Computer-Aided Drug Modelling of the Receptor Tyrosine Kinase Inhibitors
- Issued Date
- 2016
- Keyword
- Bioinformatics
- Abstract
- 타이로신 카이네이즈 수용체는 넓은 범위의 복잡한 생물학적 기능을 제어하는 것과 세포사이의 통신을 매개하는데 관여한다. 의도된 세포 사멸과 함께 세포 분열 및 형태 형성의 원활한 제어는 정상적인 조직 성장 및 패턴화에 중요하다. 이러한 기능을 담당하는 세포 신호의 불균형을 유발하는 비정상적인 변화는 제어되지 않은 세포 증식, 즉, 암을 일으킨다. 이러한 신호의 대부분은 RTK에 의해 조절되므로 다양한 유형의 암 치료에 중한 약물 표적이됩니다. 따라서, 이러한 질병을 치료하기위한 키나제 억제제의 설계 및 개발에 많은 연구가 었다. 현재 연구에서 우리는 RET, MerTK 및 FLT3 키나제와 같은 다양한 타이로신 카이네이즈를 사용했다. 우리는 분자 도킹, 분자 역학 시뮬레이션 및 MM/PBSA 결합 자유 에너지 계산을 통하여 티로신 카이네이즈의 억제에 관여하는 중요한 아미노산 잔기들을 확인하고 연구했습니다. CoMFA 및 CoMSIA의 결과는 카이네이즈 억제제의 활성을 향상시키고 새로운 강력한 억제제를 설계하는 데 있어서 구조에 관계한 정보를 제공하였다. 이 구조 정보를 기반으로, 우리는 몇 가지 새로운 RTK 억제제를 설계했습니다. 결론적으로, 본 연구는 이들 카이네이즈의 억제 메커니즘을 이해하여 보다 효율적이고 강력한 억제제의 설계에 도움이 된다.|Receptor tyrosine kinases (RTKs) are a subclass of tyrosine kinases that mediate cell-to-cell communication and control a wide range of complex biological functions. A well control of cell division and morphogenesis along with intended cell death is crucial to ensure normal tissue growth and patterning. Aberrant variations that cause an imbalance of the cellular signals which are responsible for these events lead to the uncontrolled cell proliferation that is known as cancer. Since most of these signals are regulated by RTKs, it makes them an important drug target for the treatment of various types of cancer. This has created significant concern in designing and development of kinase inhibitors to treat these diseases. In our current study, we have used various tyrosine kinases such as RET, MerTK and FLT3 kinase. We utilized a combined approach of molecular docking, molecular dynamics simulation and MM/PBSA binding free energy calculations to identify and study the crucial residues that participate in inhibition of tyrosine kinases. The results of CoMFA and CoMSIA revealed structural insights in enhancing the activity of the kinase inhibitors. Based on this structural information, we have designed some new RTK inhibitors. In summary, our study could be supportive to comprehend the inhibitory mechanism of these kinases thus assists in designing more efficient and potent inhibitors.
- Alternative Title
- 타이로신 카이네이즈 억제제의 컴퓨터를 활용한 신약 모델링 연구
- Alternative Author(s)
- SWAPNIL PANDURANG BHUJBAL
- Affiliation
- Department of Biomedical Sciences
- Department
- 일반대학원 의과학과
- Advisor
- Seung Joo Cho
- Awarded Date
- 2020-08
- Table Of Contents
- ABBREVIATIONS iv
LIST OF TABLES vi
LIST OF FIGURES viii
ABSTRACT (ENGLISH) x
ABSTRACT (KOREAN) xi
I. CHAPTER 1 - INTRODUCTION General Introduction on kinases 1
1.1 Overview on Protein Kinases 2
1.2 Structure of Protein Kinase 2
1.3 Protein Kinases as Drug Target 4
1.4 Types of Kinase Inhibitors 5
1.5 Importance of Designing New RTK Drugs 5
II. CHAPTER 2 Design of New Therapeutic Agents Targeting FLT3 Receptor Tyrosine Kinase 7
1. Introduction 8
2. Materials and methods 10
2.1. Data set 10
2.2. Molecular docking 20
2.3. CoMFA and CoMSIA 21
2.3.1. Model Validation 22
3. Results and discussion 22
3.1. Molecular docking 22
3.2. CoMFA, RF-CoMFA and COMSIA Studies 25
3.3. Contour map analysis 31
3.2.1. RF-CoMFA Contour maps 31
3.4. Designing of new potent compounds 33
4. Conclusion 38
III. CHAPTER 3 Macrocyclic effect on inhibitory activity: a modeling study on MerTK inhibitors 40
1. Introduction 41
2. Materials and methods 43
2.1. Overall procedure 43
2.2. Molecular docking 44
2.3 Structure optimization and sampling 45
2.4 Test set / training set selection for 3D-QSAR analyses 45
2.5 3D-QSAR (CoMFA and CoMSIA) 56
3. Results and discussion 58
3.1. Activity vs ring size 58
3.1. Molecular docking and pose optimization using molecular dynamics 59
3.3. CoMFA and CoMSIA 65
3.4. Contour map analysis 70
4. Conclusion 72
III. CHAPTER 4 Receptor-guided 3D-QSAR study to develop a design strategy for RET kinase antagonists 74
1. Introduction 75
2. Materials and methods 77
2.1. Dataset 77
2.2. Molecular docking 84
2.3 CoMFA and CoMSIA 85
2.3.1 Validation of CoMFA and CoMSIA models 85
3. Results and discussion 86
3.1. Molecular Docking 86
3.2. CoMFA and CoMSIA studies 88
3.3. Contour map analysis 95
3.3.1. CoMFA contour maps 96
3.3.2. CoMSIA contour maps 97
4. Conclusion 99
VI. CHAPTER 5 – Conclusion of the Study 101
References 103
Appendices 115
- Degree
- Doctor
- Publisher
- 조선대학교 대학원
- Citation
- 스왚닐 판두랑 부즈발. (2016). Computer-Aided Drug Modelling of the Receptor Tyrosine Kinase Inhibitors.
- Type
- Dissertation
- URI
- https://oak.chosun.ac.kr/handle/2020.oak/13234
http://chosun.dcollection.net/common/orgView/200000342650
- Appears in Collections:
- General Graduate School > 4. Theses(Ph.D)
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