Evolutionary insights into the active-site structures of the metallo-β-lactamase superfamily from a classification study with support vector machine.

Journal: Journal of biological inorganic chemistry : JBIC : a publication of the Society of Biological Inorganic Chemistry
Published Date:

Abstract

The metallo-β-lactamase (MβL) superfamily, which is intriguing due to its enzyme promiscuity, is a good model enzyme superfamily for studies of catalytic function evolution. Our previous study traced the evolution of the phosphotriesterase activity of the MβL superfamily and found that MβLs go through three typical active-site structures in the development of phosphotriesterase activity. In the present study, taking the three typical active-site structures as class labels, the classification and prediction models, which were established by support vector machine and amino acid composition, classified the MβL members into three classes. The indispensable amino acid compositions showed a surprising performance that was remarkably better than the performance of the dispensable amino acid compositions and even equal to the performance of the 20 native amino acids. We further traced the origin of the classification error and found that there was one subclass adopting a type of active-site structure that was the evolutionary transition between these classes. After that, our classification and prediction models were successfully used to predict several MβL active-site structures that lost the dinuclear structures during crystallization. In summary, our studies established a classification and prediction system for active-site structures that well compensated for experimental methods that recognize protein structure details and suggest that the indispensable amino acids contain much more protein structure information than the dispensable amino acids.

Authors

  • Lili Wang
    School of Logistics, Chengdu University of Information Technology, Chengdu, China.
  • Ling Yang
    Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine Shanghai 201203 China pwang@shutcm.edu.cn.
  • Yu-Lan Feng
    Biomedical Research Center, College of Life Science and Engineering, Northwest Minzu University, Lanzhou, 730030, People's Republic of China.
  • Hao Zhang
    College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China.