• MEGHA M K
• K SPOORTHI
• Ajeet Kumar Srivastav

In this project, Python is used within Google Colab to design and optimize a paracetamol drug model, employing computational techniques to predict molecular properties and interactions. By utilizing Python libraries such as RDKit and Open Babel, the project efficiently generates molecular structures, calculates physicochemical properties, and simulates interactions with biological targets, offering a cost-effective approach to drug design. To further enhance the study, a combination of AutoDock, MGL Tools, and Open Babel is employed for molecular docking studies. These tools help predict the binding affinity and orientation of paracetamol within the active sites of target enzymes, providing valuable insights into its potential efficacy. This workflow illustrates the power of integrating open-source tools into computational drug discovery, making advanced techniques more accessible and affordable. Additionally, the WebMO Demo Server is utilized to conduct quantum chemical calculations, such as geometry optimization and electronic structure analysis of paracetamol. By leveraging WebMO’s interface, which is seamlessly integrated with quantum chemistry engines like Gaussian and GAMESS, the project benefits from a user-friendly platform for sophisticated molecular modeling, aiding in the drug design process. Overall, this project showcases the effectiveness of using Python, open-source software, and web-based platforms in streamlining drug discovery. It demonstrates how these tools can be combined to create an accessible, efficient, and powerful workflow for designing and optimizing potential drug candidates like paracetamol.

Drug Design Using Computational Chemistry

"Drug Design Using Computational Chemistry", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 9, page no.a311-a315, September-2024, Available :http://www.jetir.org/papers/JETIR2409035.pdf

"Drug Design Using Computational Chemistry", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 9, page no. ppa311-a315, September-2024, Available at : http://www.jetir.org/papers/JETIR2409035.pdf