ArticleNucleic acids research2016
MutaBind estimates and interprets the effects of sequence variants on protein-protein interactions.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.
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Who cites it
69 citing papers in PubMed, 133 citations in OpenAlex.
- An interpretable molecular framework for predicting cancer driver missense mutations.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Predictive Model for Single-Site Mutations That Change Intrinsically Disordered Protein Binding Energetics.Methods in molecular biology (Clifton, N.J.) · 2026Article
- InSty: A ProDy Module for Evaluating Protein Interactions and Stability.Journal of molecular biology · 2025Article
- ProBASS-a language model with sequence and structural features for predicting the effect of mutations on binding affinity.Bioinformatics (Oxford, England) · 2025Article
- Systematic investigation of machine learning on limited data: A study on predicting protein-protein binding strength.Computational and structural biotechnology journal · 2024Article
- Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.Human genomics · 2024Article
- Robust Prediction of Relative Binding Energies for Protein-Protein Complex Mutations Using Free Energy Perturbation Calculations.Journal of molecular biology · 2024Article
- DDMut-PPI: predicting effects of mutations on protein-protein interactions using graph-based deep learning.Nucleic acids research · 2024Article
- Variant Impact Predictor database (VIPdb), version 2: Trends from 25 years of genetic variant impact predictors.bioRxiv : the preprint server for biology · 2024Article
- DeepPPAPredMut: deep ensemble method for predicting the binding affinity change in protein-protein complexes upon mutation.Bioinformatics (Oxford, England) · 2024Article
- Robust prediction of relative binding energies for protein-protein complex mutations using free energy perturbation calculations.bioRxiv : the preprint server for biology · 2024Article
- Quantification of biases in predictions of protein-protein binding affinity changes upon mutations.Briefings in bioinformatics · 2023Article
- MpbPPI: a multi-task pre-training-based equivariant approach for the prediction of the effect of amino acid mutations on protein-protein interactions.Briefings in bioinformatics · 2023Article
- Markov State Models and Perturbation-Based Approaches Reveal Distinct Dynamic Signatures and Hidden Allosteric Pockets in the Emerging SARS-Cov-2 Spike Omicron Variant Complexes with the Host Receptor: The Interplay of Dynamics and Convergent Evolution Modulates Allostery and Functional Mechanisms.Journal of chemical information and modeling · 2023Article
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- Mutational scan inferred binding energetics and structure in intrinsically disordered protein CcdA.Protein science : a publication of the Protein Society · 2023Article
- Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations.Research (Washington, D.C.) · 2023Article
- VariBench, new variation benchmark categories and data sets.Frontiers in bioinformatics · 2023Article
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9 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Proteins engage in highly selective interactions with their macromolecular partners. Sequence variants that alter protein binding affinity may cause significant perturbations or complete abolishment of function, potentially leading to diseases. There exists a persistent need to develop a mechanistic understanding of impacts of variants on proteins. To address this need we introduce a new computational method MutaBind to evaluate the effects of sequence variants and disease mutations on protein interactions and calculate the quantitative changes in binding affinity. The MutaBind method uses molecular mechanics force fields, statistical potentials and fast side-chain optimization algorithms. The MutaBind server maps mutations on a structural protein complex, calculates the associated changes in binding affinity, determines the deleterious effect of a mutation, estimates the confidence of this prediction and produces a mutant structural model for download. MutaBind can be applied to a large number of problems, including determination of potential driver mutations in cancer and other diseases, elucidation of the effects of sequence variants on protein fitness in evolution and protein design. MutaBind is available at http://www.ncbi.nlm.nih.gov/projects/mutabind/.
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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.