Premium
Structure homology modeling of human arylamine N‐acetyltransferases: Computational and experimental approaches
Author(s) -
Walraven Jason,
Trent John O,
Barker David F,
Hein David W.
Publication year - 2007
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.21.6.a1186-a
Subject(s) - nat , homology modeling , acetyltransferases , computational biology , acetylation , arylamine n acetyltransferase , docking (animal) , active site , homology (biology) , biology , biochemistry , sequence alignment , enzyme , chemistry , peptide sequence , amino acid , computer science , gene , nursing , medicine , computer network
Human arylamine N‐acetyltransferase 1 (NAT1) and 2 (NAT2) catalyze N‐acetylation and/or O‐acetylation of arylamine and heterocyclic amine pro‐carcinogens and pharmaceutical drugs. We used molecular cloning and computational modeling to create high quality human NAT enzyme models from template bacterial NAT structures. In protein alignments between mammalian and bacterial NAT sequences, 17 mammalian NAT residues have no corresponding bacterial NAT sequence, which may indicate a loop in mammalian NATs that prevents crystallization. Different alignment algorithms placed this insertion at different locations. To determine the most accurate location of the 17 residue mammalian insertion we performed computational sequence analyses and measured the activity of recombinantly expressed NAT2 mutants. Our results demonstrated that the mammalian NAT insertion is adjacent to the active site pocket at residues 167–183, that these 17 amino acids are not required for enzyme function, and they likely form an unstructured loop. With this knowledge, we generated molecular homology models of human NAT1 and NAT2 based on alignments between the human NATs and bacterial NAT templates. The best models were optimized using molecular dynamics simulations to arrive at high quality structures for future computational substrate/inhibitor docking studies. Partially supported by USPHS grants CA34627 and ES011564.