ReviewBoletin medico del Hospital Infantil de Mexico
Application of computational methods for anticancer drug discovery, design, and optimization.
Review in Boletin medico del Hospital Infantil de Mexico. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
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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.
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.
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Who cites it
31 citing papers in PubMed.
- AI-driven computational drug design: tools, workflow and challenges.RSC advances · 2026Review
- Computational-experimental repurposing reveals synergistic sorafenib/hydroxychloroquine response in KRAS-mutant breast cancer.BMC pharmacology & toxicology · 2026Article
- Prediction of angiogenesis suppression by myricetin fromHeliyon · 2025Article
- Identifying Potential Autophagy Modulators in Panch Phoron Spices (P5S): An In Silico approach.ACS omega · 2025Article
- Artificial Intelligence-Driven Computational Approaches in the Development of Anticancer Drugs.Cancers · 2024Article
- Cancer pharmacoinformatics: Databases and analytical tools.Functional & integrative genomics · 2024Review
- In silico analysis of potential inhibitors for breast cancer targeting 17beta-hydroxysteroid dehydrogenase type 1 (17beta-HSD1) catalyses.Journal of cellular and molecular medicine · 2024Article
- Comprehensive review of the repositioning of non-oncologic drugs for cancer immunotherapy.Medical oncology (Northwood, London, England) · 2024Review
- Recent advances in the area of plant-based anti-cancer drug discovery using computational approaches.Molecular diversity · 2024Review
- Anticancer Drug Discovery Based on Natural Products: From Computational Approaches to Clinical Studies.Biomedicines · 2024Review
- PredictingIn silico pharmacology · 2024Article
- In-silico study of novel dimeric flavonoid (OC251FR2) isolated from the seeds ofIn silico pharmacology · 2024Article
- Unveiling New Druggable Pockets in Influenza Non-Structural Protein 1: NS1-Host Interactions as Antiviral Targets for Flu.International journal of molecular sciences · 2023Article
- Identification of Activated Cdc42-Associated Kinase Inhibitors as Potential Anticancer Agents Using Pharmacoinformatic Approaches.Biomolecules · 2023Article
- Nanoinformatics and Personalized Medicine: An Advanced Cumulative Approach for Cancer Management.Current medicinal chemistry · 2023Review
- Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance.Bioengineering (Basel, Switzerland) · 2022Review
- Design, synthesis and evaluation of 4,7-disubstituted 8-methoxyquinazoline derivatives as potential cytotoxic agents targeting β-catenin/TCF4 signaling pathway.Translational oncology · 2022Article
- Toward the Identification of Natural Antiviral Drug Candidates against Merkel Cell Polyomavirus: Computational Drug Design Approaches.Pharmaceuticals (Basel, Switzerland) · 2022Article
- Review
- Cheminformatic Characterization of Natural Antimicrobial Products for the Development of New Lead Compounds.Molecules (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Developing a novel drug is a complex, risky, expensive and time-consuming venture. It is estimated that the conventional drug discovery process ending with a new medicine ready for the market can take up to 15 years and more than a billion USD. Fortunately, this scenario has recently changed with the arrival of new approaches. Many novel technologies and methodologies have been developed to increase the efficiency of the drug discovery process, and computational methodologies have become a crucial component of many drug discovery programs. From hit identification to lead optimization, techniques such as ligand- or structure-based virtual screening are widely used in many discovery efforts. It is the case for designing potential anticancer drugs and drug candidates, where these computational approaches have had a major impact over the years and have provided fruitful insights into the field of cancer. In this paper, we review the concept of rational design presenting some of the most representative examples of molecules identified by means of it. Key principles are illustrated through case studies including specifically successful achievements in the field of anticancer drug design to demonstrate that research advances, with the aid of in silico drug design, have the potential to create novel anticancer drugs.
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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.