Investigating PCB degradation by Indigenous Fungal Strains Isolated from the Transformer Oil-Contaminated Site: Degradation Kinetics, Bayesian Network, Artificial Neural Networks, QSAR with DFT, Molecular Docking, and Molecular Dynamics Simulation

Abstract

The widespread prevalence of polychlorinated biphenyls (PCBs) in the environment has raised major concerns due to the associated risks to human health, wildlife, and ecological systems. Here, we investigated the degradation kinetics, Bayesian Network (BN), Quantitative Structure-Activity Relationship-Density Functional Theory (QSAR-DFT), Artificial Neural Network (ANN), Molecular docking (MD) and Molecular dynamics stimulation (MS) of PCBs biodegradation i.e. PCB-10, PCB-28, PCB-52, PCB-138, PCB-153, and PCB-180 in the soil system using fungi isolated from the transformer oil-contaminated sites. Results revealed that the efficacy of PCBs biodegradation best fits the first-order kinetics (R2 ≥ 0.93). The consortium treatment (29.44–74.49%) exhibited more efficient degradation of PCBs than those of Aspergillus tamarii (27.09–71.25%), Corynespora cassiicola sp. MN69 (23.76–57.37%), and Corynespora cassiicola sp. MN70 (23.09–54.98%). 3'-methoxy-2, 4, 4'-trichloro-biphenyl as an intermediate derivative was detected in the fungal consortium treatment. The BN analysis predicted that the biodegradation efficiency of PCBs ranged from 11.6–72.9%. The ANN approach showed the importance of quantum chemical descriptors (QCD) i.e., LUMO > Molecular weight > Ionization Potential > No. of Chlorine > HOMU in PCBs removal. Furthermore, the QSAR-DFT model between the QCD and rate constant (Log K) exhibited a high fit and good robustness of R2 = 99.12% in predicting ability. The MD and MS analyses showed the lowest binding energy through Normal Mode Analysis (NMA), implying stability in the interactions of the docked complexes. These findings provide crucial insights for devising strategies focused on natural attenuation, holding substantial potential for mitigating PCBs contamination within the environment.