Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, 7408, Bangladesh.
Biological Research Division, Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhanmondi, Dhaka, 1205, Bangladesh.
Appl Biochem Biotechnol. 2021 Jan;193(1):1-18. doi: 10.1007/s12010-020-03392-w. Epub 2020 Aug 18.
The arsC gene-encoded arsenate reductase is a vital catalytic enzyme for remediation of environmental arsenic (As). Microorganisms containing the arsC gene can convert pentavalent arsenate (As[V]) to trivalent arsenite (As[III]) to be either retained in the bacterial cell or released into the air. The molecular mechanism governing this process is unknown. Here we present an in silico model of the enzyme to describe their probable active site cavities using SCFBio servers. We retrieved the amino acid sequence of bacterial arsenate reductase enzymes in FASTA format from the NCBI database. Enzyme structure was predicted using the I-TASSER server and visualized using PyMOL tools. The ProSA and the PROCHECK servers were used to evaluate the overall significance of the predicted model. Accordingly, arsenate reductase from Streptococcus pyogenes, Oligotropha carboxidovorans OM5, Rhodopirellula baltica SH 1, and Serratia ureilytica had the highest quality scores with statistical significance. The plausible cavities of the active site were identified in our examined arsenate reductase enzymes which were abundant in glutamate and lysine residues with 6 to 16 amino acids. This in silico experiment may contribute greatly to the remediation of arsenic pollution through the utilization of microbial species.
arsC 基因编码的砷酸盐还原酶是修复环境砷（As）的重要催化酶。含有 arsC 基因的微生物可以将五价砷（As[V]）转化为三价亚砷酸盐（As[III]），要么保留在细菌细胞内，要么释放到空气中。目前尚不清楚这一过程的分子机制。在这里，我们使用 SCFBio 服务器构建了该酶的计算机模型，以描述其可能的活性位点腔。我们从 NCBI 数据库以 FASTA 格式检索了细菌砷酸盐还原酶的氨基酸序列。使用 I-TASSER 服务器预测酶结构，并使用 PyMOL 工具进行可视化。使用 ProSA 和 PROCHECK 服务器评估预测模型的整体重要性。因此，酿脓链球菌、产甲烷菌 Oligotropha carboxidovorans OM5、波罗的海红假单胞菌 SH1 和粘质沙雷氏菌 ureilytica 的砷酸盐还原酶具有最高的质量评分和统计学意义。在所研究的砷酸盐还原酶中鉴定出了活性位点的可能腔，这些腔富含谷氨酸和赖氨酸残基，长度为 6 到 16 个氨基酸。这项计算机实验可能会极大地促进通过利用微生物物种来修复砷污染。
