Characterization of protein-ligand interaction sites using experimental and computational methods.
Characterization of protein-ligand interaction sites using experimental and computational methods.
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发表时间：
2006-05
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通讯作者：
S. Vajda;F. Guarnieri
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作者：
S. Vajda;F. Guarnieri
在药物设计中，识别一种能与小的、类似药物的化合物高亲和力结合的蛋白质的位点一直是一个重要的目标。准确预测可用药位点和识别结合在这些位点上的小化合物为基于片段的组合方法提供了输入，这些方法允许对化学空间进行更彻底的探索，并且有可能产生比使用传统高通量筛选发现的分子更像铅的分子。本文综述了目前用于鉴定和表征蛋白质靶标上可药物配体结合位点的实验和计算方法的进展，包括成功的核磁共振，x射线晶体学和系绳技术的讨论。还讨论了经典的几何和基于能量的计算方法，特别关注两种强大的技术，即计算溶剂映射和大规范蒙特卡罗模拟（如Locus制药公司所使用的）。这两种方法都可以用来可靠地识别蛋白质上的可药物位点，并促进设计新的低纳米分子亲和力配体。
The ability to identify the sites of a protein that can bind with high affinity to small, drug-like compounds has been an important goal in drug design. Accurate prediction of druggable sites and the identification of small compounds binding in those sites have provided the input for fragment-based combinatorial approaches that allow for a more thorough exploration of the chemical space, and that have the potential to yield molecules that are more lead-like than those found using traditional high-throughput screening. Current progress in experimental and computational methods for identifying and characterizing druggable ligand binding sites on protein targets is reviewed herein, including a discussion of successful nuclear magnetic resonance, X-ray crystallography and tethering technologies. Classical geometric and energy-based computational methods are also discussed, with particular focus on two powerful technologies, that is, computational solvent mapping and grand canonical Monte Carlo simulations (as used by Locus Pharmaceuticals Inc). Both methods can be used to reliably identify druggable sites on proteins and to facilitate the design of novel, low-nanomolar-affinity ligands.