Breast cancer in woman is the most common cancer and in 2018 there were around 2 million new cases recorded. The maximum rate of breast cancer is reported in Belgium followed by Luxembourg. It is the second most general cancer, Lung cancer being the first. If the cancer tumor is located only in the breast, the survival rate would be 99%. If the tumor has wide to lymph nodes around the survival rate would be 85% and if the tumor had extend to distant parts, the survival rate would come down to 27%. Mammary gland is an important organ in mammals which has potential function to secrete, synthesize and deliver milk to the infants for nourishment, improvement and protection. Generally, cancer is named after the body part in which it originated; thus, breast cancer refers to the erratic development and proliferation of cells that originate in the breast tissue (7). There are some kinds of tumors that may grow within various areas of the breast. Most tumors are the outcome of benign (non-cancerous) alters within the breast. The estrogen receptors (ER) in ordinary and diseased states are significant for the improvement of relevant therapeutic strategies. Two main forms of ER exist, ERα and ERβ, which are encoded by separate genes. Estrogens play a central role in breast cancer improvement with ERα status being the mainly significant predictor of breast cancer prognosis. The potent lead molecule binding mode, residue-interaction patterns and docking energy were examined by molecular docking and binding free energy studies. The lead compounds and 3ERT complex structural stability and dynamic behavior were monitored by molecular dynamics analysis. The drug-likeness properties of lead compounds were predicted ADME analysis.

Type 2 diabetes is one of the biggest health challenges in the world and WHO projects it to be the 7th leading cause of death in 2030. It is a chronic condition affecting the way our body metabolizes sugar. Insulin resistance is high risk factor marked by expression of Lipoprotein Lipases and Peroxisome Proliferator-Activated Receptor that predisposes to type 2 diabetes. AMP-dependent protein kinase in AMPK signaling pathway is a central sensor of energy status. Deregulation of AMPK signaling leads to inflammation, oxidative stress, and deactivation of autophagy which are implicated in pathogenesis of insulin resistance. SIRT4 protein deactivates AMPK as well as directly inhibits insulin secretion. SIRT4 overexpression leads to dyslipidimeia, decreased fatty acid oxidation, and lipogenesis which are the characteristic features of insulin resistance promoting type 2 diabetes. This makes SIRT4 a novel therapeutic target to control type 2 diabetes. Virtual screening and molecular docking studies were performed to obtain potential ligands. To further optimize the geometry of protein–ligand complexes Quantum Polarized Ligand Docking was performed. Binding Free Energy was calculated for the top three ligand molecules. In view of exploring the stereoelectronic features of the ligand, density functional theory approach was implemented at B3LYP/6-31G* level. 30 ns MD simulation studies of the protein–ligand complexes were done. The present research work proposes ZINC12421989 as potential inhibitor of SIRT4 with docking score (−7.54 kcal/mol), docking energy (−51.34 kcal/mol), binding free energy (−70.21 kcal/mol), and comparatively low energy gap (−0.1786 eV) for HOMO and LUMO indicating reactivity of the lead molecule.

Lymphatic filariasis is a debilitating vector borne parasitic disease that infects human lymphatic system by nematode Brugia malayi. Currently available anti-filarial drugs are effective only on the larval stages of parasite. So far, no effective drugs are available for humans to treat filarial infections. In this regard, aspartate semialdehyde dehydrogenase (ASDase) in lysine biosynthetic pathway from Wolbachia endosymbiont Brugia malayi represents an attractive therapeutic target for the development of novel anti-filarial agents. In this present study, molecular modeling combined with molecular dynamics simulations and structure-based virtual screening were performed to identify potent lead molecules against ASDase. Based on Glide score, toxicity profile, binding affinity and mode of interactions with the ASDase, five potent lead molecules were selected. The molecular docking and dynamics results revealed that the amino acid residues Arg103, Asn133, Cys134, Gln161, Ser164, Lys218, Arg239, His246, and Asn321 plays a crucial role in effective binding of Top leads into the active site of ASDase. The stability of the ASDase-lead complexes was confirmed by running the 30 ns molecular dynamics simulations. The pharmacokinetic properties of the identified lead molecules are in the acceptable range. Furthermore, density functional theory and binding free energy calculations were performed to rank the lead molecules. Thus, the identified lead molecules can be used for the development of anti-filarial agents to combat the pathogenecity of Brugia malayi.

Serratia marcescens, rod-shaped Gram-negative bacteria is classified as an opportunistic pathogen in the family Enterobacteriaceae. It causes a wide variety of infections in humans, including urinary, respiratory, ocular lens and ear infections, osteomyelitis, endocarditis, meningitis and septicemia. Unfortunately, over the past decade, antibiotic resistance has become a serious health care issue; the effective means to control and dissemination of S. marcescens resistance is the need of hour. The whole genome sequencing of S. marcescens FGI94 strain contains 4434 functional proteins, among which 690 (15.56%) proteins were classified under hypothetical. In the present study, we applied the power of various bioinformatics tools on the basis of protein family comparison, motifs, functional properties of amino acids and genome context to assign the possible functions for the HPs. The pseudo sequences (protein sequence that contain ≤100 amino acid residues) are eliminated from the study. Although we have successfully predicted the function for 483 proteins, we were able to infer the high level of confidence only for 108 proteins. The predicted HPs were classified into various classes such as enzymes, transporters, binding proteins, cell division, cell regulatory and other proteins. The outcome of the study could be helpful to understand the molecular mechanism in bacterial pathogenesis and also provide an insight into the identification of potential targets for drug and vaccine development.