ArticleMolecules (Basel, Switzerland)2019
PeptoGrid-Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries.
Article in Molecules (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Advances in Discovery and Design of Anti-influenza Virus Peptides.Current medicinal chemistry · 2026Review
- A New Advanced Approach: Design and Screening of Affinity Peptide Ligands Using Computer Simulation Techniques.Current topics in medicinal chemistry · 2024Review
- The novel peptide LCGM-10 attenuates metabotropic glutamate receptor 5 activity and demonstrates behavioral effects in animal models.Frontiers in behavioral neuroscience · 2024Article
- Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Discovery of natural products to block SARS-CoV-2 S-protein interaction with Neuropilin-1 receptor: A molecular dynamics simulation approach.Microbial pathogenesis · 2022Article
- Research on ACEI of Low-Molecular-Weight Peptides fromMolecules (Basel, Switzerland) · 2022Article
- Molecular Coevolution of Nuclear and Nucleolar Localization Signals inside the Basic Domain of HIV-1 Tat.Journal of virology · 2022Article
- Molecular docking of alpha-enolase to elucidate the promising candidates against Streptococcus pneumoniae infection.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2021Article
- Article
- Data of small peptides in SMILES and three-dimensional formats for virtual screening campaigns.Data in brief · 2019Article
- Computational Approaches for Drug Discovery.Molecules (Basel, Switzerland) · 2019Article
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Authors and funding
9 authors.
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Abstract
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.
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