MM-PBSA Analysis Research Articles

Exploring the therapeutic effect of melatonin targeting common biomarkers in testicular germ cell tumor, prostate adenocarcinoma, and male infertility: an integrated biology approach.

Globally, male infertility (MI) is a major concern. Several other comorbidities related to MI are testicular germ cell tumor (TGCT) and prostate adenocarcinoma (PRAD). This study focuses on finding the common biomarkers among these diseases and their interaction with Melatonin (MLT). The differential expressed genes were retrieved using the GEPIA2 database for TGCT and PRAD, whereas the DISGENET database for MI-related genes. InteractiVenn was performed in response to identify the common genes. The STAG3, RNF212, DDX3Y, DPY19L2, TPCN1, KLK3, GNRH1, DMD, CCDC146, and DNAH1 are found to be involved in all these diseases. The gene ontologies and pathway enrichment analysis were done for these significant genes in response to identifying and accessing the involvement of these genes in other processes. MLT is a neuroendocrine hormone with high therapeutic properties. MLT showed the best binding energy with DDX3Y among all the proteins. Molecular dynamic simulation (MDS) of MLT with DDX3Y was performed and found to be-52.382 ± 13.110kJ/mol binding energy. The RMSD, RMSF, SASA, RG, H-bond, FEL, PCA, and MM-PBSA analysis confirm the stability and compactness of the DDX3Y-MLT complex. The MDS results indicate that MLT is a promising therapeutic option for enhancing DDX3Y expression, which will support spermatogenesis. Additionally, the hub genes were identified based on MCC parameters from the merged interactive network of common genes in response to finding significant genes that can be a potential biomarker for the diagnosis of diseases.

Elucidating the α-amylase Inhibitory Activity of Phytochemicals from Artocarpus altilis: An In silico and In vitro Approach

Elucidating the α-amylase Inhibitory Activity of Phytochemicals from Artocarpus altilis: An In silico and In vitro Approach

Discovering promising drug candidates for Parkinson's disease: integrating miRNA and DEG analysis with molecular dynamics and MMPBSA.

Parkinson's disease (PD) is a progressive neurological disorder with an increasing prevalence in aging populations. Identifying effective therapeutic targets and treatments remains a critical challenge. This study aimed to discover potential therapeutic targets and design novel compounds for PD treatment. Gene expression analysis was conducted using diverse datasets, including microarray, mRNA sequencing, and miRNA sequencing. While no common genes were identified across all datasets, the RNA-seq dataset GSE-135036 was prioritized. The investigation focused on downregulated miRNAs targeting upregulated mRNAs, revealing that hsa-mir-5585 regulates Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) within the Shigellosis pathway. Given RIPK1's role in cell death and inflammation, it emerged as a promising therapeutic target for PD. To identify RIPK1 inhibitors, 67 compounds were screened via molecular docking, with CHEMBL-3109201 exhibiting the highest binding affinity. A structurally similar compound, CHEMBL-76328382, also demonstrated strong interactions. A fragment-based drug design approach generated two novel compounds, BI-1215 and BI-146, which, along with RIPK1-IN-4 and CHEMBL-70909876, were shortlisted based on docking scores and ADME profiles. Molecular dynamics simulations confirmed the stability of CHEMBL-70909876 and BI-1215, with RMSD fluctuations between 0.005 and 0.2nm. MM-PBSA analysis further validated their superior thermodynamic stability and binding affinity compared to other candidates. This study offers novel insights into PD pathogenesis and potential therapeutic interventions, marking a significant step toward effective treatment strategies for this debilitating disorder.

In vitro Antibiofilm Activity-directed In silico Identification of Natural Products Targeting Bacterial Biofilm Regulators SarA and LasR.

Antibiofilm agents serve as an essential tool in the fight against antibiotic resistance, and natural products provide a promising source for potential drug leads. This study investigates the activity of twenty Bangladeshi medicinal plants against Staphylococcus aureus and Pseudomonas aeruginosa biofilms and predicts the interactions of selected phytochemicals from five of the best performing plants with the active sites of transcriptional regulatory proteins SarA of S. aureus and LasR of P. aeruginosa. The plant extracts were tested by microtiter plate-based assay against S. aureus and P. aeruginosa biofilms. Molecular docking and molecular dynamics simulation (MD) were conducted using PyRx and GROMACS, respectively. The best activity was identified for Cassia fistula and Ananas comosus, showing ≥ 75% inhibition of biofilm formation. ent-Epicatechin-(4α→8)-epiafzelechin (EEE) of C. fistula, cyanidin-3,3',5-tri-O-β-D-glucopyranoside (CTG) of A. comosus, and 7-O-(4-hydroxy-Ecinnamoyl)- spinoside of A. spinosus showed the best predictive binding affinity (-7.6, -7.6 and - 7.7 kcal/mol, respectively) for SarA. EEE was the only ligand to exhibit a stable ligand-protein complex with SarA in the MD simulation of 200 ns (binding energy of MMPBSA analysis - 39.899 kJ/mol). Chrysophanol, epicatechin and physcion, of C. fistula (-10.5, -10.5, and -11.0 kcal/mol, respectively) and auraptene of F. limonia (-10.8 kcal/mol) showed the best predictive binding affinity for LasR. Epicatechin showed the most stable ligand-protein complex with LasR (binding energy of MMPBSA analysis -63.717 kJ/mol). Epicatechin and its derivative EEE could be used as scaffolds for the d evelopment of new antibiofilm agents against P. aeruginosa and S. aureus, respectively.

Machine learning and cheminformatics-based Identification of lichen-derived compounds targeting mutant PBP4R200L in Staphylococcus aureus.

Penicillin-binding protein 4 (PBP4) is essential in imparting significant β-lactam antibiotics resistance in Staphylococcus aureus (S. aureus) and the mutation R200L in PBP4 is linked to β-lactam non-susceptibility in natural strains, complicating treatment options. Therefore, discovering novel therapeutics against the mutant PBP4 is crucial, and natural compounds from lichen have found relevance in this regard. The aim of our study was to identify novel inhibitors against the R200L mutation by applying machine learning (ML) approach. Predictive classification models were developed using six machine learning algorithms to categorize lichen-derived compounds as either active or inactive. The models were evaluated using ROC curves, confusion matrices, and relevant statistical parameters. Among these, the Extra Trees algorithm showed superior predictive accuracy at 81%. The model identified 115 potentially active compounds from lichen, which were further evaluated for drug-likeness and structural similarity to β-lactam antibiotics. The top 23 compounds, showing similarity to β-lactam drug, were subjected to molecular docking. Among the top 10 compounds, two compounds, Barbatolic acid and Orcinyl lecanorate, displayed promising results in 200ns molecular dynamics (MD) simulations and MM-PBSA analysis, exhibiting better docking score compare to reference compound. Additionally, DFT calculations revealed negative binding energies and smaller HOMO-LUMO gaps for both compounds. The obtained results prove the utility of ML in screening natural compounds, and provide novel opportunities for the design of antimicrobial compounds in the future.

Targeting aldose reductase using natural African compounds as promising agents for managing diabetic complications.

Diabetes remains a leading cause of morbidity and mortality due to various complications induced by hyperglycemia. Inhibiting Aldose Reductase (AR), an enzyme that converts glucose to sorbitol, has been studied to prevent long-term diabetic consequences. Unfortunately, drugs targeting AR have demonstrated toxicity, adverse reactions, and a lack of specificity. This study aims to explore African indigenous compounds with high specificity as potential AR inhibitors for pharmacological intervention. A total of 7,344 compounds from the AfroDB, EANPDB, and NANPDB databases were obtained and pre-filtered using the Lipinski rule of five to generate a compound library for virtual screening against the Aldose Reductase. The top 20 compounds with the highest binding affinity were selected. Subsequently, in silico analyses such as protein-ligand interaction, physicochemical and pharmacokinetic profiling (ADMET), and molecular dynamics simulation coupled with binding free energy calculations were performed to identify lead compounds with high binding affinity and low toxicity. Five natural compounds, namely, (+)-pipoxide, Zinc000095485961, Naamidine A, (-)-pipoxide, and 1,6-di-o-p-hydroxybenzoyl-beta-d-glucopyranoside, were identified as potential inhibitors of aldose reductase. Molecular docking results showed that these compounds exhibited binding energies ranging from -12.3 to -10.7 kcal/mol, which were better than the standard inhibitors (zopolrestat, epalrestat, IDD594, tolrestat, and sorbinil) used in this study. The ADMET and protein-ligand interaction results revealed that these compounds interacted with key inhibiting residues through hydrogen and hydrophobic interactions and demonstrated favorable pharmacological and low toxicity profiles. Prediction of biological activity highlighted Zinc000095485961 and 1,6-di-o-p-hydroxybenzoyl-beta-d-glucopyranoside as having significant inhibitory activity against aldose reductase. Molecular dynamics simulations and MM-PBSA analysis confirmed that the compounds bound to AR exhibited high stability and less conformational change to the AR-inhibitor complex. This study highlighted the potential inhibitory activity of 5 compounds that belong to the African region: (+)-Pipoxide, Zinc000095485961, Naamidine A, (-)-Pipoxide, and 1,6-di-o-p-hydroxybenzoyl-beta-d-glucopyranoside. These molecules inhibiting the aldose reductase, the key enzyme of the polyol pathway, can be developed as therapeutic agents to manage diabetic complications. However, we recommend in vitro and in vivo studies to confirm our findings.

Exploration of natural products for the development of promising cholinesterase inhibitors in Alzheimer's disease treatment.

Exploration of natural products for the development of promising cholinesterase inhibitors in Alzheimer's disease treatment.

Investigating the link between microplastic exposure (benzyl butyl phthalate) and neurodegenerative diseases using high-performance computational toxicology.

Microplastics are tiny plastic particles, typically less than 5mm in size, formed from the breakdown of larger plastic products. This breakdown releases additives, including benzyl butyl phthalate (BBP), into the environment. Humans can be exposed to BBP through contaminated food and water, inhalation, and dermal contact. Research suggests that BBP, like other phthalates, may have neurotoxic effects, potentially contributing to neurodevelopmental disorders, though its specific toxic targets are not yet clear. In this study, high-performance computational methods were used to identify potential neurotoxic targets of BBP. The findings indicate that BBP has a strong potential to interact with Parkin (PRKN) and Pyruvate dehydrogenase lipoamide kinase isozyme 1 (PDK1), with binding scores of -5.35kcal/mol, -5.56kcal/mol, respectively. The PRKN and PDK1 BBP complexes were stable throughout the simulation period, as evidenced by the system's backbone exhibiting slight fluctuations and binding energies confirmed by molecular dynamics (MD) simulation trajectories. The MMPBSA analysis revealed free binding energies of -21.29kcal/mol and-27.06kcal/mol for the PRKN and PDK1 BBP complexes, respectively. The interaction energies of BBP with PRKN and PDK1 were also within an acceptable range, at -113.68±3.1kJ/mol and-117.54±6.2kJ/mol, respectively. Additionally, density-functional theory (DFT) based optimization showed negative values for the highest occupied molecular orbital (HOMO) -6.934eV and lowest unoccupied molecular orbital (LUMO) -1.562eV, indicating that BBP is energetically stable, which is crucial for forming a stable ligand-protein complex. Overall, the computational investigation reveals that BBP has the potential to interact with PRKN and PDK1, leading to neurodegeneration.

Identification and Validation of B-Cell Epitopes on the VP1 Protein of Parvovirus B19 through Molecular Docking and Dynamics Simulation.

This study aimed to identify B-cell epitope candidates using multiple epitope identification software and in silico analysis of the modeled B19 V protein against specific antibodies using molecular docking and dynamics simulation. Materials and Methods : Full-length amino acid sequences of the VP1 protein of B19 V were retrieved from NCBI. A consensus sequence was generated using CLC sequence viewer. Linear B cell epitopes were identified using Bepipred 2.0, ABCpred, and LBTope. The linear epitope was synthesized and validated against B19 V-specific antibodies. A 3D model of the B19 V VP1 consensus protein was generated using the ITASSER server. Discontinuous B cell epitopes were identified using Discotope 2.0 and Ellipro. Molecular docking and molecular dynamics simulation was performed to investigate the interaction between the modeled B19 V protein and specific anti-B19 V antibody. Results : The identified epitope was 100% conserved and similarly identified through ABCpred and LBTope. The HADDOCK score and MDS analysis, such as hydrogen bond interactions and MMPBSA analysis, revealed that the VP1 and mAb H chains formed a significantly stable complex. The MDS demonstrated that the VP1-mAb H chain complexes had lower RMSF values around 130 to 200 residues, a region responsible for the catalytic network for enzyme activity; as a result, the flexibility of the antibody-bound VP1 decreased when compared to Apo-VP1. Conclusion: A viable epitope identified through this process was synthesized and validated using ELISA, which highlighted the role of the epitope identification process in diagnostics. This study also sheds light on the complex interplay between VP1 and the mAb H chain and highlights key binding specificity and stability determinants.

Exploring the impact of deleterious missense nonsynonymous single nucleotide polymorphisms in the DRD4 gene using computational approaches

Dopamine receptor D4 (DRD4) plays a vital role in regulating various physiological functions, including attention, impulse control, and sleep, as well as being associated with various neurological diseases, including attention deficit hyperactivity disorder, novelty seeking, and so on. However, a comprehensive analysis of harmful nonsynonymous single nucleotide polymorphisms (nsSNPs) of the DRD4 gene and their effects remains unexplored. The aim of this study is to uncover novel damaging missense nsSNPs and their structural and functional effects on the DRD4 receptor. From the dbSNP database, we found 677 nsSNPs, and then we analyzed their functional consequences, disease associations, and effects on protein stability with fifteen in silico tools. Five variants, including L65ICL1P (rs1459150721), V1163.33D (rs761875546), I1293.46S (rs751467198), I1564.46T (rs757732258), and F2015.47S (rs199609858), were identified as the most deleterious mutations that were also present in the conserved region and showed lower interactions with neighboring residues. To comprehensively understand their impact, we docked agonist dopamine and antagonist nemonapride at the binding site of the receptor, followed by 200 ns molecular dynamics simulations. We identified the V116D and I129S mutations as the most damaging, followed by F201S in the dopamine-bound states. Both the V116D and I129S variants demonstrated significantly high RMSD, Rg, and SASA, and low thermodynamic stability. The F201S-dopamine complex exhibited lower compactness and higher motions, along with a significant loss of hydrogen bonds and active site interactions. By contrast, while interacting with nemonapride, the impact of the I156T and L65P mutations was highly deleterious; both showed lower stability, higher flexibility, and higher motions. Additionally, nemonapride significantly lost interactions with the active site, notably in the I156T variant. We also found the V116D-nemonapride complex as structurally damaging; however, the interaction patterns of nemonapride were less altered in the MMPBSA analysis. Overall, this study revealed five novel deleterious variants along with a comprehensive understanding of their effect in the presence of an agonist and antagonist, which could be helpful for understanding disease susceptibility, precision medicine, and developing potential drugs.

Curcumin as a potential inhibitor of TGFβ3 computational insights for breast cancer therapy

Previous research indicates that Transforming growth factor beta-3 (TGFβ3) expression levels correlate with breast cancer metastasis, and elevated TGFβ3 levels have been linked with poor overall survival in breast cancer patients. The study used computational methods to examine curcumin’s effects on TGFβ3, a chemical with antiviral and anticancer characteristics. The curcumin has low Molecular Weight 368.130 (MW) and follows Lipinski Rule, Pfizer Rule, GSK Rule, Golden Triangle, BMS Rule, zero PAINS alert and Acute Toxicity Rule with zero alert. Any drug-like contender must follow these qualities. Through molecular docking analyses, curcumin displayed favourable binding affinities at the TGFβ3 binding pocket, forming key interactions such as hydrogen bonds with residues like ASP323, ARG325, VAL333, HIS334, PRO336, LYS337, GLY393, and ARG394. 500 ns molecular dynamic simulations examined docking interactions. Molecular dynamics (MD) simulations trajectories analysis, by calculating lower structural deviation, minimal residual fluctuations, structural compactness assessment by calculating radius of gyration, surface area calculation which interact with solvent, role of hydrogen bonding, and secondary structural analyses. Furthermore, principal component, Gibbs free energy landscape and MMPBSA analysis, signifying system stability. These data suggest curcumin may inhibit TGFβ3, providing a framework for developing new compounds targeting this protein.

Repositioning of Furin inhibitors as potential drugs against SARS-CoV-2 through computational approaches

The recent spread of SARS-CoV-2 has led to serious concerns about newly emerging infectious coronaviruses. Drug repurposing is a practical method for rapid development of antiviral agents. The viral spike protein of SARS-CoV-2 binds to its major receptor ACE2 to promote membrane fusion. Following the entry process, the spike protein is further activated by cellular proteases such as TMPRSS2 and Furin to promote viral entry into human cells. A crucial factor in preventing SARS-CoV-2 from entering target cells using HIV-1 fusion inhibitors is the similarity between the fusion mechanisms of SARS-CoV-2 and HIV-1. In this investigation, the HIV-1 fusion inhibitors CMK, Luteolin, and Naphthofluorescein were selected to understand the molecular mode of interactions and binding energy of Furin with these experimental inhibitors. The binding affinity of the three inhibitors with Furin was verified by molecular docking studies. The docking scores of CMK, Luteolin and Naphthofluorescein are −7.4 kcal/mol, −9.3 kcal/mol, and −10.7 kcal/mol, respectively. Therefore, these compounds were subjected to MD, drug-likeness, ADMET, and MM-PBSA analysis. According to the results of a 200 ns MD simulation, all tested compounds show stability with the complex and can be employed as promising inhibitors targeting SARS-CoV-2 Furin protease. In addition, pharmacokinetic analysis revealed that these compounds possess favorable drug-likeness properties. Thus, this study of Furin inhibitors helps in the evaluation of these compounds for use as novel drugs against SARS-CoV-2.

Identification of Novel LCN2 Inhibitors Based on Construction of Pharmacophore Models and Screening of Marine Compound Libraries by Fragment Design.

LCN2, a member of the lipocalin family, is associated with various tumors and inflammatory conditions. Despite the availability of known inhibitors, none have been approved for clinical use. In this study, marine compounds were screened for their ability to inhibit LCN2 using pharmacophore models. Six compounds were optimized for protein binding after being docked against the positive control Compound A. Two compounds showed promising results in ADMET screening. Molecular dynamics simulations were utilized to predict binding mechanisms, with Compound 69081_50 identified as a potential LCN2 inhibitor. MM-PBSA analysis revealed key amino acid residues that are involved in interactions, suggesting that Compound 69081_50 could be a candidate for drug development.

Designing of a multiepitope-based vaccine against echinococcosis utilizing the potent Ag5 antigen: Immunoinformatics and simulation approaches.

Echinococcosis is a significant parasitic zoonotic disease with severe implications for human and animal health. To date, there has been no effective vaccine candidate available for echinococcosis. Therefore, we employed computational approaches to develop a multiepitope-based vaccine using the most potent epitopes of MHC-I, MHC-II, and B-cell derived from the Ag5 protein of Echinococcus spp. The final vaccine construct containing the epitopes, linkers, and adjuvant exhibited potent antigenicity (score > 0.1) with no evidence of allergenicity (score < 0) and toxicity (score < 0) in several computational platforms. The vaccine also exhibited favorable physicochemical characteristics such as being highly soluble (SOLpro score of 0.781243) and hydrophilic (Grand average of hydropathy of -0.433). Moreover, the tertiary structure of the vaccine was also found to be structurally stable, with a Z score of -5.71. Further, the molecular docking analysis confirmed the vaccine's significant binding affinity to the RP-105 (docking score of -1252.7) and TLR-9 (docking score of -970.9). The molecular dynamic simulations confirmed the structural stability of the docked complexes under a virtual physiological system. The negative ΔTOTAL values derived from the MM-PBSA and MM-GBSA analyses confirmed a spontaneous and thermodynamically favorable binding process between the vaccine and receptors. Moreover, the vaccine demonstrated high potentiality to elicit both innate (natural killer cell, dendritic and macrophage) and adaptive (B-cell, helper T cell and cytotoxic T cell) immune responses with sustained humoral immune responses evidenced by increased IFN-γ and IL-2 levels. Following codon optimization and in silico cloning, the vaccine was successfully expressed (CAI value of 0.9607 and average GC content of 52.34%) after being inserted into the pET-28a (+) plasmid of E. coli. These findings highlight the potential of the designed vaccine candidate to combat echinococcosis and lay the groundwork for future preclinical and clinical studies.

In silico screening of dicoumarols as potential Mur B enzyme inhibitors in Mycobacterium tuberculosis: molecular docking, ADME, QSAR and MD simulations

UDP-N-acetylenolpyruvoylglucosamine reductase (Mur B) from Mycobacterium tuberculosis has gathered significant pharmaceutical interest as a pivotal target because of its essential role in bacterial viability. This study employed computational methods to screen and assess the inhibitory potential of dicoumarol derivatives against the Mur B protein. A diverse set of dicoumarols, sourced from PubChem and Zinc database, is subjected to molecular docking, ADME studies, and MD simulations to elucidate interacting modes and stability. A QSAR model was constructed for dicoumarol derivatives based on known inhibitor MIC values against Staphylococcus aureus and Mur B. The four best dicoumarols (CID142097979, CID54716867, CID91962283, CID54705236) aligned well with the model. Subsequently, these dicoumarols were scrutinized via 200 ns MD simulations and MM-PBSA analysis to assess their complex stability with Mur B protein. Various MD simulation parameters such as RMSD, RMSF, Rg, H-bonds, PCA, and FEL were employed. The 200 ns MD simulation analysis outcomes indicated that the Mur B-CID54705236 complex exhibited the highest stability and possessed the binding energy of −59.96 kcal/mol further verifying its stability. The post-dynamic simulation analysis showed four hydrogen bond formations with Ser70, Asn71, Leu72 and Gln137 residues at the active site of Mur B. Overall, these results underscored dicoumarol derivatives as potential Mur B inhibitors and these findings can serve as a basis for further in vitro studies against Mur B protein.

Computational Studies and Antimicrobial Activity of 1-(benzo[d]oxazol-2- yl)-3,5-diphenylformazan Derivatives.

Due to the biological importance of the benzoxazole derivatives, some 1- (benzo[d]oxazol-2-yl)-3,5-diphenyl-formazans 4a-f were synthesized and screened for in-silico studies and in-vitro antibacterial activity. The benzo[d]oxazole-2-thiol (1) was prepared by reacting with 2-aminophenol and carbon disulfide in the presence of alcoholic potassium hydroxide. Then 2-hydrazinylbenzo[d] oxazole (2) was synthesized from the reaction of compound 1 with hydrazine hydrate in the presence of alcohol. Compound 2 was reacted with aromatic aldehydes to give Schiff base, 2-(2- benzylidene-hydrazinyl)benzo[d]oxazole derivatives 3a-f. The title compounds, formazan derivatives 4a-f, were prepared by a reaction of benzene diazonium chloride. All compounds were confirmed by their physical data, FTIR, 1H-NMR, and 13CNMR spectral data. All the prepared title compounds were screened for in-silico studies and in-vitro antibacterial activity on various microbial strains. Molecular docking against the 4URO receptor demonstrated that molecule 4c showed a maximum dock score of (-) 8.0 kcal/mol. MD simulation data reflected the stable ligand-receptor interaction. As per MM/PBSA analysis, the maximum free binding energy of (-) 58.831 kJ/mol was exhibited by 4c. DFT calculation data confirmed that most of the molecules were soft molecules with electrophilic nature. The synthesized molecules were validated using molecular docking, MD simulation, MMPBSA analysis, and DFT calculation. Among all the molecules, 4c showed maximum activity. The activity profile of the synthesized molecules against tested micro-organisms was found to be 4c>4b>4a>4e>4f>4d.

Harnessing natural compounds for PIM-1 kinase inhibition: A synergistic approach using virtual screening, molecular dynamics simulations, and free energy calculations.

Cancer has substantial economic ramifications for healthcare systems. PIM kinases, specifically PIM-1, are commonly upregulated in different types of cancers, thereby promoting cancer development. PIM-1 inhibitors have garnered interest for their potential efficacy in cancer therapy. This study used computational methods to screen a library of 7,600 natural compounds targeting the PIM-1 active site. Five top candidates-ZINC00388658, ZINC00316459, ZINC00197401, ZINC00001673, and ZINC00316479-were selected for subsequent interaction studies, which involved molecular dynamics simulations (MDS) and free energy calculation using the MMPBSA method. These compounds interacted with key PIM-1 residues and had multiple common binding site interactions with the co-crystallized ligand 6YN, which was used as a control. Furthermore, the selected compounds exhibited favorable drug-like properties and stable docked complexes during a 200-ns molecular dynamics simulation,followed by MMPBSA analysis. Among the candidates, ZINC00388658 had the most favorable binding energy profile, indicating exceptional stability andintense interaction with PIM 1. This makes ZINC00388658 the most promising candidate for further development as a PIM-1 inhibitor. These findings suggest that ZINC00388658 and other promising compounds holdsignificant potential for developingnew cancer therapies that target PIM-1.

Exploring potential GPR55 agonists using virtual screening, molecular docking and dynamics simulation studies

GPR55, an orphan GPCR, holds significance in the context of neurological disorders and its activation is important for regulating neurological responses. This has led us to uncover and explore a set of ligands which may act as potential agonists. We have predicted the GPR55 structural model followed by molecular docking, dynamics simulation studies, free energy landscape and MMPBSA analyses to study the dynamic nature of GPR55 in the presence of different ligands. We initially carried out structure-based virtual screening of a dataset from ChemDiv Database against the GPR55 model. Based on the docking results, it was observed that thiazole and triazole derivatives were present among the top hits and notably, two compounds – one thiazole (lead1) and one triazole (lead2) derivative were shortlisted. In addition, as we are working on the design, synthesis, structural and functional properties of several thiazole and triazole compounds, we have attempted to study the binding potential of two compounds SVS1 (thiazole derivative) and SVS2 (triazole derivative) with GPR55. The synthesis and structural aspects of SVS1 and SVS2 were previously reported by our team. Further, we have included a known agonist O-1602 in the present study for comparative analysis. All the compounds showed promising interactions with GPR55 during molecular dynamics simulations. Our findings suggest that lead1, lead2, SVS1 and SVS2 have the potential to serve as GPR55 agonists and the study throws light on the importance of thiazole and triazole moieties in the ligands. This offers a promising avenue for the development of new therapies for neurological disorders.

A multiscale in silico approach to impede the interaction between Dengue NS1 and Human RPL18, aiming to suppress the Dengue viral translation and proliferation

ABSTRACT The Non-Structural protein 1 (NS1) of the Dengue virus is a crucial viral protein that plays a key role in host evasion and viral replication. The present study explores the pathophysiology of the host during the interaction with the viral protein via computational methods like protein–protein docking, virtual screening, and molecular dynamic simulation. Therefore, in this study we have focused on Dengue NS1 and the Human RPL18, to explore the binding mechanism and study their importance in viral proliferation. The results provided an insight into the vital amino acids of DENV NS1 (Gln_70 Glu_74 and Gly_161) which are responsible for viral-host interaction. The screening results showed that the Enamine_2436, NCI_99799, Malarial_19966, and FDA_54, had the strongest interaction with a docking score of −10.71, −8.11, −7.78, and −7.19 kcal/mol. In addition to the screening, the efficacy of the leads was validated through HOMO–LUMO studies. The Molecular dynamics simulation, PCA/FEL, and MMPBSA analysis showed that the Malarial_19966 maintained overall stability and binding affinity when compared to other leads. Hence the study comprehensively provides an insight into the biological phenomena of Dengue virus NS1 binding with Human RPL18 protein, along with possible inhibitors to suppress the Dengue viral translation and proliferation.

ROC-guided virtual screening, molecular dynamics simulation, and bioactivity validation assessment Z195914464 as a 3CL Mpro inhibitor

ROC-guided virtual screening, molecular dynamics simulation, and bioactivity validation assessment Z195914464 as a 3CL Mpro inhibitor