Assessment of a Novel Scoring Method Based on Solvent Accessible Surface Area Descriptors
Assessment of a Novel Scoring Method Based on Solvent Accessible Surface Area Descriptors
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DOI：
10.1021/ci9004628
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发表时间：
2010-04-01
影响因子：
5.6
通讯作者：
Kruse, Chris G.
中科院分区：
文献类型：
--
作者：
Nunez, Sara;Venhors, Jennifer;Kruse, Chris G.
基于独特的溶剂可及表面积 (SASA) 描述符的新型评分算法与虚拟筛选 (VS) 方法 GOLD 和 Glide 的数据库富集潜力进行了比较评估。几个蛋白质测试用例，包括腺苷脱氨酶和雌激素受体α，被用于评估。基于结构的 VS 方法 GOLD 用于生成蛋白质-配体对接姿势。然后使用蛋白质-配体相互作用指纹度量对这些对接姿势进行后处理。接下来，计算每个配体及其各自处于结合/未结合状态的蛋白质的 SASA 描述符；使用 SASA 描述符学习贝叶斯模型，随后用于对筛选数据库中的剩余配体进行评分。人们发现，使用 SASA 描述符的早期数据库丰富性与 GOLD 和 Glide 相当或优于 GOLD 和 Glide。此外，SASA 描述符表现出出色的鲁棒性，可以为多种目标类别产生令人满意的早期富集。基于这些令人鼓舞的结果，这些新颖的拓扑描述符构成了命中查找实践中有价值的计算机工具。
A novel scoring algorithm based on unique solvent accessible surface area (SASA) descriptors was comparatively evaluated for its database enrichment potential against the virtual screening (VS) methods GOLD and Glide. Several protein test cases, including adenosine deaminase and estrogen receptor alpha, were used for the evaluation. The structure-based VS method GOLD was used to generate the protein-ligand docking poses. These docking poses were then postprocessed with a protein-ligand interaction fingerprint metric. Next, the SASA descriptors were computed for each ligand and its respective protein in their bound/unbound states; a Bayesian model was learned with SASA descriptors and subsequently used to score the remaining ligands in the screening databases. Early database enrichments using SASA descriptors were found comparable or superior to those of GOLD and Glide. Moreover, SASA descriptors display an outstanding robustness to produce satisfactory early enrichments for a large variety of target classes. Based on these encouraging results, these novel topological descriptors constitute a valuable in silico tool in hit finding practices.