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.

中文翻译：

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细菌菌种中未表征的砷酸还原酶的同源性建模和可能的活性位点腔预测。

arsC基因编码的砷酸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酸盐（As [V]）转换为三价砷酸盐（As [III]），以保留在细菌细胞中或释放到空气中。控制这一过程的分子机制尚不清楚。在这里，我们介绍一种酶的计算机模型，以描述使用SCFBio服务器的可能的活性位点腔。我们从NCBI数据库中以FASTA格式检索了细菌砷酸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工具可视化。ProSA和PROCHECK服务器用于评估预测模型的整体重要性。因此，化脓性链球菌的砷酸还原酶 Oligotropha carboxidovorans OM5，Rhodopirellula baltica SH 1和Serratia ureilytica的质量得分最高，具有统计学意义。在我们检查的砷酸还原酶中发现了活性位点的可能空洞，该酶富含谷氨酸和赖氨酸残基，具有6至16个氨基酸。这种计算机模拟实验可能会通过利用微生物来极大地改善砷污染。