ReviewJournal of computer-aided molecular design2014
Blind prediction of HIV integrase binding from the SAMPL4 challenge.
Review in Journal of computer-aided molecular design, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
40 citing papers in PubMed.
- Benchmarking Docking Protocols on Predicting Alternative Binding Modes.Journal of chemical information and modeling · 2026Article
- Free energy calculations in molecular modeling: from classical methods to machine learning.Journal of molecular modeling · 2026Review
- The Open Molecular Software Foundation (OMSF) and the Growing Role of Open Source Software in Molecular Modeling.Journal of chemical information and modeling · 2026Review
- ABCG2: A Milestone Charge Model for Accurate Solvation Free Energy Calculation.Journal of chemical theory and computation · 2025Article
- Toward physics-based precision medicine: Exploiting protein dynamics to design new therapeutics and interpret variants.Protein science : a publication of the Protein Society · 2024Review
- An overview of the SAMPL8 host-guest binding challenge.Journal of computer-aided molecular design · 2022Article
- SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction.Journal of computer-aided molecular design · 2022Article
- Structure-based virtual screening workflow to identify antivirals targeting HIV-1 capsid.Journal of computer-aided molecular design · 2022Article
- Thermodynamics of Pillararene•Guest Complexation: Blinded Dataset for the SAMPL9 Challenge.New journal of chemistry = Nouveau journal de chimie · 2022Article
- Application of the alchemical transfer and potential of mean force methods to the SAMPL8 host-guest blinded challenge.Journal of computer-aided molecular design · 2022Article
- Evaluation of log P, pKJournal of computer-aided molecular design · 2021Article
- Reversibly Sampling Conformations and Binding Modes Using Molecular Darting.Journal of chemical theory and computation · 2021Article
- Non-equilibrium approach for binding free energies in cyclodextrins in SAMPL7: force fields and software.Journal of computer-aided molecular design · 2021Article
- Protein storytelling through physics.Science (New York, N.Y.) · 2020Review
- Octanol-water partition coefficient measurements for the SAMPL6 blind prediction challenge.Journal of computer-aided molecular design · 2020Article
- Best Practices for Alchemical Free Energy Calculations [Article v1.0].Living journal of computational molecular science · 2020Article
- Massive-Scale Binding Free Energy Simulations of HIV Integrase Complexes Using Asynchronous Replica Exchange Framework Implemented on the IBM WCG Distributed Network.Journal of chemical information and modeling · 2019Article
- Overview of the SAMPL6 host-guest binding affinity prediction challenge.Journal of computer-aided molecular design · 2018Article
- pKJournal of computer-aided molecular design · 2018Article
- Improving Prediction Accuracy of Binding Free Energies and Poses of HIV Integrase Complexes Using the Binding Energy Distribution Analysis Method with Flattening Potentials.Journal of chemical information and modeling · 2018Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Here, we give an overview of the protein-ligand binding portion of the Statistical Assessment of Modeling of Proteins and Ligands 4 (SAMPL4) challenge, which focused on predicting binding of HIV integrase inhibitors in the catalytic core domain. The challenge encompassed three components--a small "virtual screening" challenge, a binding mode prediction component, and a small affinity prediction component. Here, we give summary results and statistics concerning the performance of all submissions at each of these challenges. Virtual screening was particularly challenging here in part because, in contrast to more typical virtual screening test sets, the inactive compounds were tested because they were thought to be likely binders, so only the very top predictions performed significantly better than random. Pose prediction was also quite challenging, in part because inhibitors in the set bind to three different sites, so even identifying the correct binding site was challenging. Still, the best methods managed low root mean squared deviation predictions in many cases. Here, we give an overview of results, highlight some features of methods which worked particularly well, and refer the interested reader to papers in this issue which describe specific submissions for additional details.
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Registered trials
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.