AUTOMATED CONFORMATIONAL SEARCH METHODS.pptx

Conformation analysis

1. AUTOMATED CONFORMATIONAL SEARCH METHODS -BY YAZHINI.P REGISTER NO. :810022237007

2. Exploring molecular shapes with computational tools Introduction : What is conformational search? Conformational search is a computational chemistry method used to explore the possible three-dimensional shapes (conformations) of a molecule. It involves systematically varying the molecular geometry to identify all potential conformations, focusing on their energies to find the most stable arrangement or lowest-energy conformers. This search is important for understanding molecular behavior, reactions, and properties.

3. Why is it important? Used in drug discovery , material science and bioengineering . fig. cylcohexane conformations

4. INTRODUCTION Why do molecules change shapes? Molecules are flexible , like bendy straws or clay models- they don’t stay rigid. Molecules shift their shape to become more stable. To understand this, scientists use computational tools to predict the most stable form.This is important in drug design, where the right shape can determine how well a drug works.

5. ENERGY LANDSCAPES -FINDING STABILITY HOW MOLECULES SETTLE INTO THEIR BEST SHAPE : Imagine rolling a ball across hills and valleys—the ball naturally stops in the lowest valley. Similarly, molecules seek out their most stable structure by adjusting their shape. In computational chemistry, this process is visualized using something called the Potential Energy Surface (PES). The deepest valley represents the most stable molecular shape, while shallow valleys correspond to less stable forms.

6. Approaches to Finding the Best Molecular Shape Different Ways to Explore Molecular Conformations: Computational methods use different strategies to explore molecular conformations: Systematic Search – A step-by-step approach that checks all possibilities. Stochastic Methods – A probability-based approach that makes random but efficient guesses. Molecular Dynamics – Simulates real movement to find natural shapes.

7. Systematic Search – The Step-by-Step Approach Systematic methods rotate molecular bonds in fixed steps to generate all possible conformations. This ensures accuracy but becomes impractical for larger, flexible molecules because of the huge number of possibilities. Computational techniques include Grid Search and Exhaustive Search to cover all options.

8. Stochastic Search – The Smarter Guessing Approach Computationally, two main stochastic methods are used: Monte Carlo Simulations: Introduces random changes to molecular structure and keeps the best ones. Genetic Algorithms: Mimic evolution, where good molecular shapes “survive” and “mutate” to improve over time. These methods are faster than systematic searches but may miss the absolute best shape.

9. Molecular Dynamics – Simulating Real Motion Molecular Dynamics (MD): It simulates molecular motion over time using physics-based calculations. Helps find stable conformations that molecules adopt in real conditions. This is especially useful for large molecules like proteins, where flexibility plays a key role in function.

10. Optimizing Conformations – Finding the Perfect Fit Two common approaches: Gradient Descent Methods: Take small steps downhill to reach the lowest energy state. Simulated Annealing: Allows occasional jumps to avoid getting stuck in less stable shapes.

11. Why This Matters – Drug Discovery & Beyond Drug Design: A drug must fit a protein like a key in a lock. Material Science: Helps design better polymers and nanomaterials. Biological Research: Understanding how proteins fold and interact.

12. Summary Molecules change shape to find the most stable conformation. Different search methods balance accuracy and speed. Automated conformational search is essential in drug discovery, bioengineering, and materials science.

13. THE END