Dataset Information

Molecular Dynamics Simulations Identify Tractable Lead-like Phenyl-Piperazine Scaffolds as eIF4A1 ATP-competitive Inhibitors.

ABSTRACT: eIF4A1 is an ATP-dependent RNA helicase whose overexpression and activity have been tightly linked to oncogenesis in a number of malignancies. An understanding of the complex kinetics and conformational changes of this translational enzyme is necessary to map out all targetable binding sites and develop novel, chemically tractable inhibitors. We herein present a comprehensive quantitative analysis of eIF4A1 conformational changes using protein-ligand docking, homology modeling, and extended molecular dynamics simulations. Through this, we report the discovery of a novel, biochemically active phenyl-piperazine pharmacophore, which is predicted to target the ATP-binding site and may serve as the starting point for medicinal chemistry optimization efforts. This is the first such report of an ATP-competitive inhibitor for eiF4A1, which is predicted to bind in the nucleotide cleft. Our novel interdisciplinary pipeline serves as a framework for future drug discovery efforts for targeting eiF4A1 and other proteins with complex kinetics.

SUBMITTER: Essegian DJ

PROVIDER: S-EPMC8482399 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Molecular Dynamics Simulations Identify Tractable Lead-like Phenyl-Piperazine Scaffolds as eIF4A1 ATP-competitive Inhibitors.

Essegian Derek J DJ Cunningham Tyler A TA Zerio Christopher J CJ Chapman Eli E Schatz Jonathan J Schürer Stephan C SC

ACS omega 20210915 38

eIF4A1 is an ATP-dependent RNA helicase whose overexpression and activity have been tightly linked to oncogenesis in a number of malignancies. An understanding of the complex kinetics and conformational changes of this translational enzyme is necessary to map out all targetable binding sites and develop novel, chemically tractable inhibitors. We herein present a comprehensive quantitative analysis of eIF4A1 conformational changes using protein-ligand docking, homology modeling, and extended mole ...[more]

PMID: 34604625

Similar Datasets

Project description:In drug design, chemical groups are sequentially added to improve a weak-binding fragment into a tight-binding lead molecule. Often, the direction to make these additions is unclear, and there are numerous chemical modifications to choose. Lead development can be guided by crystal structures of the fragment-bound protein, but this alone is unable to capture structural changes like closing or opening of the binding site and any side-chain movements. Accounting for adaptation of the site requires a dynamic approach. Here, we use molecular dynamics calculations of small organic solvents with protein-fragment pairs to reveal the nearest "hot spots". These close hot spots show the direction to make appropriate additions and suggest types of chemical modifications that could improve binding affinity. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that is well established for finding binding "hot spots" in active sites and allosteric sites of proteins. We simulated 20 fragment-bound and apo forms of key pharmaceutical targets to map out hot spots for potential lead space. Furthermore, we analyzed whether the presence of a fragment facilitates the probes' binding in the lead space, a type of binding cooperativity. To the best of our knowledge, this is the first use of cosolvent MD conducted with bound inhibitors in the simulation. Our work provides a general framework to extract molecular features of binding sites to choose chemical groups for growing lead molecules. Of the 20 systems, 17 systems were well mapped by MixMD. For the three not-mapped systems, two had lead growth out into solution away from the protein, and the third had very small modifications which indicated no nearby hot spots. Therefore, our lack of mapping in three systems was appropriate given the experimental data (true-negative cases). The simulations are run for very short time scales, making this method tractable for use in the pharmaceutical industry.

Dataset Information

Molecular Dynamics Simulations Identify Tractable Lead-like Phenyl-Piperazine Scaffolds as eIF4A1 ATP-competitive Inhibitors.

Publications

Molecular Dynamics Simulations Identify Tractable Lead-like Phenyl-Piperazine Scaffolds as eIF4A1 ATP-competitive Inhibitors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets