Title | A Computational Methodology to Overcome the Challenges Associated With the Search for Specific Enzyme Targets to Develop Drugs Against. |
Publication Type | Journal Article |
Year of Publication | 2017 |
Authors | Catharina L, Lima CRibeiro, Franca A, Guimarães ACarolina R, Alves-Ferreira M, Tuffery P, Derreumaux P, Carels N |
Journal | Bioinform Biol Insights |
Volume | 11 |
Pagination | 1177932217712471 |
Date Published | 2017 |
ISSN | 1177-9322 |
Abstract | We present an approach for detecting enzymes that are specific ofcompared withand provide targets that may assist research in drug development. This approach is based on traditional techniques of sequence homology comparison by similarity search and Markov modeling; it integrates the characterization of enzymatic functionality, secondary and tertiary protein structures, protein domain architecture, and metabolic environment. From 67 enzymes represented by 42 enzymatic activities classified by AnEnPi (Analogous Enzymes Pipeline) as specific forcompared with, only 40 (23 Enzyme Commission [EC] numbers) could actually be considered as strictly specific ofand 27 enzymes (19 EC numbers) were disregarded for having ambiguous homologies or analogies with. Among the 40 strictly specific enzymes, we identified sterol 24-C-methyltransferase, pyruvate phosphate dikinase, trypanothione synthetase, and RNA-editing ligase as 4 essential enzymes forthat may serve as targets for drug development. |
DOI | 10.1177/1177932217712471 |
Alternate Journal | Bioinform Biol Insights |
Citation Key | 2017|2039 |
PubMed ID | 28638238 |
PubMed Central ID | PMC5470852 |