ReviewExpert opinion on drug discovery2020
An up-to-date overview of computational polypharmacology in modern drug discovery.
Review in Expert opinion on drug discovery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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
29 citing papers in PubMed.
- Artificial Intelligence-Powered High-Content Analysis: Methodologies and Applications in Bioactive Compound Discovery from Natural Sources.Molecules (Basel, Switzerland) · 2026Review
- Large Library Docking for Polypharmacology.Journal of medicinal chemistry · 2026Article
- From Polyphenols to Prodrugs: Bridging the Blood-Brain Barrier with Nanomedicine and Neurotherapeutics.International journal of molecular sciences · 2026Review
- Current Computational Approaches for the Discovery of Novel Anticancer Agents Targeting VEGFR and SIRT Signaling Pathways.Pharmaceutics · 2026Review
- Daixie recipe ameliorates diet-induced MASH in miceFrontiers in endocrinology · 2026Article
- AI-Driven Polypharmacology in Small-Molecule Drug Discovery.International journal of molecular sciences · 2025Review
- Trends and Pitfalls in the Progress of Network Pharmacology Research on Natural Products.Pharmaceuticals (Basel, Switzerland) · 2025Article
- AI in Clinical Trials and Drug Development: Challenges and Potential Advancements.Current drug discovery technologies · 2025Review
- Targeting RNA-binding proteins with small molecules: perspectives and challenges.Frontiers in chemistry · 2025Review
- Bioinformatics and molecular biology tools for diagnosis, prevention, treatment and prognosis of COVID-19.Heliyon · 2024Review
- VirtuousPocketome: a computational tool for screening protein-ligand complexes to identify similar binding sites.Scientific reports · 2024Article
- Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery.Life (Basel, Switzerland) · 2024Review
- Epoxy-a-lapachone in nanosystem: a prototype drug for leishmaniasis assessed in the binomial BALB/c - Leishmania (Leishmania) amazonensis.Memorias do Instituto Oswaldo Cruz · 2024Article
- Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks.Frontiers in pharmacology · 2024Article
- Polypharmacology: promises and new drugs in 2022.Pharmacological reports : PR · 2023Review
- Development and Characterization of Folic Acid-Conjugated Amodiaquine-Loaded Nanoparticles-Efficacy in Cancer Treatment.Pharmaceutics · 2023Article
- Explaining Accurate Predictions of Multitarget Compounds with Machine Learning Models Derived for Individual Targets.Molecules (Basel, Switzerland) · 2023Article
- Challenges in phytotherapy research.Frontiers in pharmacology · 2023Article
- Dual Inhibitors of AChE and BACE-1 for Reducing Aβ in Alzheimer's Disease: From In Silico to In Vivo.International journal of molecular sciences · 2022Article
- De Novo Prediction of Drug Targets and Candidates by Chemical Similarity-Guided Network-Based Inference.International journal of molecular sciences · 2022Article
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
introductionIn recent years, computational polypharmacology has gained significant attention to study the promiscuous nature of drugs. Despite tremendous challenges, community-wide efforts have led to a variety of novel approaches for predicting drug polypharmacology. In particular, some rapid advances using machine learning and artificial intelligence have been reported with great success. AREAS COVERED: In this article, the authors provide a comprehensive update on the current state-of-the-art polypharmacology approaches and their applications, focusing on those reports published after our 2017 review article. The authors particularly discuss some novel, groundbreaking concepts, and methods that have been developed recently and applied to drug polypharmacology studies. EXPERT OPINION: Polypharmacology is evolving and novel concepts are being introduced to counter the current challenges in the field. However, major hurdles remain including incompleteness of high-quality experimental data, lack of
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.