Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
Molecular Modeling Section, Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
Drug Discov Today. 2020 Sep;25(9):1693-1701. doi: 10.1016/j.drudis.2020.06.023. Epub 2020 Jun 25.
Fragment-based drug discovery (FBDD) is an innovative approach, progressively more applied in the academic and industrial context, to enhance hit identification for previously considered undruggable biological targets. In particular, FBDD discovers low-molecular-weight (LMW) ligands (<300Da) able to bind to therapeutically relevant macromolecules in an affinity range from the micromolar (μM) to millimolar (mM). X-ray crystallography (XRC) and nuclear magnetic resonance (NMR) spectroscopy are commonly the methods of choice to obtain 3D information about the bound ligand-protein complex, but this can occasionally be problematic, mainly for early, low-affinity fragments. The recent development of computational fragment-based approaches provides a further strategy for improving the identification of fragment hits. In this review, we summarize the state of the art of molecular dynamics simulations approaches used in FBDD, and discuss limitations and future perspectives for these approaches.
基于片段的药物发现（FBDD）是一种创新方法，在学术和工业领域的应用越来越多，旨在提高对以前认为不可成药的生物靶点的命中识别。特别是，FBDD 发现了能够与治疗相关的大分子结合的低分子量（LMW）配体（<300Da），其亲和力范围从微摩尔（μM）到毫摩尔（mM）。X 射线晶体学（XRC）和核磁共振（NMR）光谱通常是获得结合配体-蛋白质复合物的 3D 信息的首选方法，但这偶尔会出现问题，主要是对于早期、低亲和力的片段。最近计算基于片段的方法的发展为提高片段命中的识别提供了另一种策略。在这篇综述中，我们总结了在 FBDD 中使用的分子动力学模拟方法的最新进展，并讨论了这些方法的局限性和未来展望。
