ReviewInternational journal of molecular sciences2019
A Structure-Based Drug Discovery Paradigm.
Review in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 237 papers, 2 of them syntheses that pooled it.
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
237 citing papers in PubMed, 2 syntheses or guidelines pooled it, 700 citations in OpenAlex.
- Hydrazones as Potential Antimelanoma Prototypes: A Systematic and Patent Review.Anti-cancer agents in medicinal chemistry · 2026Pooled it
- Anti-Obesity Therapeutic Targets Studied In Silico and In Vivo: A Systematic Review.International journal of molecular sciences · 2024Pooled it
- Article
- A Multi-Scale Computational Framework for Anti-Persister Tuberculosis Drug Discovery.Chemical biology & drug design · 2026Review
- Schiff Base Derivatives of Benzothiazole and Benzamide as Promising Antimicrobial Agents: Integrated In Silico and In Vitro Evaluation.ChemMedChem · 2026Article
- 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
- Data driven selection of consensus docking pipelines for structure based hit identification.npj drug discovery · 2026Article
- Beyond the flat screen: evaluating virtual reality as a complementary tool for molecular docking in drug discovery.Journal of computer-aided molecular design · 2026Review
- Cloud-based ligand-guided virtual screening with deep-learning-enhanced docking identifies a micromolar CXCR4 antagonist.Molecular diversity · 2026Article
- Epidermal Growth Factor Receptor as a Model Drug Target for Scrutinizing the Status Quo in Drug Discovery and Chemical Biology.ACS bio & med chem Au · 2026Review
- Teaching diffusion models physics: reinforcement learning for physically valid diffusion-based docking.Chemical science · 2026Article
- GAMT-GINE: A Graph Isomorphism Network Integrating Continuous Spatial Awareness and Multi-Task Learning for Protein-Ligand Binding Affinity Prediction.International journal of molecular sciences · 2026Article
- Free energy perturbation and machine learning-assisted identification of potential MAP3K8 hit molecules: a comprehensive structure- and ligand-based studies.Molecular diversity · 2026Article
- AI-Predicted Model-Guided Rebuilding of the Experimental Structure of Mouse δ-Aminolevulinic Acid Dehydratase.International journal of molecular sciences · 2026Article
- Explainable Artificial Intelligence (XAI) and Molecular Modeling Techniques to Discover Putative HER2 Inhibitors.International journal of molecular sciences · 2026Article
- Advancing Antiviral Design: Integrating Natural Products, Computation and Targeted Delivery.Chemical biology & drug design · 2026Review
- Automated Processes and Artificial Intelligence in Generating Candidates for Oncology Drug Repurposing: Three-Year Scoping Review of Data.Pharmacy (Basel, Switzerland) · 2026Review
- Chemical adaptation: bridging synthetic chemistry with drug development.Science China. Life sciences · 2026Review
- Machine Learning and Virtual Screening Methods to Discover Potential Cyclin-Dependent Kinase 2 (CDK2) Inhibitors.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Pep2Mol: 3D Molecule Generation Targeting Protein-Protein Interfaces with Diffusion Models.bioRxiv : the preprint server for biology · 2026Article
177 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
3 authors at 1 institution in 1 country.
Funding
Abstract
Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the "big data" generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.
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.