Identification of potential inhibitors for AIRS from de novo purine biosynthesis pathway through molecular modeling studies – a computational approach

Abstract

In cancer, de novo pathway plays an important role in cell proliferation by supplying huge demand of purine nucleotides. Aminoimidazole ribonucleotide synthetase (AIRS) catalyzes the fifth step of de novo purine biosynthesis facilitating in the conversion of formylglycinamidine ribonucleotide to aminoimidazole ribonucleotide. Hence, inhibiting AIRS is crucial due to its involvement in the regulation of uncontrollable cancer cell proliferation. In this study, the three-dimensional structure of AIRS from P. horikoshii OT3 was constructed based on the crystal structure from E. coli and the modeled protein is verified for stability using molecular dynamics for a time frame of 100 ns. Virtual screening and induced fit docking were performed to identify the best antagonists based on their binding mode and affinity. Through mutational studies, the residues necessary for catalytic activity of AIRS were identified and among which the following residues Lys35, Asp103, Glu137, and Thr138 are important in determination of AIRS function. The mutational studies help to understand the structural and energetic characteristics of the specified residues. In addition to Molecular Dynamics, ADME properties, binding free-energy, and density functional theory calculations of the compounds were carried out to find the best lead molecule. Based on these analyses, the compound from the NCI database, NCI_121957 was adjudged as the best molecule and could be suggested as the suitable inhibitor of AIRS. In future studies, experimental validation of these ligands as AIRS inhibitors will be carried out.

Keywords:

• aminoimidazole ribonucleotide synthetase
• molecular dynamics simulation
• virtual screening
• induced fit docking
• MM/GBSA free-energy calculation
• density functional theory

Acknowledgements

Authors are grateful to the computational facilities provided by DST, New Delhi, India [grant number SR/SO/BB-0079/2012 dated 09.07.2013] and Department of Bioinformatics, Alagappa University, Karaikudi.