ReviewCurrent opinion in structural biology2023
AlphaFold2 protein structure prediction: Implications for drug discovery.
Review in Current opinion in structural biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 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
69 citing papers in PubMed.
- Article
- Immunopharmacological design of a multi-epitope vaccine targeting hepatitis C virus genotype 3a.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Structure-based drug repurposing and in vitro evaluation of VAV2-associated candidates for suppression of macrophage foam-cell formation in atherosclerosis.Molecular diversity · 2026Article
- Peptide Aptamers: Innovative Design and Applications in Pathogen Detection.Chembiochem : a European journal of chemical biology · 2026Review
- Artificial intelligence and ultra-high performance computing methods and experiments for drug discovery: virtual screening, deep learning, molecular dynamics simulations, ADMET modelling, and experimental validation.Molecular biomedicine · 2026Review
- Immunopharmacological and structural design of a polyprotein based multi epitope vaccine against Powassan virus.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Bispecific antibodies for cancer therapy: evolution of structural formats and co-targeting strategies from wet-lab to AI-driven in silico modeling.Cancer letters · 2026Review
- Fungal Carbonic Anhydrases: A Systematic Review from Molecular Profiling to Pathogenic Regulation inJournal of fungi (Basel, Switzerland) · 2026Review
- Hybrid Computational Modeling with Multi-Level Validation Identifies TK1-VIM as a Robust Therapeutic Pair in Triple-Negative Breast Cancer.International journal of molecular sciences · 2026Article
- Article
- Functional Characterization of a Novel OTU-like Deubiquitinase fromInternational journal of molecular sciences · 2026Article
- Engineering molecularly imprinted polymers for receptor-specific cancer therapeutics.Nanoscale · 2026Review
- Free Energy Calculation Method Based on Enhanced Sampling of Diverse Protein Conformations Predicted by Artificial Intelligence.The journal of physical chemistry letters · 2026Article
- Evaluation of AI-Predicted GH11 Xylanase Models Against a Previously Unreported Experimental Structure: Implications for Conformational Accuracy and Ligand Binding.International journal of molecular sciences · 2026Article
- Systematic evaluation of computational tools to predict the effects of mutations on protein-ligand binding affinity in the absence of experimental structures.Briefings in bioinformatics · 2026Article
- Adversarial Sequence Mutations in AlphaFold and ESMFold Reveal Nonphysical Structural Invariance, Confidence Failures, and Concerns for Protein Design.Computational and structural biotechnology journal · 2026Article
- Article
- Computer-aided drug discovery: historical foundations, practical AI tools, and emerging ethical considerations.Frontiers in pharmacology · 2026Review
- Comprehensive genomics, systems, and structural assessment for novel target identification in penicillin-resistantFrontiers in bioinformatics · 2026Article
- Synthetic lethality in cancer drug discovery: challenges and opportunities.Nature reviews. Drug discovery · 2026Review
9 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The drug discovery process involves designing compounds to selectively interact with their targets. The majority of therapeutic targets for low molecular weight (small molecule) drugs are proteins. The outstanding accuracy with which recent artificial intelligence methods compile the three-dimensional structure of proteins has made protein targets more accessible to the drug design process. Here, we present our perspective of the significance of accurate protein structure prediction on various stages of the small molecule drug discovery life cycle focusing on current capabilities and assessing how further evolution of such predictive procedures can have a more decisive impact in the discovery of new medicines.
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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.