ArticleJournal of chemical theory and computation2020
Computing Ligands Bound to Proteins Using MELD-Accelerated MD.
Article in Journal of chemical theory and computation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025Review
- Design of target specific peptide inhibitors using generative deep learning and molecular dynamics simulations.Nature communications · 2024Article
- Rapid Rescoring and Refinement of Ligand-Receptor Complexes Using Replica Exchange Molecular Dynamics with a Monte Carlo Pose Reservoir.Journal of chemical theory and computation · 2023Article
- Structural predictions of protein-DNA binding: MELD-DNA.Nucleic acids research · 2023Article
- Assessing a computational pipeline to identify binding motifs to theFrontiers in chemistry · 2023Article
- Deep learning to decompose macromolecules into independent Markovian domains.Nature communications · 2022Article
- Accelerating the Ensemble Convergence of RNA Hairpin Simulations with a Replica Exchange Structure Reservoir.Journal of chemical theory and computation · 2022Article
- Searching for Low Probability Opening Events in a DNA Sliding Clamp.Life (Basel, Switzerland) · 2022Article
- Towards rational computational peptide design.Frontiers in bioinformatics · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
Predicting the poses of small-molecule ligands in protein binding sites is often done by virtual screening algorithms such as DOCK. In principle, molecular dynamics (MD) using atomistic force fields could give better free-energy-based pose selection, but MD is computationally expensive. Here, we ask if modeling employing limited data (MELD)-accelerated MD (MELD × MD) can pick out the best DOCK poses taken as input. We study 30 different ligand-protein pairs. MELD × MD finds native poses, based on best free energies, in 23 out of the 30 cases, 20 of which were previously known DOCK failures. We conclude that MELD × MD can add value for predicting accurate poses of small molecules bound to proteins.
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Registered trials
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