ReviewMethods in molecular biology (Clifton, N.J.)2024
High-Throughput Structure-Based Drug Design (HT-SBDD) Using Drug Docking, Fragment Molecular Orbital Calculations, and Molecular Dynamic Techniques.
Review in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Identification and validation of exosome-related biomarkers in pediatric glioblastoma.Discover oncology · 2026Article
- Identification of small molecule inhibitors targeting FGFR through molecular docking-based screening.Frontiers in oncology · 2026Article
- ACLPred: an explainable machine learning and tree-based ensemble model for anticancer ligand prediction.Scientific reports · 2025Article
- A multiscale molecular structural neural network for molecular property prediction.Molecular diversity · 2025Article
- Conquering PROTAC molecular design and drugability.Bioanalysis · 2025Review
- Exploring G Protein-Coupled Receptors in Hematological Cancers.ACS pharmacology & translational science · 2024Article
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Authors and funding
4 authors.
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Abstract
Structure-based drug design (SBDD) is rapidly evolving to be a fundamental tool for faster and more cost-effective methods of lead drug discovery. SBDD aims to offer a computational replacement to traditional high-throughput screening (HTS) methods of drug discovery. This "virtual screening" technique utilizes the structural data of a target protein in conjunction with large databases of potential drug candidates and then applies a range of different computational techniques to determine which potential candidates are likely to bind with high affinity and efficacy. It is proposed that high-throughput SBDD (HT-SBDD) will significantly enrich the success rate of HTS methods, which currently fluctuates around ~1%. In this chapter, we focus on the theory and utility of high-throughput drug docking, fragment molecular orbital calculations, and molecular dynamics techniques. We also offer a comparative review of the benefits and limitations of traditional methods against more recent SBDD advances. As HT-SBDD is computationally intensive, we will also cover the important role high-performance computing (HPC) clusters play in the future of computational drug discovery.
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Registered trials
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