Identification of natural compounds as potent inhibitors of SARS-CoV-2 main protease using combined docking and molecular dynamics simulations

Carvacrol potentiates immunity and sorafenib anti-cancer efficacy by targeting HIF-1α/STAT3/ FGL1 pathway: in silico and in vivo study

Hypoxia and tumor cell immunological escape greatly hinder the hepatocellular carcinoma (HCC) treatment efficiency. This study is designed to investigate the capability of carvacrol (CVR) to enhance sorafenib (SOR) anti-cancer efficacy and modulate anti-HCC immunity. CVR target and biological activities were predicted using Swiss Target Prediction website and PASS web server. UALCAN and LinkedOmics databases were used to examine hypoxia-inducible factor 1-alpha (HIF-1α) expression and the relationship between studied genes and tumor clinical features. Kaplan-Meier plotter (KM plotter) and TISIDB databases were used to illustrate correlation of HIF-1α with HCC prognosis and immune infiltration. The binding affinities of CVR to p300, KAT2B, CREBBP, and Hsp90 were demonstrated by molecular docking. In vivo analysis was performed in male Sprague-Dawley rats. The STAT3, JAK2, and fibrinogen-like protein 1 (FGL1) expressions were assessed by qRT-PCR. FGL1 was determined by ELISA. CD8+ T cell number was counted by flow cytometry. HIF-1α was determined by immunohistochemistry. CVR showed an HIF-1α inhibitory potential, which is highly expressed in HCC tissues. Also, elevated HIF-1α expression has been found to be correlated with clinicopathological characteristics, poor survival in HCC patients, and tumor immune cell infiltration. CVR/SOR enhanced liver functions and decreased AFP level. CVR/SOR hindered HCC progression by downregulating STAT3, JAK2, and FGL1. CVR/SOR induced tumor immunity via increasing CD8+ T cells. CVR/SOR is a powerful combination for tumor repression and enhancing SOR efficiency in HCC by modulating FGL1. Moreover, CVR/SOR might exert the aforementioned effects through HIF-1α/STAT3/FGL1 pathway.

Subtractive genomics and drug repurposing strategies for targeting Streptococcus pneumoniae: insights from molecular docking and dynamics simulations

Introduction

Streptococcus pneumoniae is a Gram-positive bacterium responsible for severe infections such as meningitis and pneumonia. The increasing prevalence of antibiotic resistance necessitates the identification of new therapeutic targets. This study aimed to discover potential drug targets against S. pneumoniae using an in silico subtractive genomics approach.

Methods

The S. pneumoniae genome was compared to the human genome to identify non-homologous sequences using CD-HIT and BLASTp. Essential genes were identified using the Database of Essential Genes (DEG), with consideration for human gut microflora. Protein-protein interaction analyses were conducted to identify key hub genes, and gene ontology (GO) studies were performed to explore associated pathways. Due to the lack of crystal structure data, a potential target was modeled in silico and subjected to structure-based virtual screening.

Results

Approximately 2,000 of the 2,027 proteins from the S. pneumoniae genome were identified as non-homologous to humans. The DEG identified 48 essential genes, which was reduced to 21 after considering human gut microflora. Key hub genes included gpi, fba, rpoD, and trpS, associated with 20 pathways. Virtual screening of 2,509 FDA-approved compounds identified Bromfenac as a leading candidate, exhibiting a binding energy of -26.335 ± 29.105 kJ/mol.

Discussion

Bromfenac, particularly when conjugated with AuAgCu2O nanoparticles, has demonstrated antibacterial and anti-inflammatory properties against Staphylococcus aureus. This suggests that Bromfenac could be repurposed as a potential therapeutic agent against S. pneumoniae, pending further experimental validation. The approach highlights the potential for drug repurposing by targeting proteins essential in pathogens but absent in the host.

Elucidating the therapeutic potential of indazole derivative bindarit against K-ras receptor: An in-silico analysis using molecular dynamics exploration

Ras gene is frequently mutated in cancer. Among different subtypes of Ras gene, K-Ras mutation occurs in nearly 30 % of human cancers. K-Ras mutation, specifically K-Ras (G12D) mutation is prevalent in cancers like lung, colon and pancreatic cancer. During cancer occurrence, mutant Ras remain in activated form (GTP bound state) for cancer cell proliferation. In the quest for a potential K-Ras inhibitor, nitrogen-containing indazole derivatives can show promise as inhibitors, as they have numerous therapeutic properties like anti-inflammatory, anti-viral and anti-tumor. Furthermore, among various indazole derivatives, "Bindarit" is an important therapeutic compound which could have potential inhibitory action against K-Ras due to its structural resemblance with reference compound "Benzimidazole". So, the current study is an attempt to find out the inhibitory effect of Bindarit against K-Ras activation by binding to a pocket which is adjacent to the switch I/II regions of the K-Ras receptor. AutoDock tool was used to investigate the binding affinity of protein ligand interaction and GROMACS package was utilised to assess their interactions in a dynamic setting. Bindarit shows better binding affinity than reference with binding energy of -7.3 kcal/mol. Upon ligand binding conformational changes take place, which could lead to the loss of GTPase activity. Consequently, further downstream signalling of the K-Ras pathway would be blocked and this could lead to the inhibition of K-Ras dependent cancer cell proliferation. However, further validation of present study can be done through experimental assay such as cytotoxic and protein expression analysis.

Unlocking the potential of in silico approach in designing antibodies against SARS-CoV-2

Antibodies are naturally produced safeguarding proteins that the immune system generates to fight against invasive invaders. For centuries, they have been produced artificially and utilized to eradicate various infectious diseases. Given the ongoing threat posed by COVID-19 pandemics worldwide, antibodies have become one of the most promising treatments to prevent infection and save millions of lives. Currently, in silico techniques provide an innovative approach for developing antibodies, which significantly impacts the formulation of antibodies. These techniques develop antibodies with great specificity and potency against diseases such as SARS-CoV-2 by using computational tools and algorithms. Conventional methods for designing and developing antibodies are frequently costly and time-consuming. However, in silico approach offers a contemporary, effective, and economical paradigm for creating next-generation antibodies, especially in accordance with recent developments in bioinformatics. By utilizing multiple antibody databases and high-throughput approaches, a unique antibody construct can be designed in silico, facilitating accurate, reliable, and secure antibody development for human use. Compared to their traditionally developed equivalents, a large number of in silico-designed antibodies have advanced swiftly to clinical trials and became accessible sooner. This article helps researchers develop SARS-CoV-2 antibodies more quickly and affordably by giving them access to current information on computational approaches for antibody creation.

Decoding SARS-CoV-2 Inhibition: Insights From Molecular Dynamics Simulation of Condensed Amino Thiourea Scaffold Small Molecules

The main protease (Mpro) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) plays a crucial role in viral replication. In this study, the binding modes and inhibitory mechanisms of eight condensed amino thiourea scaffold inhibitors of Mpro in proteins were investigated using a combination of molecular docking, molecular dynamics simulations, and MM/PBSA binding free energy calculations. The results indicated that the para-hydroxyl group on the benzene ring at the head of the inhibitor has a decisive influence on the initial docking pose and binding free energy strength of the inhibitor. Additionally, the position and length of the hydrophobic side chain on the tail six-membered ring significantly impacted the final binding pose of the inhibitor. The presence of a long hydrophobic side chain in the ortho position of this ring, through its interaction with the P4 hydrophobic pocket, led to an opposite binding mode in the protein compared with when it was present with or without the para-side chain. Different lengths of para-substituted side chains affected the positioning of the inhibitors in the enzyme. These different binding modes led to variations in the binding free energy between the inhibitor and the protein, which in turn gave rise to differences in inhibitory capability.

Structure-guided identification of mitogen-activated protein kinase-1 inhibitors towards anticancer therapeutics

Mitogen-activated protein kinase 1 (MAPK1) is a serine/threonine kinase that plays a crucial role in the MAP kinase signaling transduction pathway. This pathway plays a crucial role in various cellular processes, including cell proliferation, differentiation, adhesion, migration, and survival. Besides, many chemotherapeutic drugs targeting the MAPK pathway are used in clinical practice, and novel inhibitors of MAPK1 with improved specificity and efficacy are required. Hence, targeting MAPK1 can be crucial to control metastasis in cancer therapeutics. In this study, we utilized a structure-guided virtual screening approach to screen a library of thousands of natural compounds from the ZINC database. The Lipinski rule of five (RO5) was used as a criterion for the primary selection of natural compounds. The screened compounds were prioritized based on their binding affinity, docking scores, and specificity towards the kinase domain of MAPK1 during the molecular docking process. Subsequently, the selected hits underwent rigorous screening that included the identification of potential pan-assay interference compounds (PAINS), ADMET evaluation, and prediction of pharmacological activities using PASS analysis. Afterwards, we performed a comprehensive interaction analysis to explore the binding prototypes of the screened molecules with the key residues within the MAPK1 kinase domain. Finally, selected molecules underwent extensive all-atom molecular dynamics (MD) simulations for a time duration of 200 nanoseconds. The study pinpointed three natural compounds with ZINC database IDs ZINC0209285, ZINC02130647, and ZINC02133691 as potential inhibitors of MAPK1. The study highlights that these compounds could be explored further in preclinical and clinical investigations to develop anticancer therapeutics.

Identification of Novel Progesterone Receptor (PR) Inhibitors (Homo sapiens) from Metabolites of Biotransformation Fungal: A Bioinformatics Approach

Background/Objectives: Steroids have demonstrated selective cytotoxic properties against tumor cells. The pro-gesterone receptor (PR) plays a vital role in the proliferation, cell differentiation, and maintenance of female reproductive tissue, and its malfunction can lead to breast cancer. The use of the biocatalytic method by filamentous fungi has sparked interest in the obtained of steroids due to the advantages of the process. Methods: Pharmacokinetic and toxicological properties (rat and mouse), molecular docking simulation studies, and prediction of the spectrum of biological activity were performed to select molecules with the potential for PR inhibition, from 155 biotransformed products of the progesterone. Subsequently, the chemical structures were subjected to an evaluation of their pharmacokinetic and toxicological properties and, with the application of ADMET filters. Results: Androstenedione, 17α-hydroxyprogesterone, and dihydrotestosterone, obtained by the process of biotransformation of PR by different filamentous fungi, showed good pharmacokinetic profiles and low toxicity compared to the control groups. The in-silico data associated with molecular docking studies revealed the best binding affinity and similarity in the interactions of these molecules against the human progesterone receptor target. Thus, the results of biological activity spectrum prediction highlight the great potential to investigate the role of molecular descriptors in the attribution of anti-cancer activities. Conclusions: The biocatalytic process, by filamentous fungi, can provide important molecules as a product of progesterone biotransformation, such as androstenedione, 17α-hydroxyprogesterone, and dihydrotestosterone. In this study we showed that these molecules have good pharmacokinetic profiles and low toxicity for antineoplastic activity (breast cancer).

Investigation of bioremediation for glyphosate and its metabolite in soil using arbuscular mycorrhizal GmHsp60 protein: a molecular docking and molecular dynamics simulations approach

The widespread use of glyphosate and the high dependence of the agricultural industry on this herbicide cause environmental pollution and pose a threat to living organisms. One of the appropriate solutions in sustainable agriculture to deal with pollution caused by glyphosate and its metabolites is creating a symbiotic relationship between plants and mycorrhizal fungi. Glomalin-related soil protein is a key protein for the bioremediation of glyphosate and its metabolite aminomethyl phosphonic acid in soil. This study uses homology modeling, molecular docking, and molecular dynamic simulation approaches to investigate the binding mechanism of glomalin-related soil protein from arbuscular mycorrhiza (GmHsp60) with glyphosate and its metabolite and the role of soil protein in the removal and sequestering of common agricultural soil pollutants. GmHsp60 protein structure was predicted by homology modeling, and the quality of the generated model was assessed. Then, the interaction between glyphosate and aminomethyl phosphonic acid and the modeled GmHsp60 protein was explored by molecular docking. Based on docking results, GmHsp60 has an efficient role in the bioremediation of glyphosate and aminomethyl phosphonic acid (-6.03 and -5.34 kcal/mol). Glyphosate forms three hydrogen bonds with Lys258, Gly262, and Glu58 of GmHsp60, and aminomethyl phosphonic acid forms three hydrogen bonds with Lys258, Gly261, and Gly262 of GmHsp60. In addition, the glyphosate's and its metabolite's stability was confirmed by molecular docking simulations and binding free energy calculations using MM/PBSA analysis. This study provides a molecular-level understanding of GmHsp60 expression and function for glyphosate bioremediation.

Computational exploration of compounds in Xylocarpus granatum as a potential inhibitor of Plasmodium berghei using docking, molecular dynamics, and DFT studies

Malaria remains a global health concern, with the emergence of resistance to the antimalarial drug atovaquone through cytochrome b (cyt b) being well-documented. This study was prompted by the presence of this mutation in cyt b to enable new drug candidates capable of overcoming drug resistance. Our objective was to identify potential drug candidates from compounds of Xylocarpus granatum by computationally assessing their interactions with Plasmodium berghei cyt b. Using computational methods, we modeled cyt b (GenBank: AF146076.1), identified the binding cavity, and analyzed the Ramachandran plot against cyt b. Additionally, we conducted drug-likeness and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies, along with density functional theory (DFT) analysis of the compounds. Molecular docking and molecular dynamics simulation (MDS) were used to evaluate the binding energy and stability of the cyt b-ligand complex. Notably, our investigation highlighted kaempferol as a promising compound due to its high binding energy of 7.67 kcal/mol among all X. granatum compounds, coupled with favorable pharmacological properties (ADMET) and antiprotozoal properties at Pa 0.345 > Pi 0.009 (PASS value). DFT analysis showed that kaempferol has an energy gap of 4.514 eV. MDS indicated that all tested ligands caused changes in bonding and affected the structural conformation of cyt b, as observed before MDS (0 ns) and after MDS (100 ns). The most notable differences were observed in the types of hydrogen bonds between 0 and 100 ns. Nevertheles, MDS results from a 100 ns simulation revealed consistent behavior for kaempferol across various parameters including root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), molecular mechanics-Poisson Boltzmann surface area (MM-PBSA), and hydrogen bonds. The cyt b-kaempferol complex demonstrated favorable energy stability, as supported by the internal energy distribution values observed in principal component analysis (PCA), which closely resembled those of the atovaquone control. Additionally, trajectory stability analysis indicated structural stability, with a cumulative eigenvalue of 24.7 %. Dynamic cross-correlation matrix (DCCM) analysis revealed a positive correlation among catalytic cytochrome residues within the amino acid residues range 119-268. The results of our research indicate that the structure of kaempferol holds promise as a potential candidate against Plasmodium.

Integrative Network Pharmacology, Molecular Docking, and Dynamics Simulations Reveal the Mechanisms of Cinnamomum tamala in Diabetic Nephropathy Treatment: An In Silico Study

Diabetic nephropathy (DN) is a serious diabetes-related complication leading to kidney damage. Cinnamomum tamala (CT), traditionally used in managing diabetes and kidney disorders, has shown potential in treating DN, although its active compounds and mechanisms are not fully understood. This study aims to identify CT's bioactive compounds and explore their therapeutic mechanisms in DN. Active compounds in CT were identified using the Indian Medicinal Plants, Phytochemicals and Therapeutics database, and their potential targets were predicted with PharmMapper. DN-related targets were sourced from GeneCards, and therapeutic targets were identified by intersecting the compound-target and disease-target data. Bioinformatics analyses, including the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment studies, were performed on these targets. A protein-protein interaction network was constructed using STRING and Cytoscape. Molecular docking and dynamics simulations validated the most promising compound-target interactions. Six active compounds in CT were identified, along with 347 potential therapeutic targets, of which 70 were DN-relevant. Key targets like MMP9, EGFR, and AKT1 were highlighted, and the PPAR and PI3K-AKT signaling pathways were identified as the primary mechanisms through which CT may treat DN. CT shows promise in treating DN by modulating key pathways related to cellular development, inflammation, and metabolism.

Identification of potential Escherichia coli DNA gyrase B inhibitors targeting antibacterial therapy: an integrated docking and molecular dynamics simulation study

The alarming rise in the rate of antibiotic resistance is a matter of significant concern. DNA gyrase B (GyrB), a critical bacterial enzyme involved in DNA replication, transcription, and recombination, has emerged as a promising target for antibacterial agents. Inhibition of GyrB disrupts bacterial DNA replication, leading to cell death, making it an attractive candidate for antibiotic development. Although several classes of antibiotics targeting GyrB are currently in clinical use, the emergence of antibiotic resistance necessitates the exploration of novel inhibitors. In this study, we aimed to identify potential Escherichia coli GyrB inhibitors from a database of phytoconstituents sourced from Indian medicinal plants. Utilizing virtual screening, we performed a rigorous search to identify compounds with the most promising inhibitory properties against GyrB. Two compounds, namely Zizogenin and Cucurbitacin S, were identified based on their favorable drug likeliness and pharmacokinetic profiles. Employing advanced computational techniques, we analyzed the binding interactions of Zizogenin and Cucurbitacin S with the ATP-binding site of GyrB through molecular docking simulations. Both compounds exhibited robust binding interactions, evidenced by their high docking energy scores. To assess the stability of these interactions, we conducted extensive 100 ns molecular dynamics (MD) simulations, which confirmed the stability of Zizogenin and Cucurbitacin S when bound to GyrB. In conclusion, our study highlights Zizogenin and Cucurbitacin S as promising candidates for potential antibacterial agents targeting GyrB. Experimental validation of these compounds is warranted to further explore their efficacy and potential as novel antibiotics to combat antibiotic-resistant bacteria.Communicated by Ramaswamy H. Sarma.

Forecasting the Pharmacological Mechanisms of Plumbago zeylanica and Solanum xanthocarpum in Diabetic Retinopathy Treatment: A Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation Study

(1) Background: Diabetic retinopathy (DR) is a major complication of diabetes, marked by abnormal angiogenesis, microaneurysms, and retinal hemorrhages. Traditional Ayurvedic medicine advocates multi-target strategies for DR management. However, the mechanisms by which Solanum xanthocarpum (SX) and Plumbago zeylanica (PZ) exert therapeutic effects are not well understood; (2) Methods: To investigate these mechanisms, we employed network pharmacology and molecular docking techniques. Phytochemicals from SX and PZ were identified using the IMPPAT database and Swiss Target Prediction tool. DR-related protein targets were sourced from the GeneCards database, and common targets were identified through Venn diagram analysis. STRING and Cytoscape were used to construct and analyze protein-protein interaction networks. Pathway enrichment was performed with Gene Ontology and KEGG databases; (3) Results: We identified 28 active phytoconstituents, targeting proteins such as EGFR, SRC, STAT3, AKT1, and HSP90AA1. Molecular docking and dynamics simulations confirmed the strong binding affinities of these compounds to their targets; (4) Conclusions: The study highlights the multi-target activity of SX and PZ, particularly in pathways related to EGFR tyrosine kinase inhibitor resistance and PI3K-AKT signaling. These findings provide valuable insights into their therapeutic potential for DR, suggesting the effective modulation of key molecular pathways involved in the disease.

Identification of novel c-Kit inhibitors from natural sources using virtual screening and molecular dynamics simulations

The Mast/Stem cell growth factor receptor Kit (c-Kit), a Proto-oncogene c-Kit, is a tyrosine-protein kinase involved in cell differentiation, proliferation, migration, and survival. Its role in developing certain cancers, particularly gastrointestinal stromal tumors (GISTs) and acute myeloid leukemia (AML), makes it an attractive therapeutic target. Several small molecule inhibitors targeting c-Kit have been developed and approved for clinical use. Recent studies have focused on identifying and optimizing natural compounds as c-Kit inhibitors employing virtual screening. Still, drug resistance, off-target side effects, and variability in patient response remain significant challenges. From this perspective, phytochemicals could be an important resource for discovering novel c-Kit inhibitors with less toxicity, improved efficacy, and high specificity. This study aimed to uncover possible c-Kit inhibitors by utilizing a structure-based virtual screening of active phytoconstituents from Indian medicinal plants. Through the screening stages, two promising candidates, Anilinonaphthalene and Licoflavonol, were chosen based on their drug-like features and ability to bind to c-Kit. These chosen candidates were subjected to all-atom molecular dynamics (MD) simulations to evaluate their stability and interaction with c-Kit. The selected compounds Anilinonaphthalene from Daucus carota and Licoflavonol from Glycyrrhiza glabra showed their potential to act as selective binding partners of c-Kit. Our results suggest that the identified phytoconstituents could serve as a starting point to develop novel c-Kit inhibitors for developing new and effective therapies against multiple cancers, including GISTs and AML. The use of virtual screening and MD simulations provides a rational approach to discovering potential drug candidates from natural sources.Communicated by Ramaswamy H. Sarma.

Identification of potential inhibitors of tropomyosin receptor kinase B targeting CNS-related disorders and cancers

Tropomyosin receptor kinase B (TrkB), also known as neurotrophic tyrosine kinase receptor type 2 (NTRK2), is a protein that belongs to the family of receptor tyrosine kinases (RTKs). NTRK2 plays a crucial role in regulating the development and maturation of the central nervous system (CNS) and peripheral nervous system (PNS). Elevated TrkB expression levels observed in different pathological conditions make it a potential target for therapeutic interventions against neurological disorders, including depression, anxiety, Alzheimer's disease, Parkinson's disease, and certain types of cancer. Targeting TrkB using small molecule inhibitors is a promising strategy for the treatment of a variety of neurological disorders. In this research, a systematic virtual screening was carried out on phytoconstituents found in the IMPPAT library to identify compounds potentially inhibiting TrkB. The retrieved compounds from the IMPPAT library were first filtered using Lipinski's rule of five. The compounds were then sorted based on their docking score and ligand efficiency. In addition, PAINS, ADMET, and PASS evaluations were carried out for selecting drug-like compounds. Finally, in interaction analysis, we found two phytoconstituents, Wedelolactone and 3,8-dihydroxy-1-methylanthraquinone-2-carboxylic acid (DMCA), which possessed considerable docking scores and specificity on the TrkB ATP-binding pocket. The selected compounds were further assessed employing molecular dynamics (MD) simulations and essential dynamics. The results revealed that the elucidated compounds bind well with the TrkB binding pocket and lead to fewer conformations fluctuations. This study highlighted using phytoconstituents, Wedelolactone and DMCA as starting leads in developing novel TrkB inhibitors.Communicated by Ramaswamy H. Sarma.

Exploring the potential of phytochemicals as inhibitors of 3'-phosphoadenosine 5'-phosphosulfate synthase 1 targeting cancer therapy

3'-phosphoadenosine 5'-phosphosulfate synthase 1 (PAPSS1) is an enzyme that critically synthesises the biologically active form of sulfate (PAPS) for all sulfation reactions. The discovery of PAPSS1 as a possible drug target for cancer therapy, specifically in non-small cell lung cancer, has prompted us to investigate potential small-molecule inhibitors of PAPSS1. Here, a structure-based virtual screening method was used to search for phytochemicals in the IMPPAT database to find potential inhibitors of PAPSS1. The primary hits were selected based on their physicochemical, ADMET, and drug-like properties. Then, the binding affinities were calculated and analyzed the interactions to identify safer and more effective hits. The research identified two phytochemicals, Guggulsterone and Corylin, that exhibited significant affinity and specific interaction with the ATP-binding pocket of PAPSS1. Structural observations made by molecular docking were further accompanied by molecular dynamics (MD) simulations and principal component analysis (PCA) to examine the conformational changes and stability of PAPSS1 with the elucidated compounds Guggulsterone and Corylin. MD simulation results suggested that the binding of Guggulsterone and Corylin stabilizes the PAPSS1 structure, leading to fewer conformational changes. This implies that these compounds may be useful in developing PAPSS1 inhibitors for the therapeutic development against non-small cell lung cancer (NSCLC). This study highlights the potential of phytochemicals as PAPSS1 inhibitors and the utility of computational approaches in drug discovery.Communicated by Ramaswamy H. Sarma.

Characterization of Plant-Derived Natural Inhibitors of Dipeptidyl Peptidase-4 as Potential Antidiabetic Agents: A Computational Study

Diabetes, characterized by elevated blood sugar levels, poses significant health and economic risks, correlating with complications like cardiovascular disease, kidney failure, and blindness. Dipeptidyl peptidase-4 (DPP-4), also referred to as T-cell activation antigen CD26 (EC 3.4.14.5.), plays a crucial role in glucose metabolism and immune function. Inhibiting DPP-4 was anticipated as a potential new therapy for diabetes. Therefore, identification of plant-based natural inhibitors of DPP-4 would help in eradicating diabetes worldwide. Here, for the identification of the potential natural inhibitors of DPP-4, we developed a phytochemicals library consisting of over 6000 phytochemicals detected in 81 medicinal plants that exhibited anti-diabetic potency. The library has been docked against the target proteins, where isorhamnetin, Benzyl 5-Amino-5-deoxy-2,3-O-isopropyl-alpha-D-mannofuranoside (DTXSID90724586), and 5-Oxo-7-[4-(trifluoromethyl) phenyl]-4H,6H,7H-[1,2]thiazolo[4,5-b]pyridine 3-carboxylic acid (CHEMBL3446108) showed binding affinities of -8.5, -8.3, and -8.3 kcal/mol, respectively. These compounds exhibiting strong interactions with DPP-4 active sites (Glu205, Glu206, Tyr547, Trp629, Ser630, Tyr662, His740) were identified. ADME/T and bioactivity predictions affirmed their pharmacological safety. Density functional theory calculations assessed stability and reactivity, while molecular dynamics simulations demonstrated persistent stability. Analyzing parameters like RMSD, RG, RMSF, SASA, H-bonds, MM-PBSA, and FEL confirmed stable protein-ligand compound formation. Principal component analysis provided structural variation insights. Our findings suggest that those compounds might be possible candidates for developing novel inhibitors targeting DPP-4 for treating diabetes.

An integrated docking and molecular dynamics simulation approach to discover potential inhibitors of activin receptor-like kinase 1

Activin receptor-like kinase 1 (ALK1) is a transmembrane receptor involved in crucial signaling pathways associated with angiogenesis and vascular development. Inhibition of ALK1 signaling has emerged as a promising therapeutic strategy for various angiogenesis-related diseases, including cancer and hereditary hemorrhagic telangiectasia. This study aimed to investigate the potential of phytoconstituents as inhibitors of ALK1 using a combined approach of virtual screening and molecular dynamics (MDs) simulations. Phytoconstituents from the IMPPAT 2.0 database underwent virtual screening to identify potential inhibitors of ALK1. The compounds were initially filtered based on physicochemical parameters, following Lipinski's rules and the PAINS filter. Subsequently, compounds demonstrating high binding affinities in docking analysis were further analyzed. Additional assessments, including ADMET, PAINS, and PASS evaluations, were conducted to identify more potent hits. Through interaction analysis, a phytoconstituent, Candidine, exhibited appreciable affinity and specific interactions with the ALK1 active site. To validate the results, MD simulations and principal components analysis were performed. The MD simulations demonstrated that Candidine stabilized the ALK1 structure and reduced conformational fluctuations. In conclusion, Candidine shows promising potential as binding partners of ALK1. These findings provide a foundation for further exploration and development of Candidine as a lead molecule for therapeutic interventions targeting ALK1-associated diseases.

Probing Baicalin as potential inhibitor of Aurora kinase B: A step towards lung cancer therapy

Cell cycle regulators play pivotal roles as their dysregulation, leads to atypical proliferation and intrinsic genomic instability in cancer cells. Abnormal expression and functioning of Aurora kinase B (AURKB) are associated with cancer pathogenesis and thus exploited as a potential therapeutic target for the development of anti-cancer therapeutics. To identify effective AURKB inhibitors, a series of polyphenols was investigated to check their potential to inhibit recombinant AURKB. Their binding affinities were experimentally validated through fluorescence binding studies. Enzyme inhibition assay revealed that Mangiferin and Baicalin significantly inhibited AURKB activity with an IC50 values of 20.0 μM and 31.1 μM, respectively. To get atomistic insights into the binding mechanism, molecular docking and MD simulations of 100 ns were performed. Both compounds formed many non-covalent interactions with the residues of the active site pocket of AURKB. In addition, minimal conformational changes in the structure and formation of stable AURKB-ligand complex were observed during MD simulation analysis. Finally, cell-based studies suggested that Baicalin exhibited in-vitro cytotoxicity and anti-proliferative effects on lung cancer cell lines. Conclusively, Baicalin may be considered a promising therapeutic molecule against AURKB, adding an additional novel lead to the anti-cancer repertoire.

Identification of mitogen-activated protein kinase 7 inhibitors from natural products: Combined virtual screening and dynamic simulation studies

Mitogen-activated protein kinase 7 (MAPK7) is a serine/threonine protein kinase that belongs to the MAPK family and plays a vital role in various cellular processes such as cell proliferation, differentiation, gene transcription, apoptosis, metabolism, and cell survival. The elevated expression of MAPK7 has been associated with the onset and progression of multiple aggressive tumors in humans, underscoring the potential of targeting MAPK7 pathways in therapeutic research. This pursuit holds promise for the advancement of anticancer drug development by developing potential MAPK7 inhibitors. To look for potential MAPK7 inhibitors, we exploited structure-based virtual screening of natural products from the ZINC database. First, the Lipinski rule of five criteria was used to filter a large library of ~90,000 natural compounds, followed by ADMET and pan-assay interference compounds (PAINS) filters. Then, top hits were chosen based on their strong binding affinity as determined by molecular docking. Further, interaction analysis was performed to find effective and specific compounds that can precisely bind to the binding pocket of MAPK7. Consequently, two compounds, ZINC12296700 and ZINC02123081, exhibited significant binding affinity and demonstrated excellent drug-like properties. All-atom molecular dynamics simulations for 200 ns confirmed the stability of MAPK7-ZINC12296700 and MAPK7-ZINC02123081 docked complexes. According to the molecular mechanics Poisson-Boltzmann surface area investigation, the binding affinities of both complexes were considerable. Overall, the result suggests that ZINC12296700 and ZINC02123081 might be used as promising leads to develop novel MAPK7 inhibitors. Since these compounds would interfere with the kinase activity of MAPK7, therefore, may be implemented to control cell growth and proliferation in cancer after required validations.

The Power of Molecular Dynamics Simulations and Their Applications to Discover Cysteine Protease Inhibitors

A large family of enzymes with the function of hydrolyzing peptide bonds, called peptidases or cysteine proteases (CPs), are divided into three categories according to the peptide chain involved. CPs catalyze the hydrolysis of amide, ester, thiol ester, and thioester peptide bonds. They can be divided into several groups, such as papain-like (CA), viral chymotrypsin-like CPs (CB), papainlike endopeptidases of RNA viruses (CC), legumain-type caspases (CD), and showing active residues of His, Glu/Asp, Gln, Cys (CE). The catalytic mechanism of CPs is the essential cysteine residue present in the active site. These mechanisms are often studied through computational methods that provide new information about the catalytic mechanism and identify inhibitors. The role of computational methods during drug design and development stages is increasing. Methods in Computer-Aided Drug Design (CADD) accelerate the discovery process, increase the chances of selecting more promising molecules for experimental studies, and can identify critical mechanisms involved in the pathophysiology and molecular pathways of action. Molecular dynamics (MD) simulations are essential in any drug discovery program due to their high capacity for simulating a physiological environment capable of unveiling significant inhibition mechanisms of new compounds against target proteins, especially CPs. Here, a brief approach will be shown on MD simulations and how the studies were applied to identify inhibitors or critical information against cysteine protease from several microorganisms, such as Trypanosoma cruzi (cruzain), Trypanosoma brucei (rhodesain), Plasmodium spp. (falcipain), and SARS-CoV-2 (Mpro). We hope the readers will gain new insights and use our study as a guide for potential compound identifications using MD simulations.

Waste to Medicine: Evidence from Computational Studies on the Modulatory Role of Corn Silk on the Therapeutic Targets Implicated in Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and/or defective insulin production in the human body. Although the antidiabetic action of corn silk (CS) is well-established, the understanding of the mechanism of action (MoA) behind this potential is lacking. Hence, this study aimed to elucidate the MoA in different samples (raw and three extracts: aqueous, hydro-ethanolic, and ethanolic) as a therapeutic agent for the management of T2DM using metabolomic profiling and computational techniques. Ultra-performance liquid chromatography-mass spectrometry (UP-LCMS), in silico techniques, and density functional theory were used for compound identification and to predict the MoA. A total of 110 out of the 128 identified secondary metabolites passed the Lipinski's rule of five. The Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis revealed the cAMP pathway as the hub signaling pathway, in which ADORA1, HCAR2, and GABBR1 were identified as the key target genes implicated in the pathway. Since gallicynoic acid (-48.74 kcal/mol), dodecanedioc acid (-34.53 kcal/mol), and tetradecanedioc acid (-36.80 kcal/mol) interacted well with ADORA1, HCAR2, and GABBR1, respectively, and are thermodynamically stable in their formed compatible complexes, according to the post-molecular dynamics simulation results, they are suggested as potential drug candidates for T2DM therapy via the maintenance of normal glucose homeostasis and pancreatic β-cell function.

Computational approaches for modeling and structural design of biological systems: A comprehensive review

The convergence of biology and computational science has ushered in a revolutionary era, revolutionizing our understanding of biological systems and providing novel solutions to global problems. The field of genetic engineering has facilitated the manipulation of genetic codes, thus providing opportunities for the advancement of innovative disease therapies and environmental enhancements. The emergence of bio-molecular simulation represents a significant advancement in this particular field, as it offers the ability to gain microscopic insights into molecular-level biological processes over extended periods. Biomolecular simulation plays a crucial role in advancing our comprehension of organismal mechanisms by establishing connections between molecular structures, interactions, and biological functions. The field of computational biology has demonstrated its significance in deciphering intricate biological enigmas through the utilization of mathematical models and algorithms. The process of decoding the human genome has resulted in the advancement of therapies for a wide range of genetic disorders, while the simulation of biological systems contributes to the identification of novel pharmaceutical compounds. The potential of biomolecular simulation and computational biology is vast and limitless. As the exploration of the underlying principles that govern living organisms progresses, the potential impact of this understanding on cancer treatment, environmental restoration, and other domains is anticipated to be transformative. This review examines the notable advancements achieved in the field of computational biology, emphasizing its potential to revolutionize the comprehension and enhancement of biological systems.

Inhibition of the predicted allosteric site of the SARS-CoV-2 main protease through flavonoids

Since its emergence in 2019, coronavirus infection (COVID-19) has become a global pandemic and killed several million people worldwide. Even though several types of vaccines are available against the COVID-19 virus, SARS-CoV-2, new strains are emerging that pose a constant danger to vaccine effectiveness. In this computational study, we identified and predicted potent allosteric inhibitors of the SARS-CoV-2 main protease (Mpro). Via molecular docking and simulations, more than 100 distinct flavonoids were docked with the allosteric site of Mpro. Docking experiments revealed four top hit compounds (Hesperidin, Schaftoside, Brickellin, and Marein) that bound strongly to the Mpro predicted allosteric site. Simulation analyses further revealed that these continually interacted with the enzyme's allosteric region throughout the simulation time. ADMET and Lipinski drug likenesses were calculated to indicate the therapeutic value of the top four hits: They were non-toxic and exhibited high human intestinal absorption concentrations. These novel allosteric site inhibitors provide a higher chance of drugging SARS-CoV2 Mpro due to the rapid mutation rate of the viral enzyme's active sites. Our findings provide a new avenue for developing novel allosteric inhibitors of SARS-CoV-2 Mpro.Communicated by Ramaswamy H. Sarma.

Virtual screening and molecular dynamics simulation study of abyssomicins as potential inhibitors of COVID-19 virus main protease and spike protein

The lack of any effective cure for the infectious COVID-19 disease has created a sense of urgency and motivated the search for effective antiviral drugs. Abyssomicins are actinomyces-derived spirotetronates polyketides antibiotics known for their promising antibacterial, antitumor, and antiviral activities. In this study, computational approaches were used to investigate the binding mechanism and the inhibitory ability of 38 abyssomicins against the main protease (Mpro) and the spike protein receptor-binding domain (RBD) of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The results identified abyssomicins C, J, W, atrop-O-benzyl abyssomicin C, and atrop-O-benzyl desmethyl abyssomicin C as the most potential inhibitors of Mpro and RBD with binding energy ranges between -8.1 and -9.9 kcal mol-1; and between -6.9 and -8.2 kcal mol-1, respectively. Further analyses of physicochemical properties and drug-likeness suggested that all selected active abyssomicins, with the exception of abyssomicin J, obeyed Lipinski's rule of five. The stability of protein-ligand complexes was confirmed by performing molecular dynamics simulation for 100 ns and evaluating parameters such as such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), radius of gyration (Rg), solvent accessible surface area (SASA), total number of contacts, and secondary structure. Prime/MM-GBSA (Molecular Mechanics-General Born Surface Area) and principal component analysis (PCA) analyses also confirmed the stable nature of protein-ligand complexes. Overall, the results showed that the studied abyssomicins have significant interactions with the selected protein targets; therefore, they were deemed viable candidates for further in vitro and in vivo evaluation.Communicated by Ramaswamy H. Sarma.

In silico and in vitro analysis of the mechanisms of action of nitroxoline against some medically important opportunistic fungi

The increasing resistance to antifungal agents associated with toxicity and interactions turns therapeutic management of fungal infections difficult. This scenario emphasizes the importance of drug repositioning, such as nitroxoline - a urinary antibacterial agent that has shown potential antifungal activity. The aims of this study were to discover the possible therapeutic targets of nitroxoline using an in silico approach, and to determine the in vitro antifungal activity of the drug against the fungal cell wall and cytoplasmic membrane. We explored the biological activity of nitroxoline using PASS, SwissTargetPrediction and Cortellis Drug Discovery Intelligence web tools. After confirmation, the molecule was designed and optimized in HyperChem software. GOLD 2020.1 software was used to predict the interactions between the drug and the target proteins. In vitro investigation evaluated the effect of nitroxoline on the fungal cell wall through sorbitol protection assay. Ergosterol binding assay was carried out to assess the effect of the drug on the cytoplasmic membrane. In silico investigation revealed biological activity with alkane 1-monooxygenase and methionine aminopeptidase enzymes, showing nine and five interactions in the molecular docking, respectively. In vitro results exhibited no effect on the fungal cell wall or cytoplasmic membrane. Finally, nitroxoline has potential as an antifungal agent due to the interaction with alkane 1-monooxygenase and methionine aminopeptidase enzymes, which are not the main human therapeutic targets. These results have potentially revealed a new biological target for the treatment of fungal infections. We also consider that further studies are required to confirm the biological activity of nitroxoline on fungal cells, mainly the confirmation of the alkB gene.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

Structure-Based Identification of Natural Compounds as Potential RET-Kinase Inhibitors for Therapeutic Targeting of Neurodegenerative Diseases

BACKGROUND

Tyrosine-protein kinase receptor Ret (RET), a proto-oncogene, is considered as an attractive drug target for cancer and neurodegenerative diseases, including Alzheimer's disease (AD).

OBJECTIVE

We aimed to identify potential inhibitors of RET kinase among natural compounds present in the ZINC database.

METHODS

A multistep structure-based virtual screening approach was used to identify potential RET kinase inhibitors based on their binding affinities, docking scores, and interactions with the biologically important residues of RET kinase. To further validate the potential of these compounds as therapeutic leads, molecular dynamics (MD) simulations for 100 ns were carried out and subsequently evaluated the stability, conformational changes, and interaction mechanism of RET in-complex with the elucidated compounds.

RESULTS

Two natural compounds, ZINC02092851 and ZINC02726682, demonstrated high affinity, specificity for the ATP-binding pocket of RET and drug-likeness properties. The MD simulation outputs indicated that the binding of both compounds stabilizes the RET structure and leads to fewer conformational changes.

CONCLUSIONS

The findings suggest that ZINC02092851 and ZINC02726682 may be potential inhibitors for RET, offering valuable leads for drug development against RET-associated diseases. Our study provides a promising avenue for developing new therapeutic strategies against complex diseases, including AD. Identifying natural compounds with high affinity and specificity for RET provides a valuable starting point for developing novel drugs that could help combat these debilitating diseases.

Controlling cell proliferation by targeting cyclin-dependent kinase 6 using drug repurposing approach

Cyclin-dependent kinase 6 (CDK6) is an essential kinase in cell cycle progression, which is a viable target for inhibitors in various malignancies, including breast cancer. This study aimed to virtually screen efficient compounds as new leads in treating breast cancer using a drug repurposing approach. Apoptosis regulatory compounds were taken from the seleckchem database. Molecular docking experiments were carried out in the presence of abemaciclib, a routinely used FDA drug. Compared to conventional drugs, the two compounds demonstrated a higher binding affinity for CDK6. Compounds (N-benzyl-6-[(4-hydroxyphenyl)methyl]-8-(naphthalen-1-ylmethyl)-4,7-dioxo-3,6,9,9a-tetrahydro-2H-pyrazino[1,2-a]pyrimidine-1-carboxamide) and (1'-[4-[1-(4-fluorophenyl)indol-3-yl]butyl]spiro[1H-2-benzofuran-3,4'-piperidine]) were discovered to have an inhibitory effect against CDK6 at -8.49 and -6.78kcal/mol, respectively, compared to -8.09kcal/mol of the control molecule, the interacting residues of these two new compounds were found to fall within the binding site of the CDK6 molecule. Both compounds exhibited equal ADME features compared with abemaciclib and would be well distributed and metabolized by the body with an appropriate druglikeness range. Lastly, molecular dynamics was initiated for 200ns for the selected potent inhibitors and abemaciclib as complexed with CDK6. The RMSD, RMSF, Rg, H-Bond interactions, SASA, PCA, FEL, and MM/PBSA analysis were performed for the complexes to assess the stability, fluctuations, radius of gyration, hydrogen bond interaction, solvent accessibility, essential dynamics, free energy landscape, and MM/PBSA. The selected two compounds are small molecules in the appropriate druglikeness range. The results observed in molecular docking and molecular dynamics simulations were most promising for two compounds, suggesting their potent inhibitory effect against CDK6. We propose that these candidate compounds can undergo in vitro validation and in vivo testing for their further use against cancer.

Molecular Dynamics Simulations to Decipher the Role of Phosphorylation of SARS-CoV-2 Nonstructural Proteins (nsps) in Viral Replication

Protein phosphorylation is a post-translational modification that enables various cellular activities and plays essential roles in protein interactions. Phosphorylation is an important process for the replication of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). To shed more light on the effects of phosphorylation, we used an ensemble of neural networks to predict potential kinases that might phosphorylate SARS-CoV-2 nonstructural proteins (nsps) and molecular dynamics (MD) simulations to investigate the effects of phosphorylation on nsps structure, which could be a potential inhibitory target to attenuate viral replication. Eight target candidate sites were found as top-ranked phosphorylation sites of SARS-CoV-2. During the process of molecular dynamics (MD) simulation, the root-mean-square deviation (RMSD) analysis was used to measure conformational changes in each nsps. Root-mean-square fluctuation (RMSF) was employed to measure the fluctuation in each residue of 36 systems considered, allowing us to evaluate the most flexible regions. These analysis shows that there are significant structural deviations in the residues namely nsp1 THR 72, nsp2 THR 73, nsp3 SER 64, nsp4 SER 81, nsp4 SER 455, nsp5 SER284, nsp6 THR 238, and nsp16 SER 132. The identified list of residues suggests how phosphorylation affects SARS-CoV-2 nsps function and stability. This research also suggests that kinase inhibitors could be a possible component for evaluating drug binding studies, which are crucial in therapeutic discovery research.

An understanding of coronavirus and exploring the molecular dynamics simulations to find promising candidates against the Mpro of nCoV to combat the COVID-19: A systematic review

The first infection case of new coronavirus was reported at the end of 2019 and after then, the cases are reported in all nations across the world in a very short period. Further, the regular news of mutations in the virus has made life restricted with appropriate behavior. To date, a new strain (Omicron and its new subvariant Omicron XE) has brought fear amongst us due to a higher trajectory of increase in the number of cases. The researchers thus started giving attention to this viral infection and discovering drug-like candidates to cure the infections. Finding a drug for any viral infection is not an easy task and takes plenty of time. Therefore, computational chemistry/bioinformatics is followed to get promising molecules against viral infection. Molecular dynamics (MD) simulations are being explored to get drug candidates in a short period. The molecules are screened via molecular docking, which provides preliminary information which can be further verified by molecular dynamics (MD) simulations. To understand the change in structure, MD simulations generated several trajectories such as root mean square deviation (RMSD), root mean square fluctuation (RMSF), hydrogen bonding, and radius of gyration for the main protease (Mpro) of the new coronavirus (nCoV) in the presence of small molecules. Additionally, change in free energy for the formation of complex of Mpro of nCoV with the small molecule can be determined by applying molecular mechanics with generalized born and surface area solvation (MM-GBSA). Thus, the promising molecules can be further explored for clinical trials to combat coronavirus disease-19 (COVID-19).

Therapeutic implications and clinical manifestations of thymoquinone

Thymoquinone (TQ), a natural phytochemical predominantly found in Nigella sativa, has been investigated for its numerous health benefits. TQ showed anti-cancer, anti-oxidant, and anti-inflammatory properties, validated in various disease models. The anti-cancer potential of TQ is goverened by anti-proliferation, cell cycle arrest, apoptosis induction, ROS production, anti-metastasis and anti-angiogenesis, inhibition of cell migration and invasion action. Additionally, TQ exhibited antitumor activity via the modulation of multiple pathways and molecular targets, including Akt, ERK1/2, STAT3, and NF-κB. The present review highlighted the anticancer potential of TQ . We summarize the anti-cancer, anti-oxidant, and anti-inflammatory properties of TQ, focusing on its molecular targets and its promising action in cancer therapy. We further described the molecular mechanisms by which TQ prevents signaling pathways that mediate cancer progression, invasion, and metastasis.

Inhibiting Cyclin-Dependent Kinase 6 by Taurine: Implications in Anticancer Therapeutics

Cyclin-dependent kinase 6 (CDK6) is linked with a cyclin partner and plays a crucial role in the early stages of cancer development. It is currently a potential drug target for developing therapeutic molecules targeting cancer therapy. Here, we have identified taurine as an inhibitor of CDK6 using combined in silico and experimental studies. We performed various experiments to find the binding affinity of taurine with CDK6. Molecular docking analysis revealed critical residues of CDK6 that are involved in taurine binding. Fluorescence measurement studies showed that taurine binds to CDK6 with a significant binding affinity, with a binding constant of K = 0.7 × 10⁷ M^-1 for the CDK6-taurine complex. Enzyme inhibition assay suggested taurine as a good inhibitor of CDK6 possessing an IC₅₀ value of 4.44 μM. Isothermal titration calorimetry analysis further confirmed a spontaneous binding of taurine with CDK6 and delineated the thermodynamic parameters for the CDK6-taurine system. Altogether, this study established taurine as a CDK6 inhibitor, providing a base for using taurine and its derivatives in CDK6-associated cancer and other diseases.

Evaluation of apigenin-based biflavonoid derivatives as potential therapeutic agents against viral protease (3CLpro) of SARS-CoV-2 via molecular docking, molecular dynamics and quantum mechanics studies

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the causative agent of the pandemic COVID-19 disease that affects human respiratory function. Despite the scientific progression made in the development of the vaccine, there is an urgent need for the discovery of antiviral drugs for better performance at different stages of SARS-CoV-2 reproduction. The main protease (Mpro or 3CLpro) plays a pivotal role in the life cycle of the virus, making it an attractive target for the development of antiviral agents effective against the new strains of coronaviruses (CoVs). In this study, a series of apigenin-based natural biflavonoid derivatives as potential inhibitors of coronaviruses 3CLpro was investigated by in silico approaches. For this purpose, the molecular docking was performed to analyze the interaction of the natural biflavonoids with SARS-Cov-2 main protease and for further investigation, docking to the 3CLpro of SARS-CoV and MERS-CoV. Based on docking scores and comparison with the reference inhibitors (ritonavir and lopinavir), more than half of the biflavonoids had strong interactions with the residues of the binding pocket of the coronaviruses 3CLpro and exhibited better binding affinities toward the main protease than ritonavir and lopinavir. The top biflavonoids were further explored through molecular dynamics simulation, binding free energy calculation and residual energy contributions estimated by the MM-PBSA. Also, drug likeness property investigation by Swiss ADME tools and density functional theory (DFT) calculations were performed. The results confirmed that the 3CLpro-amentoflavone, 3CLpro-bilobetin, 3CLpro-ginkgetin, and 3CLpro-sotetsuflavone complexes possess a large amount of dynamic properties such as high stability, significant binding energy and fewer conformation fluctuations. Also, the pharmacokinetics and drug-likeness studies and HOMO-LUMO and DFT descriptor values indicated a promising result of the selected natural biflavonoids. Overall findings indicate that the apigenin-based biflavonoids may inhibit COVID-19 by significant interactions in the binding pocket and those results can pave the way in drug discovery although the effectiveness of these bioactive compounds should be further validated by in-vitro and in-vivo investigations. Communicated by Ramaswamy H. Sarma.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Investigating binding mechanism of thymoquinone to human transferrin, targeting Alzheimer's disease therapy

Iron deposition in the central nervous system (CNS) is one of the causes of neurodegenerative diseases. Human transferrin (hTf) acts as an iron carrier present in the blood plasma, preventing it from contributing to redox reactions. Plant compounds and their derivatives are frequently being used in preventing or delaying Alzheimer's disease (AD). Thymoquinone (TQ), a natural product has gained popularity because of its broad therapeutic applications. TQ is one of the significant phytoconstituent of Nigella sativa. The binding of TQ to hTf was determined by spectroscopic methods and isothermal titration calorimetry. We have observed that TQ strongly binds to hTf with a binding constant (K) of 0.22 × 10⁶ M^-1 and forming a stable complex. In addition, isothermal titration calorimetry revealed the spontaneous binding of TQ with hTf. Molecular docking analysis showed key residues of the hTf that were involved in the binding to TQ. We further performed a 250 ns molecular dynamics simulation which deciphered the dynamics and stability of the hTf-TQ complex. Structure analysis suggested that the binding of TQ doesn't cause any significant alterations in the hTf structure during the course of simulation and a stable complex is formed. Altogether, we have elucidated the mechanism of binding of TQ with hTf, which can be further implicated in the development of a novel strategy for AD therapy.

Cinnamomum zeylanicum Extract and its Bioactive Component Cinnamaldehyde Show Anti-Tumor Effects via Inhibition of Multiple Cellular Pathways

Cinnamomum zeylanicum is a tropical plant with traditional medicinal significance that possesses antimicrobial, antifungal, anti-parasitic, and anti-tumor properties. Here, we have elucidated the anti-tumor effects of Cinnamomum zeylanicum extract (CZE) and its bioactive compound cinnamaldehyde (CIN) on oral cancer and elucidated underlying molecular mechanisms. Anti-tumor activities of CZE and CIN were demonstrated by various in vitro experiments on oral cancer cells (SCC-4, SCC-9, SCC-25). The cell proliferation, growth, cell cycle arrest, apoptosis, and autophagy were analyzed by MTT, clonogenic assay, propidium iodide, annexin-V-PI, DAPI, and acridine orange staining, respectively. The binding affinity of CIN towards dihydrofolate reductase and p38-MAP kinase alpha was analyzed by molecular docking. Western blot assay was performed to assess the alteration in the expression of various proteins. CZE and CIN treatment significantly inhibited the growth and proliferation of oral cancer cells in a dose-dependent manner. These treatments further induced apoptosis, cell cycle arrest, and autophagy. CZE and CIN inhibited the invasion and cytoplasmic translocation of NF-κB in these cell lines. CIN showed a high affinity to MAP kinase P38 alpha and dihydrofolate reductase with binding affinities of −6.8 and −5.9 kcal/mol, respectively. The cancer cells showed a decreased expression of various PI3k-AKT-mTOR pathways related to VEGF, COX-2, Bcl-2, NF-κB, and proteins post-treatment.

Investigating the Mechanism of Inhibition of Cyclin-Dependent Kinase 6 Inhibitory Potential by Selonsertib: Newer Insights Into Drug Repurposing

Cyclin-dependent kinases (CDKs) play significant roles in numerous physiological, and are considered an attractive drug target for cancer, neurodegenerative, and inflammatory diseases. In the present study, we have aimed to investigate the binding affinity and inhibitory potential of selonsertib toward CDK6. Using the drug repurposing approach, we performed molecular docking of selonsertib with CDK6 and observed a significant binding affinity. To ascertain, we further performed essential dynamics analysis and free energy calculation, which suggested the formation of a stable selonsertib-CDK6 complex. The in-silico findings were further experimentally validated. The recombinant CDK6 was expressed, purified, and treated with selonsertib. The binding affinity of selonsertib to CDK6 was estimated by fluorescence binding studies and enzyme inhibition assay. The results indicated an appreciable binding of selonsertib against CDK6, which subsequently inhibits its activity with a commendable IC50 value (9.8 μM). We concluded that targeting CDK6 by selonsertib can be an efficient therapeutic approach to cancer and other CDK6-related diseases. These observations provide a promising opportunity to utilize selonsertib to address CDK6-related human pathologies.

Identification of intrinsically disorder regions in non-structural proteins of SARS-CoV-2: New insights into drug and vaccine resistance

The outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) emerged in December 2019 and caused coronavirus disease 2019 (COVID-19), which causes pneumonia and severe acute respiratory distress syndrome. It is a highly infectious pathogen that promptly spread. Like other beta coronaviruses, SARS-CoV-2 encodes some non-structural proteins (NSPs), playing crucial roles in viral transcription and replication. NSPs likely have essential roles in viral pathogenesis by manipulating many cellular processes. We performed a sequence-based analysis of NSPs to get insights into their intrinsic disorders, and their functions in viral replication were annotated and discussed in detail. Here, we provide newer insights into the structurally disordered regions of SARS-CoV-2 NSPs. Our analysis reveals that the SARS-CoV-2 proteome has a chunk of the disordered region that might be responsible for increasing its virulence. In addition, mutations in these regions are presumably responsible for drug and vaccine resistance. These findings suggested that the structurally disordered regions of SARS-CoV-2 NSPs might be invulnerable in COVID-19.

Inhibition of the main protease of SARS-CoV-2 (Mpro) by repurposing/designing drug-like substances and utilizing nature's toolbox of bioactive compounds

The emergence of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has resulted in a long pandemic, with numerous cases and victims worldwide and enormous consequences on social and economic life. Although vaccinations have proceeded and provide a valuable shield against the virus, the approved drugs are limited and it is crucial that further ways to combat infection are developed, that can also act against potential mutations. The main protease (Mpro) of the virus is an appealing target for the development of inhibitors, due to its importance in the viral life cycle and its high conservation among different coronaviruses. Several compounds have shown inhibitory potential against Mpro, both in silico and in vitro, with few of them also having entered clinical trials. These candidates include: known drugs that have been repurposed, molecules specifically designed based on the natural substrate of the protease or on structural moieties that have shown high binding affinity to the protease active site, as well as naturally derived compounds, either isolated or in plant extracts. The aim of this work is to collectively present the results of research regarding Mpro inhibitors to date, focusing on the function of the compounds founded by in silico simulations and further explored by in vitro and in vivo assays. Creating an extended portfolio of promising compounds that may block viral replication by inhibiting Mpro and by understanding involved structure-activity relationships, could provide a basis for the development of effective solutions against SARS-CoV-2 and future related outbreaks.

Lichen planus drugs re-purposing as potential anti COVID-19 therapeutics through molecular docking and molecular dynamics simulation approach

Background and Aim

The present study intends to investigate COVID-19 by targeting their main proteins with 17 selected drugs used for treating Oral Lichen Planus (OLP) which is a chronic muco-cutaneous disorder. Here, an attempt is made to gain better insight into the structure of various drugs targeting specific proteins which will be helpful in developing drugs useful for therapeutic and preventive measures.

Method

In silico studies, molecular docking and molecular dynamic simulations were performed to repurpose the therapeutic drugs (n = 17) which were used to treat OLP against COVID-19. In addition, the maximum binding affinities of the key protein spike glycoprotein, main-protease (M^pro) of coronavirus, and Angiotensin-Converting Enzyme-2 (ACE-2) in the human body were evaluated with the selected drugs.

Results

Epigallocatechin-3-gallate (EGCG) showed the highest docking values among the drugs selected for repurposing. Among the target proteins, EGCG has shown maximum binding affinity with ACE-2 receptor. Further, according to the molecular dynamic simulation studies, EGCG has shown the least conformational fluctuations with M^pro.

Conclusion

EGCG can be a potential inhibitor drug which can bind with ACE-2 receptor thus inhibiting the interaction of mainly M^pro protein and spike glycoprotein of SARS-CoV-2.

Relevance for Patients

EGCG, a natural compound shows antiviral potential having considerably high affinity and stability with SARS-CoV-2. It might be further employed as a lead drug against selective inhibitors of SARS-CoV-2 for the therapeutic management of COVID-19 patients after necessary clinical trials.

Natural products can be used in therapeutic management of COVID-19: Probable mechanistic insights

The unexpected emergence of the new Coronavirus disease (COVID-19) has affected more than three hundred million individuals and resulted in more than five million deaths worldwide. The ongoing pandemic has underscored the urgent need for effective preventive and therapeutic measures to develop anti-viral therapy. The natural compounds possess various pharmaceutical properties and are reported as effective anti-virals. The interest to develop an anti-viral drug against the novel severe acute respiratory syndrome Coronavirus (SARS-CoV-2) from natural compounds has increased globally. Here, we investigated the anti-viral potential of selected promising natural products. Sources of data for this paper are current literature published in the context of therapeutic uses of phytoconstituents and their mechanism of action published in various reputed peer-reviewed journals. An extensive literature survey was done and data were critically analyzed to get deeper insights into the mechanism of action of a few important phytoconstituents. The consumption of natural products such as thymoquinone, quercetin, caffeic acid, ursolic acid, ellagic acid, vanillin, thymol, and rosmarinic acid could improve our immune response and thus possesses excellent therapeutic potential. This review focuses on the anti-viral functions of various phytoconstituent and alkaloids and their potential therapeutic implications against SARS-CoV-2. Our comprehensive analysis provides mechanistic insights into phytoconstituents to restrain viral infection and provide a better solution through natural, therapeutically active agents.

In vitro and computational investigations of novel synthetic carboxamide-linked pyridopyrrolopyrimidines with potent activity as SARS-CoV-2-MPro inhibitors

An essential target for COVID-19 is the main protease of SARS-CoV-2 (M^pro). With the objective of targeting this receptor, a novel set of pyrido[1,2-a]pyrrolo[2,3-d]pyrimidines with terminal carboxamide fragments was designed, synthesized, and considered as an initial motif for the creation of effective pan-coronavirus inhibitors. Accordingly, nine derivatives (21–29) have been introduced for in vitro assay to evaluate their antiviral activity and cytotoxicity effect against COVID-19 virus using Vero cells. The obtained data revealed that the majority of these derivatives showed potent cellular anti-COVID-19 activity and prevent viral growth by more than 90% at two different concentrations with weak or even no detectable cytotoxic effect on Vero cells. Extensive molecular docking simulations highlighted proper non-covalent interaction of new compounds within the binding pocket of M^pro as a potential target for their antiviral activity. In vitro assay for all the synthesized derivatives against the viral M^pro target indicated that compounds 25 and 29 have promising inhibitory activity with IC₅₀ values at low micromolar concentrations. The molecular dynamic simulation results predicted the stability of compound 29 in the binding cavity of SARS-CoV-2 M^pro and hence supported the high inhibitory activity shown by the In vitro assay. These results suggested that compounds 25 and 29 merit further investigations as promising drug candidates for the management of SARS-CoV-2.

An essential target for COVID-19 is the main protease of SARS-CoV-2 (M^pro).

Identification of Phytoconstituents as Potent Inhibitors of Casein Kinase-1 Alpha Using Virtual Screening and Molecular Dynamics Simulations

Casein kinase-1 alpha (CK1α) is a multifunctional protein kinase that belongs to the serine/threonine kinases of the CK1α family. It is involved in various signaling pathways associated with chromosome segregation, cell metabolism, cell cycle progression, apoptosis, autophagy, etc. It has been known to involve in the progression of many diseases, including cancer, neurodegeneration, obesity, and behavioral disorders. The elevated expression of CK1α in diseased conditions facilitates its selective targeting for therapeutic management. Here, we have performed virtual screening of phytoconstituents from the IMPPAT database seeking potential inhibitors of CK1α. First, a cluster of compounds was retrieved based on physicochemical parameters following Lipinski's rules and PAINS filter. Further, high-affinity hits against CK1α were obtained based on their binding affinity score. Furthermore, the ADMET, PAINS, and PASS evaluation was carried out to select more potent hits. Finally, following the interaction analysis, we elucidated three phytoconstituents, Semiglabrinol, Curcusone_A, and Liriodenine, posturing considerable affinity and specificity towards the CK1α binding pocket. The result was further evaluated by molecular dynamics (MD) simulations, dynamical cross-correlation matrix (DCCM), and principal components analysis (PCA), which revealed that binding of the selected compounds, especially Semiglabrinol, stabilizes CK1α and leads to fewer conformational fluctuations. The MM-PBSA analysis suggested an appreciable binding affinity of all three compounds toward CK1α.

Screening of Severe Acute Respiratory Syndrome Coronavirus 2 RNA-Dependent RNA Polymerase Inhibitors Using Computational Approach

The detrimental effect of coronavirus disease 2019 (COVID-19) pandemic has manifested itself as a global crisis. Currently, no specific treatment options are available for COVID-19, so therapeutic interventions to tackle the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be urgently established. Therefore, cohesive and multidimensional efforts are required to identify new therapies or investigate the efficacy of small molecules and existing drugs against SARS-CoV-2. Since the RNA-dependent RNA Polymerase (RdRP) of SARS-CoV-2 is a promising therapeutic target, this study addresses the identification of antiviral molecules that can specifically target SARS-CoV-2 RdRP. The computational approach of drug development was used to screen the antiviral molecules from two antiviral libraries (Life Chemicals [LC] and ASINEX) against RdRP. Here, we report six antiviral molecules (F3407-4105, F6523-2250, F6559-0746 from LC and BDG 33693278, BDG 33693315, LAS 34156196 from ASINEX), which show substantial interactions with key amino acid residues of the active site of SARS-CoV-2 RdRP and exhibit higher binding affinity (>7.5 kcalmol-1) than Galidesivir, an Food and Drug Administration-approved inhibitor of the same. Further, molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area results confirmed that identified molecules with RdRP formed higher stable RdRP-inhibitor(s) complex than RdRP-Galidesvir complex. Our findings suggest that these molecules could be potential inhibitors of SARS-CoV-2 RdRP. However, further in vitro and preclinical experiments would be required to validate these potential inhibitors of SARS-CoV-2 protein.

Selection of SARS-CoV-2 main protease inhibitor using structure-based virtual screening

Background: Conserved domains within SARS coronavirus 2 nonstructural proteins represent key targets for the design of novel inhibitors. Methods: The authors aimed to identify potential SARS coronavirus 2 NSP5 inhibitors using the ZINC database along with structure-based virtual screening and molecular dynamics simulation. Results: Of 13,840 compounds, 353 with robust docking scores were initially chosen, of which ten hit compounds were selected as candidates for detailed analyses. Three compounds were selected as coronavirus NSP5 inhibitors after passing absorption, distribution, metabolism, excretion and toxicity study; root and mean square deviation; and radius of gyration calculations. Conclusion: ZINC000049899562, ZINC000169336666 and ZINC000095542577 are potential NSP5 protease inhibitors that warrant further experimental studies.

Identification of nut protein-derived peptides against SARS-CoV-2 spike protein and main protease

Recently, an outbreak of a novel coronavirus disease (COVID-19) has reached pandemic proportions, and there is an urgent need to develop nutritional supplements to assist with prevention, treatment, and recovery. In this study, SARS-CoV-2 inhibitory peptides were screened from nut proteins in silico, and binding affinities of the peptides to the SARS-CoV-2 main protease (M^pro) and the spike protein receptor-binding domain (RBD) were evaluated. Peptide NDQF from peanuts and peptide ASGCGDC from almonds were found to have a strong binding affinity for both targets of the coronavirus. The binding sites of the NDQF and ASGCGDC peptides are highly consistent with the M^pro inhibitor N3. In addition, NDQF and ASGCGDC exhibited an effective binding affinity for amino acid residues Tyr453 and Gln493 of the spike RBD. Molecular dynamics simulation further confirmed that the NDQF and ASGCGDC peptides could bind stably to the SARS-COV-2 M^pro and spike RBD. In summary, nut protein may be helpful as nutritional supplements for COVID-19 patients, and the screened peptides could be considered a potential lead compound for designing entry inhibitors against SARS-CoV-2.

Thymoquinone and quercetin induce enhanced apoptosis in non-small cell lung cancer in combination through the Bax/Bcl2 cascade

The treatments available for non-small cell lung cancer exert various side effects in patients, and the burden of treatment cost is high. Therefore, exploring the alternative system of medicines, including therapies based on natural compounds, has become inevitable in developing anticancer therapeutics. This study used an integrated approach involving in-silico and in-vitro methods to explore natural compounds targeting Bax and Bcl2 for their apoptotic potential. Molecular docking followed by molecular dynamics (MD) simulation of thymoquinone (Tq) and quercetin (Qu) with Bax and Bcl2 were carried out to explore their interactions and stability under explicit solvent conditions. Tq and Qu showed appreciable binding affinities toward Bax (-6.2 and -7.1 kcal/mol, respectively) and Bcl2 (-5.6 and -6.4 kcal/mol, respectively) with well-organized conformational fitting compatibility. The MD simulation results revealed the development of stable complexes maintained by various noncovalent interactions that were preserved throughout the 100 ns trajectories. Further studies with these compounds were carried out using various in-vitro experimental approaches like MTT assay, apoptotic assay, and Western blot. IC₅₀ values of Tq and Qu alone in A549 cells were found to be 45.78 and 35.69 µM, while in combination, it comes down to 22.49 µM, which is quite impressive. Similarly, in apoptosis assay, a combination of Tq and Qu shows 50.9% early apoptosis compared to Tq (40.6%) and Qu (33.3%) when taken alone. These assays signify their apoptotic induction potential, whereas both compounds significantly reduce the expression of antiapoptotic protein Bcl2 and induce proapoptotic Bax, suggestive of sensitizing NSCLS cells toward apoptosis.

Molecular Docking and Dynamics Simulation Revealed the Potential Inhibitory Activity of ACEIs Against SARS-CoV-2 Targeting the hACE2 Receptor

The rapid and global spread of a new human coronavirus, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has produced an immediate urgency to discover promising targets for the treatment of COVID-19. Here, we consider drug repurposing as an attractive approach that can facilitate the drug discovery process by repurposing existing pharmaceuticals to treat illnesses other than their primary indications. We review current information concerning the global health issue of COVID-19 including promising approved drugs, e.g., human angiotensin-converting enzyme inhibitors (hACEIs). Besides, we describe computational approaches to be used in drug repurposing and highlight examples of in-silico studies of drug development efforts against SARS-CoV-2. Alacepril and lisinopril were found to interact with human angiotensin-converting enzyme 2 (hACE2), the host entranceway for SARS-CoV-2 spike protein, through exhibiting the most acceptable rmsd_refine values and the best binding affinity through forming a strong hydrogen bond with Asn90, which is assumed to be essential for the activity, as well as significant extra interactions with other receptor-binding residues. Furthermore, molecular dynamics (MD) simulations followed by calculation of the binding free energy were also carried out for the most promising two ligand-pocket complexes from docking studies (alacepril and lisinopril) to clarify some information on their thermodynamic and dynamic properties and confirm the docking results as well. These results we obtained probably provided an excellent lead candidate for the development of therapeutic drugs against COVID-19. Eventually, animal experiments and accurate clinical trials are needed to confirm the potential preventive and treatment effect of these compounds.