Computational Framework as a Way Forward Robust Approach in Predictive Biodegradation and Underlying Toxic Hazards Assessment of Environmental Contaminants

Abstract Environmental contaminants and their resultant detrimental effects are an increasing global concern. Conventional methods for evaluating degradation and toxicity exhibit constraints in their effectiveness; therefore, it is crucial to substitute them with advanced and intelligent strategies to overcome these limitations. Computational frameworks built on various methods are emerging techniques that aim to reduce the adverse environmental impacts posed by various classes of contaminants. An array of computational methodologies has multiple advantages over conventional remediation; they may overcome the limitations of current remediation technologies while also offering a theoretical basis for analyzing degradation and cleavage patterns at the molecular level. Likewise, the toxicity evaluation across numerous endpoints for both the parent and transformed metabolites may be effectively achieved by the implementation of QSAR‐based methodologies, ensuring efficiency, cost‐effectiveness, time savings, and straightforward use. To fill the literature gap, the presented review delineates a computational framework comprising docking, MD‐simulation, multiscale quantum mechanics/molecular mechanics molecular dynamics simulations, and QSAR‐based techniques aimed at addressing the limitations associated with conventional remediation and toxicity assessments by highlighting recent advances in the domain, with concluding remarks.