Structural Modifications Introduced by NS2B Cofactor Binding to the NS3 Protease of the Kyasanur Forest Disease Virus.

Kyasanur Forest Disease virus (KFDV), a neglected human pathogenic virus, is a Flavivirus that causes severe hemorrhagic fever in humans. KFDV is transmitted to humans by the bite of the hard tick (Haemaphysalis spinigera), which acts as a reservoir of KFDV. The recent expansion of the endemic area of KFDV is of concern and requires the development of new preventive measures against KFDV. Currently, there is no antiviral therapy against KFDV, and the existing vaccine has limited efficacy. To develop a new antiviral therapy against KFDV, we focused on the nonstructural proteins NS2B and NS3 of KFDV, which are responsible for serine protease activity. Viral proteases have shown to be suitable therapeutic targets in the development of antiviral drugs against many diseases. However, success has been limited in flaviviruses, mainly because of the important features of the active site, which is flat and highly charged. In this context, the present study focuses on the dynamics of NS2B and NS3 to identify potential allosteric sites in the NS2B/NS3 protease of KDFV. To our knowledge, there are no reports on the dynamics of NS2B and NS3 in KFDV, and the crystal structure of the NS2B/NS3 protease of KFDV has not yet been solved. Overall, we created the structure of the NS2B/NS3 protease of KFDV using AlphaFold and performed molecular dynamics simulations with and without NS2B cofactor to investigate structural rearrangements due to cofactor binding and to identify alternative allosteric sites. The identified allosteric site is promising due to its geometric and physicochemical properties and druggability and can be used for new drug development. The applicability of the proposed allosteric binding sites was verified for the best-hit molecules from the virtual screening and MD simulations.

Development of machine learning models based on molecular fingerprints for selection of small molecule inhibitors against JAK2 protein.

Janus kinase 2 (JAK2) is emerging as a potential therapeutic target for many inflammatory diseases such as myeloproliferative disorders (MPD), cancer and rheumatoid arthritis (RA). In this study, we have collected experimental data of JAK2 protein containing 6021 unique inhibitors. We then characterized them based on Morgan (ECFP6) fingerprints followed by clustering into training and test set based on their molecular scaffolds. These data were used to build the classification models with various supervised machine learning (ML) algorithms that could prioritize novel inhibitors for future drug development against JAK2 protein. The best model built by Random Forest (RF) and Morgan fingerprints achieved the G-mean value of 0.84 on the external test set. As an application of our classification model, virtual screening was performed against Drugbank molecules in order to identify the potential inhibitors based on the confidence score by RF model. Nine potential molecules were identified, which were further subject to molecular docking studies to evaluate the virtual screening results of the best RF model. This proposed method can prove useful for developing novel target-specific JAK2 inhibitors.

AlteQ: a new complementarity principle-centered method for the evaluation of docking poses.

Molecular docking is the most popular and widely used method for identifying novel molecules against a target of interest. However, docking procedures and their validation are still under intense development. In the present investigation, we evaluate a quantum free-orbital AlteQ method for evaluating docking complexes generated by taking EGFR complexes as an example. The AlteQ method calculates the electron density using Slater's type atomic contributions in the interspace between the receptor and the ligand. Since the interactions are determined by the overlap of electron clouds, they follow the complementarity principle, and an equation can be obtained that describes these interactions. The AlteQ method evaluates the quality of the interaction between the receptor and the ligand, how complementary the interactions are, and due to this, it is used to reject less realistic structures obtained by docking methods. Here, three different equations were used to determine the quality of the interactions in experimental complexes and docked complexes obtained using AutoDock Vina and AutoDock 4.2.6.Communicated by Ramaswamy H. Sarma.

A systems biology investigation of curcumin potency against TGF-ß-induced EMT signaling in lung cancer.

Curcumin (diferuloylmethane) is bioactive phenolic compound which exerts diverse antimetastatic effect. Several studies have reported the antimetastatic effect of curcumin by its ability to modulate the epithelial-to-mesenchymal transition (EMT) process in different cancers, but underlying molecular mechanism is poorly understood. EMT is a highly conserved biological process in which epithelial cells acquire mesenchymal-like characteristics by losing their cell-cell junctions and polarity. As a consequence, deviation in cellular mechanism leads to cancer metastasis and thereby death. In this perspective, we explored the antimetastatic potential and mechanism of curcumin on the EMT process by establishing in vitro EMT model in lungs cancer (A549) cells induced by TGF-ß1. Our results showed that curcumin mitigates EMT by regulating the expression of crucial mesenchymal markers such as MMP2, vimentin and N-cadherin. Besides, the transcriptional analysis revealed that the curcumin treatment differentially regulated the expression of 75 genes in NanoString nCounter platform. Further protein-protein interaction network and clusters analysis of differentially expressed genes revealed their involvement in essential biological processes that plays a key role during EMT transition. Altogether, the study provides a comprehensive overview of the antimetastatic potential of curcumin in TGF-ß1-induced EMT in lung cancer cells. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-022-03360-7.

Novel Insights into the Bioactive Metabolites of Macrocybe gigantea (Agaricomycetes), Using Gas Chromatography-Mass Spectrometry Combined with Chemoinformatic Approaches.

Macrocybe gigantea is an edible mushroom and has multiple pharmacological properties, including antibacterial, antioxidant, and antitumor activities. However, only a few reports are currently available on the bioactive compounds and bioactivity of this mushroom. Therefore, the present study aimed to explore the unique chemical diversity of the fruiting body of M. gigantea. Species identification was done accurately with morphological and molecular methods, followed by mycochemical extraction in different solvent systems. The ethanolic extract of the fruiting body gave maximum yield, and gas chromatography-mass spectrometry (GC-MS) analysis was performed along with an assessment of antibacterial activity and cell viability by the MTT assay. The GC-MS analysis revealed 50 metabolites, and further cheminformatics analysis of these metabolites revealed their possible biological activities. In addition, the physicochemical and mineral element analysis of M. gigantea revealed the quality and authenticity of the species. Altogether, the current investigation gives a comprehensive overview of the bioactive metabolites of M. gigantea.

Proposition of a new allosteric binding site for potential SARS-CoV-2 3CL protease inhibitors by utilizing molecular dynamics simulations and ensemble docking.

The SARS-CoV-2 3CL protease (3CLpro) shows a high similarity with 3CL proteases of other beta-coronaviruses, such as SARS and MERS. It is the main enzyme involved in generating various non-structural proteins that are important for viral replication and is one of the most important proteins responsible for SARS-CoV-2 virulence. In this study, we have conducted an ensemble docking of molecules from the DrugBank database using both the crystallographic structure of the SARS-CoV-2 3CLpro, as well as five conformations obtained after performing a cluster analysis of a 300 ns molecular dynamics (MD) simulation. This procedure elucidated the inappropriateness of the active site for non-covalent inhibitors, but it has also shown that there exists an additional, more favorable, allosteric binding site, which could be a better target for non-covalent inhibitors, as it could prevent dimerization and activation of SARS-CoV-2 3CLpro. Two such examples are radotinib and nilotinib, tyrosine kinase inhibitors already in use for treatment of leukemia and which binding to the newly found allosteric binding site was also confirmed using MD simulations. Communicated by Ramaswamy H. Sarma.

Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking.

Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV. Communicated by Ramaswamy H. Sarma.

Anti-neoplastic pharmacophore benzophenone-1 coumarin (BP-1C) targets JAK2 to induce apoptosis in lung cancer.

Reigning of the abnormal gene activation associated with survival signalling in lung cancer leads to the anomalous growth and therapeutic failure. Targeting specific cell survival signalling like JAK2/STAT3 nexus has become a major focus of investigation to establish a target specific treatment. The 2-bromobenzoyl-4-methylphenoxy-acetyl hydra acetyl Coumarin (BP-1C), is new anti-neoplastic agent with apoptosis inducing capacity. The current study was aimed to develop antitumor phramacophore, BP-1C as JAK2 specific inhibitor against lung neoplastic progression. The study validates and identifies the molecular targets of BP-1C induced cell death. Cell based screening against multiple cancer cell lines identified, lung adenocarcinoma as its specific target through promotion of apoptosis. The BP-1C is able to induce, specific hall marks of apoptosis and there by conferring anti-neoplastic activity. Validation of its molecular mechanism, identified, BP-1C specifically targets JAK2Tyr1007/1008 phosphorylation, and inhibits its downstream STAT3Tyr705 signalling pathway to induce cell death. As a consequence, modulation in Akt/Src survival signal and altered expression of interwoven apoptotic genes were evident. The results were reproducible in an in-vivo LLC tumor model and in-ovo xenograft studies. The computational approaches viz, drug finger printing confers, BP-1C as novel class JAK2 inhibitor and molecular simulations studies assures its efficiency in binding with JAK2. Overall, BP-1C is a novel JAK2 inhibitor with experimental evidence and could be effectively developed into a promising drug for lung cancer treatment.

Complementarity principle in terms of electron density for the study of EGFR complexes.

The complementarity principle is a well-established concept in the field of chemistry and biology. This concept is widely studied as the lock-and-key relationship between two structures, such as enzyme and ligand interactions. These interactions are based on the overlap of electron clouds between two structures. In this study, a mathematical relation determining complementarity of intermolecular contacts in terms of overlaps of electron clouds was examined using a quantum orbital-free AlteQ method developed in-house for 64 EGFR-ligand complexes with experimentally measured binding affinity data. A very high correlation was found between the overlap of ligand and enzyme electron clouds and the calculated terms, providing a good basis for prognosis of bioactivity and for molecular docking studies.

Can natural products stop the SARS-CoV-2 virus? A docking and molecular dynamics study of a natural product database.

Background: The SARS-CoV-2 3CLpro is one of the primary targets for designing new and repurposing known drugs. Methodology: A virtual screening of molecules from the Natural Product Atlas was performed, followed by molecular dynamics simulations of the most potent inhibitor bound to two conformations of the protease and into two binding sites. Conclusion: Eight molecules with appropriate ADMET properties are suggested as potential inhibitors. The greatest benefit of this study is the demonstration that these ligands can bind in the catalytic site but also to the groove between domains II and III, where they interact with a series of residues which have an important role in the dimerization and the maturation process of the enzyme.

Network Pharmacology Approach Uncovering Pathways Involved in Targeting Hsp90 Through Curcumin and Epigallocatechin to Control Inflammation.

AIMS: To fetch pathways involved in targetting Hsp90 through Curcumin and Epigallocatechin through Network pharmacological approach. BACKGROUND: Hsp90 is a molecular chaperone involved in stabilizing inflammatory protein which may lead to chronic diseases. The herbal compounds Curcumin and Epigallocatechin processing antiinflammatory properties are known to follow a common pathway and control the expression of Hsp90. OBJECTIVE: To collect the gene targets of Hsp90, Curcumin and Epigallocatechin in order to understand protein-protein interactions of gene targets by constructing the interactome to identify the hub proteins. Hub proteins docking was performed with curcumin and epigallocatechin. Finally, hub proteins involvement with various human diseases were identified. METHODS: The gene targets of Hsp90, Curcumin and Epigallocatechin were obtained from there respective databases. Protein-protein interactions of Pkcδ-Nrf2 and Tlr4 pathway gene targets were collected from String database. Protein interaction network was constructed and merged to get intercession network in cytoscape and Cluego was used to predict the disease related target genes. Docking of ligands to target proteins was carried out using Autodock vina tool. RESULT: The main key regulators of Curcumin and Epigallocatechin were identified particularly from Pkcδ-Nrf2 and Tlr4 pathway. CONCLUSION: The combined action of Curcumin and Epigallocatechin can reduce the expression of Hsp90 eventually controlling the inflammation.

Protein-protein Interaction and Molecular Dynamics of Iturin A Gene on Effector Proteins of Phytophthora infestans.

AIM AND OBJECTIVES: Phytophthora infestans (Mont.) de Bary, the fungal pathogen causes late blight, which results in devastating economic loss among the Solanaceae. The bacillus lipopeptides show the antagonistic activity against the many plant pathogens, among bacillus lipopeptides reported as the antifungal gene. Hence, to understand the in silico antifungal activity, we have selected gene iturin A (AXN89987) produced by Bacillus spp to check the molecular dynamics study with the effector proteins of the P. infestanse. In this concern, known effector proteins of P. infestans were subjected to the protein-protein interaction followed by simulation. MATERIALS AND METHODS: Iturin A gene was amplified using the soil bacterium Bacillus subtilis with gene-specific primers, cloned into pTZ 57R/T vector and confirmed by sequencing. To get better insights, the protein model was developed for Iturin A using Modeller 9.17, using PDB structure of ID 4MRT (Phosphopantetheine transferase Sfp) and 1QR0 (4'-phosphopantetheinyl moiety of coenzyme A) as a template, it shared the identity 72% and expected P-value: 3e-121, respectively. The model quality was assessed using ProSA and PROCHECK programs. RESULTS: The potency of modelled protein against effector proteins of P. infestans were evaluated in silico using the HADDOCK server and the results showed the high affinity of towards the effector protein Host ATG8 (PDB-5L83). Finally, the simulation was performed to the docked conformation of with Host ATG8 to further understand the stability of the complex using the Desmond program. CONCLUSION: Altogether, the protein-protein interaction and simulation study propose a new methodology and to uncover possible antifungal activity of iturin A against effector proteins of P. infestans.

Computational insights into the binding mode of curcumin analogues against EP300 HAT domain as potent acetyltransferase inhibitors.

Acetylation plays a key role in maintaining and balancing cellular regulation and homeostasis. Acetyltransferases are an important class of enzymes which mediate this acetylation process. EP300 is a type 3 major lysine (K) acetyl transferase, and its aberrant activity is implicated in many human diseases. Hence, targeting EP300 mediated acetylation is a necessary step to control the associated diseases. Currently, a few EP300 inhibitors are known, among which curcumin is the most widely investigated molecule. However, due to its instability, chemical aggregation and reactivity, its inhibitory activity against the EP300 acetyltransferase domain is disputable. To address this curcumin problem, different curcumin analogues have been synthesized. These molecules were selected for screening against the EP300 acetyltransferase domain using in silico docking and MD analysis. We have successfully elucidated that the curcumin analogue CNB001 is a potential EP300 inhibitor with good drug-like characteristics.

Exploring the ethnomycological potential of Lentinus squarrosulus Mont. through GC-MS and chemoinformatics tools.

Deciphering the ethnopharmacological importance is one of the prime steps towards understanding the indigenous traditional medicines practised over the centuries. With the advent of modern techniques, it is possible to unravel and explore the hidden ethnopharmacological benefits, comprising complex bioactive compounds of substantial health benefits and together it helps to treat the complex diseases without any side effects as seen in the case of modern synthetic drugs. In this concern, the present study aims to identify the ethnomycologically significant mycocompounds derived from the fruiting body of wild edible macrofungi, Lentinus squarrosulus that contain a vast array of compounds with notable edibility and a wide spectrum of medicinal applications. Proper authentication of mushroom taxonomy was exclusively done using macro and microscopic observations combining ITS DNA-based methods. Further, the isolate was subjected to fractionation in different solvent systems for mycochemical examination followed by GC-MS analysis. A total of 38 mycocompounds were identified through GC-MS and further subjected to in silico studies for drug-likeness, bioactivity and ADMET predictions to explore the druggability of mycocompounds. In silico analysis revealed 10 mycocompounds having good drug-likeness and ADMET properties. Altogether, the present study explored the ethnomycological potential of L. squarrosulus and identified potential mycocompounds.

Exploring the Potential of Capsaicin Against Cancer Metastasis Based on TGF-ß Signaling Modulation Through Module-based Network Pharmacology Approachx.

BACKGROUND: Capsaicin is an active alkaloid /principal component of red pepper responsible for the pungency of chili pepper. Capsaicin by changing the intracellular redox homeostasis regulate a variety of signaling pathways ultimately producing a divergent cellular outcome. Several reports showed the potential of capsaicin against cancer metastasis, however unexplored molecular mechanism is still an active part of the research. Several growth factors have a critical role during cancer metastasis among them TGF- ß signaling play a vital role. METHODS: The present study aimed at analyzing capsaicin modulation of TGF-ß signaling using network pharmacology approach. The chemical and protein interaction data of capsaicin was curated and abstracted using STITCH4.0, PubChem and ChEMBL database. Further, the compiled data set was subjected to the pathway and functional enrichment analysis using Protein Analysis THrough Evolutionary Relationship (PANTHER) and, Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Meanwhile, the pattern of amino acid composition across the capsaicin targets was analyzed using the EMBOSS Pepstat tool. Capsaicin targets involved in TGF- ß were identified and their Protein-Protein Interaction (PPI) network constructed using STRING v10 and Cytoscape (v 3.2.1). From the above-constructed network, the clusters were mined using the MCODE clustering algorithm and finally binding affinity of capsaicin with its targets involved in TGF-ß signaling pathway was analyzed using Autodock Vina. RESULTS: The analysis explored capsaicin targets and, their associated functional and pathway annotations. Besides, the analysis also provides a detailed distinct pattern of amino acid composition across the capsaicin targets. The capsaicin targets described as MAPK14, JUN, SMAD3, MAPK3, MAPK1 and MYC involved in TGF-ß signaling pathway through pathway enrichment analysis. The binding mode analysis of capsaicin with its targets has shown high affinity with MAPK3, MAPK1, JUN and MYC. CONCLUSION: The study explores the potential of capsaicin as a potent modulator of TGF-ß signaling pathway during cancer metastasis and proposes new methodology and mechanism of action of capsaicin against TGF- ß signaling pathway.

A systems biology approach to identify the key targets of curcumin and capsaicin that downregulate pro-inflammatory pathways in human monocytes.

VEGFR1 (Flt-1), is a high-affinity tyrosine kinase receptor of VEGF found primarily on vascular endothelial cells. Recently, Flt-1 has shown to be expressed in human monocytes. However, the key intracellular signaling pathway mediated by Flt-1 receptor has been yet to be identified in monocytes. In this regard, using a robust systems biology approach, the key druggable target(s) involved in inflammatory angiogenesis mediated through VEGFR1 signaling was identified. Furthermore, experimental validation of key drug targets is conducted using PMA- and VEGF- stimulated human monocyte THP-1 cell lines. The key network pathways and corresponding disease modules were analyzed to identify the important biological processes perturbed in diseases. Using topological analysis, ICAM1 was identified as putative regulator of monocytes migration into tumor-micro environment. And these targets were examined by treating with curcumin and capsaicin molecules. Our results showed that these two molecules inhibited the over expression of targets such as ICAM1, Flt-1, and NF-κB in the VEGFR1 signalling pathway by reducing THP-1 chemotaxis. Besides, Curcumin and Capsaicin down-regulated expression of pro-inflammatory cytokines TNF-α, IL-6, and CXCL8/IL-8 and up regulated the expression of IL-10, a sign of lowered M1/M2 ratio relating to abrogation of inflammation.

Molecular docking analysis of curcumin analogues against kinase domain of ALK5.

During metastasis, cancer cells transcend from primary site to normal cells area upon attaining epithelial to mesenchymal transition (EMT) causing malignant cancer disease. Increased expression of TGF-ß and its receptor ALK5 is an important hallmark of malignant cancer. In the present study, efficacy of curcumin and its analogues as inhibitors of ALK5 (TGFßR-I) receptor was evaluated using in silico approaches. A total of 142 curcumin analogues and curcumin were retrieved from peer reviewed literature and constructed a combinatorial library. Further their drug-likeness was assessed using Molinspiration, cheminformatics and preADMET online servers. The interaction of 142 curcumin analogues and curcumin with ALK5 receptor was studied using Autodock Vina. This study revealed six curcumin analogues as promising ALK5 inhibitors with significant binding energy and H-bonding interaction.