ArticleNature communications2024
Accurate Prediction of Protein Structural Flexibility by Deep Learning Integrating Intricate Atomic Structures and Cryo-EM Density Information.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
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- Magnesium isoglycyrrhizinate alleviates alcohol-associated liver disease through targeting HSD11B1.eLife · 2026Article
- DynamicDTA: Drug-Target Binding Affinity Prediction Using Dynamic Descriptors and Graph Representation.Interdisciplinary sciences, computational life sciences · 2026Article
- The "Survivor Peptide" Hypothesis: Structural Resilience and Immunological Persistence of Food Allergens in the Gut-Mammary Axis.Nutrients · 2026Review
- GC-MS and GC-IMS Comprehensive Analysis of Volatile Compounds in the Peel and Pulp of Six Lemon Varieties and Their Interactions with Olfactory Receptors: Molecular Docking and Molecular Dynamics Simulations Studies.Foods (Basel, Switzerland) · 2026Article
- Designing Novel Aspartic Protease (NAP) Using Ancestral Sequence Reconstruction (ASR) for Cheesemaking.Molecular biotechnology · 2026Article
- Fast prediction of protein flexibility.Bioinformatics (Oxford, England) · 2026Article
- In Silico Profiling of Phytochemicals for Modulating Amyloid Beta-Mediated Immune Regulation and Neuroinflammation in Alzheimer's Disease.ACS omega · 2026Article
- Efficient sampling of large-scale transition pathways and intermediate conformations in sub-mesoscopic protein complexes.Nature communications · 2026Article
- Non-invasive pharmacological advances in early retinopathy treatment: bioactive herbal compounds, polymer delivery systems, and computational bioprospecting of functional targets.Pharmacological reports : PR · 2026Review
- Structural characterization of metal binding in human tyrosylprotein sulfotransferase 2, TPST2.Scientific reports · 2026Article
- An in silico approach to peptide-based dual-receptor targeting for IL13RA2 and VEGFR-2 extracellular domain.Journal of molecular modeling · 2026Article
- Exploring the molecular basis ofBioinformatics advances · 2026Article
- Integrating network pharmacology, molecular docking and dynamics simulation to decipher the antipyretic mechanisms of Xiaochaihu granules.Frontiers in medicine · 2026Article
- Differential Self-Assembly Behaviors and Proteolytic Stability of Bicyclic Peptides Compared to Monocyclic Peptides.Chemistry, an Asian journal · 2026Article
- In silico identification of potential inhibitors from fenugreek against the pro-inflammatory cytokine IL-17 and its receptor.Odontology · 2026Article
- Binding Specificity and Local Frustration in Structure-based Drug Discovery.Current medicinal chemistry · 2026Review
- Development of substituted 2-(4-(sulfonyl)piperazin-1-yl)quinazoline molecular hybrids as a new class of antimalarials.RSC advances · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and produces the best results in a large-scale protein dynamics dataset; this model can accurately infer the dynamic information of a protein in only a few seconds. By learning effectively from experimental protein structure data and cryo-electron microscopy (cryo-EM) data integration, our approach is able to accurately identify the interactive bidirectional constraints and supervision between cryo-EM maps and PDB models in maximizing the dynamic prediction efficacy. Rigorous 5-fold cross-validation on the dataset demonstrates that RMSF-net achieves test correlation coefficients of 0.746 ± 0.127 at the voxel level and 0.765 ± 0.109 at the residue level, showcasing its ability to deliver dynamic predictions closely approximating molecular dynamics simulations. Additionally, it offers real-time dynamic inference with minimal storage overhead on the order of megabytes. RMSF-net is a freely accessible tool and is anticipated to play an essential role in the study of protein dynamics.
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Registered trials
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