ArticleBMC molecular and cell biology2019
Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins.
Article in BMC molecular and cell biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed.
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- Albumin/Thiacalix[4]arene Nanoparticles as Potential Therapeutic Systems: Role of the Macrocycle for Stabilization of Monomeric Protein and Self-Assembly with Ciprofloxacin.International journal of molecular sciences · 2022Article
- 3pHLA-score improves structure-based peptide-HLA binding affinity prediction.Scientific reports · 2022Article
- Drug and Anti-Viral Peptide Design to Inhibit the Monkeypox Virus by Restricting A36R Protein.Bioinformatics and biology insights · 2022Article
- DINC-COVID: A webserver for ensemble docking with flexible SARS-CoV-2 proteins.Computers in biology and medicine · 2021Article
- Self-Assembling Systems Based on Pillar[5]arenes and Surfactants for Encapsulation of Diagnostic Dye DAPI.International journal of molecular sciences · 2021Article
- Prediction of the RNA Tertiary Structure Based on a Random Sampling Strategy and Parallel Mechanism.Frontiers in genetics · 2021Article
- HLA-Arena: A Customizable Environment for the Structural Modeling and Analysis of Peptide-HLA Complexes for Cancer Immunotherapy.JCO clinical cancer informatics · 2020Article
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7 authors.
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Abstract
backgroundDocking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies.
resultsOur computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered.
conclusionsOur study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking.
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