De Novo Molecular Design Using Graph Kernels

Erklärung Hiermit erkläre ich, dass ich diese Abschlussarbeit selbständig verfasst habe, keine anderen als die angegebenen Quellen/Hilfsmittel verwendet habe und alle Stellen, die wörtlich oder sinngemäßaus veröffentlichten Schriften entnommen wurden, als solche kenntlich gemacht habe. Darüber hinaus erkläre ich, dass diese Abschluss-arbeit nicht, auch nicht auszugsweise, bereits für eine andere Prüfung angefertigt wurde. Acknowledgements First I would like to thank Dr. Fabrizio Costa who proposed the subject of this thesis and closely supervised me through out the process. He came up with a lot of ideas that literally made this project possible. I would also like to thank him for the code of the NSPDK kernel which plays a major role in GraSCoM implementation. In the end I want to thank him for offering me the opportunity of working on such an interesting project. I cannot imagine a topic that I could have enjoyed more working on for my Master Thesis. I would also like to thank Prof. Dr. Rolf Backofen for having me part of the group (as a student assistant) over the years of my study. I have learned a lot and I definitely enjoyed this experience. Another big thank you needs to go to the group of Dr. Hauke Busch from the ZBSA for allowing me to run some of the experiments on their cluster. I want to also thank my parents for encouraging and supporting me over the years. A final but very special thanks goes to my girlfriend Ilinca, who supported me and made my days working on the thesis a lot nicer. Summary Synthesis of small molecules that improve on the curative properties of existing drugs or that are effective in curing previously untreatable illnesses is a very hard task on which pharmaceutical companies are investing enormous amounts of resources. Despite this, studies show that only one out of 5000 screened drug candidates reaches the market and therefore the pharmaceutical companies are looking for fail fast, fail cheap solutions. In this context, computational methods become an interesting alternative if they manage to replace the expensive and time consuming phases of design, synthesis and test. Among such methods, the computer-aided de novo molecular design approaches are particularly interesting as they produce from scratch novel molecular structures with desired pharmacological properties in an incremental fashion. One of the biggest challenges such systems have to face is the exploration of a practically infinite chemical space. In this …