ArticleProteins2025
Challenges in bridging the gap between protein structure prediction and functional interpretation.
Article in Proteins, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 20 citations in OpenAlex.
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- A Disorder-Aware Computational Framework to Identify Structurally Tractable Targets in Proliferative Vitreoretinopathy.Ophthalmology science · 2026Article
- Applications and limitations of AI tools in enzyme design.Protein science : a publication of the Protein Society · 2026Review
- Bridging Algorithms and Biocatalysis: Perspectives on AI-Supported Enzyme Engineering.Molecules (Basel, Switzerland) · 2026Review
- Integrative Structural Modeling of Intrinsically Disordered Regions in a Human HDAC2 Chromatin Remodeling Complex.bioRxiv : the preprint server for biology · 2026Article
- Comparative evaluation of the prediction accuracy of AlphaFold and ESMFold for monomeric and dimeric proteins.NAR genomics and bioinformatics · 2026Article
- Review
- Can AI-Predicted Complexes Teach Machine Learning to Compute Drug Binding Affinity?Journal of chemical information and modeling · 2025Article
- A transposon-like strategy for proteins.Nature chemical biology · 2025Article
- Comprehensive Studies on the Regulation of Type 2 Diabetes by Cucurbitane-Type Triterpenoids inPharmaceuticals (Basel, Switzerland) · 2025Article
- Deciphering the proteome ofComputational and structural biotechnology journal · 2025Article
- Type IV minor pilin ComN predicted the USS-receptor in Pasteurellaceae.Frontiers in microbiology · 2025Article
- Article
- Challenges in bridging the gap between protein structure prediction and functional interpretation.Proteins · 2025Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
The rapid evolution of protein structure prediction tools has significantly broadened access to protein structural data. Although predicted structure models have the potential to accelerate and impact fundamental and translational research significantly, it is essential to note that they are not validated and cannot be considered the ground truth. Thus, challenges persist, particularly in capturing protein dynamics, predicting multi-chain structures, interpreting protein function, and assessing model quality. Interdisciplinary collaborations are crucial to overcoming these obstacles. Databases like the AlphaFold Protein Structure Database, the ESM Metagenomic Atlas, and initiatives like the 3D-Beacons Network provide FAIR access to these data, enabling their interpretation and application across a broader scientific community. Whilst substantial advancements have been made in protein structure prediction, further progress is required to address the remaining challenges. Developing training materials, nurturing collaborations, and ensuring open data sharing will be paramount in this pursuit. The continued evolution of these tools and methodologies will deepen our understanding of protein function and accelerate disease pathogenesis and drug development discoveries.
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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.