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Introduction

Molecular modeling has become an essential tool in drug discovery and design, allowing researchers to study the interactions between drugs and their biological targets at the molecular level. By employing computational techniques, researchers can predict the binding modes of drugs to target proteins, optimize drug molecules for improved binding affinity and selectivity, and explore the dynamics of drug-target complexes. This thesis focuses on the application of molecular modeling in studying drug-target interactions, with the aim of advancing our understanding of the mechanisms underlying drug action and facilitating the discovery of new therapeutic agents.

Chapter 1: Introduction

1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review

2.1 Fundamentals of molecular modeling
2.2 Methods for studying drug-target interactions
2.3 Applications of molecular modeling in drug discovery
2.4 Case studies of successful drug design using molecular modeling
2.5 Challenges and limitations of molecular modeling in drug discovery
2.6 Recent advances in the field of molecular modeling
2.7 Comparison of different molecular modeling approaches
2.8 Role of machine learning in molecular modeling
2.9 Ethical considerations in molecular modeling research
2.10 Future directions in molecular modeling research

Chapter 3: Research Methodology

3.1 Selection of target proteins and drug molecules
3.2 Molecular docking studies
3.3 Molecular dynamics simulations
3.4 Quantitative structure-activity relationship (QSAR) analysis
3.5 Virtual screening approaches
3.6 Protein-ligand interaction analysis
3.7 Validation of computational results
3.8 Statistical analysis of data

Chapter 4: Discussion of Findings

4.1 Analysis of drug-target interactions
4.2 Docking results and binding modes
4.3 Molecular dynamics simulations insights
4.4 QSAR modeling predictions
4.5 Virtual screening hits and validation
4.6 Comparison to experimental data
4.7 Implications for drug design
4.8 Future research directions

Chapter 5: Conclusion and Summary

In conclusion, this thesis highlights the importance of molecular modeling in drug discovery and design. By employing computational techniques, researchers can gain insights into the interactions between drugs and their targets, leading to the development of more effective and selective therapeutic agents. The findings of this study contribute to the growing body of knowledge in the field of molecular modeling and provide valuable insights for future research in drug discovery.

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