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Introduction

Computational drug design is a rapidly growing field that utilizes computational methods to predict the interactions between small molecules and protein targets, with the ultimate goal of designing more effective and safer drugs. This approach has revolutionized the drug discovery process by providing a faster and more cost-effective way to identify potential drug candidates.

Proteins are essential components of living organisms and play crucial roles in various biological processes. However, when these proteins malfunction, they can lead to diseases such as cancer, diabetes, and neurodegenerative disorders. By targeting these proteins with small molecules, researchers can potentially develop drugs that can modulate their activity and treat these diseases.

This thesis aims to explore the use of computational methods in drug design against protein targets. The following chapters will provide a comprehensive discussion on the background of the study, the problem statement, the objectives, limitations, scope, significance, and the structure of the thesis. Additionally, key terms related to the topic will be defined in chapter one.

Table of Contents:

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 Overview of Computational Drug Design
2.2 Protein Targets in Drug Discovery
2.3 Computational Methods in Drug Design
2.4 Applications of Computational Drug Design
2.5 Challenges in Computational Drug Design
2.6 Success Stories in Computational Drug Design
2.7 Current Trends in Computational Drug Design
2.8 Future Directions in Computational Drug Design
2.9 Integration of Experimental and Computational Approaches
2.10 Case Studies in Computational Drug Design

Chapter 3: Research Methodology
3.1 Selection of Protein Targets
3.2 Database Search and Retrieval
3.3 Molecular Docking Studies
3.4 Pharmacophore Modeling
3.5 Molecular Dynamics Simulations
3.6 Virtual Screening
3.7 Structure-Based Drug Design
3.8 In silico ADMET Prediction

Chapter 4: Discussion of Findings
4.1 Analysis of Molecular Docking Results
4.2 Evaluation of Pharmacophore Models
4.3 Interpretation of Molecular Dynamics Simulations
4.4 Validation of Virtual Screening Results
4.5 Rational Design of Novel Drug Candidates
4.6 Prediction of Drug-like Properties
4.7 Comparison with Experimental Data
4.8 Limitations and Future Directions

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Implications of the Study
5.3 Recommendations for Future Research
5.4 Conclusion

Thesis Overview:

Computational drug design against protein targets has emerged as a powerful tool in the field of drug discovery. By leveraging computational methods, researchers can predict the interactions between small molecules and protein targets, leading to the development of more effective and safer drugs. This thesis aims to explore the use of computational approaches in drug design, focusing on the identification of protein targets, molecular docking studies, pharmacophore modeling, molecular dynamics simulations, virtual screening, and structure-based drug design. Through a comprehensive literature review and research methodology, this study seeks to contribute to the understanding of computational drug design and its applications in the development of novel therapeutics. The findings and discussions presented in this thesis will provide valuable insights into the challenges, successes, and future directions of computational drug design against protein targets.

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