Geo-Measures: A PyMOL plugin for protein structure ensembles analysis

Understanding the stability and dynamics of influenza a H5N1 polymerase PB2 CAP-Binding domain in complex with natural compounds for antiviral drug discovery

Influenza A virus, particularly the H5N1 strain, poses a significant threat to public health due to its ability to cause severe respiratory illness and its high mortality rate. Traditional antiviral drugs targeting influenza A virus have faced challenges such as drug resistance and limited efficacy. Therefore, new antiviral compounds are needed to be discovered and developed. This study concentrated on examining the stability and behavior of the H5N1 polymerase PB2 CAP-binding domain when interacting with natural compounds, aiming to identify potential candidates for antiviral drug discovery. Through the virtual screening process, four lead compounds, ZINC000096095464, ZINC000044404209, ZINC000001562130, and ZINC000059779788, were selected, and these compounds showed binding energies -9.6, -9.4, -9.3, and -9.2 kcal/mol, respectively. When complexed with PB2, the ligand showed acceptable binding stability due to significant bond formation. However, during the 200ns MD simulation analysis, three (ZINC000096095464, ZINC000044404209, and ZINC000059779788) showed significant stability, which was proven by the trajectory analysis. The Rg-RMSD-based FEL plot showed significant structural stability due to stable conformers. The free-binding energy calculation also validates the stability of these complexes. This study offers valuable insights into the stability and dynamics of the H5N1 polymerase PB2 CAP-binding domain in complexes with natural compounds. These findings highlight the potential of these natural compounds as antiviral agents against the H5N1 influenza virus. Furthermore, this research contributes to the broader field of influenza virus treatment by demonstrating the effectiveness of computational methods in predicting and evaluating the stability and dynamics of potential drug candidates.

Structural and free energy landscape analysis for the discovery of antiviral compounds targeting the cap-binding domain of influenza polymerase PB2

Influenza poses a significant threat to global health, with the ability to cause severe epidemics and pandemics. The polymerase basic protein 2 (PB2) of the influenza virus plays a crucial role in the viral replication process, making the CAP-binding domain of PB2 an attractive target for antiviral drug development. This study aimed to identify and evaluate potential inhibitors of the influenza polymerase PB2 CAP-binding domain using computational drug discovery methods. We employed a comprehensive computational approach involving virtual screening, molecular docking, and 500 ns molecular dynamics (MD) simulations. Compounds were selected from the Diverse lib database and assessed for their binding affinity and stability in interaction with the PB2 CAP-binding domain. The study utilized the generalized amber force field (GAFF) for MD simulations to further evaluate the dynamic behaviour and stability of the interactions. Among the screened compounds, compounds 1, 3, and 4 showed promising binding affinities. Compound 4 demonstrated the highest binding stability and the most favourable free energy profile, indicating strong and consistent interaction with the target domain. Compound 3 displayed moderate stability with dynamic conformational changes, while Compound 1 maintained robust interactions throughout the simulations. Comparative analyses of these compounds against a control compound highlighted their potential efficacy. Compound 4 emerged as the most promising inhibitor, with substantial stability and strong binding affinity to the PB2 CAP-binding domain. These findings suggest that compound 4, along with compounds 1 and 3, holds the potential for further development into effective antiviral agents against influenza. Future studies should focus on experimental validation of these compounds and exploration of resistance mechanisms to enhance their therapeutic utility.

Antifungal potential of marine bacterial compounds in inhibiting Candida albicans Yck2 to overcome echinocandin resistance: a molecular dynamics study

Candida albicans (C. albicans), a common fungal pathogen, poses a significant threat to immunocompromised individuals, particularly due to the emergence of resistance against echinocandins, a primary class of antifungal agents. Yck2 protein, a key regulator of cell wall integrity and signaling pathways in C. albicans, was targeted to overcome this resistance. A virtual screening was used to identify Yck2 inhibitors from marine bacterial compounds. Further re-docking, molecular dynamics simulations, and various analyses such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bonding, free binding energy calculations, and RG-RMSD-based free energy landscape were conducted to evaluate the efficacy and stability of the identified compounds. Among the compounds screened, CMNPD27166 and CMNPD27283 emerged as the most promising candidates, demonstrating superior binding affinities, enhanced stability, and favorable interaction dynamics with Yck2, surpassing both the control and other compounds in efficacy. In contrast, CMNPD19660 and CMNPD24402, while effective, showed lesser potential. These findings highlight the utility of computational drug discovery techniques in identifying and optimizing potential therapeutic agents and suggest that marine-derived molecules could significantly impact the development of novel antifungal therapies. Further experimental validation of the leading candidates, CMNPD27166 and CMNPD27283, is recommended to confirm their potential as effective antifungal agents against echinocandin-resistant C. albicans infections.

Networks of ion-pairs are responsible for the large differences in the thermal stability of two structurally similar aminopeptidases

Aminopeptidases are an important class of enzymes for protein metabolism. Leucyl aminopeptidase (PepL) preferably removes leucine from the N-terminus of small peptides. PepL of Lacticaseibacillus casei was observed to be thermally unstable, while a structurally similar aminopeptidase T (AmpT) of Thermus thermophilus is highly stable. To understand the molecular interaction responsible for the large difference in their stability, molecular dynamics simulations were carried out to study the thermal stability of PepL and AmpT at 300 K to 450 K temperature range over 100 ns. PepL sampled a larger conformational space with a rugged free-energy landscape, while AmpT navigated a smoother energy landscape to reach the global minimum. The RMSD, RMSF, radius of gyration and principal component analysis suggested large movements in PepL than in AmpT with an increase in temperature. Analysis of residue-interaction network revealed AmpT possessing a greater number of low, medium and high energy contacts in comparison to PepL. AmpT showed a higher abundance of ion-pair clusters and ionic residues per cluster compared to PepL. Moreover, AmpT retained a greater number of high-energy contacts at elevated temperatures. These findings showed that the inherently lower stability of PepL originates from a comparatively smaller number of contacts and can be pivotal in engineering PepL for higher stability.

Exploring the anti-protozoal mechanisms of Syzygium aromaticum phytochemicals targeting Cryptosporidium parvum lactate dehydrogenase through molecular dynamics simulations

Cryptosporidium parvum (C. parvum), a protozoan parasite, is known to induce significant gastrointestinal disease in humans. Lactate dehydrogenase (LDH), a protein of C. parvum, has been identified as a potential therapeutic target for developing effective drugs against infection. This study utilized a computational drug discovery approach to identify potential drug molecules against the LDH protein of C. parvum. In the present investigation, we conducted a structure-based virtual screening of 55 phytochemicals from the Syzygium aromaticum (S. aromaticum). This process identified four phytochemicals, including Gallotannin 23, Eugeniin, Strictinin, and Ellagitannin, that demonstrated significant binding affinity and dynamic stability with LDH protein. Interestingly, these four compounds have been documented to possess antibacterial, antiviral, anti-inflammatory, and antioxidant properties. The docked complexes were simulated for 100 ns using Desmond to check the dynamic stability. Finally, the free binding energy was computed from the last 10ns MD trajectories. Gallotannin 23 and Ellagitannin exhibited considerable binding affinity and stability with the target protein among all four phytochemicals. These findings suggest that these predicted phytochemicals from S. aromaticum could be further explored as potential hit candidates for developing effective drugs against C. parvum infection. The in vitro and in vivo experimental validation is still required to confirm their efficacy and safety as LDH inhibitors.

Exploring fingerprints for antidiabetic therapeutics related to peroxisome proliferator-activated receptor gamma (PPARγ) modulators: A chemometric modeling approach

This study demonstrated the correlation of molecular structures of Peroxisome proliferator-activated receptor gamma (PPARγ) modulators and their biological activities. Bayesian classification, and recursive partitioning (RP) studies have been applied to a dataset of 323 PPARγ modulators with diverse scaffolds. The results provide a deep insight into the important sub-structural features modulating PPARγ. The molecular docking analysis again confirmed the significance of the identified sub-structural features in the modulation of PPARγ activity. Molecular dynamics simulations further underscored the stability of the complexes formed by investigated modulators with PPARγ. Overall, the integration of many computational approaches unveiled key structural motifs essential for PPARγ modulatory activity that will shed light on the development of effective modulators in the future.

Phosphorylation at the D56 residue of MtrA in Mycobacterium tuberculosis enhances its DNA binding affinity by modulating inter-domain interaction

The response regulator, MtrA, plays a major role in adaptation to the host environment, cell division, replication, and dormancy activation of Mycobacterium tuberculosis (Mtb). The phosphorylation of the response regulator MtrA alters the downstream activity, typically involving changes in DNA binding activity. However, there is a substantial knowledge gap in understanding the phosphorylation-mediated structural changes in MtrA. Additionally, the active conformation of the protein has yet to be determined. Therefore, in this study, we have investigated the phosphorylation-induced conformational changes of MtrA using all-atom molecular dynamics simulations under various phosphorylation conditions. The results from this study demonstrate that the phosphorylation at D56 (pD56-MtrA) increases the compactness of the MtrA protein by stabilizing the inter-domain interaction between the regulatory domain and DNA binding domain. Notably, the higher occupancy H-bond (over 95 %) between Arg200-Asn100 in case of the pD56-MtrA condition, which is otherwise absent in the non-phosphorylated (uMtrA) condition, suggests the importance of this interaction in the active conformation of the protein. The dynamic cross-correlation analysis reveals that phosphorylation (especially pD56-MtrA) reduces the anti-correlated motions and increases correlated motions between different domains. Moreover, the higher DNA binding affinity of pD56-MtrA compared to uMtrA supported by molecular docking and MD simulation followed by MMPBSA analysis suggests that pD56-MtrA is the possible active conformation of the MtrA protein. Overall, this investigation elucidates the key structural changes in MtrA under different phosphorylated conditions, which might help in designing novel therapeutics against tuberculosis.

Investigation of small molecules disrupting dengue virus assembly by inhibiting capsid protein and blocking RNA encapsulation

Dengue fever is a significant global public health concern, causing substantial morbidity and mortality worldwide. The disease can manifest in various forms, from mild fever to potentially life-threatening complications. Developing effective treatments remains a critical challenge to healthcare systems. Despite extensive research, no antiviral drugs have been approved for either the prevention or treatment of dengue. Targeting the virus during its early phase of attachment is essential to inhibit viral replication. The capsid protein plays a crucial role in the virus's structural integrity, assembly, and viral genome release. In the present study, we employed a computational approach focused on the capsid protein to identify possible potent inhibitors against the dengue virus from a library of FDA-approved drugs. We employed high-throughput virtual screening on FDA-approved drugs to identify drug molecules that could potentially combat the disease and save both cost and time. The screening process identified four drug molecules (Nordihydroguaiaretic acid, Ifenprodil tartrate, Lathyrol, and Safinamide Mesylate) based on their highest binding affinity and MM/GBSA scores. Among these, Nordihydroguaiaretic acid showed higher binding affinity than the reference molecule with - 11.66 kcal/mol. In contrast, Ifenprodil tartrate and Lathyrol showed similar results to the reference molecule, with binding energies of - 9.42 kcal/mol and - 9.29 kcal/mol, respectively. Following the screening, molecular dynamic simulations were performed to explore the molecular stability and conformational possibilities. The drug molecules were further supported by post-molecular simulation analysis. Furthermore, binding energies were also computed using the MM/GBSA approach, and the free energy landscape was used to calculate the different transition states, revealing that the drugs exhibited significant transition states. Specifically, Nordihydroguaiaretic acid and Ifenprodil tartrate displayed higher flexibility, while Lathyrol and Safinamide Mesylate showed more predictable and consistent protein folding. This significant breakthrough offers new hope against dengue, highlighting the power of computational drug discovery in identifying potent inhibitors and paving the way for novel treatment approaches.

Identification of potential NUDT5 inhibitors from marine bacterial natural compounds via molecular dynamics and free energy landscape analysis

NUDIX hydrolase 5 (NUDT5) is an enzyme involved in the hydrolysis of nucleoside diphosphates linked to other moieties, such as ADP-ribose. This cofactor is vital in redox reactions and is essential for the activity of sirtuins and poly(ADP-ribose) polymerases, which are involved in DNA repair and genomic stability. It has been shown that NUDT5 activity can also influence NAD+ homeostasis, thereby affecting cancer cell metabolism and survival. In this regard, the discovery of NUDT5 inhibitors has emerged as a potential therapeutic approach in cancer treatment. In this study, we conducted a high-throughput virtual screening of marine bacterial compounds against the NUDT5 enzyme and four molecules were selected based on their docking scores. These compounds established strong interactions within the NUDT5 active site, with molecular analysis highlighting the key role of Trp28A and Trp46B residues. Molecular dynamics simulations over 200 ns indicated a stable behavior, in association with root mean square deviation values always below 3 Å, suggesting conformational stability. Free energy landscape analysis further supported their potential as NUDT5 inhibitors, offering avenues for novel therapeutic strategies against NUDT5-associated breast cancer.

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.

Regulation of NS5B Polymerase Activity of Hepatitis C Virus by Target Specific Phytotherapeutics: An In-Silico Molecular Dynamics Approach

Chronic hepatitis caused by the hepatitis C virus (HCV) is closely linked with the advancement of liver disease. The research hypothesis suggests that the NS5B enzyme (non-structural 5B protein) of HCV plays a pivotal role in facilitating viral replication within host cells. Hence, the objective of the present investigation is to identify the binding interactions between the structurally diverse phytotherapeutics and those of the catalytic residue of the target NS5B polymerase protein. Results of our docking simulations reveal that compounds such as arjunolic acid, sesamin, arjungenin, astragalin, piperic acid, piperidine, piperine, acalyphin, adhatodine, amyrin, anisotine, apigenin, cuminaldehyde, and curcumin exhibit a maximum of three interactions with the catalytic residues (Asp 220, Asp 318, and Asp 319) present on the Hepatitis C virus NS5B polymerase of HCV. Molecular dynamic simulation, particularly focusing on the best binding lead compound, arjunolic acid (-8.78 kcal/mol), was further extensively analyzed using RMSD, RMSF, Rg, and SASA techniques. The results of the MD simulation confirm that the NS5B-arjunolic acid complex becomes increasingly stable from 20 to 100 ns. The orientation of both arjunolic acid and sofosbuvir triphosphate (standard) within the active site was investigated through DCCM, PCA, and FEL analysis, indicating highly stable interactions of the lead arjunolic acid with the catalytic region of the NS5B enzyme. The findings of our current investigation suggest that bioactive therapeutics like arjunolic acid could serve as promising candidates for limiting the NS5B polymerase activity of the hepatitis C virus, offering hope for the future of HCV treatment.

Structural analogs of 2-(4-fluorophenyl)-6-methyl-3-(pyridin-4-yl)pyrazolo[1,5-a]pyridine for targeting Candida albicans non-essential stress kinase Yck2 through protein-ligand binding and dynamics analysis

The rise in drug-resistant fungal infections poses a significant public health concern, necessitating the development of new antifungal therapies. We aimed to address this challenge by targeting a yeast casein kinase of Candida albicans for antifungal drug development. The compound library contained 589 chemical structures similar to the previously identified kinase inhibitor GW461484A. Through virtual screening, four compounds with the PubChem IDs 102583821, 12982634, 102487860, and 86260205 were selected based on their binding energies. Hydrophobic bonds and van der Waals interactions stabilised the docked complexes. Comprehensive interaction studies and a 200-nanosecond molecular dynamics simulation suggested that these molecules can maintain stable interactions with the target, as evidenced by satisfactory RMSD and RMSF values. The Rg-RMSD-based Free Energy Landscape of these complexes indicated thermodynamic stability due to the presence of conformers with global minima. These promising findings highlight the potential for developing novel antifungal therapies targeting Yck2 in C. albicans. Further experimental validation is required to assess the efficacy of these compounds as antifungal agents. This research provides a significant step towards combating antifungal resistance and opens up a new avenue for drug discovery.

Suppressing Mycobacterium tuberculosis virulence and drug resistance by targeting Eis protein through computational drug discovery

Tuberculosis (TB) remains a critical health threat, particularly with the emergence of multidrug-resistant strains. This demands attention from scientific communities and healthcare professionals worldwide to develop effective treatments. The enhanced intracellular survival (Eis) protein is an acetyltransferase enzyme of Mycobacterium tuberculosis that functions by adding acetyl groups to aminoglycoside antibiotics, which interferes with their ability to bind to the bacterial ribosome, thereby preventing them from inhibiting protein synthesis and killing the bacterium. Therefore, targeting this protein accelerates the chance of restoring the aminoglycoside drug activity, thereby reducing the emergence of drug-resistant TB. For this, we have screened 406,747 natural compounds from the Coconut database against Eis protein. Based on MM/GBSA rescoring binding energy, the top 5 most prominent natural compounds, viz. CNP0187003 (- 96.14 kcal/mol), CNP0176690 (- 93.79 kcal/mol), CNP0136537 (- 92.31 kcal/mol), CNP0398701 (- 91.96 kcal/mol), and CNP0043390 (- 91.60 kcal/mol) were selected. These compounds exhibited the presence of a substantial number of hydrogen bonds and other significant interactions confirming their strong binding affinity with the Eis protein during the docking process. Subsequently, the MD simulation of these compounds exhibited that the Eis-CNP0043390 complex was the most stable, followed by Eis-CNP0187003 and Eis-CNP0176690 complex, further verified by binding free energy calculation, principal component analysis (PCA), and Free energy landscape analysis. These compounds demonstrated the most favourable results in all parameters utilised for this investigation and may have the potential to inhibit the Eis protein. There these findings will leverage computational techniques to identify and develop a natural compound inhibitor as an alternative for drug-resistant TB.

In-silico screening of missense nsSNPs in Delta-opioid receptor protein and their restoring tendency on MCRT interaction; focusing on dynamic nature

Delta-opioid receptor protein (OPRD1) is one of the potential targets for treating pain. The presently available opioid agonists are known to cause unnecessary side effects. To discover a novel opioid agonist, our research group has synthesized a chimeric peptide MCRT and proved its potential activity through in vivo analysis. Non-synonymous SNPs (nsSNPs) missense mutations affect the functionality and stability of proteins leading to diseases. The current research was focused on understanding the role of MCRT in restoring the binding tendency of OPRD1 nsSNPs missense mutations on dynamic nature in comparison with Deltorphin-II and morphiceptin. The deleterious effects of nsSNPs were analyzed using various bioinformatics tools for predicting structural, functional, and oncogenic influence. The shortlisted nine nsSNPs were predicted for allergic reactions, domain changes, post-translation modification, multiple sequence alignment, secondary structure, molecular dynamic simulation (MDS), and peptide docking influence. Further, the docked complex of three shortlisted deleterious nsSNPs was analyzed using an MDS study, and the highly deleterious shortlisted nsSNP A149T was further analyzed for higher trajectory analysis. MCRT restored the binding tendency influence caused by nsSNPs on the dynamics of stability, functionality, binding affinity, secondary structure, residues connection, motion, and folding of OPRD1 protein.

Predictive identification and design of potent inhibitors targeting resistance-inducing candidate genes from E. coli whole-genome sequences

Introduction: This work utilizes predictive modeling in drug discovery to unravel potential candidate genes from Escherichia coli that are implicated in antimicrobial resistance; we subsequently target the gidB, MacB, and KatG genes with some compounds from plants with reported antibacterial potentials. Method: The resistance genes and plasmids were identified from 10 whole-genome sequence datasets of E. coli; forty two plant compounds were selected, and their 3D structures were retrieved and optimized for docking. The 3D crystal structures of KatG, MacB, and gidB were retrieved and prepared for molecular docking, molecular dynamics simulations, and ADMET profiling. Result: Hesperidin showed the least binding energy (kcal/mol) against KatG (-9.3), MacB (-10.7), and gidB (-6.7); additionally, good pharmacokinetic profiles and structure-dynamics integrity with their respective protein complexes were observed. Conclusion: Although these findings suggest hesperidin as a potential inhibitor against MacB, gidB, and KatG in E. coli, further validations through in vitro and in vivo experiments are needed. This research is expected to provide an alternative avenue for addressing existing antimicrobial resistances associated with E. coli's MacB, gidB, and KatG.

Functional characterization and structural prediction of hypothetical proteins in monkeypox virus and identification of potential inhibitors

The excessive activation of the monkeypox virus (MPXV-Congo_8-156) is linked to various skin and respiratory disorders such as rashes, fluid-filled blisters, swollen lymph nodes and encephalitis (inflammation of the brain), highlighting MPXV-Congo_8-156 as a promising target for drug intervention. Despite the effectiveness of Cidofovir, in inhibiting MPXV activity, its limited ability to penetrate the skin and its strong side effects restrict its application. To address this challenge, we screened 500 compounds capable of penetrating the skin and gastrointestinal tract to identify potent MPXV inhibitors. Various characterization schemes and structural models of MPXV-Congo_8-156 were explored with bioinformatics tools like PROTPARAM, SOPMA, SWISS-MODEL and PROCHECK. Using molecular docking in PyRx, we evaluated the binding affinities of these compounds with MPXV-Congo_8-156 and identified the top five candidates ranging from - 9.2 to - 8.8 kcal/mol. ADMET analysis indicated that all five compounds were safer alternatives, showing no AMES toxicity or carcinogenicity in toxicological assessments. Molecular dynamics (MD) simulations, conducted for 100 ns each, confirmed the docking interactions of the top five compounds alongside the control (Cidofovir), validating their potential as MPXV inhibitors. The compounds with PubChem CID numbers 4061636, 4422538, 3583576, 4856107 and 4800629 demonstrated strong support in terms of root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA) value, hydrogen bond analysis, and Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) analysis. Thus, our investigation identified these five compounds as promising inhibitors of MPXV, offering potential therapeutic avenues. However, further in vivo studies are necessary to validate our findings.

Genomic and computational-aided integrative drug repositioning strategy for EGFR and ROS1 mutated NSCLC

Non-small cell lung cancer (NSCLC) has been marked as the major cause of death in lung cancer patients. Due to tumor heterogeneity, mutation burden, and emerging resistance against the available therapies in NSCLC, it has been posing potential challenges in the therapy development. Hence, identification of cancer-driving mutations and their effective inhibition have been advocated as a potential approach in NSCLC treatment. Thereof, this study aims to employ the genomic and computational-aided integrative drug repositioning strategy to identify the potential mutations in the selected molecular targets and repurpose FDA-approved drugs against them. Accordingly, molecular targets and their mutations, i.e., EGFR (V843L, L858R, L861Q, and P1019L) and ROS1 (G1969E, F2046Y, Y2092C, and V2144I), were identified based on TCGA dataset analysis. Following, virtual screening and redocking analysis, Elbasvir, Ledipasvir, and Lomitapide drugs for EGFR mutants (>-10.8 kcal/mol) while Indinavir, Ledipasvir, Lomitapide, Monteleukast, and Isavuconazonium for ROS1 mutants (>-8.8 kcal/mol) were found as putative inhibitors. Furthermore, classical molecular dynamics simulation and endpoint binding energy calculation support the considerable stability of the selected docked complexes aided by substantial hydrogen bonding and hydrophobic interactions in comparison to the respective control complexes. Conclusively, the repositioned FDA-approved drugs might be beneficial alone or in synergy to overcome acquired resistance to EGFR and ROS1-positive lung cancers.

An immuno-informatics approach for annotation of hypothetical proteins and multi-epitope vaccine designed against the Mpox virus

A worrying new outbreak of Monkeypox (Mpox) in humans is caused by the Mpox virus (MpoxV). The pathogen has roughly 28 hypothetical proteins of unknown structure, function, and pathogenicity. Using reliable bioinformatics tools, we attempted to analyze the MpoxV genome, identify the role of hypothetical proteins (HPs), and design a potential candidate vaccine. Out of 28, we identified seven hypothetical proteins using multi-server validation with high confidence for the occurrence of conserved domains. Their physical, chemical, and functional characterizations, including molecular weight, theoretical isoelectric point, 3D structures, GRAVY value, subcellular localization, functional motifs, antigenicity, and virulence factors, were performed. We predicted possible cytotoxic T cell (CTL), helper T cell (HTL) and linear and conformational B cell epitopes, which were combined in a 219 amino acid multiepitope vaccine with human β defensin as a linker. This multi-epitopic vaccine was structurally modelled and docked with toll-like receptor-3 (TLR-3). The dynamical stability of the vaccine-TLR-3 docked complexes exhibited stable interactions based on RMSD and RMSF tests. Additionally, the modelled vaccine was cloned in-silico in an E. coli host to check the appropriate expression of the final vaccine built. Our results might conform to an immunogenic and safe vaccine, which would require further experimental validation.Communicated by Ramaswamy H. Sarma.

Structural and functional effects of the L84S mutant in the SARS-COV-2 ORF8 dimer based on microsecond molecular dynamics study

The L84S mutation has been observed frequently in the ORF8 protein of SARS-CoV-2, which is an accessory protein involved in various important functions such as virus propagation, pathogenesis, and evading the immune response. However, the specific effects of this mutation on the dimeric structure of ORF8 and its impacts on interactions with host components and immune responses are not well understood. In this study, we performed one microsecond molecular dynamics (MD) simulation and analyzed the dimeric behavior of the L84S and L84A mutants in comparison to the native protein. The MD simulations revealed that both mutations caused changes in the conformation of the ORF8 dimer, influenced protein folding mechanisms, and affected the overall structural stability. In particular, the 73YIDI76 motif has found to be significantly affected by the L84S mutation, leading to structural flexibility in the region connecting the C-terminal β4 and β5 strands. This flexibility might be responsible for virus immune modulation.  The free energy landscape (FEL) and principle component analysis (PCA) have also supported our investigation. Overall, the L84S and L84A mutations affect the ORF8 dimeric interfaces by reducing the frequency of protein-protein interacting residues (Arg52, Lys53, Arg98, Ile104, Arg115, Val117, Asp119, Phe120, and Ile121) in the ORF8 dimer.  Our findings provide detail insights for further research in designing structure-based therapeutics against the SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Marine alkaloid rigidin analogues as potential selective inhibitors of SHP1, a new strategy for cancer immunotherapeutics

SHP1 is a protein tyrosine phosphatase playing a central role in immunity, cell growth, development, and survival. The inhibition of SHP1 can help in better prognosis in various disorders like breast and ovarian cancer, melanoma, atherosclerosis, hypoxia, hypoactive immune response, and familial dysautonomia. The currently available inhibitors of SHP1 have the side effect of inhibiting the activity of SHP2, which shares >60% sequence similarity with SHP1 but has distinct biological functions. Thus, there is a need to search for novel specific inhibitors of SHP1. The current study uses a combination of virtual screening and molecular dynamic simulations, followed by PCA and MM-GBSA analysis, to screen about 35000 compounds; to predict that two rigidin analogues can potentially selectively inhibit SHP1 but not SHP2. Our studies demonstrate that these rigidin analogues are more potent at inhibiting SHP1 than the commercially available inhibitor NSC-87877. Further, cross-binding studies with SHP2 exhibited poor binding efficiency and lower stability of the complex, thus indicating a specificity of the rigidin analogues for SHP1, which is crucial in preventing side effects due to the diverse physiological functions of SHP2 in cellular signaling, proliferation, and hematopoiesis. Additionally, SHP1 is essential in mediating the inhibitory signaling in antitumor immune cells like NK and T cells. Hence, the rigidin analogues that inhibit SHP1 will potentiate the anti-tumor immune response by the release of inhibitory function of NK cells, thus driving NK activating response, in addition to their intrinsic anti-tumor function. Thus, SHP1 inhibition is a novel double-blade approach towards anti-cancer immunotherapeutics.Communicated by Ramaswamy H. Sarma.

Screening of Phytocompounds for Identification of Prospective Histone Deacetylase 1 (HDAC1) Inhibitor: An In Silico Molecular Docking, Molecular Dynamics Simulation, and MM-GBSA Approach

The upregulation of HDAC1 facilitate the induction of epigenetic repression of genes responsible for suppressing tumourigenesis, thereby triggering the development of cancer. HDAC1 inhibitors have thus emerged as possible therapeutic approaches against a variety of human malignancies, as they can inhibit the activity of certain HDACs, repair the overexpression of tumour suppressor genes, and induce cell differentiation, cell cycle arrest, and apoptosis. In this study, among 810 virtually screened compounds, Pinocembrin (PHUB000396) had a significant binding affinity (-7.99 kcal/mol). In molecular dynamics simulation (MD) studies for 200 ns time scale, the compound Pinocembrin effectively undergoes conformational optimization, thereby enabling its accommodation within the active site of the receptor. This outcome serves as a rational for the observed binding affinity. The optimal binding free energy calculations using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) (-35.86 ± 7.52 kcal/mol) showed the significant role of van der Waals forces and Coulomb interactions in the stability of the respective complex. The pharmacokinetic study showed its potential as a lead compound. The in-silico cytotoxicity prediction also confirmed its potential as an active anticancer phytocompound in lung and brain cancer. Therefore, it can be predicted that Pinocembrin could be a useful bioactive compound as an HDAC1 inhibitor and could be used in developing epigenetic therapy in cancer such as brain cancer and lung cancer to regulate gene expression.

Employing advanced computational drug discovery techniques to identify novel inhibitors against ML2640c protein: a potential therapeutic approach for combatting leprosy

Leprosy, caused by Mycobacterium leprae, remains a significant global health challenge, necessitating innovative approaches to therapeutic intervention. This study employs advanced computational drug discovery techniques to identify potential inhibitors against the ML2640c protein, a key factor in the bacterium's ability to infect and persist within host cells. Utilizing a comprehensive methodology, including virtual screening, re-docking, molecular dynamics simulations, and free energy calculations, we screened a library of compounds for their interaction with ML2640c. Four compounds (24349836, 26616083, 26648979, and 26651264) demonstrated promising inhibitory potential, each exhibiting unique binding energies and interaction patterns that suggest a strong likelihood of disrupting the protein function. The study highlights the efficacy of computational methods in identifying potential therapeutic candidates, presenting compound 26616083 as a notably potent inhibitor due to its excellent binding affinity and stability. Our findings offer a foundation for future experimental validation and optimization, marking a significant step forward in the development of new treatments for leprosy. This research not only advances the fight against leprosy but also showcases the broader applicability of computational drug discovery in tackling infectious diseases.

Computational Analysis of Albaflavenone Interaction with SlMAPK1 for Drought Resistance in Tomato

As global agricultural challenges intensify, particularly drought stress, the exploration of innovative strategies for crop resilience has become crucial. This study focuses on the role of the microbial endophyte metabolite Albaflavenone in enhancing drought resistance in tomato (Solanum lycopersicum L.) through the activation of the SlMAPK1 protein in the MAPK pathway. To computationally analyze the interaction between Albaflavenone and SlMAPK1 and to elucidate the potential enhancement of drought tolerance in tomato plants through this interaction. We utilized molecular docking, homology modeling, and molecular dynamics simulations to investigate the binding affinities and interaction dynamics between SlMAPK1 and Albaflavenone. Functional network analysis was employed to examine protein-protein interactions within the MAPK pathway, while the MM-GBSA method was used to calculate binding free energies. Our computational analyses revealed that Albaflavenone exhibited a high binding affinity to SlMAPK1 with a binding energy of - 8.9 kcal/mol. Molecular dynamics simulations showed this interaction significantly stabilized SlMAPK1, suggesting enhanced activity. Specifically, the root mean square deviation (RMSD) of the Albaflavenone-SlMAPK1 complex stabilized at around 3.1 Å, while the root mean square fluctuations (RMSF) indicated consistent amino acid conformations. Additionally, the radius of gyration (Rg) analysis demonstrated minimal variance, suggesting a compact and stable protein-ligand complex. The significant binding affinity between Albaflavenone and SlMAPK1 highlights the potential of leveraging plant-microbe interactions in developing sustainable agricultural practices. These findings also demonstrate the effectiveness of computational methods in dissecting complex biological interactions, contributing to a deeper understanding of plant resilience strategies against environmental stresses.

In silico discovery of potential PPI inhibitors for anti-lung cancer activity by targeting the CCND1-CDK4 complex via the P21 inhibition mechanism

Non-Small Cell Lung Cancer (NSCLC) is a prevalent and deadly form of lung cancer worldwide with a low 5-year survival rate. Current treatments have limitations, particularly for advanced-stage patients. P21, a protein that inhibits the CCND1-CDK4 complex, plays a crucial role in cell proliferation. Computer-Aided Drug Design (CADD) based on pharmacophores can screen and design PPI inhibitors targeting the CCND1-CDK4 complex. By analyzing known inhibitors, key pharmacophores are identified, and computational methods are used to screen potential PPI inhibitors. Molecular docking, pharmacophore matching, and structure-activity relationship studies optimize the inhibitors. This approach accelerates the discovery of CCND1-CDK4 PPI inhibitors for NSCLC treatment. Molecular dynamics simulations of CCND1-CDK4-P21 and CCND1-CDK4 complexes showed stable behavior, comprehensive sampling, and P21's impact on complex stability and hydrogen bond formation. A pharmacophore model facilitated virtual screening, identifying compounds with favorable binding affinities. Further simulations confirmed the stability and interactions of selected compounds, including 513457. This study demonstrates the potential of CADD in optimizing PPI inhibitors targeting the CCND1-CDK4 complex for NSCLC treatment. Extended simulations and experimental validations are necessary to assess their efficacy and safety.

Targeting key players in Alzheimer's disease: bioactive compounds from Moringa oleifera, Desmodium gangeticum, and Centella asiatica as potential therapeutics

Alzheimer's Disease (AD) is one of the critical reasons for dementia around the world, with a huge number of cases being reported every year. The breakdown of Amyloid Precursor Protein (APP) plays a crucial role in AD development. The Beta-site APP Cleaving Enzyme 1 (BACE1) is a highly significant proteolytic enzyme found to be critically involved in the APP breakdown process and generates beta-amyloid plaques in the extracellular neuronal membrane. In this study, we have used natural compounds with cognitive and neuroprotective activities from three plants, Centella asiatica, Moringa oleifera, and Desmodium gangeticum to inhibit the activity of BACE1. We have identified nine compounds out of 73 compounds filtered out from the three plants showing high affinity with the catalytic dyad region of BACE1 through molecular docking studies. Interestingly, the 200 ns molecular dynamics simulation study further confirmed the stability of the complexes formed between 9 compounds and the BACE1 protein. Furthermore, the free energy calculations also revealed these complexes possess favorable energies. Astilbin, Delphinidin 3-glucoside, and kaempferol 7-O-glucoside showed good binding affinity and structural stability when compared to other compounds and the control CNP520. Following a preliminary screening, the Astilbin compound was chosen based on the grounds of binding affinity, ADMET Properties, Hbond formation, Molecular Dynamic simulation, and MM-PBSA studies. A subsequent 1microsecond molecular dynamics simulation was conducted for the Astilbin complex. Through microsecond simulation, it was found that Astilbin alters BACE1's behavior and induces conformational rearrangements. Thus, this study opens a gateway to inhibit the activity of BACE1 protein through Astilbin thereby disclosing the possibility of managing Alzheimer's Disease.Communicated by Ramaswamy H. Sarma.

Origin of Chemoselectivity of Halohydrin Dehalogenase-Catalyzed Epoxide Ring-Opening Reactions

By performing molecular dynamics (MD), quantum mechanical/molecular mechanical (QM/MM) calculations, and QM cluster calculations, the origin of chemoselectivity of halohydrin dehalogenase (HHDH)-catalyzed ring-opening reactions of epoxide with the nucleophilic reagent NO2- has been explored. Four possible chemoselective pathways were considered, and the computed results indicate that the pathway associated with the nucleophilic attack on the Cα position of epoxide by NO2- is most energetically favorable and has an energy barrier of 12.9 kcal/mol, which is close to 14.1 kcal/mol derived from experimental kinetic data. A hydrogen bonding network formed by residues Ser140, Tyr153, and Arg157 can strengthen the electrophilicity of the active site of the epoxide substrate to affect chemoselectivity. To predict the energy barrier trends of the chemoselective transition states, multiple analyses including distortion analysis and electrophilic Parr function (Pk+) analysis were carried out with or without an enzyme environment. The obtained insights should be valuable for the rational design of enzyme-catalyzed and biomimetic organocatalytic epoxide ring-opening reactions with special chemoselectivity.

Omecamtiv mecarbil and Mavacamten target the same myosin pocket despite opposite effects in heart contraction

Inherited cardiomyopathies are common cardiac diseases worldwide, leading in the late stage to heart failure and death. The most promising treatments against these diseases are small molecules directly modulating the force produced by β-cardiac myosin, the molecular motor driving heart contraction. Omecamtiv mecarbil and Mavacamten are two such molecules that completed phase 3 clinical trials, and the inhibitor Mavacamten is now approved by the FDA. In contrast to Mavacamten, Omecamtiv mecarbil acts as an activator of cardiac contractility. Here, we reveal by X-ray crystallography that both drugs target the same pocket and stabilize a pre-stroke structural state, with only few local differences. All-atom molecular dynamics simulations reveal how these molecules produce distinct effects in motor allostery thus impacting force production in opposite way. Altogether, our results provide the framework for rational drug development for the purpose of personalized medicine.

MolDy: molecular dynamics simulation made easy

MOTIVATION

Molecular dynamics (MD) is a computational experiment that is crucial for understanding the structure of biological macro and micro molecules, their folding, and the inter-molecular interactions. Accurate knowledge of these structural features is the cornerstone in drug development and elucidating macromolecules functions. The open-source GROMACS biomolecular MD simulation program is recognized as a reliable and frequently used simulation program for its precision. However, the user requires expertise, and scripting skills to carrying out MD simulations.

RESULTS

We have developed an end-to-end interactive MD simulation application, MolDy for Gromacs. This front-end application provides a customizable user interface integrated with the Python and Perl-based logical backend connecting the Linux shell and Gromacs software. The tool performs analysis and provides the user with simulation trajectories and graphical representations of relevant biophysical parameters. The advantages of MolDy are (i) user-friendly, does not requiring the researcher to have prior knowledge of Linux; (ii) easy installation by a single command; (iii) freely available for academic research; (iv) can run with minimum configuration of operating systems; (v) has valid default prefilled parameters for beginners, and at the same time provides scope for modifications for expert users.

AVAILABILITY AND IMPLEMENTATION

MolDy is available freely as compressed source code files with user manual for installation and operation on GitHub: https://github.com/AIBResearchMolDy/Moldyv01.git and on https://aibresearch.com/innovations.

Network pharmacology and experimental insights into STAT3 inhibition by novel isoxazole derivatives of piperic acid in triple negative breast cancer

STAT3 is a crucial member within a family of seven essential transcription factors. Elevated STAT3 levels have been identified in various cancer types, notably in breast cancer (BC). Consequently, inhibiting STAT3 is recognized as a promising and effective strategy for therapeutic intervention against breast cancer. We herein synthesize a library of isoxazole (PAIs) from piperic acid [2E, 4E)-5-(2H-1,3-Benzodioxol-5-yl) penta-2,4-dienoic acid] on treatment with propargyl bromide followed by oxime under prescribed reaction conditions. Piperic acid was obtained by hydrolysis of piperine extracted from Piper nigrum. First, we checked the binding potential of isoxazole derivatives with breast cancer target proteins by network pharmacology, molecular docking, molecular dynamic (MD) simulation and cytotoxicity analysis as potential anti-breast cancer (BC) agents. The multi-source databases were used to identify possible targets for isoxazole derivatives. A network of protein-protein interactions (PPIs) was generated by obtaining 877 target genes that overlapped gene symbols associated with isoxazole derivatives and BC. Molecular docking and MD modelling demonstrated a strong affinity between isoxazole derivatives and essential target genes. Further, the cell viability studies of isoxazole derivatives on the human breast carcinoma cell lines showed toxicity in all breast cancer cell lines. In summary, our study indicated that the isoxazole derivative showed the significant anticancer activity. The results highlight the prospective utility of isoxazole derivatives as new drug candidates for anticancer chemotherapy, suggesting route for the continued exploration and development of drugs suitable for clinical applications.

Unveiling G-protein coupled receptor kinase-5 inhibitors for chronic degenerative diseases: Multilayered prioritization employing explainable machine learning-driven multi-class QSAR, ligand-based pharmacophore and free energy-inspired molecular simulation

GRK5 holds a pivotal role in cellular signaling pathways, with its overexpression in cardiomyocytes, neuronal cells, and tumor cells strongly associated with various chronic degenerative diseases, which highlights the urgent need for potential inhibitors. In this study, multiclass classification-based QSAR models were developed using diverse machine learning algorithms. These models were built from curated compounds with experimentally derived GRK5 inhibitory activity. Additionally, a pharmacophore model was constructed using active compounds from the dataset. Among the models, the SVM-based approach proved most effective and was initially used to screen DrugBank compounds within the applicability domain. Compounds showing significant GRK5 inhibitory potential underwent evaluation for key pharmacophoric features. Prospective compounds were subjected to molecular docking to assess binding affinity towards GRK5's key active site amino acid residues. Stability at the binding site was analyzed through 200 ns molecular dynamics simulations. MM-GBSA analysis quantified individual free energy components contributing to the total binding energy with respect to binding site residues. Metadynamics analysis, including PCA, FEL, and PDF, provided crucial insights into conformational changes of both apo and holo forms of GRK5 at defined energy states. The study identifies DB02844 (S-Adenosyl-1,8-Diamino-3-Thiooctane) and DB13155 (Esculin) as promising GRK5 inhibitors, warranting further in vitro and in vivo validation studies.

Exploring the Therapeutic Potential of Petiveria alliacea L. Phytochemicals: A Computational Study on Inhibiting SARS-CoV-2's Main Protease (Mpro)

The outbreak of SARS-CoV-2, also known as the COVID-19 pandemic, is still a critical risk factor for both human life and the global economy. Although, several promising therapies have been introduced in the literature to inhibit SARS-CoV-2, most of them are synthetic drugs that may have some adverse effects on the human body. Therefore, the main objective of this study was to carry out an in-silico investigation into the medicinal properties of Petiveria alliacea L. (P. alliacea L.)-mediated phytocompounds for the treatment of SARS-CoV-2 infections since phytochemicals have fewer adverse effects compared to synthetic drugs. To explore potential phytocompounds from P. alliacea L. as candidate drug molecules, we selected the infection-causing main protease (Mpro) of SARS-CoV-2 as the receptor protein. The molecular docking analysis of these receptor proteins with the different phytocompounds of P. alliacea L. was performed using AutoDock Vina. Then, we selected the three top-ranked phytocompounds (myricitrin, engeletin, and astilbin) as the candidate drug molecules based on their highest binding affinity scores of -8.9, -8.7 and -8.3 (Kcal/mol), respectively. Then, a 100 ns molecular dynamics (MD) simulation study was performed for their complexes with Mpro using YASARA software, computed RMSD, RMSF, PCA, DCCM, MM/PBSA, and free energy landscape (FEL), and found their almost stable binding performance. In addition, biological activity, ADME/T, DFT, and drug-likeness analyses exhibited the suitable pharmacokinetics properties of the selected phytocompounds. Therefore, the results of this study might be a useful resource for formulating a safe treatment plan for SARS-CoV-2 infections after experimental validation in wet-lab and clinical trials.

Pharmacoinformatics approach for the screening of Kovidra (Bauhinia variegata) phytoconstituents against tumor suppressor protein in triple negative breast cancer

Globally, 2.3 million women were diagnosed with breast cancer, with 6,85000 mortalities in year 2021; making it the world's most prevalent cancer. This growing global burden necessitates a new treatment option, and plant-based medicines offers a promising alternative to conventional cancer treatment. In this work, screening of phytoconstituents of an indigenous therapeutic plant, Bauhinia variegata carried out for potential regulator of tumor suppressor protein p53. Here, an in-silico analysis was employed to develop more effective, pharmaceutically potent small drug-like compounds that target tumor suppressor protein p53. The methanol and aqueous powdered extracts of Bauhinia variegata were prepared and phytochemically evaluated along with antioxidant property evaluation. The LC50 of methanol (325.33 µg/ml) and aqueous extract (361.15 µg/ml) showed their cytotoxic characteristics. Further, GCMS analysis of both the extracts reveals total 57 secondary metabolites. Among these, four lead compounds; compound 1, compound 2, compound 3 and compound 4 were found to have the highest binding ability (-8.15 to -5.40 kcal/mol) with p53. MD simulation and binding free energy validates these findings with highest binding free energy (-67.09 ± 4.87 kcal/mol) towards p53 by the lead phytocompound 2. Selected compounds exhibit excellent pharmacokinetic features and drug-like characteristics. The acute toxicity (LD50) values of the lead phytocompounds ranges from 670 mg/kg to 3100 mg/kg, with toxicity classes of IV and V. As a result, these druggable phytochemicals could serve as potential lead applicants for triple negative breast cancer treatment. However, more in vitro and in vivo research is planned to produce future breast cancer medicine. HIGHLIGHTSScreening of phytoconstituents of an indigenous therapeutic plant, Bauhinia variegata, for potential regulator of tumor suppressor protein p53.The LC50 of methanol (325.33µg/ml) and aqueous extract (361.15µg/ml) showed their cytotoxic characteristics.GCMS analysis of both the extracts reveals total 57 secondary metabolites. Among these, four lead compounds were found to have the highest binding affinity (-8.153 to -5.401 kcal/mol) with tumor suppressor protein p53.MD simulation along with the Prime MM/GBSA binding free energy validates this discovery with highest binding free energy (-67.09 ± 4.87 kcal/mol) towards p53 by the lead compound 2.The acute toxicity (LD50) values of the lead phytocompounds ranges from 670 mg/kg to 3100 mg/kg, with toxicity classes of IV and V.As a result, these druggable phytochemicals could serve as potential lead applicants for triple negative breast cancer treatment.Communicated by Ramaswamy H. Sarma.

Interaction analysis of SARS-CoV-2 omicron BA1 and BA2 of RBD with fifty monoclonal antibodies: Molecular dynamics approach

This report provides detailed insights into the interaction of fifty monoclonal antibodies with two recent Omicron variants, BA1 and BA2. It has been observed that numerous mutations in the receptor binding domain (RBD) result in significant structural changes in Omicron, enhancing its ability to mediate viral infections compared to other variants of concern. The following antibodies, namely JX3S304, 7KMG, 7CH4, 7BELCOVOX45, 7CDJ, 7C01, 7JX3S2H14, 6XCA, 7CDI, 7JMO, 7B3O, 6ZER, 6XC7CR3022, JX3S309, 6XC7CC123, 7CM4, 7KMI, 7L7EAZD8895, exhibit a superior binding affinity towards the Spike when compared to the reference CR3022. Four best-docked systems were subjected to further testing through molecular dynamics (MD) simulations. The MM/GBSA free energy for the top-scored complexes of BA1 variant are BA1_JX3S3O4, BA1_7KMI, BA1_7CH4, and BA1_7KMG, with respective values of -56.120 kcal/mol, -41.30 kcal/mol, -17.546 kcal/mol, and -8.527 kcal/mol; and of BA2 variant are BA2_JX3S3O4, BA2_7CM4, BA2_KMG, and BA2_7CH4, with respective values of -40.903 kcal/mol, -23.416 kcal/mol, -17.350 kcal/mol, and -5.460 kcal/mol. Detailed structural/energetic parameters, principal component analysis, and free energy landscape (FEL) studies reveal a significant decrease in antibody resistance due to the disappearance of numerous hydrogen bond interactions and various metastable states. We believe that these crucial mechanistic insights will contribute to breakthroughs in SARS-CoV-2 research.

In silico study of androgen receptor N-terminal domain and exploration of its modulators

The androgen receptor (AR, Uniprot: P10275) signaling plays a key role in the progression of prostate cancer, various AR-related ligands have been reported to treat prostate cancer. However, some resistance mechanisms limited the treating effect of these ligands. Since DBD binding or the allosteric binding sites in LBD of AR may allow the circumvention of some drug resistance mechanisms, anti-resistance is expected especially through the NTD (N-terminal domain) targeting. What's more, studies have shown that compounds including EPI-001 and its derivatives which bind to the Tau-5 region on NTD could be promising molecules for AR-based therapeutics. Herein, we employed aMD (accelerated molecular dynamics) simulation to fold Tau-5 unit proteins into native structure correctly. Subsequently, based on the predicted structural features of Tau-5, the virtual screening was conducted to discover new compounds targeting AR-NTD. We picked up 8 compounds (according to their docking scores and partly similar structural consists as known AR ligands) and analyzed their interaction with Tau-5, compared with the positive control EPI-001, four of the pick-up compounds showed better glide scores. Interestingly, although compound 8 had a lower docking score, it consisted of a similar component as the ligand EIQPN and the amide derivatives, this predicts that compound 8 has also the potential to be modified into an excellent AR-NTD binding molecule. These 8 compounds were all commercially available and could be tested to check whether there was a hit compound to bind the AR-NTD and to regulate its bio-activities. Together, this study described an in silico VLS approach to discover AR-NTD ligands and provided more choices for developing AR-targeted therapies.Communicated by Ramaswamy H. Sarma.

Antifungal drug discovery for targeting Candida albicans morphogenesis through structural dynamics study

In response to the escalating threat of drug-resistant fungi to human health, there is an urgent need for innovative strategies. Our focus is on addressing this challenge by exploring a previously untapped target, yeast casein kinase (Yck2), as a potential space for antifungal development. To identify promising antifungal candidates, we conducted a thorough screening of the diverse-lib drug-like molecule library, comprising 99,288 molecules. Five notable drug-like compounds with diverse-lib IDs 24334243, 24342416, 17516746, 17407455, and 24360740 were selected based on their binding energy scores surpassing 11 Kcal/mol. Our investigation delved into the interaction studies and dynamic stability of these compounds. Remarkably, all selected molecules demonstrated acceptable RMSD values during the 200 ns simulation, indicating their stable nature. Further analysis through Principal Component Analysis (PCA)-based Free Energy Landscape (FEL) revealed minimal energy transitions for most compounds, signifying dynamic stability. Notably, the two compounds exhibited slightly different behaviour in terms of energy transitions. These findings mark a significant breakthrough in the realm of antifungal drugs against C. albicans by targeting the Yck2 protein. However, it is crucial to note that additional experimental validation is imperative to assess the efficacy of these molecules as potential antifungal candidates. This study serves as a promising starting point for further exploration and development in the quest for effective antifungal solutions.Communicated by Ramaswamy H. Sarma.

Identification of Pyrazole Derivatives of Usnic Acid as Novel Inhibitor of SARS-CoV-2 Main Protease Through Virtual Screening Approaches

The infection produced by the SARS-CoV-2 virus remains a significant health crisis worldwide. The lack of specific medications for COVID-19 necessitates a concerted effort to find the much-desired therapies for this condition. The main protease (Mpro) of SARS-CoV-2 is a promising target, vital for virus replication and transcription. In this study, fifty pyrazole derivatives were tested for their pharmacokinetics and drugability, resulting in eight hit compounds. Subsequent molecular docking simulations on SARS-CoV-2 main protease afforded two lead compounds with strong affinity at the active site. Additionally, the molecular dynamics (MD) simulations of lead compounds (17 and 39), along with binding free energy calculations, were accomplished to validate the stability of the docked complexes and the binding poses achieved in docking experiments. Based on these findings, compound 17 and 39, with their favorable projected pharmacokinetics and pharmacological characteristics, are the proposed potential antiviral candidates which require further investigation to be used as anti-SARS-CoV-2 medication.

Phosphoserine aminotransferase deficiency diagnosed by whole-exome sequencing and LC-MS/MS reanalysis: A case report and review of literature

BACKGROUND

Phosphoserine aminotransferase deficiency (PSATD) is an autosomal recessive disorder associated with hypertonia, psychomotor retardation, and acquired microcephaly. Patients with PSATD have low concentrations of serine in plasma and cerebrospinal fluid.

METHODS

We reported a 2-year-old female child with developmental delay, dyskinesia, and microcephaly. LC-MS/MS was used to detect amino acid concentration in the blood and whole-exome sequencing (WES) was used to identify the variants. PolyPhen-2 web server and PyMol were used to predict the pathogenicity and changes in the 3D model molecular structure of protein caused by variants.

RESULTS

WES demonstrated compound heterozygous variants in PSAT1, which is associated with PSATD, with a paternal likely pathogenic variant (c.235G>A, Gly79Arg) and a maternal likely pathogenic variant (c.43G>C, Ala15Pro). Reduced serine concentration in LC-MS/MS further confirmed the diagnosis of PSATD in this patient.

CONCLUSIONS

Our findings demonstrate the importance of WES combined with LC-MS/MS reanalysis in the diagnosis of genetic diseases and expand the PSAT1 variant spectrum in PSATD. Moreover, we summarize all the cases caused by PSAT1 variants in the literature. This case provides a vital reference for the diagnosis of future cases.

Discovery of small molecule entry inhibitors targeting the linoleic acid binding pocket of SARS-CoV-2 spike protein

Spike glycoprotein has a significant role in the entry of SARS-CoV-2 to host cells, which makes it a potential drug target. Continued accumulation of non-synonymous mutations in the receptor binding domain of spike protein poses great challenges in identifying antiviral drugs targeting this protein. This study aims to identify potential entry inhibitors of SARS-CoV-2 using virtual screening and molecular dynamics (MD) simulations from three distinct chemical libraries including Pandemic Response Box, Drugbank and DrugCentral, comprising 6971 small molecules. The molecules were screened against a binding pocket identified in the receptor-binding domain (RBD) region of the spike protein which is known as the linoleic acid binding pocket, a highly conserved motif among several SARS-CoV-2 variants. Through virtual screening and binding free energy calculations, we identified four top-scoring compounds, MMV1579787 ([2-Oxo-2-[2-(3-phenoxyphenyl)ethylamino]ethyl]phosphonic acid), Tretinoin, MMV1633963 ((2E,4E)-5-[3-(3,5-dichlorophenoxy)phenyl]penta-2,4-dienoic acid) and Polydatin, which were previously reported to have antibacterial, antifungal or antiviral properties. These molecules showed stable binding on MD simulations over 100 ns and maintained stable interactions with TYR365, PHE338, PHE342, PHE377, TYR369, PHE374 and LEU368 of the spike protein RBD that are found to be conserved among SARS-CoV-2 variants. Our findings were further validated with free energy landscape, principal component analysis and dynamic cross-correlation analysis. Our in silico analysis of binding mode and MD simulation analyses suggest that the identified compounds may impede viral entrance by interacting with the linoleic acid binding site of the spike protein of SARS-CoV-2 regardless of its variants, and they thus demand for further in vitro and in vivo research.Communicated by Ramaswamy H. Sarma.

QSAR modeling approaches to identify a novel ACE2 inhibitor that selectively bind with the C and N terminals of the ectodomain

Due to the high rates of drug development failure and the massive expenses associated with drug discovery, repurposing existing drugs has become more popular. As a result, we have used QSAR modelling on a large and varied dataset of 657 compounds in an effort to discover both explicit and subtle structural features requisite for ACE2 inhibitory activity, with the goal of identifying novel hit molecules. The QSAR modelling yielded a statistically robust QSAR model with high predictivity (R2tr=0.84, R2ex=0.79), previously undisclosed features, and novel mechanistic interpretations. The developed QSAR model predicted the ACE2 inhibitory activity (PIC50) of 1615 ZINC FDA compounds. This led to the detection of a PIC50 of 8.604 M for the hit molecule (ZINC000027990463). The hit molecule's docking score is -9.67 kcal/mol (RMSD 1.4). The hit molecule revealed 25 interactions with the residue ASP40, which defines the N and C termini of the ectodomain of ACE2. The HIT molecule conducted more than thirty contacts with water molecules and exhibited polar interaction with the ARG522 residue coupled with the second chloride ion, which is 10.4 nm away from the zinc ion. Both molecular docking and QSAR produced comparable findings. Moreover, MD simulation and MMGBSA studies verified docking analysis. The MD simulation showed that the hit molecule-ACE2 receptor complex is stable for 400 ns, suggesting that repurposed hit molecule 3 is a viable ACE2 inhibitor.

Protracted molecular dynamics and secondary structure introspection to identify dual-target inhibitors of Nipah virus exerting approved small molecules repurposing

Nipah virus (NiV), with its significantly higher mortality rate compared to COVID-19, presents a looming threat as a potential next pandemic, particularly if constant mutations of NiV increase its transmissibility and transmission. Considering the importance of preventing the facilitation of the virus entry into host cells averting the process of assembly forming the viral envelope, and encapsulating the nucleocapsid, it is crucial to take the Nipah attachment glycoprotein-human ephrin-B2 and matrix protein as dual targets. Repurposing approved small molecules in drug development is a strategic choice, as it leverages molecules with known safety profiles, accelerating the path to finding effective treatments against NiV. The approved small molecules from DrugBank were used for repurposing and were subjected to extra precision docking followed by absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling. The 4 best molecules were selected for 500 ns molecular dynamics (MD) simulation followed by Molecular mechanics with generalized Born and surface area solvation (MM-GBSA). Further, the free energy landscape, the principal component analysis followed by the defined secondary structure of proteins analysis were introspected. The inclusive analysis proposed that Iotrolan (DB09487) and Iodixanol (DB01249) are effective dual inhibitors, while Rutin (DB01698) and Lactitol (DB12942) were found to actively target the matrix protein only.

Discovery of thiazolidinedione-based pancreatic lipase inhibitors as anti-obesity agents: synthesis, in silico studies and pharmacological investigations

A series of new 2,5-disubstituted arylidene derivatives of thiazolidinedione (16a-e, 17a-d, 18a-c) designed using molecular hybridization approach were synthesized, structurally characterized, and explored for their anti-obesity potential via inhibition of Pancreatic Lipase (PL). Compound 18a presented the most potent PL inhibitory activity with IC50 = 2.71 ± 0.31 µM, as compared to the standard drug, Orlistat (IC50 = 0.99 µM). Kinetic study revealed reversible competitive mode of enzyme inhibition by compound 18a with an inhibitory constant value of 1.19 µM. The most promising compound 18a revealed satisfactory binding mode within the active site of the target protein (human PL, PDB ID: 1LPB). Also, MM/PBSA binding free energy and molecular dynamics (MD) simulation analysis were performed for the most promising compound 18a, which showed potent inhibition according to the results of in vitro studies. Furthermore, a stable conformation of the 1LPB-ligand suggested the stability of this compound in the dynamic environment. The ADME and toxicity analysis of the compounds were examined using web-based online platforms. Results of in vivo studies confirmed the anti-obesity efficacy of compound 18a, wherein oral treatment with compound 18a (30 mg/kg) resulted in a significant reduction in the body weight, BMI, Lee index, feed intake (in Kcal), body fat depots and serum triglycerides. Compound 18a significantly decreased the levels of serum total cholesterol (TC) to 128.6 ± 0.59 mg/dl and serum total triglycerides (TG) to 95.73 ± 0.67 mg/dl as compared to the HFD control group. The present study identified disubstituted TZD derivatives as a new promising class of anti-obesity agents.Communicated by Ramaswamy H. Sarma.

Monophasic coamorphous sulpiride: a leap in physicochemical attributes and dual inhibition of GlyT1 and P-glycoprotein, supported by experimental and computational insights

Study aimed to design and development of a supramolecular formulation of sulpiride (SUL) to enhance its solubility, dissolution and permeability by targeting a novel GlyT1 inhibition mechanism. SUL is commonly used to treat gastric and duodenal ulcers, migraine, anti-emetic, anti-depressive and anti-dyspeptic conditions. Additionally, Naringin (NARI) was incorporated as a co-former to enhance the drug's intestinal permeability by targeting P-glycoprotein (P-gp) efflux inhibition. NARI, a flavonoid has diverse biological activities, including anti-apoptotic, anti-oxidant, and anti-inflammatory properties. This study aims to design and develop a supramolecular formulation of SUL with NARI to enhance its solubility, dissolution, and permeability by targeting a novel GlyT1 inhibition mechanism, extensive experimental characterization was performed using solid-state experimental techniques in conjunction with a computational approach. This approach included quantum mechanics-based molecular dynamics (MD) simulation and density functional theory (DFT) studies to investigate intermolecular interactions, phase transformation and various electronic structure-based properties. The findings of the miscibility study, radial distribution function (RDF) analysis, quantitative simulations of hydrogen/π-π bond interactions and geometry optimization aided in comprehending the coamorphization aspects of SUL-NARI Supramolecular systems. Molecular docking and MD simulation were performed for detailed binding affinity assessment and target validation. The solubility, dissolution and ex-vivo permeability studies demonstrated significant improvements with 31.88-fold, 9.13-fold and 1.83-fold increments, respectively. Furthermore, biological assessments revealed superior neuroprotective effects in the SUL-NARI coamorphous system compared to pure SUL. In conclusion, this study highlights the advantages of a drug-nutraceutical supramolecular formulation for improving the solubility and permeability of SUL, targeting novel schizophrenia treatment approaches through combined computational and experimental analyses.Communicated by Ramaswamy H. Sarma.

Netting into the Sophoretin pool: An approach to trace GSTP1 inhibitors for reversing chemoresistance

Chemoresistance, a significant challenge in cancer treatment, is often associated with the cellular glutathione-related detoxification system. The GSTP1 isoenzyme (glutathione S-transferases) plays a critical role in the cytoplasmic inactivation of anticancer drugs. This suggests the identification of GSTP1 inhibitors to combat chemoresistance. We screened Sophoretin (also called quercetin) derivatives for molecular properties, pharmacokinetics, and toxicity profiles. Following that, we conducted molecular docking and simulations between selected derivatives and GSTP1. The best-docked complex, GSTP1-quercetin 7-O-β-D-glucoside, exhibited a binding affinity of -8.1 kcal/mol, with no predicted toxicity and good pharmacokinetic properties. Molecular dynamics simulations confirmed the stability of this complex. Quercetin 7-O-β-D-glucoside shows promise as a lead candidate for addressing chemoresistance in cancer patients, although further experimental studies are needed to validate its efficacy and therapeutic potential.

Integrating network pharmacology and in silico analysis deciphers Withaferin-A's anti-breast cancer potential via hedgehog pathway and target network interplay

This study examines the remarkable effectiveness of Withaferin-A (WA), a withanolide obtained from Withania somnifera (Ashwagandha), in encountering the mortiferous breast malignancy, a global peril. The predominant objective is to investigate WA's intrinsic target proteins and hedgehog (Hh) pathway proteins in breast cancer targeting through the application of in silico computational techniques and network pharmacology predictions. The databases and webtools like Swiss target prediction, GeneCards, DisGeNet and Online Mendelian Inheritance in Man were exploited to identify the common target proteins. The culmination of the WA network and protein-protein interaction network were devised using Stitch and String web tools, through which the drug-target network of 30 common proteins was constructed employing Cytoscape-version 3.9. Enrichment analysis was performed by incorporating Gprofiler, Metascape and Cytoscape plugins. David compounded the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and enrichment was computed through bioinformatics tools. The 20 pivotal proteins were docked harnessing Glide, Schrodinger Suite 2023-2. The investigation was governed by docking scores and affinity. The shared target proteins underscored the precise Hh and WA network roles with the affirmation enrichment P-value of <0.025. The implications for hedgehog and cancer pathways were profound with enrichment (P < 0.01). Further, the ADMET and drug-likeness assessments assisted the claim. Robust interactions were noticed with docking studies, authenticated through molecular dynamics, molecular mechanics generalized born surface area scores and bonds. The computational investigation emphasized WA's credible anti-breast activity, specifically with Hh proteins, implying stem-cell-level checkpoint restraints. Rigorous testament is imperative through in vitro and in vivo studies.

Deciphering Campylobacter jejuni DsbA1 protein dynamics in the presence of anti-virulent compounds: a multi-pronged computer-aided approach

The current study aims to evaluate Asinex library compounds against Campylobacter jejuni DsbA1 protein, a thiol disulfide oxidoreductase enzyme that plays a major role in the oxidative folding of bacterial virulence proteins, making it a promising anti-viral drug target. By employing several techniques of computer-aided drug design, BDC25697459, BDD33601083, and BDC30129064 were identified with binding energy scores of -8.8 kcal/mol, -8.8 kcal/mol, and -8.3 kcal/mol, respectively. However, the control molecule, tetraethylene glycol, exhibited a binding energy score of -7.0 kcal/mol. The control, BDD33601083, and BDC30129064 were unveiled to bind the same co-crystallized binding site (pocket 1), while BDC25697459 interacted with a new binding pocket (pocket 2) adjacent to the control binding region. The molecular dynamics simulation showed that complexes exhibit stable dynamics without significant global or residue-level fluctuations. The average RMSD values were in the range of 2.07 Å-2.45 Å. Similarly, mean RMSF was recorded between 1.30 and 1.42 Å. The C. jejuni DsbA1 was also observed as compact in the presence of the compounds, showing a mean RoG value in the range of 16.42 Å-16.55 Å. In terms of MM/PBSA binding energy, the BDC30129064 complex was ranked top with -44.88 ± 4.14 kcal/mol, whereas the positive control molecule exhibited -22.22 ± 3.33 kcal/mol. From a pharmacokinetic perspective, the compounds are suitable candidates for clinical trial investigation. Preliminary computational analysis of these virtual hits indicates that these compounds have a low potential for ADME and toxicity-associated liabilities. In summary, the compounds displayed a high affinity for the C. jejuni DsbA1 protein, indicating potential efficacy that requires further investigation.Communicated by Ramaswamy H. Sarma.

Application of in-silico drug discovery techniques to discover a novel hit for target-specific inhibition of SARS-CoV-2 Mpro's revealed allosteric binding with MAO-B receptor: A theoretical study to find a cure for post-covid neurological disorder

Several studies have revealed that SARS-CoV-2 damages brain function and produces significant neurological disability. The SARS-CoV-2 coronavirus, which causes COVID-19, may infect the heart, kidneys, and brain. Recent research suggests that monoamine oxidase B (MAO-B) may be involved in metabolomics variations in delirium-prone individuals and severe SARS-CoV-2 infection. In light of this situation, we have employed a variety of computational to develop suitable QSAR model using PyDescriptor and genetic algorithm-multilinear regression (GA-MLR) models (R2 = 0.800-793, Q2LOO = 0.734-0.727, and so on) on the data set of 106 molecules whose anti-SARS-CoV-2 activity was empirically determined. QSAR models generated follow OECD standards and are predictive. QSAR model descriptors were also observed in x-ray-resolved structures. After developing a QSAR model, we did a QSAR-based virtual screening on an in-house database of 200 compounds and found a potential hit molecule. The new hit's docking score (-8.208 kcal/mol) and PIC50 (7.85 M) demonstrated a significant affinity for SARS-CoV-2's main protease. Based on post-covid neurodegenerative episodes in Alzheimer's and Parkinson's-like disorders and MAO-B's role in neurodegeneration, the initially disclosed hit for the SARS-CoV-2 main protease was repurposed against the MAO-B receptor using receptor-based molecular docking, which yielded a docking score of -12.0 kcal/mol. This shows that the compound that inhibits SARS-CoV-2's primary protease may bind allosterically to the MAO-B receptor. We then did molecular dynamic simulations and MMGBSA tests to confirm molecular docking analyses and quantify binding free energy. The drug-receptor complex was stable during the 150-ns MD simulation. The first computational effort to show in-silico inhibition of SARS-CoV-2 Mpro and allosteric interaction of novel inhibitors with MAO-B in post-covid neurodegenerative symptoms and other disorders. The current study seeks a novel compound that inhibits SAR's COV-2 Mpro and perhaps binds MAO-B allosterically. Thus, this study will enable scientists design a new SARS-CoV-2 Mpro that inhibits the MAO-B receptor to treat post-covid neurological illness.

Assessing the potential of Psidium guajava derived phytoconstituents as anticholinesterase inhibitor to combat Alzheimer's disease: an in-silico and in-vitro approach

Acetylcholinesterase (AChE) inhibitors play a crucial role in the treatment of Alzheimer's disease. These drugs increase acetylcholine levels by inhibiting the enzyme responsible for its degradation, which is a vital neurotransmitter involved in memory and cognition. This intervention intermittently improves cognitive symptoms and augments neurotransmission. This study investigates the potential of Psidium guajava fruit extract as an acetylcholinesterase (AChE) inhibitor for Alzheimer's disease treatment. Molecular characteristics and drug-likeness were analyzed after HR-LCMS revealed phytocompounds in an ethanolic extract of Psidium guajava fruit. Selected phytocompounds were subjected to molecular docking against AChE, with the best-docked compound then undergoing MD simulation, MMGBSA, DCCM, FEL, and PCA investigations to evaluate the complex stability. The hit compound's potential toxicity and further pharmacokinetic features were also predicted. Anticholinesterase activity was also studied using in vitro assay. The HR-LCMS uncovered 68 compounds. Based on computational analysis, Fluspirilene was determined to have the highest potential to inhibit AChE. It was discovered that the Fluspirilene-AChE complex is stable and that Fluspirilene has a high binding affinity for AChE. Extract of Psidium guajava fruit significantly inhibits AChE (88.37% at 200 μg/ml). It is comparable to the standard AChE inhibitor Galantamine. Fluspirilene exhibited remarkable binding to AChE. Psidium guajava fruit extract demonstrated substantial AChE inhibitory activity, indicating its potential for Alzheimer's treatment. The study underscores natural sources' significance in drug discovery.Communicated by Ramaswamy H. Sarma.

In silico and in vitro studies: investigating the chemical composition, DFT, molecular docking, and dynamic simulation of Satureja candidissima (Munby) Briq essential oil as a potential antibacterial agent

This study aimed to investigate the chemical composition and antibacterial properties of the essential oil (EO) derived from the aerial parts of Satureja candidissima (Munby) Briq (SC), as well as the mechanisms of interaction between SCEO chemical components and target proteins related to antibacterial activity mechanisms using a molecular docking approach, and for more accuracy molecular dynamic simulation and DFT calculations were carried out. The GC-MS technique was used to analyze the chemical composition of SCEO. The results showed that SCEO contained various chemical compounds, with pulegone being identified as the major component (53.26%). The results also indicated the presence of (+)-menthone (11.02%), borneol (4.43%), 2-cyclohexen-1-one, 3-methyl-6-(1-methylethylidene) (2.50%), and 3-octanol (2.09%). The study revealed that the SCEO displayed antibacterial activity against all tested gram-positive bacteria. To further understand the mechanism behind its antibacterial activity, in silico molecular docking studies were performed. The results indicated that the antibacterial effect of SCEO compounds could be due to the combination with enoyl-[acyl-carrier-protein] reductase [NADPH] FabI (PDB ID: 4ALL) in a variety of ways. The molecular dynamics simulation analysis yielded favorable outcomes for the docked complex involving 1H-cycloprop[e]azulen-7-ol, decahydro-1,1,7-trimethyl-4-methylene, and 1,4,7-tetramethyldecahydro-1H-cyclopropa[e]azulen-4-ol with enoyl-[acyl-carrier-protein] reductase [NADPH]. Geometry optimization, coupled with Density Functional Theory (DFT), can be employed to assess the importance of quantum chemical descriptors in elucidating potential antibacterial activity. Quantum descriptors were computed based on EHOMO and ELUMO. The results of this study provide important insights into the potential use of Satureja candidissima (Munby) Briq EO as antibacterial agent.Communicated by Ramaswamy H. Sarma.

Exploration of comprehensive marine natural products database against dengue viral non-structural protein 1 using high-throughput computational studies

Dengue virus (DENV) non-structural protein 1 (NS1) is a versatile quasi-protein essential for the multiplication of the virus. This study applied high-throughput virtual screening (HTVS) and molecular dynamics (MD) simulation to detect the potential marine natural compounds against the NS1 of DENV. The structure of the NS1 protein was retrieved from Protein Data Bank with (PDB ID: 4O6B). Missing residues were added using modeler software. Molecular operating environment (MOE) programme was used to prepare the protein before docking. Virtual screening was performed on PyRx software to identify natural compounds retrieved from Comprehensive Marine Natural Products Database (CMNPD) against the NS1 protein, and best-docked compounds were examined by molecular docking and molecular dynamic (MD) simulation. Out of 31,561 marine compounds, the top 10 compounds showed docking scores lesser than -8.0 kcal/mol. One of the best hit compounds, CMNPD6802, was further analyzed using MD simulation study at 100 nanoseconds and Molecular Mechanics with Generalized Born and Surface Area Solvation (MM/GBSA). Based on its total binding energy, determined using the MM/GBSA approach, CMNPD6802 was ranked first. Its pharmacokinetic properties concerning the target protein NS1 were also evaluated. The results of the MD simulation showed that CMNPD6802 remained in close contact with the protein throughout the activation period, mapped using principal component analysis. These findings suggest that CMNPD6802 could serve as an NS1 inhibitor and may be a potential candidate for treating DENV infections.Communicated by Ramaswamy H. Sarma.

A combined ligand-based and structure-based in silico molecular modeling approach to pinpoint the key structural attributes of hydroxamate derivatives as promising meprin β inhibitors

Human meprin β is a Zn2+-containing multidomain metalloprotease enzyme that belongs to the astacin family of the metzincin endopeptidase superfamily. Meprin β, with its diverse tissue expression pattern and wide substrate specificity, plays a significant role in various biological processes, including regulation of IL-6R pathways, lung fibrosis, collagen deposition, cellular migration, neurotoxic amyloid β levels, and inflammation. Again, meprin β is involved in Alzheimer's disease, hyperkeratosis, glomerulonephritis, diabetic kidney injury, inflammatory bowel disease, and cancer. Despite a crucial role in diverse disease processes, no such promising inhibitors of meprin β are marketed to date. Thus, it is an unmet requirement to find novel promising meprin β inhibitors that hold promise as potential therapeutics. In this study, a series of arylsulfonamide and tertiary amine-based hydroxamate derivatives as meprin β inhibitors has been analyzed through ligand-based and structure-based in silico approaches to pinpoint their structural and physiochemical requirements crucial for exerting higher inhibitory potential. This study identified different crucial structural features such as arylcarboxylic acid, sulfonamide, and arylsulfonamide moieties, as well as hydrogen bond donor and hydrophobicity, inevitable for exerting higher meprin β inhibition, providing valuable insight for their further future development.Communicated by Ramaswamy H. Sarma.