Peptogrid—rescoring function for autodock vina to identify new bioactive molecules from short peptide libraries
Zalevskij 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.
Molecules
Vol.24, Issue2, Num.277
Опубликовано: 2019
Тип ресурса: Статья
DOI:10.3390/molecules24020277
Аннотация:
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. © 2019 by the authors.
Ключевые слова:
Danio rerio; Docking; Gabab receptor; Peptides; Rescoring
peptide; algorithm; animal; chemistry; computer simulation; drug development; molecular docking; molecular dynamics; peptide library; reproducibility; structure activity relation; zebra fish; Algorithms; Animals; Computer Simulation; Drug Discovery; Molecular Docking Simulation; Molecular Dynamics Simulation; Peptide Library; Peptides; Reproducibility of Results; Structure-Activity Relationship; Zebrafish
Язык текста: Английский
ISSN: 1420-3049
Zalevskij A. O. Artur Olegovich 1990-
Zlobin A. S.
Gedzun V. R.
Reshetnikov R. V. Roman Vladimirovich 1979-
Lovat M. L.
Malyshev A. V.
Doronin I. I.
Babkin G. A.
Golovin A. V. Andrej Viktorovich 1975-
Залевский А. О. Артур Олегович 1990-
Злобин А. С.
Гедзун В. Р.
Решетников Р. В. Роман Владимирович 1979-
Ловат М. Л.
Малyшев А. В.
Доронин И. И.
Бабкин Г. А.
Головин А. В. Андрей Викторович 1975-
Peptogrid—rescoring function for autodock vina to identify new bioactive molecules from short peptide libraries
Текст визуальный непосредственный
Molecules
Springer-Verlag GmbH
Vol.24, Issue2 Num.277
2019
Статья
Danio rerio Docking Gabab receptor Peptides Rescoring
peptide algorithm animal chemistry computer simulation drug development molecular docking molecular dynamics peptide library reproducibility structure activity relation zebra fish Algorithms Animals Computer Simulation Drug Discovery Molecular Docking Simulation Molecular Dynamics Simulation Peptide Library Peptides Reproducibility of Results Structure-Activity Relationship Zebrafish
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. © 2019 by the authors.