-diabetic activity. A total of 36 phytochemical ligands were subjected for protein-ligand docking analysis. Among the phytochemicals, Taraxerol and Epoxywithanolide-I demonstrated significant binding free energy of - 10.2 kcal/mol and - 11.9 kcal/mol respectively, which was higher than the reference acarbose with - 8.6 kcal/mol. These molecules were subjected for molecular dynamics simulation (MDS) analysis with alpha-amylase protein for a duration of 150 ns. Among the three complexes, Taraxerol and Epoxywithanolide-I complexes demonstrates strong potential as inhibitors of the target protein. MDS results were analyzed via root mean square deviation (RMSD), fluctuation of residues, potential energy, radii of gyration and solvent access surface area analysis. Taraxerol demonstrated a significantly low potential energy of - 1,924,605.25 kJ/mol, and Epoxywithanolide-I demonstrated - 1,964,113.3 kJ/mol of potential energy. RMSD plot shows that Epoxywithanolide-I has much higher stability than the other MDS complexes. Drugability and toxicity studies show that the test ligands are demonstrating strong potential as drug like molecules. The results of the study conclude that, Taraxerol of C. indica and Epoxywithanolide-I of W. coagulans are strong inhibitors of alpha-amylase enzyme and that, this is one of the possible mechanisms of action of the plants for their reported anti-diabetic activities. Further in-vitro analysis is in demand to prove the observed results.

GMXPolymer: a generated polymerization algorithm based on GROMACS.

CONTEXT: This work introduces a method for generating generalized structures of amorphous polymers using simulated polymerization and molecular dynamics equilibration, with a particular focus on amorphous polymers. The techniques and algorithms used in this method are described in the main text, and example input scripts are provided for the GMXPolymer code, which is based on the GROMACS molecular dynamics package. To demonstrate the efficacy of our method, we apply it to different glassy polymers exhibiting varying degrees of functionality, polarity, and rigidity. The reliability of the method is validated by comparing simulation results with experimental data in various structural and thermal properties, both of which show excellent agreement. METHODS: This work implements the GMXPolymer simulated polymerization algorithm on the GROMACS program. GMXPolymer code controls the main polymerization loop. The energy minimizations and molecular dynamics simulations use the GROMACS program called by the GMXPolymer code. A new ITP file is generated when a new bond is formed, and the necessary additions to the ITP file are made to include new bonds, angles, and dihedrals. In preparing the ITP file of the monomer, the charge of the reactive atom must be modified before the code runs so that it is a correct value after bonding.

Computational approach for drug discovery against Gardnerella vaginalis in quest for safer and effective treatments for bacterial vaginosis.

Bacterial vaginosis (BV), primarily attributed to Gardnerella vaginalis, poses significant challenges due to antibiotic resistance and suboptimal treatment outcomes. This study presents an integrated approach to identify potential drug targets and screen compounds against this bacterium by leveraging a computational methodology. Subtractive proteomics of the reference strain ASM286196v1/UMB0386 (assembly accession: GCA_002861965.1) facilitated the prioritization of proteins with essential bacterial functions and pathways as potential drug targets. We selected 3-deoxy-7-phosphoheptulonate synthase (aroG gene product; also known as DAHP synthase) for downstream analysis. Molecular docking was employed in PyRx (AutoDock Vina) to predict binding affinities between aroG inhibitors from the ZINC database and 3-deoxy-7-phosphoheptulonate synthase. Molecular dynamics simulations of 100 ns, using GROMACS, validated the stability of drug-target interactions. Additionally, ADMET profiling aided in the selection of compounds with favorable pharmacokinetic properties and safety profile for human hosts. PBPK profiling showed that ZINC98088375 had the highest bioavailability and efficient systemic circulation. Conversely, ZINC5113880 demonstrated the lowest absorption rate (39.661%). Moreover, cirrhosis, steatosis, and renal impairment appeared to influence blood concentration of the drug, impacting bioavailability. The integrative -omics approach utilized in this study underscores the potential of computer-aided drug design and offers a rational strategy for targeted inhibitor discovery against G. vaginalis. The strategy is an attempt to address the limitations of current BV treatments, including antibiotic resistance, and pave way for the development of safer and more effective therapeutics.

Virtual screening and molecular dynamics simulation of natural compounds as potential inhibitors of serine/threonine kinase 16 for anticancer drug discovery.

Serine/threonine kinase 16 (STK 16) is involved in many facets of cellular regulation; activation of STK 16 plays a crucial role in the migration of cancer cells. Therefore, it is a novel target for the discovery of anticancer agents. Herein, virtual screening and dynamics simulation were used to screen a large library of natural compounds against STK 16 using Schrodinger suit 2021-2 and GROMACS 2021.6. The results predicted five molecules with high binding affinity against the target, with NPC132329 (Arcyriaflavin C) and NPC160898 having higher binding affinity and molecular mechanics generalized born surface area (MM/GBSA), suggesting that it is better than the standard inhibitor. The molecular dymanics (MD) simulation studies showed that the STK 16-NPC132329 complex has the lowest root mean square deviation, and STK 16-NPC160898 was the most stable compared with the standard drug and selective STK 16 inhibitor. The minimal fluctuation was observed in the STK 16-NPC132329 and STK 16-NPC160898 complexes based on the root mean square fluctuation trajectory with NPC132329 and NPC160898 forming 2 and 3 hydrogen bonds respectively with the amino acid residue of the target's binding site. Overall, NPC132329 and NPC160898 are better STK 16 inhibitors than the standard drug and selective inhibitor, which can be further studied to discover novel anticancer drugs.

Identification and Design of Novel Potential Antimicrobial Peptides Targeting Mycobacterial Protein Kinase PknB.

Antimicrobial peptides have gradually gained advantages over small molecule inhibitors for their multifunctional effects, synthesising accessibility and target specificity. The current study aims to determine an antimicrobial peptide to inhibit PknB, a serine/threonine protein kinase (STPK), by binding efficiently at the helically oriented hinge region. A library of 5626 antimicrobial peptides from publicly available repositories has been prepared and categorised based on the length. Molecular docking using ADCP helped to find the multiple conformations of the subjected peptides. For each peptide served as input the tool outputs 100 poses of the subjected peptide. To maintain an efficient binding for relatively a longer duration, only those peptides were chosen which were seen to bind constantly to the active site of the receptor protein over all the poses observed. Each peptide had different number of constituent amino acid residues; the peptides were classified based on the length into five groups. In each group the peptide length incremented upto four residues from the initial length form. Five peptides were selected for Molecular Dynamic simulation in Gromacs based on higher binding affinity. Post-dynamic analysis and the frame comparison inferred that neither the shorter nor the longer peptide but an intermediate length of 15 mer peptide bound well to the receptor. Residual substitution to the selected peptides was performed to enhance the targeted interaction. The new complexes considered were further analysed using the Elastic Network Model (ENM) for the functional site's intrinsic dynamic movement to estimate the new peptide's role. The study sheds light on prospects that besides the length of peptides, the combination of constituent residues equally plays a pivotal role in peptide-based inhibitor generation. The study envisages the challenges of fine-tuned peptide recovery and the scope of Machine Learning (ML) and Deep Learning (DL) algorithm development. As the study was primarily meant for generation of therapeutics for Tuberculosis (TB), the peptide proposed by this study demands meticulous invitro analysis prior to clinical applications.

Application of the molecular dynamics simulation GROMACS in food science.

Food comprises proteins, lipids, sugars and various other molecules that constitute a multicomponent biological system. It is challenging to investigate microscopic changes in food systems solely by performing conventional experiments. Molecular dynamics (MD) simulation serves as a crucial bridge in addressing this research gap. The Groningen Machine for Chemical Simulations (GROMACS) is an open-source, high-performing molecular dynamics simulation software that plays a significant role in food science research owing to its high flexibility and powerful functionality; it has been used to explore the molecular conformations and the mechanisms of interaction between food molecules at the microcosmic level and to analyze their properties and functions. This review presents the workflow of the GROMACS software and emphasizes the recent developments and achievements in its applications in food science research, thus providing important theoretical guidance and technical support for obtaining an in-depth understanding of the properties and functions of food.

Design and computational evaluation of a novel multi-epitope hybrid vaccine against monkeypox virus: Potential targets and immunogenicity assessment for pandemic preparedness.

Monkeypox is a type of DNA-enveloped virus that belongs to the orthopoxvirus family, closely related to the smallpox virus. It can cause an infectious disease in humans known as monkeypox disease. Although there are multiple drugs and vaccines designed to combat orthopoxvirus infections, with a primary focus on smallpox, the recent spread of the monkeypox virus to over 50 countries have ignited a mounting global concern. This unchecked viral proliferation has raised apprehensions about the potential for a pandemic corresponding to the catastrophic impact of COVID-19. This investigation explored the structural proteins of monkeypox virus as potential candidates for designing a novel hybrid multi-epitope vaccine. The epitopes obtained from the selected proteins were screened to ensure their non-allergenicity, non-toxicity, and antigenicity to trigger T and B-cell responses. The interaction of the vaccine with toll-like receptor-3 (TLR-3) and major histocompatibility complexes (MHCs) was assessed using Cluspro 2.0. To establish the reliability of the docked complexes, a comprehensive evaluation was conducted using Immune and MD Simulations and Normal Mode Analysis. However, to validate the computational results of this study, additional in-vitro and in-vivo research is essential.

Enhancing MD simulations: ASGARD's automated analysis for GROMACS.

Molecular Dynamics (MD) simulations are essential in analyzing the physical movement of molecules, with GROMACS being a widely recognized open-source package for this purpose. However, conducting analyses individually in GROMACS can take excessive time and effort. Addressing this challenge, we introduce ASGARD, an innovative workflow designed to streamline and automate the analysis of MD simulation of protein or protein-ligand complex. Unlike the traditional, manual approach, ASGARD enables researchers to generate comprehensive analyses with a single command line, significantly accelerating the research process and avoiding the laborious task of manual report generation. This tool automatically performs a range of analyses post-simulation, including system stability and flexibility assessments through RMSD Fluctuation and Distribution calculations. It further provides dynamic analysis using SASA, DSSP method graphs, and various interaction analyses. A key feature of ASGARD is its user-friendly design; it requires no additional installations or dependencies, making it highly accessible for researchers. In conclusion, ASGARD simplifies the MD simulation analysis process and substantially enhances efficiency and productivity in molecular research by providing an integrated, one-command analysis solution.Communicated by Ramaswamy H. Sarma.

Molecular dynamic investigation for Roco4 kinase inhibitor as treatment options for parkinsonism.

CONTEXT: Parkinson's disease is a neurodegenerative condition characterized by the degeneration of dopaminergic neurons, resulting in motor disabilities such as rigidity, bradykinesia, postural instability, and resting tremors. While the exact cause of Parkinson's remains uncertain, both familial and sporadic forms are often associated with the G2019S mutation found in the kinase domain of LRRK2. Roco4 is an analogue of LRRK2 protein in Dictyostelium discoideum which is an established model organism to investigate LRRK2 inhibitors. In this study, the potential treatment of Parkinson's was explored by inhibiting the activity of the mutated LRRK2 protein using Roco4 as the base protein structure. Mongolicain-A and Bacoside-A exhibited significant selectivity towards the G2019S mutation, displaying a binding affinity of - 12.3 Kcal/mol and - 11.4 Kcal/mol respectively. Mongolicain-A demonstrated increased specificity towards Roco4, while Bacoside-A demonstrated significant binding affinity to all 34 kinases proteins alike. The Molecular Dynamics Studies (MDS) results strongly suggests that Mongolicain-A is a significant inhibitor of Roco4 kinase. ADMET and drugability analysis also suggests that among the two best ligands, Mongolicain-A demonstrates significant physicochemical properties to be suitable for best drug like molecule. Based on the in-silico molecular docking, molecular dynamic simulation, ADMET and drugability analyses, it is strongly suggested that, Mongolicain-A could be a potential candidate for treatment and management of Parkinson's disease via inhibition of LRRK2 protein. Further in-vitro and in-vivo investigations are in demand to validate these findings. METHODS: To identify potential inhibitors, 3069 phytochemicals were screened using molecular docking via AutoDock Vina. Molecular Dynamics Simulation was carried out using GROMACS 2022.2 for a duration of 100ns per complex to study the stability and inhibition potential of the protein ligand complexes. ADMET analysis was carriedout using Molinspiration and preADMET web tool.

Molecular Design and Spodumene Flotation-A Review.

Spodumene flotation stands as the most commonly used method to concentrate lithium minerals. However, it faces significant challenges related to low collector recoveries and similarity in the surface characteristics of the minerals, which make the effective separation of this valuable mineral difficult. For this reason, numerous researchers have conducted studies to address and confront this problem. In this work, an exhaustive bibliographic search was carried out using keywords and search queries, and the results were structured in three sections according to temporal, methodological, and thematic criteria. The first section covers the period from 1950 to 2004, focusing on experimental tests. The second section covers from 2004 to the present and focuses on flotation tests and measurement analysis. Simultaneously, the third section spans from 2011 to the present and is based on molecular dynamics simulations. Topics covered include spodumene surface properties, the influence of metal ions, pre-treatment techniques, and the use of collectors. Ultimately, molecular dynamics simulations are positioned as a tool that accurately represents experimental phenomena. In this context, specialized software such as Materials Studio or Gromacs prove to be reliable instruments that allow a detailed study of mineral surfaces and other elements to be carried out, which justifies their consideration for future research in this scientific field.

Virtual screening of flavonoids as potential RIPK1 inhibitors for neurodegeneration therapy.

Background: Global prevalence of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration. Methods: In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations. Results: From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from -11.7 to -10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0.39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding. Conclusion: Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.

Escherichia coli FtsZ molecular dynamics simulations.

Earlier molecular dynamics studies of the FtsZ protein revealed that the protein has high intrinsic flexibility which the crystal structures cannot reveal. However, the input structure in these simulation studies was based on the available crystal structure data and therefore, the effect of the C-terminal Intrinsically Disordered Region (IDR) of FtsZ could not be observed in any of these studies. Recent investigations have revealed that the C-terminal IDR is crucial for FtsZ assembly in vitro and Z ring formation in vivo. Therefore, in this study, we simulated FtsZ with the IDR. Simulations of the FtsZ monomer in different nucleotide bound forms (without nucleotide, GTP, GDP) were performed. In the conformations of FtsZ monomer with GTP, GTP binds variably with the protein. Such a variable interaction with the monomer has not been observed in any previous simulation studies of FtsZ and not observed in crystal structures. We found that central helix bends towards the C-terminal domain in the GTP bound form, hence, making way for polymerization. A nucleotide dependent shift/rotation of the C-terminal domain was observed in simulation time averaged structures.Communicated by Ramaswamy H. Sarma.

A computational investigation of potential plant-based bioactive compounds against drug-resistant Staphylococcus aureus of multiple target proteins.

Drug-resistant Staphylococcus aureus (DRSA) poses a significant global health threat, like bacteremia, endocarditis, skin, soft tissue, bone, and joint infections. Nowadays, the resistance against conventional drugs has been a prompt and focused medical concern. The present study aimed to explore the inhibitory potential of plant-based bioactive compounds (PBBCs) against effective target proteins using a computational approach. We retrieved and verified 22 target proteins associated with DRSA and conducted a screening process that involved testing 87 PBBCs. Molecular docking was performed between screened PBBCs and reference drugs with selected target proteins via AutoDock. Subsequently, we filtered the target proteins and top PBBCs based on their binding affinity scores. Furthermore, molecular dynamic simulation was carried out through GROMACS for a duration of 100 ns, and the binding free energy was calculated using the gmx_MMPBSA. The result showed consistent hydrogen bonding interactions among the amino acid residues Ser 149, Arg 151, Thr 165, Thr 216, Glu 239, Ser 240, Ile 14, as well as Asn 18, Gln 19, Lys 45, Thr 46, Tyr 109, with their respective target proteins of the penicillin-binding protein and dihydrofolate reductase complex. Additionally, we assessed the pharmacokinetic properties of screened PBBCs via SwissADME and AdmetSAR. The findings suggest that ß-amyrin, oleanolic acid, kaempferol, quercetin, and friedelin have the potential to inhibit the selected target proteins. In future research, both in vitro and in vivo, experiments will be needed to establish these PBBCs as potent antimicrobial drugs for DRSA.Communicated by Ramaswamy H. Sarma.

CHAPERONg: A tool for automated GROMACS-based molecular dynamics simulations and trajectory analyses.

Molecular dynamics (MD) simulation is a powerful computational tool used in biomolecular studies to investigate the dynamics, energetics, and interactions of a wide range of biological systems at the atomic level. GROMACS is a widely used free and open-source biomolecular MD simulation software recognized for its efficiency, accuracy, and extensive range of simulation options. However, the complexity of setting up, running, and analyzing MD simulations for diverse systems often poses a significant challenge, requiring considerable time, effort, and expertise. Here, we introduce CHAPERONg, a tool that automates the GROMACS MD simulation pipelines for protein and protein-ligand systems. CHAPERONg also integrates seamlessly with GROMACS modules and third-party tools to provide comprehensive analyses of MD simulation trajectories, offering up to 20 post-simulation processing and trajectory analyses. It also streamlines and automates established pipelines for conducting and analyzing biased MD simulations via the steered MD-umbrella sampling workflow. Thus, CHAPERONg makes MD simulations more accessible to beginner GROMACS users whilst empowering experts to focus on data interpretation and other less programmable aspects of MD simulation workflows. CHAPERONg is written in Bash and Python, and the source code is freely available at https://github.com/abeebyekeen/CHAPERONg. Detailed documentation and tutorials are available online at dedicated web pages accessible via https://abeebyekeen.com/chaperong-online.

SBS 3.1, a novel natural product small molecule regulates TNF-α-induced NF-κB activation and key signals of inflammation to promote apoptosis in lung cancer tumour microenvironment.

Chronic inflammation leads to many maladies in lung cancer. Tumor necrosis factor-alpha (T NF- α), a pleiotropic proinflammatory cytokine regulates the activation of the nuclear factor-κB (NF-κB) to drive many physiological and pathological signaling pathways in inflammation and cancer apoptosis. This study identified a novel natural product to inhibit T NF-α induced NF-κB activation. Virtual docking of ZINC natural product library and computational modeling analysis showed compounds that target crucial amino acid residues on p50 protein involved in DNA binding. Molecular dynamic simulation showed, compound SBS-3.1, as the best lead compound that binds efficiently and stably with p50 protein. MMP BSA analysis of the lead compound predicted a favorable binding free energy. The compound inhibited the proliferations of T NF-α induced A-549 with a GI50 value of 30.53 µM. SBS-3.1 decreased the percentage of T NF-α induced NF-κB-65, p38 and ERK1/2 positive lung cancer cells, while the apoptosis in these cells were elevated. In summary, SBS-3.1, a natural product, was identified as the lead compound targeting Rel-homology region of p50. Inhibition of NF-κB and inflammatory signals by SBS 3.1 promoted apoptosis in lung cancer. Further research can bring new therapeutic strategies for treating inflammation associated T ME of lung cancer cells.Communicated by Ramaswamy H. Sarma.

Discovery of novel potent drugs for influenza by inhibiting the vital function of neuraminidase via fragment-based drug design (FBDD) and molecular dynamics simulation strategies.

The current work describes a fragment linking methodology to generate new neuraminidase inhibitors. A total number of 28,977 fragments from Zinc 20 have been obtained and screened for neuraminidase receptor affinity. Using Schrödinger software, the highest-scoring 270 fragment hits (with scores greater than -7.6) were subjected to fragment combining to create 100 new molecules. These 100 novel compounds were studied using XP docking to evaluate the molecular interaction modes and their binding affinity to neuraminidase receptor. The top ten molecules were selected, for ADMET, drug-likeness features. Based on these characteristics, the best four developed molecules and Zanamivir were submitted to a molecular dynamics simulation investigation to estimate their dynamics within the neuraminidase receptor using Gromacs software. All MD simulation findings show that the generated complexes are very stable when compared to the clinical inhibitor (Zanamivir). In addition, the four designed neuraminidase inhibitors formed very stable complexes with neuraminidase receptor (with total binding energies ranging from -83.50 to -107.85 Kj/mol) according to the total binding energy calculated by MM-PBSA. For the objective of developing new influenza medications, these novel molecules have the potential to be further evaluated in vitro and in vivo for influenza drug discovery.Communicated by Ramaswamy H. Sarma.

Influence of dexamethasone on the interaction between glucocorticoid receptor and SOX9: A molecular dynamics study.

The glucocorticoid receptor (GR) is a nuclear receptor that controls critical biological processes by regulating the transcription of specific genes. GR transcriptional activity is modulated by a series of ligands and coenzymes, where a ligand can act as an agonist or antagonist. GR agonists, such as the glucocorticoids dexamethasone (DEX) and prednisolone, are widely prescribed to patients with inflammatory and autoimmune diseases. DEX is also used to induce osteogenic differentiation in vitro. Recently, it has been highlighted that DEX induces changes in the osteogenic differentiation of human mesenchymal stromal cells by downregulating the transcription factor SRY-box transcription factor 9 (SOX9) and upregulating the peroxisome proliferator-activated receptor γ (PPARG). SOX9 is fundamental in the control of chondrogenesis, but also in osteogenesis by acting as a dominant-negative of RUNX2. Many processes remain to be clarified during cell fate determination, such as the interplay between the key transcription factors. The main objective pursued by this work is to shed light on the interaction between GR and SOX9 in the presence and absence of DEX at an atomic level of resolution using molecular dynamics simulations. The outcome of this research could help the understanding of possible molecular interactions between GR and SOX9 and their role in the determination of cell fate. The results highlight the key residues at the interface between GR and SOX9 involved in the complexation process and shed light on the mechanism through which DEX modulates GR-SOX9 binding and exerts its biological activity.

Computational assessment of lipid facilitated membrane permeation of vancomycin using force-probe molecular dynamic simulation.

In this study the efficacy of different edible lipids for drug permeation enhancement of vancomycin through biological membrane was investigated using molecular dynamic simulation. In this regard, at first the ability of the lipids for complex formation with the drug was evaluated for number of most common edible lipids including tripalmitin (TPA), trimyristin (TMY), labrafil (LAB), glycerol monostearate (GMS), glycerol monooleate (GMO), Distearoylphosphorylethanolamine (DSPE), dipalmitoylphosphatidylethanolamine (DPPE), Dipalmitoylphosphatidylcholine (DPPC), cholesterol (CL), stearic acid (SA), palmitic acid (PA) and oleic acid (OA). Then the complexes were pulled thorough a bilayer membrane while the changes in force were probed. The results showed that besides the SA, PA and OA the other examined lipids were able to perform a perfect molecular complex with the drug. Also the results of pulling simulation revealed that the least of force was needed for drug transmittance through the membrane when it was covered by LAB, TMY and DSPE. These results indicated that these lipids can be the excellent materials of choice as permeation enhancer for preparing a proper oral formulation of vancomycin.Communicated by Ramaswamy H. Sarma.

gmXtal: Cooking Crystals with GROMACS.

Molecular dynamics (MD) simulations are routinely performed of biomolecules in solution, because this is their native environment. However, the structures used in such simulations are often obtained with X-ray crystallography, which provides the atomic coordinates of the biomolecule in a crystal environment. With the advent of free electron lasers and time-resolved techniques, X-ray crystallography can now also access metastable states that are intermediates in a biochemical process. Such experiments provide additional data, which can be used, for example, to optimize MD force fields. Doing so requires that the simulation of the biomolecule is also performed in the crystal environment. However, in contrast to simulations of biomolecules in solution, setting up a crystal is challenging. In particular, because not all solvent molecules are resolved in X-ray crystallography, adding a suitable number of solvent molecules, such that the properties of the crystallographic unit cell are preserved in the simulation, can be difficult and typically is a trial-and-error based procedure requiring manual interventions. Such interventions preclude high throughput applications. To overcome this bottleneck, we introduce gmXtal, a tool for setting up crystal simulations for MD simulations with GROMACS. With the information from the protein data bank (rcsb.org) gmXtal automatically (i) builds the crystallographic unit cell; (ii) sets the protonation of titratable residues; (iii) builds missing residues that were not resolved experimentally; and (iv) adds an appropriate number of solvent molecules to the system. gmXtal is available as a standalone tool https://gitlab.com/pbuslaev/gmxtal .

pyGROMODS: a Python package for the generation of input files for molecular dynamic simulation with GROMACS.

The pyGROMODS, an easy-to-use cross-platform python-based package, with a graphical user interface, for the generation of molecular dynamic (MD) input files and running MD simulation (MDS) of proteins, peptides, and protein-ligand complex using GROMACS, is here presented. Four routes, with underlining Python scripts, are implemented in pyGROMODS for the generation of MD input files. They are 'RLmulti' for processing multi-ligand protein complex, 'RLmany' for processing multiple ligands against a single protein target, 'RLsingle' for processing multiple pairs of proteins and ligands, and 'PPmore' for processing peptides or proteins without ligands or non-standard residues. In addition, using the package, the generated input files or appropriate input files from other sources can be uploaded to run MDS with GROMACS. The pyGROMODS is implemented with a unique ability to search the host machine systems for the installation of the required software, update and/or install required Python packages, allow the user to pre-define working directory, and generate unique workflow organization with well-defined folders and files in a well-organized manner. The pyGROMODS, which is released under the MIT License, is freely available for download via the GitHub (https://github.com/Dankem/pyGROMODS) and Zenodo (https://doi.org/10.5281/zenodo.7912747) repositories. The precompiled executables can also be downloaded from Zenodo (https://doi.org/10.5281/zenodo.8087090), and a video tutorial can be downloaded from https://youtu.be/I4OKc6uVx1M.Communicated by Ramaswamy H. Sarma.