ABSTRACT
Mucormycosis is an uncommon illness caused by the fungus Mucorales. India was concerned about mucormycosis and COVID-19 in 2020. To minimize morbidity and occurrence, prevent, and treat mucormycosis, analysis is required. Combining systems biology and bioinformatics-based mucormycosis research, this study simulates the Genome-scale metabolic model (GSSM) of a Rhizopus oryzae strain for the comprehension of the organism's metabolic mechanism. Several key metabolic pathways for a mucormycosis-causing fungus strain were identified in research publications and targeted for inclusion in a model of a metabolic network. Based on the Flux Balance Analysis (FBA) approach, an integrated model of these pathways at the scale of the genome's metabolism was developed and appropriate constraints were applied to the numerous reactions involved in Rhizopus oryzae's metabolism using the COBRA package in MATLAB. Hence, unique evidence of pharmacological targets and biomarkers that may function as diagnostic, early analytic, and therapeutic agents in mucormycosis was discovered. Our study investigates the role of key metabolites in the model by applying constraints and altering fluxes, which provides valuable candidates for drug development. . © 2023 IEEE.