Biology subjects

Sohraby, F.

Publications and source records attributed to Sohraby, F..

4 recordsLinked to original sources

bioRxiv2021

Reconstruction of the binding pathway of an anti-HIV drug, Indinavir, in complex with the HTLV-1 protease by Unaggregated Unbiased Molecular Dynamics simulation

Retroviruses are a growing concern for the health of human beings, and one of the dangerous members of this family is the Human T-cell Leukemia Virus 1 (HTLV-1) virus. It has affected more than 20 million people so far, and since there are no registered treatments against it yet, urgent treatment solutions are needed. One of the most promising drug targets to fight this virus is the protease enzyme of the viruss protein machinery. In this study, by utilizing a computational method called Unaggregated Unbiased Molecular Dynamics (UUMD), we reconstructed the binding pathway of a HTLV-1 protease inhibitor, Indinavir, to find the details of the binding pathway, the influential residues, and also the stable states of the binding pathway. We achieved the native conformation of the inhibitor in 6 rounds, 360 replicas by performing over 4 micro-seconds of UMD simulations. We found 3 Intermediate states between the solvated state and the native conformation state in the binding pathway. We also discovered that aromatic residues such as Trp98 and Trp98', catalytic residues Asp32 and Asp32', and the flap regions residues have the most influential roles in the binding pathway and also have the most contribution to the total interaction energies. We believe that the details found in this study would be a great guide for developing new treatment solutions against the HTLV-1 virus by inhibiting the HTLV-1 protease.

bioinformatics↗

bioRxiv2021

Comparative analysis of the unbinding pathways of antiviral drug Indinavir from HIV and HTLV1 proteases by Supervised Molecular Dynamics simulation

Determining the unbinding pathways of potential small molecule compounds from their target proteins is of great significance for designing efficacious treatment solutions. One of these potential compounds is the approved HIV-1 protease inhibitor, Indinavir, which has a weak effect on the HTLV-1 protease. In this work, by employing the SuMD method, we reconstructed the unbinding pathways of Indinavir from HIV and HTLV-1 proteases to compare and understand the mechanism of the unbinding and discover the reasons for the lack of inhibitory activity against the HTLV-1 protease. We achieved multiple unbinding events from both HIV and HTLV-1 proteases. Also, we found that the mobility and fluctuations of the flap region are higher in the HTLV-1 protease, making the drug less stable. We realized that critically positioned aromatic residues such as Trp98/Trp98' and Phe67/Phe67' in the HTLV-1 protease could make strong {pi}-Stacking interactions with Indinavir, which are unfavorable for the stability of Indinavir in the active site. The details found in this study can make a reasonable explanation for the lack of inhibitory activity of this drug against HTLV-1 protease. We believe the details discovered in this work can help design more effective and more selective inhibitors for the HTLV-1 protease.

bioinformatics↗

bioRxiv2020

Complete reconstruction of the unbinding pathway of an anticancer drug by conventional unbiased molecular dynamics simulation

Understanding the details of unbinding mechanism of small molecule drugs is an inseparable part of rational drug design. Reconstruction of the unbinding pathway of small molecule drugs, todays, can be achieved through molecular dynamics simulations. Nonetheless, simulating a process in which a drug unbinds from its receptor demands lots of time, mostly up to several milliseconds. This amount of time is neither reasonable nor affordable; therefore, many researchers utilize various biases that there are still many doubts about their trustworthiness. In this work we have utilized short-run simulations, replicas, to make such time-consuming process cost effective. By replicating those snapshots of the trajectories which, after careful analyses, were selected as potential candidates we increased our systems efficiency considerably. As a matter of fact, we have implemented a sort of human bias, inspecting trajectories visually, to achieve multiple unbinding events. We would like to call this stratagem, replicating of potent snapshots, "rational sampling" as it is, in fact, benefiting from human logic. In our case, an anticancer drug, the dasatinib, completely unbounded from its target protein, c-Src kinase, in only 392.6 ns, and this was gained without applying any internal biases and potentials which can increase error level. Thus, we achieved important structural details that can alter our viewpoint as well as assist drug designers.

bioinformatics↗

bioRxiv2019

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↗