一种基于知识的提高蛋白-配体亲合性预测精度的计算方法
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- 英文论文题名：Knowledge-Based Prediction of Protein-Ligand Binding Affinity
- 论文作者：王任小
- 英文论文作者：Renxiao Wang ; State Key Laboratory of Bioorganic and Natural Products Chemistry ; Collaborative Innovation Center of Chemistry for Life Sciences ; Shanghai Institute of Organic Chemistry ; Chinese Academy of Sciences
- 年：2016
- 作者机构：中国科学院上海有机化学研究所生命有机化学国家重点实验室;
- 论文关键词：蛋白-配体相互作用 ; 亲合性计算方法 ; 三维作用指纹 ; 打分函数 ; 药物分子设计
- 会议召开时间：2016-07-01
- 会议录名称：中国化学会第30届学术年会摘要集-第二十五分会：化学信息学与化学计量学
- 语种：中文
- 分类号：TQ460.1
- 学会代码：ZGHY
- 会议名称：中国化学会第30届学术年会-第二十五分会 ; 化学信息学与化学计量学
- 会议地点：中国辽宁大连
- 主办单位：中国化学会
- 学会名称：中国化学会
- 页数：1
- 文件大小：162k
- 原文格式：D
- 会议级别：全国
摘要
为了提高打分函数用于预测蛋白-配体亲合性的精度,我们在前期工作中发展了"基于知识的打分策略"(Knowledge-Guided Scoring,KGS)~([1])。该策略的关键思想是:对于一个给定蛋白-配体复合物,首先寻找一个结构类似的参考复合物,根据参考复合物的已知亲合性实验数据来修正计算结果。我们进一步发展了改进的KGS2方法,其主要改进在于引入三维蛋白-配体相互作用指纹来匹配参考复合物~([2])。我们选择了5种不同类型的打分函数与KGS2联合使用,在5种靶标蛋白上进行了测试。在已知复合物晶体结构来计算亲合性的原位打分测试中,应用KGS2在大部分情况下获得了精度提升的计算结果。在分子对接测试中,应用KGS2在某些情况下也获得了精度提升的计算结果。我们发展的KGS2方法,可以方便地提升现有打分函数的性能,并不需要对这些打分函数本身做任何修改,而且其应用范围在理论上不受靶标蛋白类型的限制。KGS2方法为在分子靶向药物分子设计中提高预测蛋白-配体亲合性的精度提供了一种实用的方法。
In order to improve the accuracy in binding affinity prediction,we previously reported the Knowledge-Guided Scoring(KGS) method.The key idea is to compute the binding affinity of a given protein-ligand complex based on the known binding affinity of an appropriate reference complex.In this study,we have developed an upgraded version,i.e.KGS2,by introducing 3D protein-ligand interaction fingerprints into reference complex selection.KGS2 was evaluated in couple with five selected scoring functions on five drug targets.This new method showed promising performance in both in situ scoring test as well as molecular docking test.It has the potential to serve as a practical option for enhancing the performance of current scoring functions.
In order to improve the accuracy in binding affinity prediction,we previously reported the Knowledge-Guided Scoring(KGS) method.The key idea is to compute the binding affinity of a given protein-ligand complex based on the known binding affinity of an appropriate reference complex.In this study,we have developed an upgraded version,i.e.KGS2,by introducing 3D protein-ligand interaction fingerprints into reference complex selection.KGS2 was evaluated in couple with five selected scoring functions on five drug targets.This new method showed promising performance in both in situ scoring test as well as molecular docking test.It has the potential to serve as a practical option for enhancing the performance of current scoring functions.
引文
[1]Cheng,T.;Liu,Z.;Wang,R.*,BMC Bioinformatics,2010,11,193-208.
[2]Liu,J.;Liu,Z.;Li,J.;Li,Y.;*Wang,R.Improved Prediction of Protein-Ligand Binding Affinity with the Aid of 3D Interaction Fingerprints(under reviewing).
[2]Liu,J.;Liu,Z.;Li,J.;Li,Y.;*Wang,R.Improved Prediction of Protein-Ligand Binding Affinity with the Aid of 3D Interaction Fingerprints(under reviewing).