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Aliyar, M.

Publications and source records attributed to Aliyar, M..

3 recordsLinked to original sources

Ultraefficient Unbiased Molecular Dynamics simulation of protein-ligand interactions: How profound yet affordable can it be?

Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased molecular dynamics simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased molecular dynamics simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) molecular dynamics simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical bindings process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nano-second timescales, surprisingly as little as [~]30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction.

bioinformatics

Identification of new inhibitors of the Toxoplasma gondii by using in-silico drug repurposing

IntroductionThe common treatment for toxoplasmosis was pyrimethamine. In recent years, it has been found that this parasite is getting resistant to this treatment, therefore urgent alternative treatments are needed. Material and MethodsIn this study, by using drug repurposing and in silico methods we tried to make a selective treatment by inhibiting the Calcium-Dependent Protein Kinase 1 from Toxoplasma gondii which doesnt exist in mammalians. We screened the FDA approved drugs by molecular docking and after ranking them by their binding energies and inspecting the top scored ones, we chose Cefpiramide, Ceftriaxone and Cefotiam as the hit compounds. After that, we used molecular dynamics simulations to test the hit compounds in a much more realistic environment. ResultsBy analyzing the results, we found that all of the hit compounds and good and can bind strongly to the active site of the protein. Therefore, they can be potential candidates for inhibiting Calcium-Dependent Protein Kinase 1 from Toxoplasma gondii. ConclusionMoreover, because the predicted compounds are FDA approved drugs, their toxicity profiles are well known and their newly predicted use can be tested in clinical trials.

bioinformatics

In-silico predictive identification of K-RasG12V inhibitors in natural compounds

As RAS protein is highly significant in signaling pathways, involving cell growth, differentiation and apoptosis; the Ras GTPase proteins play a significant as a master switch in the appearance of many diseases, including 20-30% of all cancers. So, the K-RasG12V mutant was selected as a drug target in present study. This mutant is involved in gastric cancer, lung and pancreatic carcinoma, and colon cancers. So, we employed the structure-based drug design methods and molecular dynamics simulations to undergo virtual screening on natural products small molecules and predicted some new potent therapeutic inhibitors. Finally, ZINC15671852, ZINC85592862, ZINC85567582 and ZINC03616630 final Hits were identified as potent inhibitors from among more than 79,000 bioactive compounds from natural resource. Molecular Mechanics Poisson-Boltzmann Surface Area (MM-P/GBSA) calculation results have also demonstrated that these molecules obtained higher binding free energy than co-crystalized reference ligand.

bioinformatics