Binding order of substrate and cofactor in sulfonamide monooxygenase during sulfa drug degradation: in silico studies

Abstract

For decades, sulfonamide antibiotics have been used across industries such as agriculture and animal husbandry. However, the use and inadvertent misuse of these antibiotics have resulted in the advent of sulfonamide-drug-resistant strains due to antibiotic pollution. Enzymatic bioremediation of antibiotics remains a potential emerging solution to combat antibiotic pollution. Here, we propose an enzymatic model for the degradation of sulfonamides by Microbacterium sp. We have employed a multi-pronged computational strategy involving – protein structure modelling, ligand docking and molecular dynamics simulations to decipher a plausible binding order for the enzymatic degradation of sulfonamides by the bacterial sulfonamide monooxygenase, SulX. Our results enable us to predict that this degradation is achieved through the sequential binding of the antibiotic sulfonamide followed by the reduced flavin cofactor FMNH₂, thereby laying the computational foundation for further advancements in enzyme-mediated degradation of the antibiotic. We also provide a list of experiments which may be performed to verify and follow-up on our in-silico studies.

Communicated by Ramaswamy H. Sarma

Acknowledgements

The authors thank Indian Institute of Science Education and Research (IISER) Tirupati for computing facilities and Department of Biotechnology, Govt. of India for funds under iBEC2020 to RM. Special thanks are extended to Dr. Aneesh Chandran for help with ligand parameterization and Dr. Sorakayala Thripati for assistance in high-performance computing. The authors are also deeply indebted to Matt Sinclair from the University of Illinois at Urbana-Champaign and Mohammad Shafeeullah from IISER Tirupati for helpful discussions. We dedicate this work in memory of our friend and iGEM2020 team lead, Omkar Mohapatra.

Authors contributions

AD and VM contributed equally. AD and VM conceived this study, performed the computations, and contributed to the writing. RR and RM suggested the types of computations to be performed, provided scientific insights based on the data obtained, overall supervised the study, provided facilities, and contributed to writing/editing the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by DST-INSPIRE Scholarships for Higher Education (SHE) program to AD and VM; Department of Biotechnology, Ministry of Science and Technology, India [iBEC2020].