In Search of New Analogues as Anti-Fungal Agents

Authors

  • Souvik Sur Research and Development Center, Teerthanker Mahaveer University, Moradabad, Uttar Pradesh 244001, India.

DOI:

https://doi.org/10.48165/

Keywords:

Clotrimazole, Designed-derivatives, anti-fungal drugs, PATCHDOCK, Docking score

Abstract

Development of new Clotrimazole derivatives was studied here. Automated prediction of protein-small  molecule interactions is one of the most challenging problems in structural biology as well as in  medicinal chemistry. Many biological studies, both in academia and in industry, may benefit from  credible high-accuracy interaction predictions. The molecular interactions with target protein have been  discussed. A target based designing of new derivatives for future drug development presented, which  can be further informative and marketed if their biological significance stand out better than the  marketed one. The report concludes with a description of the initial efforts to prepare synthesized  compounds to recognize as better antifungal agents than the regular prescribed drugs in market. The in silico drug designing leading to initial successes are described along with future directions. 

Downloads

Download data is not yet available.

References

Yadav, B. S., & Tripathi, V. (2018). Recent Advances in the System Biology-based Target Identification and Drug Discovery. Current topics in medicinal chemistry, 18(20), 1737-1744.

Luo, J., Wei, W., Waldispühl, J., &Moitessier, N. (2019). Challenges and current status of computational methods for docking small molecules to nucleic acids. European journal of medicinal chemistry, 168, 414-425.

Clark, R. D., Strizhev, A., Leonard, J. M., Blake, J. F., & Matthew, J. B. (2002). Consensus scoring for ligand/protein interactions. Journal of Molecular Graphics and Modelling, 20(4), 281-295.

Lengauer, T., &Rarey, M. (1996). Computational methods for biomolecular docking. Current opinion in structural biology, 6(3), 402-406.

Sousa, S. F., Fernandes, P. A., & Ramos, M. J. (2006). Protein–ligand docking: current status and future challenges. Proteins: Structure, Function, and Bioinformatics, 65(1), 15-26.

Seeliger, D., & de Groot, B. L. (2010). Ligand docking and binding site analysis with PyMOL and Autodock/Vina. Journal of computer-aided molecular design, 24(5), 417-

Verdonk, M. L., Cole, J. C., Hartshorn, M. J., Murray, C. W., & Taylor, R. D. (2003). Improved protein–ligand docking using GOLD. Proteins: Structure, Function, and Bioinformatics, 52(4), 609-623.

Schneidman-Duhovny, D., Inbar, Y., Nussinov, R., & Wolfson, H. J. (2005). PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic acids research, 33(suppl_2), W363-W367.

Hirst, G. C., Rafferty, P., Ritter, K., Calderwood, D., Wishart, N., Arnold, L. D., & Friedman, M. M. (2005). U.S. Patent No.

,921,763. Washington, DC: U.S. Patent and Trademark Office.

Molecular graphics and analyses performed with UCSF Chimera, developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco, with support from NIH P41-GM103311.

Mast, N., Charvet, C., Pikuleva, I. A., & Stout, C. D. (2010). Structural basis of drug binding to CYP46A1, an enzyme that

controls cholesterol turnover in the brain. Journal of Biological Chemistry, 285(41), 31783-31795.

Duhovny D, Nussinov R, Wolfson HJ. Efficient Unbound Docking of Rigid Molecules. In Gusfield et al., Ed. Proceedings of the 2'nd Workshop on Algorithms in Bioinformatics (WABI) Rome, Italy, Lecture Notes in Computer Science 2452, pp. 185-200, Springer Verlag, 2002.

Published

2022-12-15

How to Cite

In Search of New Analogues as Anti-Fungal Agents . (2022). Bulletin of Pure and Applied Sciences-Chemistry , 41(2), 82–88. https://doi.org/10.48165/