In Silico Screening of Quorum Sensing Inhibitor Candidates Obtained by Chemical Similarity Search.

Quorum sensing (QS) is a bacterial communication using signal molecules, by which they sense population density of their own species, leading to group behavior such as biofilm formation and virulence. Autoinducer-2 (AI2) is a QS signal molecule universally used by both gram-positive and gram-negative bacteria. Inhibition of QS mediated by AI2 is important for various practical applications, including prevention of gum-disease caused by biofilm formation of oral bacteria. In this research, molecular docking and molecular dynamics (MD) simulations were performed for molecules that are chemically similar to known AI2 inhibitors that might have a potential to be quorum sensing inhibitors. The molecules that form stable complexes with the AI2 receptor protein were found, suggesting that they could be developed as a novel AI2 inhibitors after further in vitro validation. The result suggests that combination of ligand-based drug design and computational methods such as MD simulation, and experimental verification, may lead to development of novel AI inhibitor, with a broad range of practical applications.

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.

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 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.