High-Throughput Structure-Based Drug Design (HT-SBDD) Using Drug Docking, Fragment Molecular Orbital Calculations, and Molecular Dynamic Techniques.
| Autor: | Martin RL; Research Department of Structural & Molecular Biology, Division of Biosciences, University College London, London, UK. reuben.martin.18@ucl.ac.uk.; Evotec (UK) Ltd., Abingdon, Oxfordshire, UK. reuben.martin.18@ucl.ac.uk., Heifetz A; In Silico Research and Development, Evotec UK Ltd., Abingdon, UK. alexander.heifetz@evotec.com., Bodkin MJ; Evotec (UK) Ltd., Abingdon, Oxfordshire, UK., Townsend-Nicholson A; Research Department of Structural & Molecular Biology, Division of Biosciences, University College London, London, UK. |
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| Jazyk: | angličtina |
| Zdroj: | Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2024; Vol. 2716, pp. 293-306. |
| DOI: | 10.1007/978-1-0716-3449-3_13 |
| Abstrakt: | 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. (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.) |
| Databáze: | MEDLINE |
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