MHC2AffyPred: A machine-learning approach to estimate affinity of MHC class II peptides based on structural interaction fingerprints.

Understanding how MHC class II (MHC-II) binding peptides with differing lengths exhibit specific interaction at the core and extended sites within the large MHC-II pocket is a very important aspect of immunological research for designing peptides. Certain efforts were made to generate peptide conformations amenable for MHC-II binding and calculate the binding energy of such complex formation but not directed toward developing a relationship between the peptide conformation in MHC-II structures and the binding affinity (BA) (IC50 ). We present here a machine-learning approach to calculate the BA of the peptides within the MHC-II pocket for HLA-DRA1, HLA-DRB1, HLA-DP, and HLA-DQ allotypes. Instead of generating ensembles of peptide conformations conventionally, the biased mode of conformations was created by considering the peptides in the crystal structures of pMHC-II complexes as the templates, followed by site-directed peptide docking. The structural interaction fingerprints generated from such docked pMHC-II structures along with the Moran autocorrelation descriptors were trained using a random forest regressor specific to each MHC-II peptide lengths (9-19). The entire workflow is automated using Linux shell and Perl scripts to promote the utilization of MHC2AffyPred program to any characterized MHC-II allotypes and is made for free access at https://github.com/SiddhiJani/MHC2AffyPred. The MHC2AffyPred attained better performance (correlation coefficient [CC] of .612-.898) than MHCII3D (.03-.594) and NetMHCIIpan-3.2 (.289-.692) programs in the HLA-DRA1, HLA-DRB1 types. Similarly, the MHC2AffyPred program achieved CC between .91 and .98 for HLA-DP and HLA-DQ peptides (13-mer to 17-mer). Further, a case study on MHC-II binding 15-mer peptides of severe acute respiratory syndrome coronavirus-2 showed very close competency in computing the IC50 values compared to the sequence-based NetMHCIIpan v3.2 and v4.0 programs with a correlation of .998 and .570, respectively.

Repurposing of anticancer phytochemicals for identifying potential fusion inhibitor for SARS-CoV-2 using molecular docking and molecular dynamics (MD) simulations.

The viral particle, SARS-CoV-2 is responsible for causing the epidemic of Coronavirus disease 2019 (COVID-19). To combat this situation, numerous strategies are being thought for either creating its antidote, vaccine, or agents that can prevent its infection. For enabling research on these strategies, several target proteins are identified where, Spike (S) protein is of great potential. S-protein interacts with human angiotensin-converting-enzyme-2 (ACE2) for entering the cell. S-protein is a large protein and a portion of it designated as a receptor-binding domain (RBD) is the key region that interacts with ACE2, following to which the viral membrane fuses with the alveolar membrane to enter the human cell. The hypothesis is to identify molecules from the pool of anticancer phytochemicals as a lead possessing the ability to interact and mask the amino acids of RBD, making them unavailable to form associations with ACE2. Such a molecule is termed as 'fusion inhibitor'. We hypothesized to identify fusion inhibitors from the NPACT library of anticancer phytochemicals. For this, all the molecules from the NPACT were screened using molecular docking, the five top hits (Theaflavin, Ginkgetin, Ursolic acid, Silymarin and Spirosolane) were analyzed for essential Pharmacophore features and their ADMET profiles were studied following to which the best two hits were further analyzed for their interaction with RBD using Molecular Dynamics (MD) simulation. Binding free energy calculations were performed using MM/GBSA, proving these phytochemicals containing anticancer properties to serve as fusion inhibitors.Communicated by Ramaswamy H. Sarma.

Network pharmacology-based evaluation of natural compounds with paclitaxel for the treatment of metastatic breast cancer.

Metastatic breast cancer is a prevalent life-threatening disease. Paclitaxel (PTX) is widely used in metastatic breast cancer therapy, but the side effects limit its chemotherapeutic application. Multidrug strategies have recently been used to maximize potency and decrease the toxicity of a particular drug by reducing its dosage. Therefore, we have evaluated the combined anti-cancerous effect of PTX with tested natural compounds (andrographolide (AND), silibinin (SIL), mimosine (MIM) and trans-anethole (TA)) using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, trypan blue dye exclusion assay, proliferating cell nuclear antigen (PCNA) staining, network pharmacology, molecular docking, molecular dynamics (MD) and in vivo chick chorioallantoic membrane (CAM) angiogenesis assay. We observed a reduction in the IC50 value of PTX with tested natural compounds. Further, the network pharmacology-based analysis of compound-disease-target (C-D-T) network showed that PTX, AND, SIL, MIM and TA targeted 55, 61, 56, 31 and 18 proteins of metastatic breast cancer, respectively. Molecular docking results indicated that AND and SIL inhibited the C-D-T network's core target kinase insert domain receptor (KDR) protein more effectively than others. While MD showed that the binding of AND with KDR was stronger and more stable than others. In trypan blue dye exclusion assay and PCNA staining, AND and SIL along with PTX were found to be more effective than PTX alone. CAM assay results suggested that AND, SIL and TA increase the anti-angiogenic potential of PTX. Thus, natural compounds can be used to improve the anti-cancer potential of PTX.

Identification of potential inhibitors of coronavirus hemagglutinin-esterase using molecular docking, molecular dynamics simulation and binding free energy calculation.

The pandemic outbreak of the Corona viral infection has become a critical global health issue. Biophysical and structural evidence shows that spike protein possesses a high binding affinity towards host angiotensin-converting enzyme 2 and viral hemagglutinin-acetylesterase (HE) glycoprotein receptor. We selected HE as a target in this study to identify potential inhibitors using a combination of various computational approaches such as molecular docking, ADMET analysis, dynamics simulations and binding free energy calculations. Virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin as potential HE inhibitors with better binding energy. Furthermore, molecular dynamics simulations for 100 ns time scale revealed that most of the key HE contacts were retained throughout the simulations trajectories. Binding free energy calculations using MM/PBSA approach ranked the top-five potential NPACT compounds which can act as effective HE inhibitors.

Transcriptome-wide miRNA identification of Bacopa monnieri: a cross-kingdom approach.

Bacopa monnieri known as 'Brahmi' is a well-known medicinal plant belonging to Scrophulariaceae family for its nootropic properties. To the best of our knowledge, no characterization data is available on the potential role of micro RNAs (miRNAs) from this plant till date. We present here the first report of computational characterizations of miRNAs from B. monnieri. Owing to the high conservation of miRNAs in nature, new and potential miRNAs can be identified in plants using in silico techniques. Using the plant miRNA sequences present in the miRBase repository, a total of 12 miRNAs were identified from B. monnieri which pertained to 11 miRNA families from the shoot and root transcriptome data. Furthermore, gene ontology analysis of the identified 68 human target genes exhibited significance in various biological processes. These human target genes were associated with signaling pathways like NF-kB and MAPK with TRAF2, CBX1, IL1B, ITGA4 and ITGB1BP1 as the top five hub nodes. This cross-kingdom study provides initial insights about the potential of miRNA-mediated cross-kingdom regulation and unravels the essential target genes of human with implications in numerous human diseases including cancer.

Cardiotonic steroids as potential Na+/K+-ATPase inhibitors - a computational study.

Cardiotonic steroids (CTS) are steroidal drugs, processed from the seeds and dried leaves of the genus Digitalis as well as from the skin and parotid gland of amphibians. The most commonly known CTS are ouabain, digoxin, digoxigenin and bufalin. CTS can be used for safer medication of congestive heart failure and other related conditions due to promising pharmacological and medicinal properties. Ouabain isolated from plants is widely utilized in in vitro studies to specifically block the sodium potassium (Na+/K+-ATPase) pump. For checking, whether ouabain derivatives are robust inhibitors of Na+/K+-ATPase pump, molecular docking simulation was performed between ouabain and its derivatives using YASARA software. The docking energy falls within the range of 8.470 kcal/mol to 7.234 kcal/mol, in which digoxigenin was found to be the potential ligand with the best docking energy of 8.470 kcal/mol. Furthermore, pharmacophore modeling was applied to decipher the electronic features of CTS. Molecular dynamics simulation was also employed to determine the conformational properties of Na+/K+-ATPase-ouabain and Na+/K+-ATPase-digoxigenin complexes with the plausible structural integrity through conformational ensembles for 100 ns which promoted digoxigenin as the most promising CTS for treating conditions of congestive heart failure patients.

Pharmacophore-based virtual screening of catechol-o-methyltransferase (COMT) inhibitors to combat Alzheimer's disease.

Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.

Molecular dynamics-assisted pharmacophore modeling of caspase-3-isatin sulfonamide complex: Recognizing essential intermolecular contacts and features of sulfonamide inhibitor class for caspase-3 binding.

The identification of isatin sulfonamide as a potent small molecule inhibitor of caspase-3 had fuelled the synthesis and characterization of the numerous sulfonamide class of inhibitors to optimize for potency. Recent works that relied on the ligand-based approaches have successfully shown the regions of optimizations for sulfonamide scaffold. We present here molecular dynamics-based pharmacophore modeling of caspase-3-isatin sulfonamide crystal structure, to elucidate the essential non-covalent contacts and its associated pharmacophore features necessary to ensure caspase-3 optimal binding. We performed 20ns long dynamics of this crystal structure to extract global conformation states and converted into structure-based pharmacophore hypotheses which were rigorously validated using an exclusive focussed library of experimental actives and inactives of sulfonamide class by Receiver Operating Characteristic (ROC) statistic. Eighteen structure-based pharmacophore hypotheses with better sensitivity and specificity measures (>0.6) were chosen which collectively showed the role of pocket residues viz. Cys163 (S1 sub-site; required for covalent and H bonding with Michael acceptor of inhibitors), His121 (S1; π stack with bicyclic isatin moiety), Gly122 (S1; H bond with carbonyl oxygen) and Tyr204 (S2; π stack with phenyl group of the isatin sulfonamide molecule) as stringent binding entities for enabling caspase-3 optimal binding. The introduction of spatial pharmacophore site points obtained from dynamics-based pharmacophore models in a virtual screening strategy will be helpful to screen and optimize molecules belonging to sulfonamide class of caspase-3 inhibitors.

Receptor-Guided De Novo Design of Dengue Envelope Protein Inhibitors.

Inhibitor design associated with the dynamics of dengue envelope protein at pre-fusion stage is a prominent strategy to interfere fusion transition of dengue virus with the host cell membrane. Receptor-guided de novo inhibitors were designed based on the knowledge of co-crystallized detergent, ß-octyl glucoside. Pharmacophore features distribution showed the preference of aromatic groups with H bonding features connected to aliphatic bulky group as the skeleton for inhibitor design. Molecular dynamic simulations revealed (2R)-2-[(6-amino-1-oxohexan-2-yl)amino]-4-[6-(4-phenylpiperidine-1-yl)-1,2-benzoxazol-3-yl]butanoate as the probable binder which developed extensive conservative interactions despite the local pocket residues movements especially from kl ß-hairpin, the key structural unit for initiating conformational changes required for fusion transition. The electronic and hydrophobic potentials also indicated that butanoate molecule as the initial lead for envelope protein inhibitors.

Structural insights into the theoretical model of Plasmodium falciparum NADH dehydrogenase and its interaction with artemisinin and derivatives: towards global health therapeutics.

It is a continuing quest to uncover the principal molecular targets of malarial parasites to understand the antimalarial activity and mechanism of action of artemisinin, a potent antimalarial. A series of parasite proteins are experimentally validated as potential targets, such as translationally controlled tumor protein (TCTP) and sarco/endoplasmic reticulum membrane calcium ATP-ase (SERCA). The present study addressed the development of a theoretical model of Plasmodium falciparum NADH dehydrogenase with inference from artemisinin in vivo inhibitory activity. We report here the predicted binding modes of artemisinin and its derivatives. The modeled protein resembled the structural architecture of flavoproteins and oxidoreductases, consisting of two Rossmann folds and dedicated binding sites for its cofactors. Docked poses of the ligand dataset revealed its interactions at or near the si face, indicating being activated. This may aid in generation of reactive oxygen species, thereby disrupting the membrane potential of parasite mitochondria and leading to the clearance from the blood. These observations open up new strategies for development of novel therapeutics, or improvement of existing pharmacotherapies against malaria, a major burden for global health.

Epitope-based immunoinformatics and molecular docking studies of nucleocapsid protein and ovarian tumor domain of crimean-congo hemorrhagic Fever virus.

Crimean-Congo hemorrhagic fever virus (CCHFV), the fatal human pathogen is transmitted to humans by tick bite, or exposure to infected blood or tissues of infected livestock. The CCHFV genome consists of three RNA segments namely, S, M, and L. The unusual large viral L protein has an ovarian tumor (OTU) protease domain located in the N terminus. It is likely that the protein may be autoproteolytically cleaved to generate the active virus L polymerase with additional functions. Identification of the epitope regions of the virus is important for the diagnosis, phylogeny studies, and drug discovery. Early diagnosis and treatment of CCHF infection is critical to the survival of patients and the control of the disease. In this study, we undertook different in silico approaches using molecular docking and immunoinformatics tools to predict epitopes which can be helpful for vaccine designing. Small molecule ligands against OTU domain and protein-protein interaction between a viral and a host protein have been studied using docking tools.