ArticleBriefings in bioinformatics2018
Sixty-five years of the long march in protein secondary structure prediction: the final stretch?
Article in Briefings in bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
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88 citing papers in PubMed, 258 citations in OpenAlex.
- Computational modelling of a multiepitope vaccine targeting glycoprotein-D for herpes simplex virus 2 (HSV-2): an immunoinformatic analysis.Molecular diversity · 2025Article
- TruMPET: A New Method for Protein Secondary Structure Prediction Using Neural Networks Trained on Multiple Pre-Selected Physicochemical and Structural Features.International journal of molecular sciences · 2025Article
- Enriching stabilizing mutations through automated analysis of molecular dynamics simulations using BoostMut.Protein science : a publication of the Protein Society · 2025Article
- SARST2 high-throughput and resource-efficient protein structure alignment against massive databases.Nature communications · 2025Article
- In silico prediction of variant effects: promises and limitations for precision plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- MULAN: multimodal protein language model for sequence and structure encoding.Bioinformatics advances · 2025Article
- Post-processing enhances protein secondary structure prediction with second order deep learning and embeddings.Computational and structural biotechnology journal · 2025Article
- Machine Learning Techniques to Infer Protein Structure and Function from Sequences: A Comprehensive Review.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Recent Advances in Computational Prediction of Secondary and Supersecondary Structures from Protein Sequences.Methods in molecular biology (Clifton, N.J.) · 2025Review
- Advancements in one-dimensional protein structure prediction using machine learning and deep learning.Computational and structural biotechnology journal · 2025Review
- Article
- Are genomic language models all you need? Exploring genomic language models on protein downstream tasks.Bioinformatics (Oxford, England) · 2024Article
- Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering.Cell research · 2024Article
- Annotation Vocabulary (Might Be) All You Need.bioRxiv : the preprint server for biology · 2024Article
- Evaluating generalizability of artificial intelligence models for molecular datasets.bioRxiv : the preprint server for biology · 2024Article
- In silico design and analysis of a multiepitope vaccine against Chlamydia.Pathogens and disease · 2024Article
- The origin and structural evolution of de novo genes in Drosophila.Nature communications · 2024Article
- 3 = 1 + 2: how the divide conquered de novo protein structure prediction and what is next?National science review · 2023Article
- Effective Local and Secondary Protein Structure Prediction by Combining a Neural Network-Based Approach with Extensive Feature Design and Selection without Reliance on Evolutionary Information.International journal of molecular sciences · 2023Article
- Invasive Californian death caps develop mushrooms unisexually and bisexually.Nature communications · 2023Article
28 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein secondary structure prediction began in 1951 when Pauling and Corey predicted helical and sheet conformations for protein polypeptide backbone even before the first protein structure was determined. Sixty-five years later, powerful new methods breathe new life into this field. The highest three-state accuracy without relying on structure templates is now at 82-84%, a number unthinkable just a few years ago. These improvements came from increasingly larger databases of protein sequences and structures for training, the use of template secondary structure information and more powerful deep learning techniques. As we are approaching to the theoretical limit of three-state prediction (88-90%), alternative to secondary structure prediction (prediction of backbone torsion angles and Cα-atom-based angles and torsion angles) not only has more room for further improvement but also allows direct prediction of three-dimensional fragment structures with constantly improved accuracy. About 20% of all 40-residue fragments in a database of 1199 non-redundant proteins have <6 Å root-mean-squared distance from the native conformations by SPIDER2. More powerful deep learning methods with improved capability of capturing long-range interactions begin to emerge as the next generation of techniques for secondary structure prediction. The time has come to finish off the final stretch of the long march towards protein secondary structure prediction.
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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.