CONCEPTS TO INTERFERE WITH PROTEIN-PROTEIN COMPLEX FORMATIONS: DATA ANALYSIS, STRUCTURAL EVIDENCE AND STRATEGIES FOR FINDING SMALL MOLECULE MODULATORS DISSERTATION ZUR ERLANGUNG DES DOKTORGRADES DER NATURWISSENSCHAFTEN (DR. RER. NAT.) dem Fachbereich Pharmazie der PHILIPPS-UNIVERSITÄT MARBURG vorgelegt von Peter Block aus Bergisch Gladbach Marburg an der Lahn, im November 2005 Vom Fachbereich Pharmazie der PHILIPPS-UNIVERSITÄT MARBURG als Dissertation angenommen am: 15.12.2005 Erstgutachter: Prof. Dr. G. Klebe Zweitgutachter: Prof. Dr. E. Hüllermeier Tag der mündlichen Prüfung: 16.12.2005 I would like to express my gratitude to PROF. DR. GERHARD KLEBE for being a patient supervisor and for supporting this work with ideas, criticism, and encouragement. PROF. DR. EYKE HÜLLERMEIER for collaboration in the EPIC project and guidance in the field of Machine Learning. DR. CHRISTOPH SOTRIFFER for helpful discussions and hints during the entire PhD and for the very accurate reviewing of the manuscript. The teamwork in the development of AFFINDB was outstanding. JURI PÄRN for the enjoyable collaboration in the EPIC project. the group of PROF. DR. ALFRED WITTINGHOFER, namely DR. ALEXANDER WOLF, DR. CHRISTIAN JELICH-OTTMANN and DR. MICHAEL WEYAND for the collaboration in the 14-3-3 project and their never-ending patience with the in vitro testing of compounds. my room mate HANS VELEC for long and helpful discussions about the projects and the teamwork in the development of visual DrugScore. CHRISTOF GERLACH and MATTHIAS ZENTGRAF for assistance in various screening applications and NILS WESKAMP for the help with Cavbase. DR. ANDREAS BERGNER for support and helpful discussions, especially regarding the EPIC project. ANGELA SCHOLZ for invaluable administrative work. my PARENTS for their love and for their support during my entire PhD. my girlfriend SARINA for her love, her support, and her never-ending patience. TABLE OF CONTENTS Introduction ....................................................................................................................... 8 PHYSICOCHEMICAL DESCRIPTORS TO DISCRIMINATE PROTEIN-PROTEIN INTERACTIONS IN PERMANENT AND TRANSIENT COMPLEXES SELECTED BY MEANS OF MACHINE LEARNING ALGORITHMS Introduction ..................................................................................................................... 11 Theory and Methods ....................................................................................................... 18 Protein-Protein Interfaces ........................................................................................... 18 ACV with ACE & Sybyl Atom Type Notation (ACVACE, ACVSybyl) ...................... 20 DrugScore Contact Vectors (DCV) ....................................................................... 21 SFCscore Descriptor Vectors (SDV) ..................................................................... 22 Machine Learning Algorithms ................................................................................... 22 Support Vector Machines (SVM) .......................................................................... 24 Decision Trees (C4.5) ............................................................................................ 25 K Nearest Neighbors (KNN) ................................................................................. 27 Naïve Bayes (NB) .................................................................................................. 27 Feature Selection Approaches .................................................................................... 29 Filter Approach ...................................................................................................... 29 Wrapper Approach ................................................................................................. 30 Genetic Algorithms ................................................................................................ 31 Feature Analysis ......................................................................................................... 32 Results and Discussion ................................................................................................... 33 Classification of Monomer versus Homodimer Complexes ...................................... 33 Classification of Folding Complexes versus Recognition Complexes ...................... 35 Feature Analysis with Genetic Algorithms ................................................................ 39 Summary and Conclusions ............................................................................................. 49 References ....................................................................................................................... 51 TABLE OF CONTENTS STRATEGIES TO SEARCH AND DESIGN STABILIZERS OF PROTEIN-PROTEIN INTERACTIONS: A FEASIBILITY STUDY Introduction ..................................................................................................................... 55 Materials and Methods .................................................................................................... 57 Data Analysis and Tools for Virtual Screening .......................................................... 57 Stabilizers of Protein-Protein Interactions ............................................................. 58 Screening for Novel Targets .................................................................................. 58 The H+-ATPase/14-3-3 System .............................................................................. 60 The Fusicoccin Binding Site ................................................................................. 61 Water and the Fusicoccin Binding Pocket ............................................................. 63 Virtual Screening Campaigns ..................................................................................... 65 Preprocessing of the Candidate Molecules ............................................................ 67 Docking Fusicoccin ............................................................................................... 68 “Hot Spot” Analysis .............................................................................................. 69 FTrees .................................................................................................................... 70 Unity Database Search .......................................................................................... 72 Scoring ................................................................................................................... 75 Pharmacophore Post-Filtering ............................................................................... 75 Visual Inspection ................................................................................................... 77 Docking with Gold and AutoDock ........................................................................ 77 Visual DrugScore ................................................................................................... 78 Results and Discussion ................................................................................................... 78 Virtual Screening for Stabilizers of the H+-ATPase/14-3-3 Interaction ..................... 86 Summary and Conclusions ........................................................................................... 100 References ..................................................................................................................... 102 TABLE OF CONTENTS AFFINDB: A FREELY ACCESSIBLE DATABASE OF AFFINITIES FOR PROTEIN- LIGAND COMPLEXES FROM THE PDB Introduction ....................................................................................................................111 Methods......................................................................................................................... 113 Database Architecture .............................................................................................. 113 Data Collection and Database Content .................................................................... 113 Database Access ...................................................................................................... 118 Discussion ..................................................................................................................... 119 References ..................................................................................................................... 123 SUMMARY Zusammenfassung ......................................................................................................... 127 APPENDIX Publications Arising from this Work ............................................................................. 132 Articles ..................................................................................................................... 132 Posters ...................................................................................................................... 132 Awards ...................................................................................................................... 133 Curriculum Vitae ........................................................................................................... 134 INTRODUCTION 8 INTRODUCTION “LIFE IS CONTROLLED BY OVER 50.000 PROTEIN-PROTEIN INTERACTIONS.” (ANDREW HAMILTON, YALE UNIVERSITY, MARCH 2005, INTERNATIONAL WORKSHOP NAD3 IN RAUISCHHOLZHAUSEN, GERMANY) Protein-Protein interactions are playing a crucial role