The benzosulfonamide and heterocyclic nitrogen moieties may be considered as pharmacophores for designing new anticancer leads with better docking score and admissible ADME properties. Our study helps in the identification of potential inhibitors against Rab38 and melanoma cancer.
Cancer is a class of diseases characterized by uncontrolled cell growth. Every year more than 2 million people are affected by the disease. Rho family proteins are actively involved in cytoskeleton regulation. Over-expression of Rho family proteins show oncogenic activity and promote cancer progression. In the present work RhoG protein is considered as novel target of cancer. It is a member of Rho family and Rac subfamily protein, which plays pivotal role in regulation of microtubule formation, cell migration and contributes in cancer progression. In order to understand the binding interaction between RhoG protein and the DH domain of Ephexin-4 protein, the 3D structure of RhoG was evaluated and Molecular Dynamic Simulations was performed to stabilize the structure. The 3D structure of RhoG protein was validated and active site identified using standard computational protocols. Protein-protein docking of RhoG with Ephexin-4 was done to understand binding interactions and the active site structure. Virtual screening was carried out with ligand databases against the active site of RhoG protein. The efficiency of virtual screening is analysed with enrichment factor and area under curve values. The binding free energy of docked complexes was calculated using prime MM-GBSA module. The SASA, FOSA, FISA, PISA and PSA values of ligands were carried out. New ligands with high docking score, glide energy and acceptable ADME properties were prioritized as potential inhibitors of RhoG protein.
Keratinocyte growth factor (KGF) protein is a member of the fibroblast growth factor (FGF) family, which is also known as FGF-7. The FGF-7 plays an important role in tumor angiogenesis. In the present work, FGF-7 is treated as a potential therapeutic target to prevent angiogenesis in cancerous tissue. Computational techniques are applied to evaluate and validate the 3D structure of FGF-7 protein. The active site region of the FGF-7 protein is identified based on hydrophobicity calculations using CASTp and Q-site Finder active site prediction tools. The protein-protein docking study of FGF-7 with its natural receptor FGFR2b is carried out to confirm the active site region in FGF-7. The amino acid residues Asp34, Arg67, Glu116, and Thr194 in FGF-7 interact with the receptor protein (FGFR2b). A grid is generated at the active site region of FGF-7 using Glide module of Schrödinger suite. Subsequently, a virtual screening study is carried out at the active site using small molecular structural databases to identify the ligand molecules. The binding interactions of the ligand molecules, with piperazine moiety as a pharmacophore, are observed at Arg67 and Glu149 residues of the FGF-7 protein. The identified ligand molecules against the FGF-7 protein show permissible pharmacokinetic properties (ADME). The ligand molecules with good docking scores and satisfactory pharmacokinetic properties are prioritized and identified as novel ligands for the FGF-7 protein in cancer therapy.
The development of novel antituberculosis therapeutic molecules is a global health concern. Complex gene expression in Mycobacterium tuberculosis is mediated mainly by various sigma factors. The SigK protein binds to RNA polymerase, facilitating the expression of genes encoding the antigenic proteins mpt70 and mpt83. The anti-SigK protein is a negative regulator of SigK and inhibits the initiation of transcription. This study focuses on the interactions between SigK and the N-terminal domain of anti-SigK. The 3D structures of SigK (187 residues) and the N-terminal domain of anti-SigK (92 residues) are elucidated, using the crystal structures of the A and B chains of sigma E and anti-sigma ChrR of Rhodobacter spheroides (PDB code: 2Q1Z) as templates, respectively. Molecular dynamic simulations were performed for the SigK and anti-SigK proteins to refine their structures. The predicted active sites of SigK and anti-SigK and the results of protein-protein docking studies revealed the residues that are important for binding. The models generated and the binding site residues identified in this work throw new light on the interactions between the sigma K and anti-sigma K proteins, which should further aid the modulation of antigenic protein production in Mycobacterium tuberculosis.
The present study treats Suppressor of cytokine signalling 3 (SOCS-3) as a novel target for type 2 diabetes mellitus (T2DM) drug discovery. An in silico 3D structural evaluation and validation of the SOCS-3 and its cognate receptor, Insulin Receptor Beta (IRÀB) was carried out. The active site of SOCS-3 was identified using computational tools and Protein-Protein docking with IRÀB. The docking study with T2DM drugs and corroborating with the results of virtual screening using small molecules, ratify the residues of the catalytic site of SOCS-3, i. e. Arg-71 along with Asp-72, Ser-73, Ser-74, and Asp-92, to facilitate the binding. The T2DM drugs which belong to Sulfonylureas class show partial affinity towards SOCS-3. The ligands show acceptable pharmacokinetic properties in terms of Lipinski's rule of 5, Jorgensen's rule of 3, brain/blood partition coefficient, binding to human serum albumin and skin permeability. The identified ligands show good predicted IC 50 values and hence can act as SOCS-3 antagonists. The structural data of SOCS-3 active site and the identified ligands are useful in development of new T2DM therapeutics.
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