ReviewDrug discovery today2014
Modelling three-dimensional protein structures for applications in drug design.
Review in Drug discovery today, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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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.
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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.
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Who cites it
56 citing papers in PubMed.
- Article
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- Benchmarking deep learning methods for Cα atom prediction in cryo-EM density maps.Bioinformatics (Oxford, England) · 2026Article
- Shoebill: an interpretable AlphaFold2-informed predictor of protein crystallization propensity using XGBoost.Briefings in bioinformatics · 2026Article
- Comprehensive Evolutionary and Structural Analysis of the H5N1 Clade 2.4.3.4b Influenza a Virus Based on the Sequences and Data Mining of the Hemagglutinin, Nucleoprotein and Neuraminidase Genes Across Multiple Hosts.Pathogens (Basel, Switzerland) · 2025Article
- Prediction of aggregation in monoclonal antibodies from molecular surface curvature.Scientific reports · 2025Article
- High-speed atomic force microscopy and 3D modeling reveal the structural dynamics of ADAR1 complexes.Nature communications · 2025Article
- Molecular Modelling in Bioactive Peptide Discovery and Characterisation.Biomolecules · 2025Review
- The Potential of Peptide-Based Inhibitors in Disrupting Protein-Protein Interactions for Targeted Cancer Therapy.International journal of molecular sciences · 2025Review
- Conformational ensembles for protein structure prediction.Scientific reports · 2025Article
- Isomer-sourced structure iteration methods forComputational and structural biotechnology journal · 2024Article
- Article
- Article
- Bioinformatics Approaches in the Development of Antifungal Therapeutics and Vaccines.Current genomics · 2024Review
- Molecular characterization and phylogenetic analyses of MetAP2 gene and protein ofFrontiers in veterinary science · 2024Article
- Development of Alpha-Synuclein protein model against therapeutic aspects of Parkinson's disease.Indian journal of pharmacology · 2024Article
- Article
- Article
- Computational Approaches for Identification of Potential Plant Bioactives as Novel G6PD Inhibitors Using Advanced Tools and Databases.Molecules (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
A structural perspective of drug target and anti-target proteins, and their molecular interactions with biologically active molecules, largely advances many areas of drug discovery, including target validation, hit and lead finding and lead optimisation. In the absence of experimental 3D structures, protein structure prediction often offers a suitable alternative to facilitate structure-based studies. This review outlines recent methodical advances in homology modelling, with a focus on those techniques that necessitate consideration of ligand binding. In this context, model quality estimation deserves special attention because the accuracy and reliability of different structure prediction techniques vary considerably, and the quality of a model ultimately determines its usefulness for structure-based drug discovery. Examples of G-protein-coupled receptors (GPCRs) and ADMET-related proteins were selected to illustrate recent progress and current limitations of protein structure prediction. Basic guidelines for good modelling practice are also provided.
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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.