Title

A QSAR model of benzoxazole derivatives as potential inhibitors for inosine 5`-monophosphate dehydrogenase from Cryptosporidium parvum

Authors

Pratibha Teotia, Surya Prakash Dwivedi & Neeraja Dwivedi*

Affiliation

School of Biotechnology, IFTM University, Moradabad, Utter Predesh, India;

Email

Neeraja Dwivedi – Email: neer.miet@gmail.com, *Corresponding author

Article Type

Hypothesis

Date

Received November 8, 2016; Revised November 21, 2015; Accepted November 24, 2015; Published June 15, 2016

Cryptosporidium parvum is the common enteric protozoan pathogen causing cryptosporidiosis in human. Available drugs to treat cryptosporidiosis are ineffective and there is yet no vaccine against C. parvum. Therefore, it is of interest to design an improved yet effective drug against C. parvum. Here, we docked benzoxazole derivatives (collected from literature) with inosine 5`-
monophosphate dehydrogenase (IMPDH) from Cryptosporidium parvum using the program AutoDock 4.2. The docked protein - inhibitor complex structure was optimized using molecular dynamics simulation for 5 ps with the CHARMM-22 force field using NAMD (NAnoscale Molecular Dynamics program) incorporated in visual molecular dynamics (VMD 1.9.2) and then evaluating
the stability of complex structure by calculating RMSD values. NAMD is a parallel, object-oriented molecular dynamics code designed for high-performance simulation of large biomolecular systems. A quantitative structure activity relationship (QSAR) model was built using energy-based descriptors as independent variable and pIC50 value as dependent variable of fifteen known benzoxazole derivatives with C. parvum IMPDH protein, yielding correlation coefficient r2 of 0.7948. The predictive performance of QSAR model was assessed using different cross-validation procedures. Our results suggest that a ligand-receptor binding interaction for inosine 5`-monophosphate dehydrogenase using a QSAR model is promising approach to design more potent inosine 5`-monophosphate dehydrogenase inhibitors prior to their synthesis.

Citation

Teotia et al. Bioinformation 12(3): 119-123 (2016)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.