Developing similarity matrices for antibody-protein binding interactions.
Developing similarity matrices for antibody-protein binding interactions.
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DOI：
10.1371/journal.pone.0293606
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发表时间：
2023
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
AlphaFold和RoseTTAFold的发明正在彻底改变计算蛋白质科学，因为它们能够可靠地预测蛋白质结构。他们前所未有的成功是由于并行考虑几种类型的信息，其中之一是蛋白质序列相似性信息。序列同源性已经研究了几十年，并且依赖于相似性矩阵来定义蛋白质序列彼此之间的相似性或不同性。预测蛋白质结构的自然延伸是预测蛋白质之间的相互作用，但蛋白质-蛋白质相互作用的相似性矩阵并不存在。本研究对384个非冗余抗体-蛋白抗原复合物进行了突变分析，以计算抗体-蛋白相互作用相似性矩阵。将每种抗体和每种抗原中的每个重要残基突变为其他19种常见氨基酸中的每一种，并使用三种力场计算相互作用能的百分比变化：CHARMM、Amber和Rosetta。这些数据用于构建六个相互作用相似性矩阵，一个用于抗体，另一个用于使用每个力场的抗原。基质表现出共同点，如芳香族和带电残基的突变是最有害的，和差异，如Rosetta预测丝氨酸的突变比琥珀或CHARMM更好地耐受。与先前发表的9个蛋白质序列相似性矩阵的比较显示，新的相互作用矩阵彼此之间比它们与任何先前的矩阵更相似。所创建的相似性矩阵可用于力场特定应用中，以帮助指导关于蛋白质-蛋白质结合界面中的突变的决策。
The inventions of AlphaFold and RoseTTAFold are revolutionizing computational protein science due to their abilities to reliably predict protein structures. Their unprecedented successes are due to the parallel consideration of several types of information, one of which is protein sequence similarity information. Sequence homology has been studied for many decades and depends on similarity matrices to define how similar or different protein sequences are to one another. A natural extension of predicting protein structures is predicting the interactions between proteins, but similarity matrices for protein-protein interactions do not exist. This study conducted a mutational analysis of 384 non-redundant antibody–protein antigen complexes to calculate antibody-protein interaction similarity matrices. Every important residue in each antibody and each antigen was mutated to each of the other 19 commonly occurring amino acids and the percentage changes in interaction energies were calculated using three force fields: CHARMM, Amber, and Rosetta. The data were used to construct six interaction similarity matrices, one for antibodies and another for antigens using each force field. The matrices exhibited both commonalities, such as mutations of aromatic and charged residues being the most detrimental, and differences, such as Rosetta predicting mutations of serines to be better tolerated than either Amber or CHARMM. A comparison to nine previously published similarity matrices for protein sequences revealed that the new interaction matrices are more similar to one another than they are to any of the previous matrices. The created similarity matrices can be used in force field specific applications to help guide decisions regarding mutations in protein-protein binding interfaces.
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DOI：
10.1073/pnas.89.22.10915
发表时间：
1992-11-15
影响因子：
11.1
作者：
HENIKOFF, S;HENIKOFF, JG
通讯作者：
HENIKOFF, JG
影响因子：
64.8
作者：
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通讯作者：
Hassabis D
影响因子：
3.7
作者：
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通讯作者：
Kim PM
DOI：
10.1016/j.pbiomolbio.2016.10.002
发表时间：
2017-09-01
影响因子：
3.8
作者：
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通讯作者：
Ascher, David B.
影响因子：
2.9
作者：
Jia K;Jernigan RL
通讯作者：
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