Shedding Light on the Molecular Recognition of Sub-Kilodalton Macrocyclic Peptides on Thrombin by Supervised Molecular Dynamics.

Front Mol Biosci

Molecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.

Published: August 2021

AI Article Synopsis

  • Macrocycles are promising for drug development due to their ability to bind to flat surfaces and disrupt protein-protein interactions.
  • Recent efforts have produced diverse libraries of low-molecular-weight macrocycles with therapeutic potential.
  • The SuMD computational protocol effectively reproduced the binding state of a macrocyclic peptide in a thrombin active site, demonstrating its utility for studying macrocycle-protein interactions efficiently.

Article Abstract

Macrocycles are attractive structures for drug development due to their favorable structural features, potential in binding to targets with flat featureless surfaces, and their ability to disrupt protein-protein interactions. Moreover, large novel highly diverse libraries of low-molecular-weight macrocycles with therapeutically favorable characteristics have been recently established. Considering the mentioned facts, having a validated, fast, and accurate computational protocol for studying the molecular recognition and binding mode of this interesting new class of macrocyclic peptides deemed to be helpful as well as insightful in the quest of accelerating drug discovery. To that end, the ability of the in-house supervised molecular dynamics protocol called SuMD in the reproduction of the X-ray crystallography final binding state of a macrocyclic non-canonical tetrapeptide-from a novel library of 8,988 sub-kilodalton macrocyclic peptides-in the thrombin active site was successfully validated. A comparable binding mode with the minimum root-mean-square deviation (RMSD) of 1.4 Å at simulation time point 71.6 ns was achieved. This method validation study extended the application domain of the SuMD sampling method for computationally cheap, fast but accurate, and insightful macrocycle-protein molecular recognition studies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438215PMC
http://dx.doi.org/10.3389/fmolb.2021.707661DOI Listing

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