ArticleNucleic acids research2023
Structural predictions of protein-DNA binding: MELD-DNA.
Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- RGTBind: RBF-gate graph transformer with spatially biased attention for protein-DNA binding-site prediction.Journal of molecular modeling · 2026Article
- Ensemble Sensitivity to Chemical Modifications in Free and Bound Macrocyclic Peptides.The journal of physical chemistry. B · 2026Article
- A structure-guided approach to noncoding variant evaluation for transcription factor binding using AlphaFold 3.Nucleic acids research · 2026Article
- Article
- RNA sequence design and protein-DNA specificity prediction with NA-MPNN.bioRxiv : the preprint server for biology · 2025Article
- Molecular dynamics simulations of proteins: an in-depth review of computational strategies, structural insights, and their role in medicinal chemistry and drug development.Biological cybernetics · 2025Review
- Variations in flanking or less conserved positions of Reb1 and Abf1 consensus binding sites lead to major changes in their ability to modulate nucleosome sliding activity.Biological research · 2025Article
- Hierarchical Extended Linkage Method (HELM)'s Deep Dive into Hybrid Clustering Strategies.Journal of chemical information and modeling · 2025Article
- MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025Review
- Article
- Bioinformatics Approaches for Understanding the Binding Affinity of Protein-Nucleic Acid Complexes.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Probing Electrostatic Interactions in DNA-Bound CRISPR/Cas9 Complexes by Molecular Dynamics Simulations.ACS omega · 2024Article
- Improving prediction performance of general protein language model by domain-adaptive pretraining on DNA-binding protein.Nature communications · 2024Article
- Geometric deep learning of protein-DNA binding specificity.Nature methods · 2024Article
- ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein-DNA binding site prediction.Briefings in bioinformatics · 2024Article
- Probing the role of the protonation state of a minor groove-linker histidine in Exd-Hox-DNA binding.Biophysical journal · 2024Article
- Structural Insights into Protein-Aptamer Recognitions Emerged from Experimental and Computational Studies.International journal of molecular sciences · 2023Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Structural, regulatory and enzymatic proteins interact with DNA to maintain a healthy and functional genome. Yet, our structural understanding of how proteins interact with DNA is limited. We present MELD-DNA, a novel computational approach to predict the structures of protein-DNA complexes. The method combines molecular dynamics simulations with general knowledge or experimental information through Bayesian inference. The physical model is sensitive to sequence-dependent properties and conformational changes required for binding, while information accelerates sampling of bound conformations. MELD-DNA can: (i) sample multiple binding modes; (ii) identify the preferred binding mode from the ensembles; and (iii) provide qualitative binding preferences between DNA sequences. We first assess performance on a dataset of 15 protein-DNA complexes and compare it with state-of-the-art methodologies. Furthermore, for three selected complexes, we show sequence dependence effects of binding in MELD predictions. We expect that the results presented herein, together with the freely available software, will impact structural biology (by complementing DNA structural databases) and molecular recognition (by bringing new insights into aspects governing protein-DNA interactions).
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