A new benchmark illustrates that integration of geometric constraints inferred from enzyme reaction chemistry can increase enzyme active site modeling accuracy

被引:6
作者
Bertolani, Steve J. [1 ]
Siegel, Justin B. [1 ,2 ,3 ]
机构
[1] Univ Calif Davis, Dept Chem, Davis, CA 95616 USA
[2] Univ Calif Davis, Dept Biochem & Mol Med, Davis, CA 95616 USA
[3] Univ Calif Davis, Genome Ctr, Davis, CA 95616 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
PROTEIN-STRUCTURE PREDICTION; CRYSTAL-STRUCTURE; COMPLEX; SEQUENCE; ALIGNMENT; ROSETTA; SPECIFICITY; GLYCOSIDASE; INHIBITORS; TEMPLATES;
D O I
10.1371/journal.pone.0214126
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Enzymes play a critical role in a wide array of industrial, medical, and research applications and with the recent explosion of genomic sequencing, we now have sequences for millions of enzymes for which there is no known structure. In order to utilize modern computational design tools for constructing inhibitors or engineering novel catalysts, the ability to accurately model enzymes is critical. A popular approach for modeling enzymes are comparative modeling techniques which can often accurately predict the global structural features. However, achieving atomic accuracy of an active site remains a challenge and is an issue when trying to utilize the molecular details for designing inhibitors or enhanced catalysts. Here we explore integrating knowledge about the required geometric orientation of conserved catalytic residues into the comparative modeling process in order to improve modeling accuracy. In order to investigate the utility of adding this information, we first carefully construct a benchmark set of reference structures to use. Consistent with previous findings, our benchmark demonstrates that the geometry between catalytic residues across an enzyme family is conserved and does not tend to deviate by more than 0.5 angstrom. We then find that by integrating these geometric constraints during modeling, we can double the number of atomic level accuracy models (<1 angstrom RMSD to the crystal structure ligand) within our benchmarking dataset, even for targets with templates as low as 20-30% sequence identity. Catalytic residues within an enzyme family are highly conserved and can often be readily identified through comparative sequence analysis to a known structure within the enzyme family. Therefore utilizing this readily available information has the potential to significantly improve drug design and enzyme engineering efforts for which there is no known structure for the enzyme of interest.
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页数:15
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