ArticleBioinformatics (Oxford, England)2018
Predicting protein-DNA binding free energy change upon missense mutations using modified MM/PBSA approach: SAMPDI webserver.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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Who cites it
38 citing papers in PubMed, 78 citations in OpenAlex.
- An information theory approach to quantifying the sequence-dependent response of nucleic acid motors with applications to nanopore DNA sequencing.Nature communications · 2026Article
- iDLDDG: predicting protein stability changes from missense mutations in DNA-binding proteins using integrated deep learning features.Briefings in bioinformatics · 2026Article
- Topological machine learning for protein-nucleic acid binding affinity changes upon mutation.Machine learning: science and technology · 2025Article
- Multisite λ-Dynamics for Protein-DNA Binding Affinity Prediction.Journal of chemical theory and computation · 2025Article
- Decoding the effects of mutation on protein interactions using machine learning.Biophysics reviews · 2025Review
- Article
- PRITrans: A Transformer-Based Approach for the Prediction of the Effects of Missense Mutation on Protein-RNA Interactions.International journal of molecular sciences · 2024Article
- PNBACE: an ensemble algorithm to predict the effects of mutations on protein-nucleic acid binding affinity.BMC biology · 2024Article
- Insights into the DNA and RNA Interactions of Human Topoisomerase III Beta Using Molecular Dynamics Simulations.Journal of chemical information and modeling · 2024Article
- Prediction of Protein-DNA Interface Hot Spots Based on Empirical Mode Decomposition and Machine Learning.Genes · 2024Article
- Functional characterization of HNF4A gene variants identify promoter and cell line specific transactivation effects.Human molecular genetics · 2024Article
- The Optimized Preparation Conditions of Cellulose Triacetate Hollow Fiber Reverse Osmosis Membrane with Response Surface Methodology.Polymers · 2023Article
- Computational studies indicated the effectiveness of human metabolites against SARS-Cov-2 main protease.Molecular diversity · 2023Article
- Predicting the Effect of Single Mutations on Protein Stability and Binding with Respect to Types of Mutations.International journal of molecular sciences · 2023Article
- Prediction of hot spots in protein-DNA binding interfaces based on discrete wavelet transform and wavelet packet transform.BMC bioinformatics · 2023Article
- Article
- VariBench, new variation benchmark categories and data sets.Frontiers in bioinformatics · 2023Article
- SAMPDI-3D: predicting the effects of protein and DNA mutations on protein-DNA interactions.Bioinformatics (Oxford, England) · 2021Article
- HISNAPI: a bioinformatic tool for dynamic hot spot analysis in nucleic acid-protein interface with a case study.Briefings in bioinformatics · 2021Article
- Nabe: an energetic database of amino acid mutations in protein-nucleic acid binding interfaces.Database : the journal of biological databases and curation · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Motivation: Protein-DNA interactions are essential for regulating many cellular processes, such as transcription, replication, recombination and translation. Amino acid mutations occurring in DNA-binding proteins have profound effects on protein-DNA binding and are linked with many diseases. Hence, accurate and fast predictions of the effects of mutations on protein-DNA binding affinity are essential for understanding disease-causing mechanisms and guiding plausible treatments. Results: Here we report a new method Single Amino acid Mutation binding free energy change of Protein-DNA Interaction (SAMPDI). The method utilizes modified Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) approach along with an additional set of knowledge-based terms delivered from investigations of the physicochemical properties of protein-DNA complexes. The method is benchmarked against experimentally determined binding free energy changes caused by 105 mutations in 13 proteins (compiled ProNIT database and data from recent references), and results in correlation coefficient of 0.72. Availability and implementation: http://compbio.clemson.edu/SAMPDI. Contact: ealexov@clemson.edu. Supplementary information: Supplementary data are available at Bioinformatics online.
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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.