Providencia alcalifaciens—Assisted Bioremediation of Chromium-Contaminated Groundwater: A Computational Study

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Abstract

In Saudi Arabia, seawater desalination is the primary source of acquiring freshwater, and groundwater contains a high concentration of toxic heavy metals. Chromium (Cr) is one of the heavy metals that is widely distributed in the environment, particularly in the groundwater of Madinah. Diverse techniques are employed to eliminate the toxicity of heavy metals from the environment, but, lately, the focus has shifted to biological remediation systems, due to their higher removal efficiencies, lower costs, and more ecologically benign characteristics than the conventional methods. Providencia bacteria engage in a variety of adsorption processes to interact with heavy metals. In this study, we aim to investigate the role of potential active site residues in the bioengineering of chromate reductase (ChrR) from Providencia alcalifaciens to reduce the Cr to a lesser toxic form by employing robust computational approaches. This study highlights Cr bioremediation by providing high-quality homology-modeled structures of wild type and mutants and key residues of ChrR for bioengineering to reduce the Cr toxicity in the environment. Glu79 is found to be a key residue for Cr binding. The mutant models of Arg82Cys, Gln126Trp, and Glu144Trp are observed to establish more metallic interactions within the binding pocket of ChrR. In addition, the wild type ChrR (P. alcalifaciens) has been found to be unstable. However, the mutations stabilized the structure by preserving the metallic contacts between the critical amino acid residues of the identified motifs and the Cr(VI). Therefore, the mutants discovered in the study can be taken into account for protein engineering to create reliable and effective enzymes to convert Cr(VI) into a lesser toxic form.

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Tasleem, M., Hussein, W. M., El-Sayed, A. A. A. A., & Alrehaily, A. (2023). Providencia alcalifaciens—Assisted Bioremediation of Chromium-Contaminated Groundwater: A Computational Study. Water (Switzerland), 15(6). https://doi.org/10.3390/w15061142

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