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西亚试剂:Structure-based activity prediction for an enzyme of unknow

发布时间:2025-09-04

Structure-based activity prediction for an enzyme of unknown function

Johannes C. Hermann1, Ricardo Marti-Arbona2, Alexander A. Fedorov3, Elena Fedorov3, Steven C. Almo3, Brian K. Shoichet1 & Frank M. Raushel2

  1. Department of Pharmaceutical Chemistry, University of California, San Francisco, MC 2550 1700 4th Street, San Francisco, California 94158-2330, USA
  2. Department of Chemistry, P.O. Box 30012, Texas A&M University, College Station, Texas 77842-3012, USA
  3. Department of Biochemistry, Albert Einstein College of Medicine, Ullmann Building, Room 411, 1300 Morris Park Avenue, Bronx, New York 10461, USA

Correspondence to: Brian K. Shoichet1 Correspondence and requests for materials related to docking should be addressed to B.K.S. (Email: shoichet@cgl.ucsf.edu).

Abstract

With many genomes sequenced, a pressing challenge in biology is predicting the function of the proteins that the genes encode. When proteins are unrelated to others of known activity, bioinformatics inference for function becomes problematic. It would thus be useful to interrogate protein structures for function directly. Here, we predict the function of an enzyme of unknown activity, Tm0936 from Thermotoga maritima, by docking high-energy intermediate forms of thousands of candidate metabolites. The docking hit list was dominated by adenine analogues, which appeared to undergo C6-deamination. Four of these, including 5-methylthioadenosine and S-adenosylhomocysteine (SAH), were tested as substrates, and three had substantial catalytic rate constants (105 M-1 s-1). The X-ray crystal structure of the complex between Tm0936 and the product resulting from the deamination of SAH, S-inosylhomocysteine, was determined, and it corresponded closely to the predicted structure. The deaminated products can be further metabolized by T. maritima in a previously uncharacterized SAH degradation pathway. Structure-based docking with high-energy forms of potential substrates may be a useful tool to annotate enzymes for function.

 

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