ArticlePloS one2015
Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers.
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Who cites it
93 citing papers in PubMed.
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- Lab to codes: multimodel advanced AI-driven pipelines to drive antimicrobial peptide design for the post-antibiotic era.Frontiers in cellular and infection microbiology · 2026Review
- Structural insights into xyloglucan recognition by an ABC transporter from a Gram-positive, thermophilic bacterium.bioRxiv : the preprint server for biology · 2025Article
- Small molecule activator of phosphatase PP2A remodels scaffold PR65 structural dynamics to promote holoenzyme assembly.bioRxiv : the preprint server for biology · 2025Article
- Small Molecule Modulation of MHC-I Surface Expression: A Click Chemistry-Based Discovery Approach.Journal of medicinal chemistry · 2025Article
- Ultra-large library screening with an evolutionary algorithm in Rosetta (REvoLd).Communications chemistry · 2025Article
- Buttressing ligand-binding pockets in de novo designed NTF2-like domains.Protein science : a publication of the Protein Society · 2025Article
- A generalizable deep learning framework for structure-based protein-ligand affinity ranking.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- MarK, a Novosphingobium aromaticivorans kinase required for catabolism of multiple aromatic monomers.The Journal of biological chemistry · 2025Article
- Cache: Utilizing ultra-large library screening in Rosetta to identify novel binders of the WD-repeat domain of Leucine-Rich Repeat Kinase 2.Journal of cheminformatics · 2025Article
- Orthogonal replication with optogenetic selection evolves yeast JEN1 into a mevalonate transporter.Molecular systems biology · 2025Article
33 more citing papers are in PubMed but not listed here.
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3 authors.
Funding
Abstract
RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial 'low-resolution' docking step. It combines the translational and rotational adjustments to the ligand pose in a single transformation step. The new algorithm is both more accurate and more time-efficient. The docking success rate is improved by 10-15% in a benchmark set of 43 protein/ligand complexes, reducing the number of models that typically need to be generated from 1000 to 150. The average time to generate a model is reduced from 50 seconds to 10 seconds. As a result we observe an effective 30-fold speed increase, making RosettaLigand appropriate for docking medium sized ligand libraries. We demonstrate that this improved initial placement of the ligand is critical for successful prediction of an accurate binding position in the 'high-resolution' full atom refinement step.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.