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This review gives an overview about the some of the most important possible analyzes, technical challenges, and existing protocols that can be performed on the biological membrane by the molecular dynamics simulation.

Non-Structural Protein 16 (nsp-16), a viral RNA methyltransferase (MTase), is one of the highly viable targets for drug discovery of coronaviruses including SARS-CoV-2. In this study, drug discovery of SARS-CoV-2 nsp-16 has been performed by a virtual drug repurposing approach. First, drug shapebased screening (among FDA approved drugs) with a known template of MTase inhibitor, sinefungin was done and best compounds with high similarity scores were selected. In addition to the selected compounds, 4 nucleoside analogs of anti-viral (Raltgravir, Maraviroc and Favipiravir) and anti-inflammatory (Prednisolone) drugs were selected for further investigations. Then, binding energies and interaction modes were found by molecular docking approaches and compouds with lower energy were selected for further investigation. After that, Molecular dynamics (MD) simulation was carried to test the potential selected compounds in a realistic environment. The results showed that Raltegravir and Maraviroc among other compounds can bind strongly to the active site of the protein compared to sinefungin, and can be potential candidates to inhibit NSP-16. Also, the MD simulation results suggested that the Maraviroc and Raltegravir are more effective drug candidates than Sinefungin for inhibiting the enzyme. It is concluded that Raltegravir and Maraviroc which may be used in the treatment of COVID-19 after Invitro and invivo studies and clinical trial for final confirmation of drug effectiveness.

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Several studies have shown that testis-specific gene antigen (TSGA10) could be considered as a cancer testis antigen (CTA), except for one study which has identified it as a tumor suppressor gene. In order to exert its function, TSGA10 interacts closely with hypoxia inducible factor (HIF-1α) and since this interaction is still not completely defined, the exact role of TSGA10 in angiogenesis and invasion is also under question. The current study was conducted to investigate the function of TSGA10 gene and evaluate its potential effects on tumor angiogenesis and invasion. To do so, TSGA10 vector was designed for a stable transfection in HeLa cells, and then clonal selection was applied. The efficiency of transfection and the role of TSGA10 in abovementioned targets were evaluated by real-time PCR, western blot, zymography and ELISA tests in both normoxia and hypoxia. Invasion, migration and angiogenesis were assessed. Three-dimensional model of TSGA10 protein was accurately built in which TSGA10 docked to 2 domains of HIF-1α. Increased expression of TSGA10 correlated with decreased HIF-1α transcriptional activity and inhibited angiogenesis and HeLa cells invasion in normoxia as well as hypoxia. Docking analysis indicated that binding affinity of TSGA10 with TAD-C (CBP) domain of HIF-1α would be stronger than that with PAS-B domain. Our findings showed that overexpression of TSGA10 would induce disruption of HIF-1α axis and exert potent inhibitory effects on tumor angiogenesis and metastasis. Therefore, TSGA10 could be considered as a potent therapeutic candidate, prognostic factor and a cancer management tool.

Principal component analysis (PCA), as a well-known multivariate data analysis and data reduction technique, is an important and useful algebraic tool in drug design and discovery. PCA, in a typical quantitative structure-activity relationship (QSAR) study, analyzes an original data matrix in which molecules are described by several intercorrelated quantitative dependent variables (molecular descriptors). Although extensively applied, there is disparity in the literature with respect to the applications of PCA in the QSAR studies. This study investigates the different applications of PCA in QSAR studies using a dataset including CCR5 inhibitors. The different types of preprocessing are used to compare the PCA performances. The use of PC plots in the exploratory investigation of matrix of descriptors is described. This work is also proved PCA analysis to be a powerful technique for exploring complex datasets in QSAR studies for identification of outliers. This study shows that PCA is able to easily apply to the pool of calculated structural descriptors and also the extracted information can be used to help decide upon an appropriate harder model for further analysis.

In this study, homology modeling, molecular docking and molecular dynamics simulation were performed to explore structural features and binding mechanism of some inhibitors of chemokine receptor type 5 (CCR5), and to construct a model for designing new CCR5 inhibitors for preventing HIV attachment to the host cell. A homology modeling procedure was employed to construct a 3D model of CCR5. For this procedure, the X-ray crystal structure of bovine rhodopsin (1F88A) at 2.80Å resolution was used as template. After inserting the constructed model into a hydrated lipid bilayer, a 20ns molecular dynamics (MD) simulation was performed on the whole system. After reaching the equilibrium, twenty-four CCR5 inhibitors were docked in the active site of the obtained model. The binding models of the investigated antagonists indicate the mechanism of binding of the studied compounds to the CCR5 obviously. Moreover, 3D pictures of inhibitor-protein complex provided precious data regarding the binding orientation of each antagonist into the active site of this protein. One additional 20 ns MD simulation was performed on the initial structure of the CCR5-ligand 21 complex, resulted from the previous docking calculations, embedded in a hydrated POPE bilayer to explore the effects of the presence of lipid bilayer in the vicinity of CCR5-ligand complex. This article is part of a Special Issue entitled Protein translocation across or insertion into membranes.

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