POAP: A GNU parallel based multithreaded pipeline of open babel and AutoDock suite for boosted high throughput virtual screening

Sesamin regulates breast cancer through reprogramming of lipid metabolism

Metabolic reprogramming is one of the hallmarks of breast cancer (BC), involving elevated synthesis and uptake of lipids, for catering to increased energy demand of cancer cells and to suppress the host immune system. Besides promoting proliferation and survival of BC cells, lipid metabolism reprogramming (LMR) is associated with stemness and chemoresistance. Recently, lignans have been reported for their therapeutic potential against different cancers, including BC. Here, we explored the potential of lignans to target LMR pathways in BC through computational approach. Initially, 88 lignans having potential anticancer activities, underwent druglikeness and pharmacokinetics analysis, displaying promising pharmacokinetic properties, except for 13 molecules with violations. Molecular docking assessed the interaction of 88 lignans (NPACT) with therapeutic targets of LMR including 3-Hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), Sterol regulatory element-binding proteins 1 and 2 (SREBP1 and 2), Low-density lipoprotein receptor (LDLR), Acetyl-CoA Acetyltransferase 1 (ACAT1), ATP-binding cassette transporter (ABCA1), Liver X receptor α (LXRα), Apolipoprotein A1 (APOA1), Fatty Acid Synthase (FASN), Peroxisome proliferator-activated receptor gamma (PPARG), Stearoyl-CoA desaturase (SCD1), Acetyl-CoA carboxylase 1 and 2 (ACC1/ACACA, and ACC2/ACACB). In silico screening revealed sesamin (SE) as the best-identified hit that showed stable and consistent binding with all the selected targets of LMR. The stability of these complexes was validated by a 100 ns simulation run, and their binding free energy calculation was determined by MM-PBSA method. Interestingly, SE modulated the mRNA expression of genes involved in LMR in BC cell lines, MCF-7 and MDA-MB-231, thereby suggesting its potential as an inhibitor of LMR.

In silico, in vitro, and in vivo assessment of chitosan-diltiazem nanoparticles against pulmonary fibrosis

AIMS

Diltiazem (DIL), a calcium channel blocker, has demonstrated potential ininhibiting fibrosis-related processes, including TGF-β activation, collagen production, and epithelial-mesenchymal transition, making it a promising candidate for idiopathic pulmonary fibrosis (IPF). This study evaluates the anti-fibrotic efficacy of DIL-loaded chitosan (DIL-CHT) and trimethyl chitosan (DIL-TMC) nanoparticles through molecular and experimental approaches.

METHODS

DIL-CHT and DIL-TMC nanoformulations were developed and analyzed particle size, ζ-potential, entrapment efficiency, and in vitro release. Antifibrotic efficacy in bleomycin (BLM)-induced IPF rat model, was tested at subtherapeutic doses (3 mg/kg/day, i.t.) and DIL alone (10 mg/kg/day, p.o.). DFT (B3LYP/6-31 G**) optimization and molecular docking were conducted to assess electronic properties and interactions among CHT, TMC, and DIL.

RESULTS

DIL-TMC and DIL-CHT nanoparticles were 175.6 nm and 267.8 nm, with entrapment efficiencies of 81.72% and 66.0%, respectively; TMC showed a superior 24-hour sustained release. TMC's larger HOMO-LUMO gap (ΔE = -0.260 eV vs. -0.253 eV for CHT) suggests greater stability, supporting its enhanced interaction with DIL. TMC nanoparticles significantly reduced BLM-induced IPF symptoms, i.e. BLM induced increased lung index, hydroxyproline accumulation, oxidative stress in lung tissue, and blood pressure.

CONCLUSIONS

These findings indicate the strong therapeutic potential of DIL-TMC for IPF with minimal cardiovascular side effects.

Exploring disulfiram mechanisms in renal fibrosis: insights from biological data and computational approaches

Background

Disulfiram (DSF) is an anti-alcoholic drug that has been reported to inhibit the epithelial-to-mesenchymal transition and crosslinking during fibrosis, pyroptosis, and inflammatory NF-κB and Nrf-2 signaling pathways. However, there is insufficient evidence to support the mechanisms of DSF in preventing renal fibrosis (RF). Therefore, the current study aimed to elucidate the DSF-modulated targets and pathways in renal fibrosis.

Methods

The common proteins between DSF and RF were screened for protein-protein interaction, pathway enrichment, cluster, and gene ontology analysis. Molecular docking was executed for core genes using AutoDock Vina through the POAP pipeline. Molecular dynamics (MD) simulation (100 ns) was performed to infer protein-ligand stability, and conformational changes were analyzed by free energy landscape (FEL).

Results

A total of 78 targets were found to be common between DSF and RF, of which NFKB, PIK3CA/R1, MTOR, PTGS2, and MMP9 were the core genes. PI3K-Akt signaling followed by JAK-STAT, TNF, Ras, ErbB, p53, phospholipase D, mTOR, IL-17, NF-κB, AMPK, VEGF, and MAPK signaling pathways were modulated by DSF in RF. DSF showed a direct binding affinity with active site residues of core genes, and except for DSF with NF-κB, all other complexes, including the standard, were found to be stable during 100 ns MD simulation with minimal protein-ligand root mean squared deviation and residual fluctuations and higher compactness with broad conformational changes.

Conclusion

DSF protects against renal fibrosis, and this study paves the way for experimental investigation to repurpose DSF for treating RF.

Flavonoids of Andrographis paniculata regulate hepatitis B virus replication and hepatocellular carcinoma progression: evidence from computational and experimental studies

BACKGROUND

The HBx protein of hepatitis B virus (HBV) plays a crucial role in HBV pathogenesis, yet current treatments like HIV reverse transcriptase (RT) inhibitors, which target HBV RT due to similar active sites, have severe side effects, risk of drug resistance, and high costs. The present study investigates the anti-hepatitis B virus (HBV) properties of Andrographis paniculata (AP) and Thespesia populnea (TP) on HBV expressing HepG2.2.15 cells and by computational analysis.

METHODS

In vitro cytotoxicity, reverse transcriptase inhibitory, DNA and pgRNA quantification by qRT-PCR, time course analysis of HBsAg and HBeAg, and HBX-HBXIP interaction inhibition studies were conducted. The interaction of HBX with HBXIP, and phytocompounds' interaction with HBx was analyzed through molecular docking and dynamics studies.

RESULTS

AP exhibits lower cytotoxicity (CC50 = 832.915 µg/mL) than TP (CC50 = 593.122 µg/mL) after 24 h, with Tenofovir disoproxil fumarate (TDF) showing minimal cytotoxicity (CC50 > 500 µM). Both AP and TP significantly decreased intracellular HBV DNA with a > 25 fold reduction at higher concentrations (125-500 µg/mL) but had no significant effect on pgRNA level. AP and TP 500 µg/mL effectively inhibited HBsAg secretion (95% and 80% inhibition, respectively), over 120 h. AP also showed inhibition of HBeAg secretion (75-82%), while TP exhibited a higher inhibition of 90% at 24 h. TDF showed consistent but lower inhibitory effects on HBsAg and HBeAg. The HBx-HBXIP interaction inhibition assay showed AP's greater inhibitory capacity (IC50 < 62.5 µg/mL) compared to TP (IC50 = 806.69 µg/mL). Computational studies further validated these findings, showing stable binding interactions of AP compounds (flavonoids) with HBx protein (with Arg138 and His139, Lys140, and Trp141 residues participating in the interaction with HBXIP), corroborating their potential in disrupting HBV replication. Molecular dynamics simulations confirmed the stability of these interactions over 100ns.

CONCLUSIONS

AP exhibits potent anti-HBV activities, making it a promising candidate for further therapeutic development.

High-Affinity Peptides for Target Protein Screened in Ultralarge Virtual Libraries

High-throughput virtual screening (HTVS) has emerged as a pivotal strategy for identifying high-affinity peptides targeting functional proteins, which are crucial for diagnostic and therapeutic applications. In the HTVS of peptides, expanding the library capacity to enhance peptide sequence diversity, thereby screening out excellent affinity peptide candidates, remains a significant challenge. This study presents a de novo design strategy that leverages directed mutation driven HTVS to evolve vast virtual libraries and screen peptides with ultrahigh affinities for various target proteins. Utilizing a computer-generated library of 104 random 15-mer peptide scaffolds, we employed a self-developed algorithm for parallelized HTVS with Autodock Vina. The top 1% of designs underwent random mutations at a rate of 20% for six generations, theoretically expanding the library to 1014 members. This approach was applied to various protein targets, including a tumor marker (alpha fetoprotein, AFP) and virus surface proteins (SARS-CoV-2 RBD and norovirus P-domain). Starting from the same 104 random 15-mer peptide library, peptides with high affinities in the nanomolar range for three protein targets were successfully identified. The energy-saving and high-efficient design strategy presents new opportunities for the cost-effective development of more effective high-affinity peptides for various environmental and health applications.

Recent Applications of In Silico Approaches for Studying Receptor Mutations Associated with Human Pathologies

In recent years, the advent of computational techniques to predict the potential activity of a drug interacting with a receptor or to predict the structure of unidentified proteins with aberrant characteristics has significantly impacted the field of drug design. We provide a comprehensive review of the current state of in silico approaches and software for investigating the effects of receptor mutations associated with human diseases, focusing on both frequent and rare mutations. The reported techniques include virtual screening, homology modeling, threading, docking, and molecular dynamics. This review clearly shows that it is common for successful studies to integrate different techniques in drug design, with docking and molecular dynamics being the most frequently used techniques. This trend reflects the current emphasis on developing novel therapies for diseases resulting from receptor mutations with the recently discovered AlphaFold algorithm as the driving force.

Barosmin against postprandial hyperglycemia: outputs from computational prediction to functional responses in vitro

Previously, barosmin has been demonstrated to possess anti-diabetic action. However, its effect to inhibit α-amylase and α-glucosidase, including glucose utilization efficacy, has yet to be revealed. Hence, the current study attempted to assess the efficiency of barosmin in inhibiting the α-amylase, α -glucosidase, and dipeptidyl peptidase 4 enzymes, including glucose uptake efficacy. Molecular docking and simulation were performed using AutoDock Vina and Gromacs respectively followed by gene ontology analysis using the database for annotation, visualization, and integrated discovery. Further, in vitro enzyme inhibitory activities and glucose uptake assay were performed in L6 cell lines. Density functional theory analysis detailed mechanistic insights into the crucial interaction sites of barosmin of which the electron-dense region was prone to nucleophilic attack (O-atoms) whereas hydroxyl groups (-OH) showed affinity for electrophilic attacks. Barosmin showed good binding affinity with α-amylase (-9.2 kcal/mol), α-glucosidase (-10.7 kcal/mol), and dipeptidyl peptidase 4 (-10.0 kcal/mol). Barosmin formed stable nonbonded contacts with active site residues of aforementioned enzymes throughout 200 ns molecular dynamics simulation. Further, it regulated pathway concerned with glucose homeostasis i.e. tumor necrosis factor signaling pathway. In addition, barosmin showed α-amylase (IC50= 95.77 ± 23.33 µg/mL), α-glucosidase (IC50= 68.13 ± 2.95 µg/mL), and dipeptidyl peptidase 4 (IC50= 13.27 ± 1.99 µg/mL) inhibitory activities including glucose uptake efficacy in L6 cell lines (EC50= 12.46 ± 0.90 µg/mL) in the presence of insulin. This study presents the efficacy of the barosmin to inhibit α-amylase and α-glucosidase and glucose uptake efficacy in L6 cell lines via the use of multiple system biology tools and in vitro techniques.Communicated by Ramaswamy H. Sarma.

Investigation of cathinone analogs targeting human dopamine transporter using molecular modeling

In a step towards understanding the structure-property relationship among Synthetic Cathinones (SCs), a combined methodology based on Density Functional Theory (DFT), Administration, Distribution, Metabolism, Excretion, and Toxicity (ADMET) predictions, docking and molecular dynamics simulations have been applied to correlate physicochemical descriptors of various SCs to their biological activity. The results from DFT and molecular docking studies correlate well with each other explaining the biological activity trends of the studied SCs. Quantum mechanical descriptors viz. polarizability, electron affinity, ionization potential, chemical hardness, electronegativity, molecular electrostatic potential, and ion interaction studies unravel the distinguishingly reactive nature of Group D (pyrrolidine substituted) and Group E (methylenedioxy and pyrrolidine substituted) compounds. According to ADMET analysis, Group D and Group E molecules have a higher probability of permeating through the blood-brain barrier. Molecular docking results indicate that Phe76, Ala77, Asp79, Val152, Tyr156, Phe320, and Phe326 constitute the binding pocket residues of hDAT in which the most active ligands MDPV, MDPBP, and MDPPP are bound. Finally, to validate the derived quantum chemical descriptors and docking results, Molecular Dynamics (MD) simulations are performed with homology-modelled hDAT (human dopamine transporter). The MD simulation results revealed that the majority of SCs remain stable within the hDAT protein's active sites via non-bonded interactions after 100 ns long simulations. The findings from DFT, ADMET analysis, molecular docking, and molecular dynamics simulation studies complement each other suggesting that pyrrolidine-substituted SCs (Group D and E), specifically, MPBP and PVN are proven potent SCs along with MDPV, validating various experimental observations.

Virtual Screening of Small Molecules Targeting BCL2 with Machine Learning, Molecular Docking, and MD Simulation

This study aimed to identify potential BCL-2 small molecule inhibitors using deep neural networks (DNN) and random forest (RF), algorithms as well as molecular docking and molecular dynamics (MD) simulations to screen a library of small molecules. The RF model classified 61% (2355/3867) of molecules as 'Active'. Further analysis through molecular docking with Vina identified CHEMBL3940231, CHEMBL3938023, and CHEMBL3947358 as top-scored small molecules with docking scores of -11, -10.9, and 10.8 kcal/mol, respectively. MD simulations validated these compounds' stability and binding affinity to the BCL2 protein.

Targeting the hSSB1-INTS3 Interface: A Computational Screening Driven Approach to Identify Potential Modulators

Human single-stranded DNA binding protein 1 (hSSB1) forms a heterotrimeric complex, known as a sensor of single-stranded DNA binding protein 1 (SOSS1), in conjunction with integrator complex subunit 3 (INTS3) and C9ORF80. This sensory protein plays an important role in homologous recombination repair of double-strand breaks in DNA to efficiently recruit other repair proteins at the damaged sites. Previous studies have identified elevated hSSB1-mediated DNA repair activities in various cancers, highlighting its potential as an anticancer target. While prior efforts have focused on inhibiting hSSB1 by targeting its DNA binding domain, this study seeks to explore the inhibition of the hSSB1 function by disrupting its interaction with the key partner protein INTS3 in the SOSS1 complex. The investigative strategy entails a molecular docking-based screening of a specific compound library against the three-dimensional structure of INTS3 at the hSSB1 binding interface. Subsequent assessments involve in vitro analyses of protein-protein interaction (PPI) disruption and cellular effects through co-immunoprecipitation and immunofluorescence assays, respectively. Moreover, the study includes an evaluation of the structural stability of ligands at the INTS3 hot-spot site using molecular dynamics simulations. The results indicate a potential in vitro disruption of the INTS3-hSSB1 interaction by three of the tested compounds obtained from the virtual screening with one impacting the recruitment of hSSB1 and INTS3 to chromatin following DNA damage. To our knowledge, our results identify the first set of drug-like compounds that functionally target INTS3-hSSB1 interaction, and this provides the basis for further biophysical investigations that should help to speed up PPI inhibitor discovery.

Investigation of alpha amylase inhibitors from Bidens pilosa L. by in silico and in vitro studies

Bidens pilosa L. has been traditionally used as an anti-diabetic herbal medicine; however, its mechanism of action remains elusive. In this study, the potential role of B. pilosa compounds on alpha-amylase inhibition and regulation of multiple pathways was investigated via computational and experimental studies. The phytocompounds were retrieved from plant databases and published literature. The druggability profile of these compounds was predicted using MolSoft. The probable targets of these phytocompounds were predicted using BindingDB (similarity index ≥ 0.7). Further, compound-gene set-pathway and functional enrichment analysis were performed using STRING and KEGG pathway databases. The network between compound-protein-pathway was constructed using Cytoscape. Molecular docking was performed using AutoDock Vina, executed through the POAP pipeline. The stability of the best docked complex was subjected to all-atom molecular dynamics (MD) simulation for 100 ns to investigate their structural stabilities and intermolecular interactions using GROMACS software. Finally, B. pilosa hydroalcoholic extract was subjected to LC-MS and tested for dose- and time-dependent alpha-amylase inhibitory activity. Out of 31 bioactive compounds, 13 were predicted to modulate the human pancreatic alpha-amylase (AMY2A) and 12 pathways associated with diabetes mellitus. PI3K-Akt signaling pathway (hsa04151) scored the lowest false discovery rate by triggering 15 genes. Further intermolecular interaction analysis of the docked complex revealed that Brassidin had the highest active site interaction and lowest binding energy compared to standard acarbose, and MD reveals the formation of a stable complex throughout 100 ns production run. LC-MS analysis revealed the presence of 13 compounds (targeting AMY2A) in B. pilosa hydroalcoholic extract, which showed potent AMY2A inhibition by in vitro studies that corroborate in silico findings for its anti-diabetic activity. Based on these findings, enriched fractions/pure compounds inhibitory activity that can be performed in future for drug discovery.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00187-9.

Synergistic effects of Momordica charantia, Nigella sativa, and Anethum graveolens on metabolic syndrome targets: In vitro enzyme inhibition and in silico analyses

Momordica charantia, Nigella sativa, and Anethum graveolens are established medicinal plants possessing noted anti-diabetic and anti-obesity properties. However, the molecular mechanisms underscoring their inhibitory effects on pancreatic lipase, α-glucosidase, and HMG-CoA reductase remain unexplored. This study aimed to elucidate the efficacy of various NS, MC, and AG blends in modulating the enzymatic activity of pancreatic lipase, HMG-CoA reductase, and a-glucosidase, utilizing an integrative approach combining in vitro assessments and molecular modeling techniques. A factorial design matrix generated eight distinct concentration combinations of NS, MC, and AG, subsequently subjected to in vitro enzyme inhibition assays. Molecular docking analyses using AutoDock Vina, molecular dynamics simulations, MMPBSA calculations, and principal component analysis, were executed with Gromacs to discern the interaction dynamics between the compounds and target enzymes. A formulation comprising NS:MC:AG at a 215:50:35 μg/mL ratio yielded significant inhibition of pancreatic lipase (IC50: 74.26 ± 4.27 μg/mL). Moreover, a concentration combination of 215:80:35 μg/mL effectively inhibited both α-glucosidase (IC50: 66.09 ± 3.98 μg/mL) and HMGCR (IC50: 129.03 μg/mL). Notably, MC-derived compounds exhibited superior binding affinity towards all three enzymes, compared to their reference molecules, with diosgenin, Momordicoside I, and diosgenin displaying binding affinities of -11.0, -8.8, and -7.9 kcal/mol with active site residues of pancreatic lipase, α-glucosidase, and HMGCR, respectively. Further, 100 ns molecular dynamics simulations revealed the formation and stabilization of non-bonded interactions between the compounds and the enzymes' active site residues. Through a synergistic application of in vitro and molecular modeling methodologies, this study substantiated the potent inhibitory activity of the NS:MC:AG blend (at a ratio of 215:80:35 μg/mL) and specific MC compounds against pancreatic lipase, α-glucosidase, and HMGCR. These findings provide invaluable insights into the molecular underpinnings of these medicinal plants' anti-diabetic and anti-obesity effects and may guide future therapeutic development.

Virtual screening of flavonoids as potential RIPK1 inhibitors for neurodegeneration therapy

Background

Global prevalence of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration.

Methods

In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations.

Results

From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from -11.7 to -10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0.39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding.

Conclusion

Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.

Identification of Novel EGFR Inhibitors for the Targeted Therapy of Colorectal Cancer Using Pharmacophore Modelling, Docking, Molecular Dynamic Simulation and Biological Activity Prediction

BACKGROUND

Colorectal cancer (CRC) is considered the second deadliest cancer in the world. One of the reasons for the occurrence of this cancer is the deregulation of the Epidermal Growth Factor Receptor (EGFR), which plays a critical role in regulating cell division, persistence, differentiation, and migration. The overexpression of the EGFR protein leads to its dysregulation and causes CRC.

OBJECTIVES

Hence, this work aims to identify and validate novel EGFR inhibitors for the treatment of colorectal cancer employing various computer aided techniques such as pharmacophore modeling, docking, molecular dynamic simulation and Quantitative Structure-Activity Relationship (QSAR) analysis.

METHODS

In this work, a shared-featured ligand-based pharmacophore model was generated using the known inhibitors of EGFR. The best model was validated and screened against ZincPharmer and Maybridge databases, and 143 hits were obtained. Pharmacokinetic and toxicological properties of these hits were studied, and the acceptable ligands were docked against EGFR. The best five protein-ligand complexes with binding energy less than -5 kcal/mol were selected. The molecular dynamic simulation studies of these complexes were conducted for 100 nanoseconds (ns), and the results were analyzed. The biological activity of this ligand was calculated using QSAR analysis.

RESULTS

The best complex with Root Mean Square Deviation (RMSD) 3.429 Å and Radius of Gyration (RoG) 20.181 Å was selected. The Root Mean Square Fluctuations (RMSF) results were also found to be satisfactory. The biological activity of this ligand was found to be 1.38 μM.

CONCLUSION

This work hereby proposes the ligand 2-((1,6-dimethyl-4-oxo-1,4-dihydropyridin-3-yl)oxy)-N- (1H-indol-4-yl)acetamide as a potential EGFR inhibitor for the treatment of colorectal cancer. The wet lab analysis must be conducted, however, to confirm this hypothesis.

In silico discovery of novel calcineurin inhibitors using ligand-based 3-D pharmacophore modelling and molecular dynamics simulation

Calcineurin is a serine-threonine protein phosphatase that is activated with the binding of calmodulin in the presence of increased calcium concentration and has a major role in various signaling pathways. Its role in regulating homeostasis, developmental processes, and different disease progression has already been reported. The dysregulated Ca2+/calcineurin/NFAT1-4 pathway is observed in Autoimmune disorders and hence the use of Calcineurin inhibitors like Cyclosporin A (CsA) and Tacrolimus (FK506) is widely done in such cases. Recent studies indicate the uncontrolled overexpression of the Calcineurin protein in the pathophysiological pathway of neurodegenerative diseases. The in vitro and animal model studies with standard calcineurin inhibitors (CnIs), which are widely labeled as immunosuppressant drugs, have shown a significant reduction of neurodegeneration in respective models. These results compel the identification of novel calcineurin inhibitors against neurodegenerative diseases. With this scenario, the present work focuses on the computer-aided identification of novel CnIs via ligand-based 3-D pharmacophore modelling. Known CnIs, CsA, and FK506, were used to build the pharmacophore models which were validated and screened against external databases to retrieve possible hits. Docking investigations, pharmacokinetic properties, and molecular dynamics simulations along with toxicity predictions were performed on the hits that were obtained. According to the study, a total of 5 molecules ILB 162, ILB 005, ILB 439, ILB 390, and ILB 198, were found to be the best calcineurin inhibitors with binding affinity in the range of -9.7 to -9.0 Kcal/mol with 1MF8 (PDB). The stability of interactions of these molecules was further validated via Molecular dynamics simulation studies to confirm these to be the potential calcineurin-inhibiting molecules. HIGHLIGHTSCalcineurin inhibitors can be a novel therapeutic candidate against neurodegenerative diseases.The identification of novel Calcineurin inhibitors was done in silico using ligand-based 3-D pharmacophore modelling using Ligand Scout Essential 4.4. software.The model could identify 440 hits from various external databases like PubChem (2432 molecules), ChemSpider, MayBridge, DrugBank, and e-Drug 3D by Cheminformatic Tools and Databases for Pharmacology.Out of which 5 molecules: ILB 162, ILB 005, ILB 439, ILB 390, and ILB 198, were found to be the best calcineurin inhibitors with binding affinity in the range of -9.7 to -9.0 Kcal/mol with 1MF8 (PDB) which were further confirmed to be the best CnI candidates via Molecular dynamics simulation studies.Communicated by Ramaswamy H. Sarma.

Structural insights into modeling of hepatitis B virus reverse transcriptase and identification of its inhibitors from potential medicinal plants of Western Ghats: an in silico and in vitro study

The present study was proposed to model full-length HBV-RT and investigate the intermolecular interactions of known inhibitor and libraries of phytocompounds to probe the potential natural leads by in silico and in vitro studies. Homology modeling of RT was performed by Phyre2 and Modeller and virtual screening of ligands implemented through POAP pipeline. Molecular dynamics (MD) simulation (100 ns) and MM-GBSA calculations were performed using Schrodinger Desmond and Prime, respectively. Phytocompounds probable host protein targets gene set pathway enrichment and network analysis were executed by KEGG database and Cytoscape software. Prioritized plant extracts/enriched fraction LC-MS analysis was performed and along with pure compound, RT inhibitory activity, time-dependent HBsAg and HBeAg secretion, and intracellular HBV DNA, and pgRNA by qRT-PCR was performed in HepG2.2.15 cell line. Among the screened chemical library of 268 phytocompounds from 18 medicinal plants, 15 molecules from Terminalia chebula (6), Bidens pilosa (5), and Centella asiatica (4)) were identified as potential inhibitors of YMDD and RT1 motif of HBV-RT. MD simulation demonstrated stable interactions of 15 phytocompounds with HBV-RT, of which 1,2,3,4,6-Pentagalloyl Glucose (PGG) was identified as lead molecule. Out of 15 compounds, 11 were predicted to modulate 39 proteins and 15 molecular pathways associated with HBV infection. TCN and TCW (500 µg/mL) showed potent RT inhibition, decreased intracellular HBV DNA, and pgRNA, and time-dependent inhibition of HBsAg and HBeAg levels compared to PGG and Tenofovir Disoproxil Fumarate. We propose that the identified lead molecules from T. chebula as promising and cost-effective moieties for the management of HBV infection.Communicated by Ramaswamy H. Sarma.

Network pharmacology based anti-diabetic attributes of bioactive compounds from Ocimum gratissimum L. through computational approach

The present research was framed to determine the key compounds present in the plant Ocimum gratissimum L. targeting protein molecules of Diabetes Mellitus (DM) by employing In-silico approaches. Phytochemicals previously reported to be present in this herb were collated through literature survey and public phytochemical databases, and their probable targets were anticipated using BindingDB (p ≥ 0.7). STRING and KEGG pathway databases were employed for pathway enrichment analysis. Homology modelling was executed to elucidate the structures of therapeutic targets. Further, Phytocompounds from O. gratissimum were subjected for docking with four therapeutic targets of DM by using AutoDock vina through POAP pipeline implementation. 30 compounds were predicted to target 136 protein molecules including aldose reductase, DPP4, alpha-amylase, and alpha-glucosidase. Neuroactive ligand-receptor interaction, MAPK, PI3K-Akt, starch and insulin resistance were predicted to have potentially modulation by phytocompounds. Based on the phytocompound's binding score with the four targets of DM, Rutin scored the lowest binding energy (-11 kcal/mol) with Aldose reductase by forming 17 intermolecular interactions. In conclusion, based on the network and binding score, phytocompounds from O. gratissimum have a synergistic and considerable effect in the management of DM via multi-compound, multi-target, and multi-pathway mechanisms.

Elucidation of intermolecular interactions between chlorogenic acid and glucose-6-phosphate translocase: A step towards chemically induced glycogen storage disease type 1b model

Glucose-6-phosphate translocase enzyme, encoded by SLC37A4 gene, is a crucial enzyme involved in transporting glucose-6-phosphate into the endoplasmic reticulum. Inhibition of this enzyme can cause Von-Gierke's/glycogen storage disease sub-type 1b. The current study dealt to elucidate the intermolecular interactions to assess the inhibitory activity of Chlorogenic acid (CGA) against SLC37A4 was assessed by molecular docking and dynamic simulation. The alpha folded model of SLC37A4 and CGA 3D structure were optimized using CHARMM force field, using energy minimization protocol in the Discovery Studio software. Glucose-6-phosphate (G6P) and CGA molecular docking, Molecular dynamics (MD) simulation, analysis of binding free energy of G6P-SLC37A4 and CGA-SLC37A4 complexes was performed for 100 ns using GROMACS, followed by principal component analysis (PCA). The docking score of the CGA-SLC37A4 complex exhibited a higher docking score (- 8.2 kcal/mol) when compared to the G6P-SLC37A4 complex (- 6.5 kcal/mol), suggesting a stronger binding interaction between CGA and SLC37A4. Further, the MD simulation demonstrated a stable backbone and complex Root Mean Square Deviation (RMSD), the least RMS fluctuation, and stable active site residue interactions throughout the 100 ns production run. The CGA complex with SLC37A4 exhibits higher compactness and formed 8 hydrogen bonds to achieve stability. The binding free energy of the G6P-SLC37A4 and CGA-SLC37A4 complex was found to be - 12.73 and - 31.493 kcal/mol. Lys29 formed stable contact for both G6P (- 4.73 kJ/mol) and SLC37A4 (- 2.18 kJ/mol). This study imparts structural insights into the competitive inhibition of SLC37A4 by CGA. CGA shows potential as a candidate to induce manifestations of GSD1b by inhibiting glycogenolysis, and gluconeogenesis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03661-5.

Computational and experimental pharmacology to decode the efficacy of Theobroma cacao L. against doxorubicin-induced organ toxicity in EAC-mediated solid tumor-induced mice

Background and objective: Doxorubicin is extensively utilized chemotherapeutic drug, and it causes damage to the heart, liver, and kidneys through oxidative stress. Theobroma cacao L (cocoa) is reported to possess protective effects against several chemical-induced organ damages and also acts as an anticancer agent. The study aimed to determine whether the administration of cocoa bean extract reduces doxorubicin-induced organ damage in mice with Ehrlich ascites carcinoma (EAC) without compromising doxorubicin efficacy. Methodology: Multiple in vitro methods such as cell proliferation, colony formation, chemo-sensitivity, and scratch assay were carried out on cancer as well as normal cell lines to document the effect of cocoa extract (COE) on cellular physiology, followed by in vivo mouse survival analysis, and the organ-protective effect of COE on DOX-treated animals with EAC-induced solid tumors was then investigated. In silico studies were conducted on cocoa compounds with lipoxygenase and xanthine oxidase to provide possible molecular explanations for the experimental observations. Results: In vitro studies revealed potent selective cytotoxicity of COE on cancer cells compared to normal. Interestingly, COE enhanced DOX potency when used in combination. The in vivo results revealed reduction in EAC and DOX-induced toxicities in mice treated with COE, which also improved the mouse survival time; percentage of lifespan; antioxidant defense system; renal, hepatic, and cardiac function biomarkers; and also oxidative stress markers. COE reduced DOX-induced histopathological alterations. Through molecular docking and MD simulations, we observed chlorogenic acid and 8'8 methylenebiscatechin, present in cocoa, to have the highest binding affinity with lipoxygenase and xanthine oxidase, which lends support to their potential in ameliorating oxidative stress. Conclusion: The COE reduced DOX-induced organ damage in the EAC-induced tumor model and exhibited powerful anticancer and antioxidant effects. Therefore, COE might be useful as an adjuvant nutritional supplement in cancer therapy.

Antioxidant and anticancer potential of ethyl acetate extract of bark and flower of Tecoma stans (Linn) and In Silico studies on phytoligands against Bcl2 and VEGFR2 factors

This study was designed to appraise the antioxidant and anticancer competence of solvent extracts of Tecoma stans (Linn) and analyze the phytoligands interaction against Bcl2 VEGFR2 through in silico studies. The phytochemical analysis revealed that the ethyl acetate extract contains more number of pharmaceutically valuable phytochemicals than other solvent extracts. Among the various phytochemicals, flavonoid was found as a predominant component, and UV-Vis- spectrophotometer analysis initially confirmed it. Hence, the column chromatogram was performed to purify the flavonoid, and High-performance liquid chromatography (HPLC) was performed. It revealed that the flavonoid enriched fraction by compared with standard flavonoid molecules. About 84.69% and 80.43% of antioxidant activity were found from ethyl acetate extract of bark and flower at the dosage of 80 μg mL^-1 with the IC₅₀ value of 47.24 and 43.40 μg mL^-1, respectively. In a dose-dependent mode, the ethyl acetate extract of bark and flower showed cytotoxicity against breast cancer cell line MCF 7 (Michigan Cancer Foundation-7) as up to 81.38% and 80.94% of cytotoxicity respectively. Furthermore, the IC₅₀ was found as 208.507 μg mL^-1 and 207.38 μg mL^-1 for bark and flower extract correspondingly. About 10 medicinal valued flavonoid components were identified from bark (6) and flower (4) ethyl acetate extract through LC-MS analysis. Out of 10 components, the 3,5-O-dicaffeoylquinic acid (ΔG -8.8) and Isorhamnetin-3-O-rutinoside (ΔG -8.3) had the competence to interact with Bcl2 (B-Cell Lymphoma 2) and VEGFR2 (Vascular Endothelial Growth Factor Receptor 2) respectively with more energy. Hence, these results confirm that the ethyl acetate extract of bark and flower of T. stans has significant medicinal potential and could be used as antioxidant and anticancer agent after some animal performance study.

Design and Computational Analysis of an MMP9 Inhibitor in Hypoxia-Induced Glioblastoma Multiforme

The main therapeutic difficulties in treating hypoxia-induced glioblastoma multiforme (GBM) are toxicity of current treatments and the resistance brought on by the microenvironment. More effective therapeutic alternatives are urgently needed to reduce tumor lethality. Hence, we screened plant-based natural product panels intending to identify novel drugs without elevating drug resistance. We explored GEO for the hypoxia GBM model and compared hypoxic genes to non-neoplastic brain cells. A total of 2429 differentially expressed genes expressed exclusively in hypoxia were identified. The functional enrichment analysis demonstrated genes associated with GBM, further PPI network was constructed, and biological pathways associated with them were explored. Seven webtools, including GEPIA2.0, TIMER2.0, TCGA-GBM, and GlioVis, were used to validate 32 hub genes discovered using Cytoscape tool in GBM patient samples. Four GBM-specific hypoxic hub genes, LYN, MMP9, PSMB9, and TIMP1, were connected to the tumor microenvironment using TIMER analysis. 11 promising hits demonstrated positive drug-likeness with nontoxic characteristics and successfully crossed blood-brain barrier and ADMET analyses. Top-ranking hits have stable intermolecular interactions with the MMP9 protein according to molecular docking, MD simulation, MM-PBSA, PCA, and DCCM analyses. Herein, we have reported flavonoids, 7,4'-dihydroxyflavan, (3R)-3-(4-hydroxybenzyl)-6-hydroxy-8-methoxy-3,4-dihydro-2H-1-benzopyran, and 4'-hydroxy-7-methoxyflavan, to inhibit MMP9, a novel hypoxia gene signature that could serve as a promising predictor in various clinical applications, including GBM diagnosis, prognosis, and targeted therapy.

Exploring the Potential of Phytocompounds for Targeting Epigenetic Mechanisms in Rheumatoid Arthritis: An In Silico Study Using Similarity Indexing

Finding structurally similar compounds in compound databases is highly efficient and is widely used in present-day drug discovery methodology. The most-trusted and -followed similarity indexing method is Tanimoto similarity indexing. Epigenetic proteins like histone deacetylases (HDACs) inhibitors are traditionally used to target cancer, but have only been investigated very recently for their possible effectiveness against rheumatoid arthritis (RA). The synthetic drugs that have been identified and used for the inhibition of HDACs include SAHA, which is being used to inhibit the activity of HDACs of different classes. SAHA was chosen as a compound of high importance as it is reported to inhibit the activity of many HDAC types. Similarity searching using the UNPD database as a reference identified aglaithioduline from the Aglaia leptantha compound as having a ~70% similarity of molecular fingerprints with SAHA, based on the Tanimoto indexing method using ChemmineR. Aglaithioduline is abundantly present in the shell and fruits of A. leptantha. In silico studies with aglaithioduline were carried out against the HDAC8 protein target and showed a binding affinity of -8.5 kcal mol. The complex was further subjected to molecular dynamics simulation using Gromacs. The RMSD, RMSF, compactness and SASA plots of the target with aglaithioduline, in comparison with the co-crystallized ligand (SAHA) system, showed a very stable configuration. The results of the study are supportive of the usage of A. leptantha and A. edulis in Indian traditional medicine for the treatment of pain-related ailments similar to RA. Our study therefore calls for further investigation of A. leptantha and A. edulis for their potential use against RA by targeting epigenetic changes, using in vivo and in vitro studies.

Coumarin derivative as a potent drug candidate against triple negative breast cancer targeting the frizzled receptor of wingless-related integration site signaling pathway

Triple negative breast cancer constitutes to about 21.8 percent of the total breast cancer related cases. Its ability to affect young ladies and in pre-menstrual stage makes this a disease of concern worldwide. The current treatment regimens involve chemotherapy which are used for treatment of other cancer types. In this regard, there is a need for specific and targeted drug candidate for its effective treatment. In the current study, assessment of coumarin derivative 2-(2-(6- Methyl-2-Oxo-2H-chromen-4-yl) acetamido)-3-phenylpropanoic acid is carried out both In-silico and In-vitro methods. Frizzled transmembrane proteins of Wingless-related integration site signaling pathway was targeted in which Frizzled-7 proved to a prospective target and showed a binding energy of -6.78 kcal/mol. The complex was subjected to molecular dynamics simulation for 200 ns and showed stable interaction with cysteine rich domain of the receptor. Cell proliferation, viability and apoptosis assay were performed on MDA-MB-231 and MDA-MB-468 cell lines with an IC₅₀ value of 81.23 and 84.68 µM, respectively. The results provide a drug candidate which is derivative of a natural compound with targeted TNBC inhibitory effect. Communicated by Ramaswamy H. Sarma.

Comparative Assessment of Docking Programs for Docking and Virtual Screening of Ribosomal Oxazolidinone Antibacterial Agents

Oxazolidinones are a broad-spectrum class of synthetic antibiotics that bind to the 50S ribosomal subunit of Gram-positive and Gram-negative bacteria. Many crystal structures of the ribosomes with oxazolidinone ligands have been reported in the literature, facilitating structure-based design using methods such as molecular docking. It would be of great interest to know in advance how well docking methods can reproduce the correct ligand binding modes and rank these correctly. We examined the performance of five molecular docking programs (AutoDock 4, AutoDock Vina, DOCK 6, rDock, and RLDock) for their ability to model ribosomal-ligand interactions with oxazolidinones. Eleven ribosomal crystal structures with oxazolidinones as the ligands were docked. The accuracy was evaluated by calculating the docked complexes' root-mean-square deviation (RMSD) and the program's internal scoring function. The rankings for each program based on the median RMSD between the native and predicted were DOCK 6 > AD4 > Vina > RDOCK >> RLDOCK. Results demonstrate that the top-performing program, DOCK 6, could accurately replicate the ligand binding in only four of the eleven ribosomes due to the poor electron density of said ribosomal structures. In this study, we have further benchmarked the performance of the DOCK 6 docking algorithm and scoring in improving virtual screening (VS) enrichment using the dataset of 285 oxazolidinone derivatives against oxazolidinone binding sites in the S. aureus ribosome. However, there was no clear trend between the structure and activity of the oxazolidinones in VS. Overall, the docking performance indicates that the RNA pocket's high flexibility does not allow for accurate docking prediction, highlighting the need to validate VS. protocols for ligand-RNA before future use. Later, we developed a re-scoring method incorporating absolute docking scores and molecular descriptors, and the results indicate that the descriptors greatly improve the correlation of docking scores and pMIC values. Morgan fingerprint analysis was also used, suggesting that DOCK 6 underpredicted molecules with tail modifications with acetamide, n-methylacetamide, or n-ethylacetamide and over-predicted molecule derivatives with methylamino bits. Alternatively, a ligand-based approach similar to a field template was taken, indicating that each derivative's tail groups have strong positive and negative electrostatic potential contributing to microbial activity. These results indicate that one should perform VS. campaigns of ribosomal antibiotics with care and that more comprehensive strategies, including molecular dynamics simulations and relative free energy calculations, might be necessary in conjunction with VS. and docking.

Deciphering the interaction mechanism of natural actives against larval proteins of Aedes aegypti to identify potential larvicides: a computational biology analysis

Aedes aegypti is the target for repellents to curb incidences of vector-borne diseases. Stopping breeding of this mosquito species at its larval stages helps in controlling spread of insect-borne diseases. Therefore, the present study focused on deciphering the mechanism of interaction of selected natural actives against larval proteins of A. aegypti to identify potential natural alternative larvicides. 65 larval proteins were identified from literature, whose structures were modelled and validated using RaptorX and ProCheck. 11 natural actives were selected for predicting their ligand properties and toxicities via Toxicity Estimation Software Tool and ProTox-II. Molecular docking studies were carried out using POAP followed by 100 ns molecular dynamic simulation studies for top three best docked complexes to better understand the robustness of docking, complex stabilities and molecular mechanisms of interactions. Toxicity predictions revealed that 6 molecules belonged to toxicity class 4, and five to toxicity class 5, implying that they were all safe to use. Complexes goniothalamin-translation elongation factor (-10 kcal/mol), andrographolide-acetyl-CoA C-myristoyltransferase (-9.2 kcal/mol) and capillin-translation elongation factor (-8.4 kcal/mol) showed best binding energies. When simulated, capillin-translation elongation factor showed most stability, while the remaining two also evidenced robust docking. Evolutionary studies for top two larval proteins disclosed 100 other insect species in which these proteins can be targeted using various larvicides. Protein-protein interaction network analysis revealed several protein pathways that might be affected due to aforesaid naturals. Therefore, this study provides computational insights into the molecular interaction of naturals against larval proteins, acting as potential natural larvicides.Communicated by Ramaswamy H. Sarma.

In Silico Study on the Interactions, Molecular Docking, Dynamics and Simulation of Potential Compounds from Withania somnifera (L.) Dunal Root against Cancer by Targeting KAT6A

Cancer is characterized by the abnormal development of cells that divide in an uncontrolled manner and further take over the body and destroy the normal cells of the body. Although several therapies are practiced, the demand and need for new therapeutic agents are ever-increasing because of issues with the safety, efficacy and efficiency of old drugs. Several plant-based therapeutics are being used for treatment, either as conjugates with existing drugs or as standalone formulations. Withania somnifera (L.) Dunal is a highly studied medicinal plant which is known to possess immunomodulatory activity as well as anticancer properties. The pivotal role of KAT6A in major cellular pathways and its oncogenic nature make it an important target in cancer treatment. Based on the literature and curated datasets, twenty-six compounds from the root of W. somnifera and a standard inhibitor were docked with the target KAT6A using Autodock vina. The compounds and the inhibitor complexes were subjected to molecular dynamics simulation (50 ns) using Desmond to understand the stability and interactions. The top compounds (based on the docking score of less than -8.5 kcal/mol) were evaluated in comparison to the inhibitor. Based on interactions at ARG655, LEU686, GLN760, ARG660, LEU689 and LYS763 amino acids with the inhibitor WM-8014, the compounds from W. somnifera were evaluated. Withanolide D, Withasomniferol C, Withanolide E, 27-Hydroxywithanone, Withanolide G, Withasomniferol B and Sitoindoside IX showed high stability with the residues of interest. The cell viability of human breast cancer MCF-7 cells was evaluated by treating them with W. Somnifera root extract using an MTT assay, which showed inhibitory activity with an IC50 value of 45 µg/mL. The data from the study support the traditional practice of W. somnifera as an anticancer herb.

Systems and in vitro pharmacology profiling of diosgenin against breast cancer

Aim: The purpose of this study was to establish a mode of action for diosgenin against breast cancer employing a range of system biology tools and to corroborate its results with experimental facts. Methodology: The diosgenin-regulated domains implicated in breast cancer were enriched in the Kyoto Encyclopedia of Genes and Genomes database to establish diosgenin-protein(s)-pathway(s) associations. Later, molecular docking and the lead complexes were considered for molecular dynamics simulations, MMPBSA, principal component, and dynamics cross-correlation matrix analysis using GROMACS v2021. Furthermore, survival analysis was carried out for the diosgenin-regulated proteins that were anticipated to be involved in breast cancer. For gene expression analyses, the top three targets with the highest binding affinity for diosgenin and tumor expression were examined. Furthermore, the effect of diosgenin on cell proliferation, cytotoxicity, and the partial Warburg effect was tested to validate the computational findings using functional outputs of the lead targets. Results: The protein-protein interaction had 57 edges, an average node degree of 5.43, and a p-value of 3.83e-14. Furthermore, enrichment analysis showed 36 KEGG pathways, 12 cellular components, 27 molecular functions, and 307 biological processes. In network analysis, three hub proteins were notably modulated: IGF1R, MDM2, and SRC, diosgenin with the highest binding affinity with IGF1R (binding energy -8.6 kcal/mol). Furthermore, during the 150 ns molecular dynamics (MD) projection run, diosgenin exhibited robust intermolecular interactions and had the least free binding energy with IGF1R (-35.143 kcal/mol) compared to MDM2 (-34.619 kcal/mol), and SRC (-17.944 kcal/mol). Diosgenin exhibited the highest cytotoxicity against MCF7 cell lines (IC₅₀ 12.05 ± 1.33) µg/ml. Furthermore, in H₂O₂-induced oxidative stress, the inhibitory constant (IC₅₀ 7.68 ± 0.51) µg/ml of diosgenin was lowest in MCF7 cell lines. However, the reversal of the Warburg effect by diosgenin seemed to be maximum in non-cancer Vero cell lines (EC₅₀ 15.27 ± 0.95) µg/ml compared to the rest. Furthermore, diosgenin inhibited cell proliferation in SKBR3 cell lines more though. Conclusion: The current study demonstrated that diosgenin impacts a series of signaling pathways, involved in the advancement of breast cancer, including FoxO, PI3K-Akt, p53, Ras, and MAPK signaling. Additionally, diosgenin established a persistent diosgenin-protein complex and had a significant binding affinity towards IGF1R, MDM2, and SRC. It is possible that this slowed down cell growth, countered the Warburg phenomenon, and showed the cytotoxicity towards breast cancer cells.

Elucidating type 2 diabetes mellitus risk factor by promoting lipid metabolism with gymnemagenin: An in vitro and in silico approach

Introduction: Adipose tissue functions as a key endocrine organ which releases multiple bioactive substances and regulate obesity-linked complications. Dysregulation of adipocyte differentiation, triglyceride metabolism, adipokines production and lipid transport contributes to impaired lipid metabolism resulting in obesity, insulin resistance and type 2 diabetes. Gymnema sylvestre plant is frequently used in Ayurveda for treatment of diabetes and obesity. Gymnemagenin is a major bioactive compound of Gymnema sylvestre. The present study was undertaken to elucidate the role of gymnemagenin in lipid metabolism by in vitro and computational approaches. Methods: A panel of twelve genes viz., Fasn, Lipe, Lpl, Pparg, Plin2, Cidea, Scd1, Adipoq, Lep, Ccl2, Fabp4, and Slc2a4, essential in lipid metabolism were selected and gene expression pattern and triglyceride content were checked in adipocytes (3T3L1 cells) with/without treatment of gymnemagenin by Real time PCR and colorimetric estimation, respectively. Mode of action of gymnemagenin on Pparg and Fabp4 was accomplished by computational studies. Gene set enrichment and network pharmacology were performed by STRING and Cytoscape. Molecular docking was performed by AutoDock vina by POAP pipeline. Molecular dynamics, MM-PBSA were done by Gromacs tool. Results: In vitro study showed that gymnemagenin improved triglyceride metabolism by up regulating the expression of lipase genes viz., Lipe and Lpl which hydrolyse triglyceride. Gymnemagenin also up regulated the expression of anti-inflammatory gene Adipoq. Importantly, gymnemagenin treatment up regulated the expression of Pparg gene and the downstream target genes (Plin2, Cidea, and Scd1) which are associated with adipogenesis. However, gymnemagenin has no effect on expression of Fabp4, codes for a lipid transport protein. In silico study revealed that gymnemagenin targeted 12 genes were modulating 6 molecular pathways involved in diabetes and obesity. Molecular docking and dynamics revealed that gymnemagenin stably bind to active site residue of Pparg and failed to bind to Fabp4 active site compared to its standard molecules throughout 100 ns MD production run. Gymnemagenin scored binding free energy of -177.94 and -25.406 kJ/mol with Pparg and Fabp4, respectively. Conclusion: Gymnemagenin improved lipid metabolism by increasing triglyceride hydrolysis (lipolysis), up regulating the crucial gene of adipogenesis and increasing the expression of anti-inflammatory adipokine proving its therapeutic importance as anti-obesity and anti-diabetic phytocompound.

Comprehensive Molecular Interaction Studies to Construe the Repellent/Kill Activity of Geraniol During Binding Event Against Aedes aegypti Proteins

Aedes aegypti is an etiological agent for dengue, chikungunya, zika, and yellow fever viruses. With the advent of the use of natural alternatives as repellents, their precise mode of action during the event of binding is still unclear. Geraniol is one such bioactive natural that has been previously shown to have some insecticide properties. Thus, the present study aimed to understand the mechanism of the binding event of geraniol with the whole proteome of A. aegypti. Twenty protein target categories were shortlisted for the mosquito, wherein the proteins were downloaded with respect to the reference proteome. Conserved domain analysis was performed for the same using the CDD search tool to find the proteins that have common domains. 309 proteins were modeled using RaptorX standalone tool, and validated using Ramachandran plots from SAVES v6.0 from ProCheck. These modeled and validated proteins were then docked against geraniol, using POAP software, for understanding the binding energies. The top 3 best-docked complexes were then analyzed for their stabilities and event of binding via 100 ns simulation studies using DESMOND's Maestro environment. The docking results showed that the geraniol-voltage-gated sodium channel had the best energy of - 7.1 kcal/mol, followed by geraniol-glutathione-S-transferase (- 6.8 kcal/mol) and geraniol-alpha esterase (- 6.8 kcal/mol). The simulations for these 3 complexes revealed that several residues of the proteins interacted well with geraniol at a molecular level, and all three docked complexes were found to be stable when simulated (RMSD: 16-18 Å, 3.6-4.8 Å, 4.8-5.6 Å, respectively). Thus, the present study provides insights into the mechanism of the binding event of geraniol with the major A. aegypti targets, thereby, assisting the use of geraniol as a natural repellent.

A computational study to target necroptosis via RIPK1 inhibition

The human receptor-interacting serine/threonine-protein kinase 1 (RIPK1) is a critical necroptosis regulator implicated in cancer, psoriasis, ulcerative colitis, rheumatoid arthritis, Alzheimer's disease, and multiple sclerosis. Currently, there are no specific RIPK1 antagonists in clinical practice. In this study, we took a target-based computational approach to identify blood-brain-barrier-permeable potent RIPK1 ligands with novel chemotypes. Using molecular docking, we virtually screened the Marine Natural Products (MNP) library of 14,492 small molecules. Initial 18 hits were subjected to detailed ADMET profiling for bioavailability, brain penetration, druglikeness, and toxicities and eventually yielded 548773-66-6 as the best ligand. RIPK1 548773-66-6 binding was validated through duplicated molecular dynamics (MD) simulations where the co-crystallized ligand L8D served as a reference. Trajectory analysis indicated negligible Root-Mean-Square-Deviations (RMSDs) of the best ligand 548773-66-6 relative to the protein backbone: 0.156 ± 0.043 nm and 0.296 ± 0.044 nm (mean ± standard deviations) in two individual simulations. Visual inspection confirmed that 548773-66-6 occupied the RIPK1 ligand-binding pocket associated with the kinase activation loop. Further computations demonstrated consistent hydrogen bond interactions of the ligand with the residue ASP156. Binding free energy estimation also supported stable interactions of 548773-66-6 and RIPK1. Together, our in silico analysis predicted 548773-66-6 as a novel ligand for RIPK1. Therefore, 548773-66-6 could be a viable lead for inhibiting necroptosis in central nervous system inflammatory disorders.

Curcumin improves D-galactose and normal-aging associated memory impairment in mice: In vivo and in silico-based studies

Aging-induced memory impairment is closely associated with oxidative stress. D-Galactose (D-gal) evokes severe oxidative stress and mimics normal aging in animals. Curcumin, a natural flavonoid, has potent antioxidant and anti-aging properties. There are several proteins like glutathione S-transferase A1 (GSTA1), glutathione S-transferase omega-1 (GSTO1), kelch-like ECH-associated protein 1 (KEAP1), beta-secretase 1 (BACE1), and amine oxidase [flavin-containing] A (MAOA) are commonly involved in oxidative stress and aging. This study aimed to investigate the interaction of curcumin to these proteins and their subsequent effect on aging-associated memory impairment in two robust animal models: D-Gal and normal aged (NA) mice. The aging mice model was developed by administering D-gal intraperitoneally (i.p). Mice (n = 64) were divided into the eight groups (8 mice in each group): Vehicle, Curcumin-Control, D-gal (100mg/kg; i.p), Curcumin + D-gal, Astaxanthin (Ast) + D-gal, Normal Aged (NA), Curcumin (30mg/kg Orally) + NA, Ast (20mg/kg Orally) + NA. Retention and freezing memories were assessed by passive avoidance (PA) and contextual fear conditioning (CFC). Molecular docking was performed to predict curcumin binding with potential molecular targets. Curcumin significantly increased retention time (p < 0.05) and freezing response (p < 0.05) in PA and CFC, respectively. Curcumin profoundly ameliorated the levels of glutathione, superoxide dismutase, catalase, advanced oxidation protein products, nitric oxide, and lipid peroxidation in mice hippocampi. In silico studies revealed favorable binding energies of curcumin with GSTA1, GSTO1, KEAP1, BACE1, and MAOA. Curcumin improves retention and freezing memory in D-gal and nature-induced aging mice. Curcumin ameliorates the levels of oxidative stress biomarkers in mice. Anti-aging effects of curcumin could be attributed to, at least partially, the upregulation of antioxidant enzymes through binding with GSTA1, GSTO1, KEAP1, and inhibition of oxidative damage through binding with BACE1 and MAOA.

Network pharmacology and in vitro testing of Theobroma cacao extract's antioxidative activity and its effects on cancer cell survival

Theobroma cacao L. is a commercially important food/beverage and is used as traditional medicine worldwide against a variety of ailments. In the present study, computational biology approaches were implemented to elucidate the possible role of cocoa in cancer therapy. Bioactives of cocoa were retrieved from the PubChem database and queried for targets involved in cancer pathogenesis using BindingDB (similarity index ≥0.7). Later, the protein-protein interactions network was investigated using STRING and compound-protein via Cytoscape. In addition, intermolecular interactions were investigated via molecular docking. Also, the stability of the representative complex Hirsutrin-epidermal growth factor receptor (EGFR) complex was explored using molecular dynamics simulations. Crude extract metabolite profile was carried out by LC-MS. Further, anti-oxidant and cytotoxicity studies were performed in Chinese hamster ovary (normal) and Ehrlich ascites carcinoma (cancer) cell lines. Herein, the gene set enrichment and network analysis revealed 34 bioactives in cocoa targeting 50 proteins regulating 21 pathways involved in cancer and oxidative stress in humans. EGFR scored the highest edge count amongst 50 targets modulating 21 key pathways. Hence, it was selected as a promising anticancer target in this study. Structural refinement of EGFR was performed via all-atom molecular dynamics simulations in explicit solvent. A complex EGFR-Hirsutrin showed the least binding energy (-7.2 kcal/mol) and conserved non-bonded contacts with binding pocket residues. A stable complex formation of EGFR-Hirsutrin was observed during 100 ns MD simulation. In vitro studies corroborated antioxidant activity for cocoa extract and showed a significantly higher cytotoxic effect on cancer cells compared to normal cells. Our study virtually predicts anti-cancer activity for cocoa affected by hirsutrin inhibiting EGFR. Further wet-lab studies are needed to establish cocoa extract against cancer and oxidative stress.

Hepatitis C Virus NS3/4A Inhibition and Host Immunomodulation by Tannins from Terminalia chebula: A Structural Perspective

Terminalia chebula Retz. forms a key component of traditional folk medicine and is also reported to possess antihepatitis C virus (HCV) and immunomodulatory activities. However, information on the intermolecular interactions of phytochemicals from this plant with HCV and human proteins are yet to be established. Thus, by this current study, we investigated the HCV NS3/4A inhibitory and host immune-modulatory activity of phytocompounds from T. chebula through in silico strategies involving network pharmacology and structural bioinformatics techniques. To start with, the phytochemical dataset of T. chebula was curated from biological databases and the published literature. Further, the target ability of the phytocompounds was predicted using BindingDB for both HCV NS3/4A and other probable host targets involved in the immune system. Further, the identified targets were docked to the phytochemical dataset using AutoDock Vina executed through the POAP pipeline. The resultant docked complexes with significant binding energy were subjected to 50 ns molecular dynamics (MD) simulation in order to infer the stability of complex formation. During network pharmacology analysis, the gene set pathway enrichment of host targets was performed using the STRING and Reactome pathway databases. Further, the biological network among compounds, proteins, and pathways was constructed using Cytoscape 3.6.1. Furthermore, the druglikeness, side effects, and toxicity of the phytocompounds were also predicted using the MolSoft, ADVERpred, and PreADMET methods, respectively. Out of 41 selected compounds, 10 were predicted to target HCV NS3/4A and also to possess druglike and nontoxic properties. Among these 10 molecules, Chebulagic acid and 1,2,3,4,6-Pentagalloyl glucose exhibited potent HCV NS3/4A inhibitory activity, as these scored a lowest binding energy (BE) of −8.6 kcal/mol and −7.7 kcal/mol with 11 and 20 intermolecular interactions with active site residues, respectively. These findings are highly comparable with Asunaprevir (known inhibitor of HCV NS3/4A), which scored a BE of −7.4 kcal/mol with 20 key intermolecular interactions. MD studies also strongly suggest that chebulagic acid and 1,2,3,4,6-Pentagalloyl glucose as promising leads, as these molecules showed stable binding during 50 ns of production run. Further, the gene set enrichment and network analysis of 18 protein targets prioritized 10 compounds and were predicted to potentially modulate the host immune system, hemostasis, cytokine levels, interleukins signaling pathways, and platelet aggregation. On overall analysis, this present study predicts that tannins from T. chebula have a potential HCV NS3/4A inhibitory and host immune-modulatory activity. However, further experimental studies are required to confirm the efficacies.

A Review on Parallel Virtual Screening Softwares for High-Performance Computers

Drug discovery is the most expensive, time-demanding, and challenging project in biopharmaceutical companies which aims at the identification and optimization of lead compounds from large-sized chemical libraries. The lead compounds should have high-affinity binding and specificity for a target associated with a disease, and, in addition, they should have favorable pharmacodynamic and pharmacokinetic properties (grouped as ADMET properties). Overall, drug discovery is a multivariable optimization and can be carried out in supercomputers using a reliable scoring function which is a measure of binding affinity or inhibition potential of the drug-like compound. The major problem is that the number of compounds in the chemical spaces is huge, making the computational drug discovery very demanding. However, it is cheaper and less time-consuming when compared to experimental high-throughput screening. As the problem is to find the most stable (global) minima for numerous protein-ligand complexes (on the order of 106 to 1012), the parallel implementation of in silico virtual screening can be exploited to ensure drug discovery in affordable time. In this review, we discuss such implementations of parallelization algorithms in virtual screening programs. The nature of different scoring functions and search algorithms are discussed, together with a performance analysis of several docking softwares ported on high-performance computing architectures.

Identification of structurally diverse menaquinone-binding antibiotics with in vivo activity against multidrug-resistant pathogens

The emergence of multidrug-resistant bacteria poses a threat to global health and necessitates the development of additional in vivo active antibiotics with diverse modes of action. Directly targeting menaquinone (MK), which plays an important role in bacterial electron transport, is an appealing, yet underexplored, mode of action due to a dearth of MK-binding molecules. Here we combine sequence-based metagenomic mining with a motif search of bioinformatically predicted natural product structures to identify six biosynthetic gene clusters that we predicted encode MK-binding antibiotics (MBAs). Their predicted products (MBA1-6) were rapidly accessed using a synthetic bioinformatic natural product approach, which relies on bioinformatic structure prediction followed by chemical synthesis. Among these six structurally diverse MBAs, four make up two new MBA structural families. The most potent member of each new family (MBA3, MBA6) proved effective at treating methicillin-resistant Staphylococcus aureus infection in a murine peritonitis-sepsis model. The only conserved feature present in all MBAs is the sequence 'GXLXXXW', which we propose represents a minimum MK-binding motif. Notably, we found that a subset of MBAs were active against Mycobacterium tuberculosis both in vitro and in macrophages. Our findings suggest that naturally occurring MBAs are a structurally diverse and untapped class of mechanistically interesting, in vivo active antibiotics.

Molecular docking-based computational platform for high-throughput virtual screening

Structure-based virtual screening is a key, routine computational method in computer-aided drug design. Such screening can be used to identify potentially highly active compounds, to speed up the progress of novel drug design. Molecular docking-based virtual screening can help find active compounds from large ligand databases by identifying the binding affinities between receptors and ligands. In this study, we analyzed the challenges of virtual screening, with the aim of identifying highly active compounds faster and more easily than is generally possible. We discuss the accuracy and speed of molecular docking software and the strategy of high-throughput molecular docking calculation, and we focus on current challenges and our solutions to these challenges of ultra-large-scale virtual screening. The development of Web services helps lower the barrier to drug virtual screening. We introduced some related web sites for docking and virtual screening, focusing on the development of pre- and post-processing interactive visualization and large-scale computing.

An integrated method for optimized identification of effective natural inhibitors against SARS-CoV-2 3CLpro

The current severe situation of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has not been reversed and posed great threats to global health. Therefore, there is an urgent need to find out effective antiviral drugs. The 3-chymotrypsin-like protease (3CLpro) in SARS-CoV-2 serve as a promising anti-virus target due to its essential role in the regulation of virus reproduction. Here, we report an improved integrated approach to identify effective 3CLpro inhibitors from effective Chinese herbal formulas. With this approach, we identified the 5 natural products (NPs) including narcissoside, kaempferol-3-O-gentiobioside, rutin, vicenin-2 and isoschaftoside as potential anti-SARS-CoV-2 candidates. Subsequent molecular dynamics simulation additionally revealed that these molecules can be tightly bound to 3CLpro and confirmed effectiveness against COVID-19. Moreover, kaempferol-3-o-gentiobioside, vicenin-2 and isoschaftoside were first reported to have SARS-CoV-2 3CLpro inhibitory activity. In summary, this optimized integrated strategy for drug screening can be utilized in the discovery of antiviral drugs to achieve rapid acquisition of drugs with specific effects on antiviral targets.

Structure-Based Virtual Screening and Molecular Dynamics Simulation to Identify Potential SARS-CoV-2 Spike Receptor Inhibitors from Natural Compound Database

The outbreak of respiratory disease, COVID-19 caused by SARS-CoV-2 has now been spread globally and the number of new infections is rising every moment. There are no specific medications that are currently available to combat the disease. The spike receptor of SARS-CoV-2 facilitates the viral entry into a host cell and initiation of infection. Targeting the viral entry at the initial stage has a better advantage than inhibiting it in later stages of the viral life cycle. This study deals with identification of the potential natural molecule or its derivatives from MolPort Databank as SARS-CoV-2 spike receptor inhibitors using structure-based virtual screening followed by molecular dynamics simulation. On the basis of ADME properties, docking score, MMGBSAbinding energy, 150 ns molecular docking studies, and final molecular dynamics analysis, two natural compounds - 3 (MolPort-002-535-004) docking score -9.10 kcal mol-1 and 4 (MolPort-005-910-183) docking score -8.5 kcal mol-1, are selected as potential in-silico spike receptor inhibitors. Both hits are commercially available and can be further used for in-vitro and in-vivo studies. Findings of this study can facilitate rational drug design against SARS-CoV-2 spike receptor.

A scaffolded approach to unearth potential antibacterial components from epicarp of Malaysian Nephelium lappaceum L

The emergence and spread of antimicrobial resistance have been of serious concern to human health and the management of bacterial infectious diseases. Effective treatment of these diseases requires the development of novel therapeutics, preferably free of side effects. In this regard, natural products are frequently conceived to be potential alternative sources for novel antibacterial compounds. Herein, we have evaluated the antibacterial activity of the epicarp extracts of the Malaysian cultivar of yellow rambutan fruit (Nephelium lappaceum L.) against six pathogens namely, Bacillus subtilis, methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pyogenes, Pseudomonas aeruginosa, Klebsiella pneumoniae and Salmonella enterica. Among a series of solvent extracts, fractions of ethyl acetate and acetone have revealed significant activity towards all tested strains. Chemical profiling of these fractions, via HPLC, LC-MS and GC-MS, has generated a library of potentially bioactive compounds. Downstream virtual screening, pharmacological prediction, and receptor-ligand molecular dynamics simulation have eventually unveiled novel potential antibacterial compounds, which can be extracted for medicinal use. We report compounds like catechin, eplerenone and oritin-4-beta-ol to be computationally inhibiting the ATP-binding domain of the chaperone, DnaK of P. aeruginosa and MRSA. Thus, our work follows the objective to propose new antimicrobials capable of perforating the barrier of resistance posed by both the gram positives and the negatives.

Metabolite Profiling of Malaysian Gracilaria edulis Reveals Eplerenone as Novel Antibacterial Compound for Drug Repurposing Against MDR Bacteria

With a continuous threat of antimicrobial resistance on human health worldwide, efforts for new alternatives are ongoing for the management of bacterial infectious diseases. Natural products of land and sea, being conceived to be having fewer side effects, pose themselves as a welcome relief. In this respect, we have taken a scaffolded approach to unearthing the almost unexplored chemical constituents of Malaysian red seaweed, Gracilaria edulis. Essentially, a preliminary evaluation of the ethyl acetate and acetone solvent extracts, among a series of six such, revealed potential antibacterial activity against six MDR species namely, Klebsiella pneumoniae, Pseudomonas aeruginosa, Salmonella enterica, methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pyogenes, and Bacillus subtilis. Detailed analyses of the inlying chemical constituents, through LC-MS and GC-MS chromatographic separation, revealed a library of metabolic compounds. These were led for further virtual screening against selected key role playing proteins in the virulence of the aforesaid bacteria. To this end, detailed predictive pharmacological analyses added up to reinforce Eplerenone as a natural alternative from the plethora of plausible bioactives. Our work adds the ongoing effort to re-discover and repurpose biochemical compounds to combat the antimicrobial resistance offered by the Gram-positive and the -negative bacterial species.

Phytochemical Moieties From Indian Traditional Medicine for Targeting Dual Hotspots on SARS-CoV-2 Spike Protein: An Integrative in-silico Approach

SARS-CoV-2 infection across the world has led to immense turbulence in the treatment modality, thus demanding a swift drug discovery process. Spike protein of SARS-CoV-2 binds to ACE2 receptor of human to initiate host invasion. Plethora of studies demonstrate the inhibition of Spike-ACE2 interactions to impair infection. The ancient Indian traditional medicine has been of great interest of Virologists worldwide to decipher potential antivirals. Hence, in this study, phytochemicals (1,952 compounds) from eight potential medicinal plants used in Indian traditional medicine were meticulously collated, based on their usage in respiratory disorders, along with immunomodulatory and anti-viral potential from contemporary literature. Further, these compounds were virtually screened against Receptor Binding Domain (RBD) of Spike protein. The potential compounds from each plant were prioritized based on the binding affinity, key hotspot interactions at ACE2 binding region and glycosylation sites. Finally, the potential hits in complex with spike protein were subjected to Molecular Dynamics simulation (450 ns), to infer the stability of complex formation. Among the compounds screened, Tellimagrandin-II (binding energy of −8.2 kcal/mol and binding free energy of −32.08 kcal/mol) from Syzygium aromaticum L. and O-Demethyl-demethoxy-curcumin (binding energy of −8.0 kcal/mol and binding free energy of −12.48 kcal/mol) from Curcuma longa L. were found to be highly potential due to their higher binding affinity and significant binding free energy (MM-PBSA), along with favorable ADMET properties and stable intermolecular interactions with hotspots (including the ASN343 glycosylation site). The proposed hits are highly promising, as these are resultant of stringent in silico checkpoints, traditionally used, and are documented through contemporary literature. Hence, could serve as promising leads for subsequent experimental validations.

Identification of a novel inhibitor of SARS-CoV-2 3CL-PRO through virtual screening and molecular dynamics simulation

Background

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has ravaged lives across the globe since December 2019, and new cases are still on the rise. Peoples’ ongoing sufferings trigger scientists to develop safe and effective remedies to treat this deadly viral disease. While repurposing the existing FDA-approved drugs remains in the front line, exploring drug candidates from synthetic and natural compounds is also a viable alternative. This study employed a comprehensive computational approach to screen inhibitors for SARS-CoV-2 3CL-PRO (also known as the main protease), a prime molecular target to treat coronavirus diseases.

Methods

We performed 100 ns GROMACS molecular dynamics simulations of three high-resolution X-ray crystallographic structures of 3CL-PRO. We extracted frames at 10 ns intervals to mimic conformational diversities of the target protein in biological environments. We then used AutoDock Vina molecular docking to virtual screen the Sigma–Aldrich MyriaScreen Diversity Library II, a rich collection of 10,000 druglike small molecules with diverse chemotypes. Subsequently, we adopted in silico computation of physicochemical properties, pharmacokinetic parameters, and toxicity profiles. Finally, we analyzed hydrogen bonding and other protein-ligand interactions for the short-listed compounds.

Results

Over the 100 ns molecular dynamics simulations of 3CL-PRO’s crystal structures, 6LZE, 6M0K, and 6YB7, showed overall integrity with mean Cα root-mean-square deviation (RMSD) of 1.96 (±0.35) Å, 1.98 (±0.21) Å, and 1.94 (±0.25) Å, respectively. Average root-mean-square fluctuation (RMSF) values were 1.21 ± 0.79 (6LZE), 1.12 ± 0.72 (6M0K), and 1.11 ± 0.60 (6YB7). After two phases of AutoDock Vina virtual screening of the MyriaScreen Diversity Library II, we prepared a list of the top 20 ligands. We selected four promising leads considering predicted oral bioavailability, druglikeness, and toxicity profiles. These compounds also demonstrated favorable protein-ligand interactions. We then employed 50-ns molecular dynamics simulations for the four selected molecules and the reference ligand 11a in the crystallographic structure 6LZE. Analysis of RMSF, RMSD, and hydrogen bonding along the simulation trajectories indicated that S51765 would form a more stable protein-ligand complexe with 3CL-PRO compared to other molecules. Insights into short-range Coulombic and Lennard-Jones potentials also revealed favorable binding of S51765 with 3CL-PRO.

Conclusion

We identified a potential lead for antiviral drug discovery against the SARS-CoV-2 main protease. Our results will aid global efforts to find safe and effective remedies for COVID-19.

Structure-based design of small molecule and peptide inhibitors for selective targeting of ROCK1: an integrative computational approach

Rho-associated, coiled-coil-containing protein kinase (ROCK1) regulates cell contraction, morphology, and motility by phosphorylating its downstream targets. ROCK1 is a proven target for many pathological conditions like cancer, atherosclerosis, glaucoma, neuro-degeneration, etc. Though many kinase inhibitors are available, there is a dearth of studies on repurposing approved drugs and novel peptide inhibitors that could potentially target ROCK1. Hence, in this study, an extensive integration of open-source pipelines was employed to probe the potential inhibitors (ligand/peptide) for targeting ROCK1. To start with, a systematic enrichment analysis was performed to delineate the most optimal ROCK1 crystal structure that can be harnessed for drug design. A comparative analysis of conformational flexibility between monomeric and dimeric forms was also performed to prioritize the optimal assembly for structural studies. Subsequently, Virtual screening of FDA-approved drugs in Drugbank was performed using POAP pipeline. Further, the top hits were probed for binding affinity, crucial interaction fingerprints, and complex stability during MD simulation. In parallel, a combinatorial tetrapeptide library was also virtually screened against ROCK1 using the PepVis pipeline. Following which, all these shortlisted inhibitors (compounds/peptides) were subjected to Kinomerun analysis to infer other potential kinase targets. Finally, Polydatin and conivaptan were prioritized as the most potential repurposable inhibitors, and WWWF, WWVW as potential inhibitory peptides for targeting ROCK1. The prioritized inhibitors are highly promising for use in therapeutics, as these are resultants of the multilevel stringent filtration process. The computational strategies implemented in this study could potentially serve as a scaffold towards selective inhibitor design for other kinases.Communicated by Ramaswamy H. Sarma.

Therapeutic Potentials of Colocasia affinis Leaf Extract for the Alleviation of Streptozotocin-Induced Diabetes and Diabetic Complications: In vivo and in silico-Based Studies

INTRODUCTION

Hypoglycemia in diabetes mellitus (DM) correlates with hepatic impairment, nephropathy, lipid abnormalities, and oxidative stress and subsequently complicates the disease pathogenesis. Medicinal plants have been used for the management of diabetes since ancient times. In this study, we explored the potentials of Colocasia affinis (CA), a plant known to possess anti-allergic and anti-inflammatory activities, as a remedy for diabetes and related complications.

METHODS

We induced diabetes in rats using a single intraperitoneal dose (65 mg/kg) of streptozotocin (STZ). We next treated the rats with an ethanolic extract of leaves of CA to reveal its antidiabetic and organ-protective potentials. Biomarkers of diabetes, inflammation, and oxidative stress were measured using biochemical and histopathological analysis. We also performed molecular docking for three major phytochemicals (kaempferol, myricetin, and rosmarinic acid) of CA.

RESULTS

Oral administration of the CA leaves extract at 250 mg/kg and 500 mg/kg doses decreased blood glucose level significantly (p<0.05) in STZ-induced diabetic rats. The extract also considerably attenuated plasma HbA1c levels and normalized blood lipids, glycogen, alanine aminotransferase (ALT), and aspartate aminotransferase (AST). Additionally, treatment with the extract improved kidney complications by decreasing serum creatinine and blood urea nitrogen (BUN) levels. Furthermore, CA leaves extract normalized nitric oxide (NO) and advance oxidative protein products (AOPP) in diabetic rats. The extract also showed significant improvement of the antioxidant enzymes glutathione dismutase (GSH) and superoxide dismutase (SOD) at a dose of 500 mg/kg. Besides, histological investigation demonstrated attenuation of inflammation of the vital organs, including the liver and the kidney. In silico studies revealed that three major phytochemicals (kaempferol, myricetin, and rosmarinic acid) of the ethanolic extract of leaves of CA can inhibit several molecular targets of diabetes and inflammation.

CONCLUSION

Collectively, our results demonstrated the therapeutic potentials of CA for the mitigation of diabetes and diabetic complications.

Structural based study to identify new potential inhibitors for dual specificity tyrosine-phosphorylation- regulated kinase

Background and Objectives The Dual-specificity tyrosine-phosphorylation regulated kinase-1A (DYRK1A) a serine/threonine kinase that has freshly gained recognition as an essential drug target due to the discovery of its involvement in pathological diseases. The development of new potent inhibitors of DYRK1A would contribute to clarify the molecular mechanisms of associated diseases. It would administer a new lead compound for molecular-targeted protein, which was the primary focus of our study. Methods The library of in-house synthesized pyrrolone-fused benzosuberene (PBS) compounds was docked with DYRK1A receptor. Further, molecular mechanics-Poisson Boltzmann surface area (MM-PBSA) estimations were conducted to confirm our docking outcomes and compared the stability of chosen complexes with the 2C3 (standard molecule) complex. Results This study reports Ligand15, Ligand14, and Ligand11 as potent inhibitors which showed higher ligand efficiency, binding affinity, lipophilic ligand efficiency, and favorable torsion values as compared to 2C3. Conclusion The stated methodologies revealed a unique mechanism of active site binding. The binding interactions within the active site showed that the chosen molecules had notable interactions than the standard molecule, which led to the generation of potential compounds to inhibit DYRK1A.

Structure based design of inhibitory peptides targeting ornithine decarboxylase dimeric interface and in vitro validation in human retinoblastoma Y79 cells

Polyamine synthesis in human cells is initiated by catalytic action of Ornithine decarboxylase (ODC) on Ornithine. Elevated levels of polyamines are manifested proliferating cancer cells and are found to promote tumour cell adhesion. Di-flouro methyl orninthine is a known inhibitor of ODC, however its usage is limited due its low affinity quick clearance and incompetent cellular uptake, thus posing a need for potential inhibitors. Currently, peptides are substituting drugs, as these are highly selective, specific and potent. Hence, in this study, the interacting interfaces of native homodimeric form of ODC and its heterodimer with Antizyme were probed to design inhibitory peptides targeting ODC. The designed peptides were validated for structural fitness by extensive molecular dynamics simulations and Circular dichroism studies. Finally, these peptides were validated in Y79 retinoblastoma cells for impact on ODC activity, cytotoxicity cell cycle and cell adhesion. On collective analysis, Peptide3 (Pep 3) and Peptide4 (Pep 4) were found to be potentially targeting ODC, as these peptides showed significant decrease in intracellular polyamine levels, cell adhesion and cell cycle perturbation in Y79 cells. Thus, Pep 3 and Pep 4 shall be favourably considered as therapeutic agents for targeting ODC mediated proliferation in retinoblastoma.Communicated by Ramaswamy H. Sarma.