ReviewBritish journal of pharmacology2007
In silico pharmacology for drug discovery: applications to targets and beyond.
Review in British journal of pharmacology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 128 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
128 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Role of Artemisinin and its Derivatives in Cancer Therapy via Ferroptosis: A Systematic Review ofAnti-cancer agents in medicinal chemistry · 2026Pooled it
- Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci.American journal of human genetics · 2014Pooled it
- Computational Evaluation of Carbazole-Chalcone Urea and Thiourea Derivatives Against EGFR: Molecular Docking, Pharmacokinetic Profiling, Target Prediction, and Molecular Dynamics Simulation.Molecules (Basel, Switzerland) · 2026Article
- Target identification and assessment in the era of AI.Nature reviews. Drug discovery · 2026Review
- Developmental Consequences of Early-Life Exposure and Adulticidal Effects ofMolecules (Basel, Switzerland) · 2026Article
- Chemical Composition, Antioxidant, and Anti-Inflammatory Activity of the Antarctic LichenInternational journal of molecular sciences · 2026Article
- A Herbal Pair ofFood science & nutrition · 2026Article
- QSAR-Guided Design of Serotonin Transporter Inhibitors Supported by Molecular Docking and Biased Molecular Dynamics.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Computational identification of Terminalia arjuna phytochemicals as potential 3α-HSD3 inhibitors.Scientific reports · 2026Article
- Article
- Dietary Sources of Glycine Betaine and Proline Betaine in Plant Foods and Their Potential Biological Relevance in Human Nutrition.Foods (Basel, Switzerland) · 2026Article
- Atypical protein kinase C activation drives intestinal glucose excretion in diabetes mellitus.Nature communications · 2026Article
- Boswellic Acid Derived Molecules as SARS-Cov-2 Spike Protein Inhibitors: A Comprehensive Virtual Screening, Triplicate Molecular Dynamic Simulation and Biochemical Validation.Current medicinal chemistry · 2026Article
- In Silico Post-screening of Anti-polymerization Agents to Treat Sickle Cell Disease.bioRxiv : the preprint server for biology · 2025Article
- From AI-AssistedPharmaceuticals (Basel, Switzerland) · 2025Review
- Uncovering a fibroblast differentiation-based keloid classification by integration of single-cell and bulk RNA sequencing.Communications biology · 2025Article
- Molecular docking to homology models of human and Trypanosoma brucei ERK8 that identified ortholog-specific inhibitors.PLoS neglected tropical diseases · 2025Article
- Article
- Harnessing AI-driven reverse docking in drug discovery: a comprehensive review of opportunities, challenges, and emerging trends.Journal of molecular modeling · 2025Review
- Cracking the code: the clinical and molecular impact of aminopyridines; a review (2019-2024).RSC advances · 2025Review
68 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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediting the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets.
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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.