蛋白质—蛋白质对接方法的研究
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摘要
蛋白质-蛋白质相互作用与识别的研究是分子生物学领域的重要课题。由于实验测定蛋白质复合物结构的困难，目前，通过计算机模拟来预测分子间结合模式的对接方法受到了很大的关注。分子对接的最终目的是预测未知复合物结构的受体和配体之间的结合情况，对这种自由态分子的对接问题，在一定程度上考虑分子的柔性是非常必要的。然而，在蛋白质-蛋白质对接中，体系原子数和自由度数的增加使模拟复合物形成中的构象变化十分困难。另外，搜索过程可能产生数百万的对接构象，在用精细的能量函数打分之前，如何对这些结构进行初步筛选以得到尽可能多的近天然构象是目前方法研究中极具挑战性的问题。
使用打分函数的目的，是在合理的时间内对结构作出有效评价，以区分出近天然构象。目前，很多对接算法所使用的打分函数是基于热力学假设，即天然蛋白质复合物的结构是结合自由能最低的构象。因此，发展一个计算快且足够准确的结合自由能计算方法是结构预测中十分重要的一步。
本文包括三个部分。第一部分，针对自由态分子对接问题，提出了一个有效的蛋白质-蛋白质软对接方法；第二部分，在软对接方法的基础上，我们发展了一个依赖于复合物类型的分子对接算法；第三部分是关于对接算法中打分函数的研究。论文的主要研究内容包括以下方面：
(1)在Wodak和Janin的刚性对接算法基础上，针对自由态分子对接问题，提出了一个蛋白质-蛋白质软对接方法。采用简化蛋白模型：一个残基用一个球来表示，模拟分子的表面，并采用软化分子表面的方式考虑了分子的柔性。由于蛋白质表面氨基酸残基Arg、Lys、Asp、Glu和Met具有较大的柔性，因此，
北京工业大学工学博士学位论文
一
我们对蛋白质分子表面的这五种氨基酸模型作了修正，调整了残基球心的位置
和半径的数值，使分子表面的氨基酸残基在对接时具有一定程度的可交叠性。
在结构过滤中，将复合物界面残基成对偏好性引入到几何匹配过滤方法中，发
展了双重过滤技术来筛选合理的结合模式。最后对这些保留下来的结构进行能
量优化和打分排序以获得近天然结构（native－like structure）。打分函数中包括
静电相互作用能、去水化自由能和范德华能。用该方法对26个蛋白质－蛋白质
复合物体系作了测试，结果发现以上改进确实大大提高了自由态分子对接预测
的成功率。其中，在胰蛋白酶－APPI复合物结构预测中，尽管抑制剂 APPI的 15
号残基Arg侧链在复合物形成过程中发生了较大的构象变化，但其近天然结构
仍然被找到了，并在打分中排在了第一位。
仅）在软对接方法的基础上，我们对过滤方案作了进一步的改进，得到了
依赖于复合物类型的分子对接方法。根据复合物界面的特性，对蛋白酶－抑制剂
类、抗原。抗体类和其它类复合物采用不同的过滤方法，其中考虑了界面几何匹
配、疏水性和静电互补性。用该方法对46个蛋白质－蛋白质复合物体系进行了
对接测试，其中有 25个蛋白酶－抑制剂类、11个抗体－抗原类、10个其它类型，
结果全部找到了近天然结构，并有30个体系的近天然构象排在了前20位。与
第一部分的软对接算法相比，依赖于复合物类型的对接方法抓住了不同类型复
合物中分子间相互作用与识别的重要差异，能够在过滤中筛选到更多的近天然
构象，提高了结构预测的成功率。
另外，采用该分子对接方法，我们对 2002年 CAPRI（Critical Assessment o7
Prediction of Interactions）学术大会提供的三种不同突变形式的骆驼 VHH抗体
和胰腺a．淀粉酶分子之间相互作用与识别进行了预测（分别记作T04、T05和
T06）。才据抗体分于的 CDRS（CO＊plCmeflt盯ity DCtC＊illiflg RCgioflS）与其抗
原发生结合这一假设来限制抗体表面的搜索范围。在几何匹配过滤和静电相互
作用能过滤后，对筛选得到的结构用最陡下降法优化，然后再进行打分排序。
互I
摘 要
打分中考虑了去水化自由能和静电相互作用能，分别用修正的原子接触能模型
和有限差分解泊松－玻尔兹曼方程方法（Finite Difference Polsson刁oltZmann，
FDPB）来计算。在预测结果中，对T06，有两个近天然结构排在了前五位。
可以认为此结构的预测是非常成功的，这也得到了CAPRI检测小组的肯定。
对T04和 T05，尽管没有找到近天然构象，但预测也并不是完全失败的，在前
五个结构中，我们各找到了两个这样的结构，其中抗体识别到了抗原决定簇一
半以上的氨基酸残基，但抗体相对于抗原的方位是错误的。与其他参赛小组相
比，我们的预测结果还是可信的。这也进一步说明依赖于复合物类型的软对接
算法与相关的生物信息相结合能够对一些复合物的结构作出很好的预测，可以
作为研究分子识别的有效工具。
（）通过分析蛋白质分子间静电、疏水作用和嫡效应与相对于蛋白质晶体
结构主链原子的均方根偏差（ILMSD）的相关性，定量地考察了它们在蛋白质－
蛋?
Investigation of protein-protein interaction and recognition is an important problem in the field of molecular biology. Given the difficulties in experimentally determining the structures of protein complexes, the docking method to computationally predict potential binding modes is currently of great interest. The final goal of molecular docking is to construct a complex using the unbound structures of the receptor and the ligand. For the unbound docking problem, it is necessary to take into account molecular flexibility in some degree. In protein-protein docking, however, because of the large number of atoms and degrees of freedom involved, it has been very difficult to simulate the conformational changes occurring during the formation of complexes. Additionally, a search procedure may produce millions of docked structures. How to drastically eliminate the incorrect structures and retain the near-native ones as many as possible before scoring them with a refined energy function is a serious challenge topic of current researches.
The main goal of a scoring function is to distinguish between the near-native structures and a large number of incorrect ones within a reasonable time. Currently, the scoring functions used in many docking algorithms are based on the thermodynamic hypothesis that the native protein-protein complex is the structure with the lowest binding free energy. Thus, an important step in this approach is to develop the binding free energy functions that are computationally feasible and yet accurate enough to discriminate the near-native conformations from the incorrect ones.
In the present work three parts are included. In the first part, aiming at the unbound docking problem, we have proposed an efficient protein-protein soft docking method. In the second part, the complex type-dependent docking algorithm is developed according to the soft docking method. The last part is a study on the scoring function in protein-protein docking algorithm. The main concept of this work includes the following aspects:
(1) Our soft docking method is proposed based on Wodak and Janin's protein-protein rigid docking algorithm. In our method, the "simplified protein" model is used with one sphere per residue, and the molecule is of flexibility to some extent taken into account through softening the molecular surface. Because the large conformational changes occurring upon complex formation are frequently confined to the protein surface, especially for the side chains of flexible amino acids Arg, Lys, Asp, Glu and Met, the locations of the mass centers and the values of radii of these residues are modified for modeling protein surface. This tolerates overlap in some degree between the amino acid side chains on the surfaces of the receptor and the ligand. The interface residue pairing preferences are introduced into the geometric matching .filter, and a double filtering technique is implemented to eliminate most of the unreasonable binding modes. The energy minimization is performed on the retained structures, and then these structures are evaluated with a scoring function which includes electrostatic, desolvation and van der Waals energy terms. The 26 complexes were used to test this docking algorithm and good results were obtained. The results indicate that because of the improvement in two aspects mentioned above, the successful probability of the docking prediction is increased from unbound structures. For the case of enzyme trypsin-inhibitor APPI, although the large conformational change occurs to the Arg 15 side chain of APPI upon complex
formation, the native-like structure was still found and ranked first.
(2) On the basis of the soft docking method, the further improvement is made in the filtering stage to develop the complex type-dependent docking algorithm. In terms of the interface features of complexes, the different filtering methods based on the geometric matching, hydrophobicity and electrostatic complementarity of interfaces are applied to different types of complexes including
使用打分函数的目的，是在合理的时间内对结构作出有效评价，以区分出近天然构象。目前，很多对接算法所使用的打分函数是基于热力学假设，即天然蛋白质复合物的结构是结合自由能最低的构象。因此，发展一个计算快且足够准确的结合自由能计算方法是结构预测中十分重要的一步。
本文包括三个部分。第一部分，针对自由态分子对接问题，提出了一个有效的蛋白质-蛋白质软对接方法；第二部分，在软对接方法的基础上，我们发展了一个依赖于复合物类型的分子对接算法；第三部分是关于对接算法中打分函数的研究。论文的主要研究内容包括以下方面：
(1)在Wodak和Janin的刚性对接算法基础上，针对自由态分子对接问题，提出了一个蛋白质-蛋白质软对接方法。采用简化蛋白模型：一个残基用一个球来表示，模拟分子的表面，并采用软化分子表面的方式考虑了分子的柔性。由于蛋白质表面氨基酸残基Arg、Lys、Asp、Glu和Met具有较大的柔性，因此，
北京工业大学工学博士学位论文
一
我们对蛋白质分子表面的这五种氨基酸模型作了修正，调整了残基球心的位置
和半径的数值，使分子表面的氨基酸残基在对接时具有一定程度的可交叠性。
在结构过滤中，将复合物界面残基成对偏好性引入到几何匹配过滤方法中，发
展了双重过滤技术来筛选合理的结合模式。最后对这些保留下来的结构进行能
量优化和打分排序以获得近天然结构（native－like structure）。打分函数中包括
静电相互作用能、去水化自由能和范德华能。用该方法对26个蛋白质－蛋白质
复合物体系作了测试，结果发现以上改进确实大大提高了自由态分子对接预测
的成功率。其中，在胰蛋白酶－APPI复合物结构预测中，尽管抑制剂 APPI的 15
号残基Arg侧链在复合物形成过程中发生了较大的构象变化，但其近天然结构
仍然被找到了，并在打分中排在了第一位。
仅）在软对接方法的基础上，我们对过滤方案作了进一步的改进，得到了
依赖于复合物类型的分子对接方法。根据复合物界面的特性，对蛋白酶－抑制剂
类、抗原。抗体类和其它类复合物采用不同的过滤方法，其中考虑了界面几何匹
配、疏水性和静电互补性。用该方法对46个蛋白质－蛋白质复合物体系进行了
对接测试，其中有 25个蛋白酶－抑制剂类、11个抗体－抗原类、10个其它类型，
结果全部找到了近天然结构，并有30个体系的近天然构象排在了前20位。与
第一部分的软对接算法相比，依赖于复合物类型的对接方法抓住了不同类型复
合物中分子间相互作用与识别的重要差异，能够在过滤中筛选到更多的近天然
构象，提高了结构预测的成功率。
另外，采用该分子对接方法，我们对 2002年 CAPRI（Critical Assessment o7
Prediction of Interactions）学术大会提供的三种不同突变形式的骆驼 VHH抗体
和胰腺a．淀粉酶分子之间相互作用与识别进行了预测（分别记作T04、T05和
T06）。才据抗体分于的 CDRS（CO＊plCmeflt盯ity DCtC＊illiflg RCgioflS）与其抗
原发生结合这一假设来限制抗体表面的搜索范围。在几何匹配过滤和静电相互
作用能过滤后，对筛选得到的结构用最陡下降法优化，然后再进行打分排序。
互I
摘 要
打分中考虑了去水化自由能和静电相互作用能，分别用修正的原子接触能模型
和有限差分解泊松－玻尔兹曼方程方法（Finite Difference Polsson刁oltZmann，
FDPB）来计算。在预测结果中，对T06，有两个近天然结构排在了前五位。
可以认为此结构的预测是非常成功的，这也得到了CAPRI检测小组的肯定。
对T04和 T05，尽管没有找到近天然构象，但预测也并不是完全失败的，在前
五个结构中，我们各找到了两个这样的结构，其中抗体识别到了抗原决定簇一
半以上的氨基酸残基，但抗体相对于抗原的方位是错误的。与其他参赛小组相
比，我们的预测结果还是可信的。这也进一步说明依赖于复合物类型的软对接
算法与相关的生物信息相结合能够对一些复合物的结构作出很好的预测，可以
作为研究分子识别的有效工具。
（）通过分析蛋白质分子间静电、疏水作用和嫡效应与相对于蛋白质晶体
结构主链原子的均方根偏差（ILMSD）的相关性，定量地考察了它们在蛋白质－
蛋?
Investigation of protein-protein interaction and recognition is an important problem in the field of molecular biology. Given the difficulties in experimentally determining the structures of protein complexes, the docking method to computationally predict potential binding modes is currently of great interest. The final goal of molecular docking is to construct a complex using the unbound structures of the receptor and the ligand. For the unbound docking problem, it is necessary to take into account molecular flexibility in some degree. In protein-protein docking, however, because of the large number of atoms and degrees of freedom involved, it has been very difficult to simulate the conformational changes occurring during the formation of complexes. Additionally, a search procedure may produce millions of docked structures. How to drastically eliminate the incorrect structures and retain the near-native ones as many as possible before scoring them with a refined energy function is a serious challenge topic of current researches.
The main goal of a scoring function is to distinguish between the near-native structures and a large number of incorrect ones within a reasonable time. Currently, the scoring functions used in many docking algorithms are based on the thermodynamic hypothesis that the native protein-protein complex is the structure with the lowest binding free energy. Thus, an important step in this approach is to develop the binding free energy functions that are computationally feasible and yet accurate enough to discriminate the near-native conformations from the incorrect ones.
In the present work three parts are included. In the first part, aiming at the unbound docking problem, we have proposed an efficient protein-protein soft docking method. In the second part, the complex type-dependent docking algorithm is developed according to the soft docking method. The last part is a study on the scoring function in protein-protein docking algorithm. The main concept of this work includes the following aspects:
(1) Our soft docking method is proposed based on Wodak and Janin's protein-protein rigid docking algorithm. In our method, the "simplified protein" model is used with one sphere per residue, and the molecule is of flexibility to some extent taken into account through softening the molecular surface. Because the large conformational changes occurring upon complex formation are frequently confined to the protein surface, especially for the side chains of flexible amino acids Arg, Lys, Asp, Glu and Met, the locations of the mass centers and the values of radii of these residues are modified for modeling protein surface. This tolerates overlap in some degree between the amino acid side chains on the surfaces of the receptor and the ligand. The interface residue pairing preferences are introduced into the geometric matching .filter, and a double filtering technique is implemented to eliminate most of the unreasonable binding modes. The energy minimization is performed on the retained structures, and then these structures are evaluated with a scoring function which includes electrostatic, desolvation and van der Waals energy terms. The 26 complexes were used to test this docking algorithm and good results were obtained. The results indicate that because of the improvement in two aspects mentioned above, the successful probability of the docking prediction is increased from unbound structures. For the case of enzyme trypsin-inhibitor APPI, although the large conformational change occurs to the Arg 15 side chain of APPI upon complex
formation, the native-like structure was still found and ranked first.
(2) On the basis of the soft docking method, the further improvement is made in the filtering stage to develop the complex type-dependent docking algorithm. In terms of the interface features of complexes, the different filtering methods based on the geometric matching, hydrophobicity and electrostatic complementarity of interfaces are applied to different types of complexes including
引文
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