Next Article in Journal
Biochemical Basis of Anti-Cancer-Effects of Phloretin—A Natural Dihydrochalcone
Previous Article in Journal
Anti-Arthritis Effect through the Anti-Inflammatory Effect of Sargassum muticum Extract in Collagen-Induced Arthritic (CIA) Mice
Previous Article in Special Issue
Toward of Safer Phenylbutazone Derivatives by Exploration of Toxicity Mechanism
Article Menu
Issue 2 (January-2) cover image

Export Article

Open AccessCommunication
Molecules 2019, 24(2), 277;

PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries

Faculty of Bioengineering, Lomonosov Moscow State University, Moscow 119234, Russia
Ineractomics Lab, Institute of Molecular Medicine, Sechenov First Moscow State Medical University, Moscow 119146, Russia
Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow 117997, Russia
Lactocore Inc., Plymouth, MI 48170, USA
Department of Human and Animal Physiology, Faculty of Biology, Lomonosov Moscow State University, Moscow 119899, Russia
Faculty of Computer Science, National Research University Higher School of Economics, Moscow 101000, Russia
Author to whom correspondence should be addressed.
Received: 26 November 2018 / Revised: 5 January 2019 / Accepted: 9 January 2019 / Published: 13 January 2019
(This article belongs to the Special Issue Computational Approaches for Drug Discovery)
Full-Text   |   PDF [2074 KB, uploaded 13 January 2019]   |  


Peptides are promising drug candidates due to high specificity and standout safety. Identification of bioactive peptides de novo using molecular docking is a widely used approach. However, current scoring functions are poorly optimized for peptide ligands. In this work, we present a novel algorithm PeptoGrid that rescores poses predicted by AutoDock Vina according to frequency information of ligand atoms with particular properties appearing at different positions in the target protein’s ligand binding site. We explored the relevance of PeptoGrid ranking with a virtual screening of peptide libraries using angiotensin-converting enzyme and GABAB receptor as targets. A reasonable agreement between the computational and experimental data suggests that PeptoGrid is suitable for discovering functional leads. View Full-Text
Keywords: docking; peptides; rescoring; gabab receptor; Danio rerio docking; peptides; rescoring; gabab receptor; Danio rerio

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary materials


Share & Cite This Article

MDPI and ACS Style

Zalevsky, A.O.; Zlobin, A.S.; Gedzun, V.R.; Reshetnikov, R.V.; Lovat, M.L.; Malyshev, A.V.; Doronin, I.I.; Babkin, G.A.; Golovin, A.V. PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries. Molecules 2019, 24, 277.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Molecules EISSN 1420-3049 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top