ReviewInternational journal of molecular sciences2022
Application of Computational Biology and Artificial Intelligence in Drug Design.
Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 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
46 citing papers in PubMed.
- Breaking through the radiation dilemma: development and clinical translation of anti-radiation drugs.Pharmaceutical science advances · 2026Review
- Identification of novel PI3Kα inhibitors for colon cancer treatment via virtual screening, molecular dynamics simulation, and in vitro activity validation.Molecular diversity · 2026Article
- Hierarchical Contrastive Learning for Protein-Protein Interaction Prediction Across Organisms.International journal of molecular sciences · 2026Article
- Machine learning-guided discovery of spirocyclic inhibitors targeting Mycobacterium tuberculosis FtsZ.Folia microbiologica · 2026Article
- Organoids, organ-on-a-chip, and microtumors: Biomimetic 3D tumor models advancing drug development and precision medicine.Acta pharmaceutica Sinica. B · 2026Review
- Targeting Selectivity: Improving Golgi α-Mannosidase II (GMII) Inhibitors Through In Silico Studies.Biomolecules · 2026Review
- Virtual cell: Current perspectives and future prospects.The Journal of international medical research · 2026Review
- Identification of potential MenT3 inhibitors for Mycobacterium tuberculosis using the generative artificial intelligence and SilicoXplore platform.Scientific reports · 2026Article
- Redefining Therapies for Drug-Resistant Tuberculosis: Synergistic Effects of Antimicrobial Peptides, Nanotechnology, and Computational Design.Advanced healthcare materials · 2026Review
- Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases.Clinical and experimental medicine · 2026Review
- Artificial Intelligence and the Discovery of Antibiotics: Reinventing with Opportunities, Challenges, and Clinical Translation.Antibiotics (Basel, Switzerland) · 2026Review
- Elucidating the molecular mechanisms of paeoniflorin intervention in oral lichen planus: a computational biology and bioinformatics-based research strategy.Frontiers in bioinformatics · 2026Article
- AI-Integrated Micro/Nanorobots for Biomedical Applications: Recent Advances in Design, Fabrication, and Functions.Biosensors · 2025Review
- Antibody-drug conjugates in cancer therapy: current landscape, challenges, and future directions.Molecular cancer · 2025Review
- Strategies for robust, accurate, and generalizable benchmarking of drug discovery platforms.Bioinformatics (Oxford, England) · 2025Article
- Artificial intelligence for autoimmune diseases.NPJ digital medicine · 2025Article
- Marine Bioactive Peptides in the Regulation of Inflammatory Responses: Current Trends and Future Directions.Proteomes · 2025Review
- Knowledge, attitude and practice of artificial intelligence among dietitians in Saudi Arabia: a cross-sectional study.BMJ open · 2025Article
- Accurate Protein Dynamic Conformational Ensembles: Combining AlphaFold, MD, and AmideInternational journal of molecular sciences · 2025Article
- Strategies for robust, accurate, and generalizable benchmarking of drug discovery platforms.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Traditional drug design requires a great amount of research time and developmental expense. Booming computational approaches, including computational biology, computer-aided drug design, and artificial intelligence, have the potential to expedite the efficiency of drug discovery by minimizing the time and financial cost. In recent years, computational approaches are being widely used to improve the efficacy and effectiveness of drug discovery and pipeline, leading to the approval of plenty of new drugs for marketing. The present review emphasizes on the applications of these indispensable computational approaches in aiding target identification, lead discovery, and lead optimization. Some challenges of using these approaches for drug design are also discussed. Moreover, we propose a methodology for integrating various computational techniques into new drug discovery and design.
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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.