Department of Chemistry, Seoul National University, Seoul 151-742, Korea.
BMC Bioinformatics. 2010 May 18;11:256. doi: 10.1186/1471-2105-11-256.
Modelling the ligand binding site of a protein is an important component of understanding protein-ligand interactions and is being actively studied. Even if the side chains are restricted to rotamers, a set of commonly-observed low-energy conformations, the exhaustive combinatorial search of ligand binding site conformers is known as NP-hard. Here we propose a new method, ROTAIMAGE, for modelling the plausible conformers for the ligand binding site given a fixed backbone structure.
ROTAIMAGE includes a procedure of selecting ligand binding site residues, exhaustively searching rotameric conformers, clustering them by dissimilarities in pocket shape, and suggesting a representative conformer per cluster. Prior to the clustering, the list of conformers generated by exhaustive search can be reduced by pruning the conformers that have near identical pocket shapes, which is done using simple bit operations. We tested our approach by modelling the active-site inhibitor binding pockets of matrix metalloproteinase-1 and -13. For both cases, analyzing the conformers based on their pocket shapes substantially reduced the 'computational complexity' (10 to 190 fold). The subsequent clustering revealed that the pocket shapes of both proteins could be grouped into approximately 10 distinct clusters. At this level of clustering, the conformational space spanned by the known crystal structures was well covered. Heatmap analysis identified a few bit blocks that combinatorially dictated the clustering pattern. Using this analytical approach, we demonstrated that each of the bit blocks was associated with a specific pocket residue. Identification of residues that influenced the shape of the pocket is an interesting feature unique to the ROTAIMAGE algorithm.
ROTAIMAGE is a novel algorithm that was efficient in exploring the conformational space of the ligand binding site. Its ability to identify 'key' pocket residues also provides further insight into conformational flexibility with specific implications for protein-ligand interactions.
对蛋白质的配体结合位点进行建模是理解蛋白质-配体相互作用的重要组成部分，目前正在积极研究中。即使侧链被限制在构象中，即一组常见的低能量构象，配体结合位点构象的穷举组合搜索也被称为 NP 难问题。在这里，我们提出了一种新的方法 ROTAIMAGE，用于对给定固定骨架结构的配体结合位点的可能构象进行建模。
ROTAIMAGE 包括选择配体结合位点残基的过程，对构象进行穷举搜索，根据口袋形状的差异对它们进行聚类，并为每个聚类建议一个代表性构象。在聚类之前，可以使用简单的位操作来减少通过近相同口袋形状修剪的构象，从而减少穷举搜索生成的构象列表。我们通过对基质金属蛋白酶-1 和 -13 的活性位点抑制剂结合口袋进行建模来测试我们的方法。对于这两种情况，基于口袋形状分析构象大大降低了“计算复杂度”（10 到 190 倍）。随后的聚类表明，这两种蛋白质的口袋形状可以分为大约 10 个不同的簇。在这个聚类水平上，已知晶体结构所涵盖的构象空间很好。热图分析确定了几个组合决定聚类模式的位块。使用这种分析方法，我们证明了每个位块都与特定的口袋残基相关联。鉴定影响口袋形状的残基是 ROTAIMAGE 算法的一个有趣特征。
ROTAIMAGE 是一种有效的探索配体结合位点构象空间的新算法。它识别“关键”口袋残基的能力也为构象灵活性提供了进一步的见解，对蛋白质-配体相互作用具有特定的意义。
