Biology subjects

Aryapour, H.

Publications and source records attributed to Aryapour, H..

7 recordsLinked to original sources

bioRxiv2022

Comparative study of the unbinding process of some HTLV-1 protease inhibitors using Unbiased Molecular Dynamics simulation

The HTLV-1 protease is one of the major antiviral targets to overwhelm this virus. Several research groups have been developing protease inhibitors over the years, but none has been successful. In this regard, the development of new HTLV-1 protease inhibitors based on fixing the defects of previous inhibitors will overcome the absence of curative treatment for this oncovirus. Thus, we decided to study the unbinding pathways of the most potent (compound 10, Ki = 15 nM) and one of the weakest (compound 9, Ki = 7900 nM) protease inhibitors, which are very structurally similar, with the PDB IDs: 4YDG, 4YDF, using the Supervised Molecular Dynamics (SuMD) method. In this project, we had various short and long-time-scale simulations, that in total, we could have 12 successful unbindings (a total of 14.8 s) for the two compounds in both mp forms. This comparative study measured all the essential factors simultaneously in two different inhibitors, which improved our results. This study revealed that Asp32 or Asp32' in the two forms of mp state similarly exert super power effects on maintaining both potent and weak inhibitors in the binding pocket of HTLV-1 protease. In parallel with the important impact of these two residues, in the potent inhibitors unbinding process, His66' was a great supporter, that was absent in the weak inhibitors unbinding pathway. In contrast, in the weak inhibitors unbinding process, Trp98/Trp98' by pi-pi stacking interactions were unfavorable for the stability of the inhibitor in the binding site. In our opinion, these results will assist in designing more potent and effective inhibitors for the HTLV-1 protease.

bioinformatics↗

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↗

bioRxiv2019

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↗

bioRxiv2018

Are Zinc oxide nanoparticles safe? A structural study on human serum albumin using in vitro and in silico methods

With due attention to adsorption of proteins on the nanoparticles surface and the formation of nanoparticle-protein corona, investigation of nanoparticles toxicity on the structure of proteins is important. Therefore, this work was done to evaluate toxicity of Zinc oxide nanoparticles (ZnO NPs) on the structure of human serum albumin (HSA) through in vitro and in silico studies. First, ZnO NPs were synthesized using hydrothermal method and their size and morphology were determined by SEM and TEM methods and then to study its toxicity on the HSA structure were used UV-Vis and fluorescence spectroscopy. Also, in order to investigate interaction mechanism of ZnO NP with HSA at the atomistic level was used molecular dynamics (md) simulation. The obtained images from SEM and TEM showed that ZnO NPs were nanosheet with size of less than 40 nm. The results of spectroscopic studies showed ZnO NPs lead to significant conformational changes in the proteins absorption and emission spectra. Moreover, md results showed the minor structure changes in HSA due to interaction with ZnO NP during the 100 ns simulation and the formation of nanoparticle-protein corona complex that is mainly because of electrostatic interactions between charge groups of HSA and ZnO NP.

biochemistry↗