Protein-ligand interaction is an imperative subject in structure-based drug design and protein function prediction process. Molecular docking is a computational method which predicts the binding of a ligand molecule to the particular receptor. It predicts the binding pose, strength and binding affinity of the molecules using various scoring functions. Molecular docking and molecular dynamics simulations are widely used in combination to predict the binding modes, binding affinities and stability of different protein-ligand systems. With advancements in algorithms and computational power, molecular dynamics simulation is now a fundamental tool to investigative bio-molecular assemblies at atomic level. These methods in association with experimental support have been of great value in modern drug discovery and development. Nowadays, it has become an increasingly significant method in drug discovery process. In this review, we focus on protein-ligand interactions using molecular docking, virtual screening and molecular dynamics simulations. Here, we cover an overview of the available methods for molecular docking and molecular dynamics simulations, and their advancement and applications in the area of modern drug discovery. The available docking software and their advancement including application examples of different approaches for drug discovery are also discussed. We have also introduced the physicochemical foundations of molecular docking and simulations, mainly from the perception of bio-molecular interactions.

Exploring protein–ligand interactions is a subject of immense interest, as it provides deeper insights into molecular recognition, mechanism of interaction and subsequent functions. Predicting an accurate model for a protein–ligand interaction is a challenging task. Molecular docking is a computational method used for predicting the preferred orientation, binding conformations and the binding affinity of a ligand to a macromolecular target, especially protein. It has been applied in ‘virtual high-throughput screening’ of chemical libraries containing millions of compounds to find potential leads in drug design and discovery. Here, we have developed InstaDock, a free and open access Graphical User Interface (GUI) program that performs molecular docking and high-throughput virtual screening efficiently. InstaDock is a single-click GUI that uses QuickVina-W, a modified version of AutoDock Vina for docking calculations, made especially for the convenience of non-bioinformaticians and for people who are not experts in using computers. InstaDock facilitates onboard analysis of docking and visual results in just a single click. To sum up, InstaDock is the easiest and more interactive interface than ever existing GUIs for molecular docking and high-throughput virtual screening. InstaDock is freely available for academic and industrial research purposes via https://hassanlab.org/instadock.

A sedentary lifestyle or lack of physical activity increases the risk of different diseases, including obesity, diabetes, heart diseases, certain types of cancers, and some neurological diseases. Physical exercise helps improve quality of life and reduces the risk of many diseases. Irisin, a hormone induced by exercise, is a fragmented product of FNDC5 (a cell membrane protein) and acts as a linkage between muscles and other tissues. Over the past decade, it has become clear that irisin is a molecular mimic of exercise and shows various beneficial effects, such as browning of adipocytes, modulation of metabolic processes, regulation of bone metabolism, and functioning of the nervous system. Irisin has a role in carcinogenesis; numerous studies have shown its impact on migration, invasion, and proliferation of cancer cells. The receptor of irisin is not completely known; however, in some tissues it probably acts via a specific class of integrin receptors. Here, we review research from the past decade that has identified irisin as a potential therapeutic agent in the prevention or treatment of various metabolic-related and other diseases. This article delineates structural and biochemical aspects of irisin and provides an insight into the role of irisin in different pathological conditions.

Serum and glucocorticoid-regulated kinase 1 (SGK1) is a serine/threonine kinase that works under acute transcriptional control by several stimuli, including serum and glucocorticoids. It plays a significant role in the cancer progression and metastasis, as it regulates inflammation, apoptosis, hormone release, neuro-excitability, and cell proliferation. SGK1 has recently been considered as a potential drug target for cancer, diabetes, and neurodegenerative diseases. In the present study, we have performed structure-based virtual high-throughput screening of natural compounds from the ZINC database to find potential inhibitors of SGK1. Initially, hits were selected based on their physicochemical, absorption, distribution, metabolism, excretion, and toxicity (ADMET), and other drug-like properties. Afterwards, PAINS filter, binding affinities estimation, and interaction analysis were performed to find safe and effective hits. We found four compounds bearing appreciable binding affinity and specificity towards the binding pocket of SGK1. The docking results were complemented by all-atom molecular dynamics simulation for 100 ns, followed by MM/PBSA, and principal component analysis to investigate the conformational changes, stability, and interaction mechanism of SGK1 in-complex with the selected compound ZINC00319000. Molecular dynamics simulation results suggested that the binding of ZINC00319000 stabilizes the SGK1 structure, and it leads to fewer conformational changes. In conclusion, the identified compound ZINC00319000 might be further exploited as a scaffold to develop promising inhibitors of SGK1 for the therapeutic management of associated diseases, including cancer.

Due to the lack of efficient therapeutic options and clinical trial limitations, the FDA approved drugs can be a good choice to handle Coronavirus disease (COVID-19). Many reports have enough evidence for the use of FDA-approved drugs which have inhibitory potential against target proteins of SARS-CoV-2. Here, we utilized a structure-based drug design approach to find possible drug candidates from the existing pool of FDA-approved drugs and checked their effectiveness against the SARS-CoV-2. We performed virtual screening of the FDA approved drugs against the main protease (Mpro) of SARS-CoV-2, an essential protein, and a potential drug target. Using well-defined computational methods, we identified Glecaprevir and Maraviroc as the best inhibitors CoV-2 Mpro. Both drugs bind to the substrate-binding pocket of SARS-CoV-2 Mpro and form a significant number of non-covalent interactions. Glecaprevir and Maraviroc bind to the conserved substrate-binding pocket of SARS-CoV-2 M^pro. This work provides sufficient evidence for the use of Glecaprevir and Maraviroc for the therapeutic management of COVID-19.