Satish kumar Yadav
Mohd Wasiullah
Piyush Yadav
Shreya Sahu
Akash Mishra
- Associate professor Department of Pharmacy, Prasad Institute of Technology Uttar Pradesh India
- Principal Department of Pharmacy, Prasad Institute of Technology Uttar Pradesh India
- Academic Head Department of Pharmacy, Prasad Institute of Technology Uttar Pradesh India
- Scholar Department of Pharmacy, Prasad Institute of Technology Uttar Pradesh India
- Assistant professor Department of Pharmacy, Prasad Institute of Technology Uttar Pradesh India
Abstract
The discovery and development of a contemporary sedate is widely acknowledged as an extremely difficult task that requires significant resources and effort. Therefore, computer-aided medication design techniques are widely utilized today to increase the productivity of the drug discovery and development process. Among structure-based and ligand-based drug design approaches, both recognized for their efficiency in drug discovery and development, various CADD (Computer-Aided Drug Design) techniques are evaluated based on specific requirements. Atomic docking, a crucial method, enables virtual screening for lead identification and optimization within these frameworks. Recently, the pharmaceutical industry has extensively utilized computational tools to enhance drug viability, reflecting their significant role in modern drug development strategies. These techniques facilitate the analysis and improvement of potential drug candidates, streamlining the process and increasing the effectiveness of therapeutic discoveries. Overall, the integration of computational methods has revolutionized the approach to drug design, making it more precise and efficient.
Keywords: Virtual screening, Molecular Docking, Structure-Based, Ligand-Based, and Computer-Aided Drug Discovery.
[This article belongs to Trends in Drug Delivery(tdd)]
Browse Figures
References
1. Meek PJ, Liu Z, Tian L, Wang CY, Welsh WJ, Zauhar RJ. Shape Signatures: speeding up computer aided drug discovery. Drug discovery today. 2006 Oct 1;11(19-20):895-904.
2. Drug Discovery Today: Technologies, “New technologies in computer-aided drug design: Toward target identification and new chemical entity
3. Daina A, Blatter MC, Baillie Gerritsen V, Palagi PM, Marek D, Xenarios I, Schwede T, Michielin O, Zoete V. Drug design workshop: A web-based educational tool to introduce computer-aided drug design to the general public. Journal of Chemical Education. 2017 Mar 14;94(3):335-44.
4. Xiang M, Cao Y, Fan W, Chen L, Mo Y. Computer-aided drug design: lead discovery and optimization. Combinatorial chemistry & high throughput screening. 2012; 15(4):328-37.
5. Hopfinger AJ. Computer-assisted drug design. Journal of medicinal chemistry. 1985 Sep;28(9):1133-9.
6. Imam SS, Gilani SJ. Computer Aided Drug Design: A Novel Loom To Drug Discovery. Org. Med. Chem. 2017; 1 (3):113-8.
7. Ferreira LG, dos Santos RN, Oliva G, Andricopulo AD. Molecular docking and structure-based drug design strategies. Molecules. 2015; 20(7):13384-421.
8. Daina A, Blatter MC, Baillie Gerritsen V, Palagi PM, Marek D, Xenarios I, et al. Drug Design Workshop: A Web-Based Educational Tool To Introduce Computer-Aided Drug Design to the General Public. Journal of Chemical Education. 2017; 94(3):335-44.
9. Xiang M, Cao Y, Fan W, Chen L, Mo Y. Computer-aided drug design: lead discovery and optimization. Combinatorial chemistry & high throughput screening. 2012; 15(4):328-37.
10. Hopfinger AJ. Computer-assisted drug design. Journal of medicinal chemistry. 1985; 28(9):1133-9 Molecules. 2015; 20(7):13384-421.
11. Anderson AC. The process of structure-based drug design. Chemistry & biology. 2003; 10(9):
787-97.
12. Hoque I, Chatterjee A, Bhattacharya S, Biswas R. An Approach of Computer-Aided Drug Design (CADD) Tools for In Silico Pharmaceutical Drug Design and Development. Int. J. Adv. Res. Biol. Sci. 2017; 4(2) 60-71.
13. Macalino SJ, Gosu V, Hong S, Choi S. Role of computer-aided drug design in modern drug discovery. Archives of pharmacal research. 2015; 38(9):1686-701.
14. Hollingsworth S. A., Dror R. O. Molecular dynamics simulation for all. Neuron. 2018;99(6):1129–1143. doi: 10.1016/j.neuron.2018.08.011.
15. Durrant J. D., McCammon J. A. Molecular dynamics simulations and drug discovery. BMC Biology. 2011;9(1):1–9. doi: 10.1186/1741-7007-9-71
16. Morris G. M., Huey R., Lindstrom W., et al. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. Journal of Computational Chemistry. 2009;30(16):2785–2791. doi: 10.1002/jcc.21256.
17. Trott O., Olson A. J. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry. 2009;31(2):455–461. doi: 10.1002/jcc.21334.
18. Jones G., Willett P., Glen R. C., Leach A. R., Taylor R. Development and validation of a genetic algorithm for flexible docking1. Journal of Molecular Biology. 1997;267(3):727–748. doi: 10.1006/jmbi.1996.0897.
19. Wu G., Robertson D. H., Brooks C. L., III, Vieth M. Detailed analysis of grid-based molecular docking: a case study of CDOCKER?A CHARMm-based MD docking algorithm. Journal of Computational Chemistry. 2003;24(13):1549–1562. doi: 10.1002/jcc.10306.
Trends in Drug Delivery
| Volume | 11 |
| Issue | 02 |
| Received | May 10, 2024 |
| Accepted | May 16, 2024 |
| Published | June 15, 2024 |