We are pleased to invite post-graduate students from colleges offering a post-graduate degree in pharmaceutical chemistry to participate in our two-day hands-on training program on molecular modeling techniques in drug discovery
Docking is a powerful software tool widely used in the pharmaceutical industry for predicting the binding of small molecules to macromolecular targets. Our training program aims to equip students with the essential knowledge and skills required to use different molecular modeling softwares, making it an integral part of the pharmaceutical chemistry curriculum.
Importance of Docking (Autodock) in the Pharmaceutical Chemistry Curriculum:
Docking(AutoDock) plays a critical role in the drug discovery process. It enables pharmaceutical chemists to predict how a drug molecule may interact with its target protein, facilitating the development of new drugs. Therefore, it is essential for post-graduate students studying pharmaceutical chemistry to receive training in the use of this software tool.
Training Program Details:
Our two-day training program will consist of both theoretical and practical sessions. In the theoretical sessions, students will learn the fundamental concepts of molecular modelling, docking, and simulation. In the practical sessions, students will gain hands-on experience in using AutoDock to perform docking simulations and analyze the results.
Target Audience:
This training program is designed for post-graduate students from colleges offering a post-graduate degree in pharmaceutical chemistry. The program is ideal for students who wish to acquire advanced knowledge and practical skills in molecular modelling.
Registration Details:
The registration fee for the training program is Rs 700 per student. To register, please visit our website and follow the registration instructions. The deadline for registration is [insert date].
Don't miss this exciting opportunity to enhance your skills and knowledge in molecular modelling! Register now for our hands-on training program on molecular modeling techniques in drug discovery