ReviewAnnual review of biophysics2023
Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes.
Review in Annual review of biophysics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
44 citing papers in PubMed.
- Biomolecular Interaction Prediction in the Pre- and Post-AlphaFold Era: The 8th CAPRI Evaluation.Proteins · 2026Article
- Lessons learned from a Kaggle challenge for particle picking in cryo-electron tomography.Nature methods · 2026Article
- From sites to structure to serology: a roadmap for structure-aware molecular evolution of antigenically evolving viruses.Journal of virology · 2026Review
- Artificial intelligence in drug discovery - what it is, where we stand and the path forward.Nature reviews. Drug discovery · 2026Review
- Caveat emptor: predicting and modeling protein-DNA recognition and binding via machine-learning computational approaches.Nucleic acids research · 2026Review
- Reverse engineering of BNIP3 identifies a mitochondrial protective peptide.Nature communications · 2026Article
- Improving protein and protein interactions using pseudo-dimers derived from monomeric proteins.Nature communications · 2026Article
- YAP1 and QSER1 are key modulators of embryonic signaling pathways in the mammalian epiblast.EMBO reports · 2026Article
- Experimentally validated deep learning control of protein aggregation.Communications chemistry · 2026Article
- Article
- Integrative Structural Modeling of Intrinsically Disordered Regions in a Human HDAC2 Chromatin Remodeling Complex.bioRxiv : the preprint server for biology · 2026Article
- TZ1391: a computationally designed circular mRNA multi-epitope vaccine candidate against Mycobacterium tuberculosis via TLR3 immunomodulation.BMC immunology · 2026Article
- Updates to the CASP Infrastructure in 2024.Proteins · 2026Article
- Untangling the Complexity of Binding Across Biomolecular Interfaces with Interaction Network Models.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Predicting Protein-Protein Interactions from Machine-Learned Representations.Advances in experimental medicine and biology · 2026Review
- mRNA Cancer Vaccines: From Pandemic Paradigm to Personalized Oncology Therapeutics.Cancer innovation · 2025Review
- High-accuracy protein complex structure modeling based on sequence-derived structure complementarity.Nature communications · 2025Article
- An AI-Designed Antibody-Engineered Probiotic Therapy Targeting Urease to CombatMicroorganisms · 2025Article
- GRAMMCell: Docking-based Cell Modeling Resource.Journal of molecular biology · 2025Article
- In silico screening of epitopes as potential vaccine candidates against pathogenic Acinetobacter baumannii.Genes & genomics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.
Indexed as
Identifiers
What OpenQuestion holds
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.