Development of a protein-ligand docking program based on global optimization

다국어 초록 (Multilingual Abstract)

Protein-ligand docking has become an essential tool for computer-aided drug discovery since docking programs were first developed in 1980’s. The goals of docking are to predict 1) the binding mode and 2) the binding affinity of a given protein-ligand complex accurately. Accurate prediction of binding mode requires appropriate sampling of both protein and ligand conformations. Many available docking programs sample ligand structures successfully because ligand has a relatively small number of degrees of freedom. However, a lot of current docking programs treat receptor as a rigid molecule although receptor often adapts its shape to bound ligand because treating receptor flexibility is a very complicated problem. First of all, the large conformational space of receptor is a challenge for typical sampling methods. In addition, current energy functions such as empirical docking score functions or force field-based energy functions do not accurately describe flexible receptor-flexible ligand interactions yet.
In this thesis, the development process of an efficient docking program that treats receptor flexible, called GalaxyDock, is described. A powerful global optimization technique, called conformational space annealing, was employed for simultaneous sampling of the conformational space of protein and ligand. In addition, a new energy function for flexible-receptor docking was designed by combining the AutoDock energy function and a knowledge-based ROTA potential. With these components for sampling and scoring, GalaxyDock shows high performances in the binding pose prediction and virtual screening benchmark tests when compared to other state-of-art docking programs. This result suggests that the GalaxyDock program can provide a firm basis for further method developments and for practical applications to in sillico drug discovery processes.

목차 (Table of Contents)

• Abstract .............................................................................................
• i
• Contents .............................................................................................
• iii
• List of Figures .................................................................................
• vi
• List of Tables ...................................................................................
• viii
• 1. Introduction ..................................................................................
• 1
• 1.1. Overview of protein-ligand docking ....................................
• 1
• 1.2. Sampling methods of protein-ligand docking .....................
• 2
• 1.3. Scoring problem of protein-ligand docking ........................
• 3
• 1.4. Flexble-receptor docking ........................................................
• 5
• 1.5. Outline of this thesis .............................................................
• 7
• 2. LigDockCSA: a rigid-receptor docking program .....................
• 9
• 2.1. Overview of this section .......................................................
• 9
• 2.2. Methods ...................................................................................
• 10
• 2.2.1. Benchmark set and AutoDock calculations ....................
• 10
• 2.2.2. Energy function for protein-ligand docking ...................
• 11
• 2.2.3. Application of conformational space annealing to
• protein-ligand docking .....................................................
• 13
• 2.3. Results and discussion ...........................................................
• 16
• 2.3.1. Performance of CSA when combined with the
• AutoDock scoring function .............................................
• 16
• 2.3.2. Energy function for LigDockCSA ..................................
• 20
• 2.3.3. Performance of LigDockCSA ..........................................
• 25
• 2.4. Conclusion of this section ....................................................
• 32
• 3. GalaxyDock: a flexible-receptor docking program ..................
• 33
• 3.1. Overview of this section .......................................................
• 33
• 3.2. Methods ...................................................................................
• 34
• 3.2.1. Energy function for flexible protein-ligand docking .....
• 34
• 3.2.2. GalaxyDock sampling that incorporates side-chain
• flexibility ...........................................................................
• 37
• 3.2.3. Cross-docking benchmark test .........................................
• 39
• 3.2.3.1. HIV protease ................................................................
• 40
• 3.2.3.2. LXRβ .............................................................................
• 41
• 3.2.3.3. cAPK .............................................................................
• 41
• 3.2.3.4. Diverse set ....................................................................
• 42
• 3.3. Results and discussion ...........................................................
• 43
• 3.3.1. Test results on the HIV protease set .............................
• 48
• 3.3.2. Test results on the LXRβ set .........................................
• 50
• 3.3.3. Test results on the cAPK set ..........................................
• 54
• 3.3.4. Test results on the diverse set ........................................
• 55
• 3.3.5. Effect of using rotamers ..................................................
• 58
• 3.4. Conclusion of this section ....................................................
• 60
• 4. GalaxyDock2: improving GalaxyDock using beta-complex
• and binding affinity prediction .................................................
• 61
• 4.1. Overview of this section .......................................................
• 61
• 4.2. Methods ...................................................................................
• 63
• 4.2.1. Initial bank generation using Voronoi diagrams ...........
• 63
• 4.2.2. Benchmark test sets for binding mode prediction ........
• 66
• 4.2.3. Development of binding affinity function ......................
• 67
• 4.2.4. Virtual screening benchmark set .....................................
• 73
• 4.2.4.1. Virtual screening using GalaxyDock2 .......................
• 74
• 4.2.4.2. Virtual screening using AutoDock4 ...........................
• 74
• 4.2.4.3. Virtual screening using UCSF DOCK6 ....................
• 75
• 4.2.4.4. Measures for assessing virtual screening results ......
• 75
• 4.2.5. Protein and ligand preparation ........................................
• 77
• 4.3. Results and discussion ...........................................................
• 77
• 4.3.1. Binding mode prediction ..................................................
• 77
• 4.3.2. Binding affinity prediction ...............................................
• 86
• 4.3.3. Virtual screening ...............................................................
• 92
• 4.4. Conclusion of this section ....................................................
• 97
• 5. Conclusion ....................................................................................
• 99
• Appendix ...........................................................................................
• 102
• Bibliography ......................................................................................
• 111
• 국문초록 ...........................................................................................
• 121