Computational Modeling of Glycyl Radical Enzymes: Novel Insights to the Mechanism of Pyruvate Formate-Lyase

Computational modeling of glycyl radical enzymes: Novel insights to the mechanism of Pyruvate Formate-Lyase Computermodellierung von Glycyl-Radikalenzymen: Neue Einblicke in den Mechanismus von Pyruvat-Formiat-Lyase Der Naturwissenschaftlichen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg zur Erlangung des Doktorgrades Dr. rer. nat. vorgelegt von Marko Hanževački aus Zagreb, Kroatien Als Dissertation genehmigt von der Naturwissenschaftlichen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg Tag der mündlichen Prüfung: 30.10.2020 Vorsitzender des Promotionsorgans: Prof. Dr. Wolfgang Achtziger Gutacher/in: Prof. Dr. Ana-Sunčana Smith Prof. Dr. Timothy Clark Table of Contents Acknowledgments I would like to express my sincere appreciation to my supervisors David and Ana Smith for always being friendly, patient, and understanding. David, as my main supervisor you have been a constant source of support and influence. You have demonstrated dedication and belief in the research topic – and me. Thank you for sharing your indispensable expertise and knowledge, as well as for all constructive guidance and motivation. Thank you, Ana, for taking the role of co-supervisor and strongly assisting in steering me through to the end with enthusiastic encouragement, inspiring and dynamic discussions, and useful critiques of my research work. I admire you both for your excellence in science, supervisory qualities, and authority. I will always appreciate you as my mentors and positive role models and do my best to apply the knowledge and skills I have obtained in my future career. I want to kindly thank all those who helped me in the scientific work and in learning new techniques and tools. Accordingly, I would like to pay my special regards to Radha Dilip Banhatti for providing a great deal of professional support and assistance in keeping my progress on schedule and for her valuable and constructive suggestions during the development of this research work. My deepest gratitude is also extended to Karmen Čondic-Jurkić for her willingness to dedicate her time so generously and for transferring essential knowledge and experience about molecular simulations and enzyme catalysis. During the last couple of years, I have met many wonderful people, but three of them are very special to me and I want to acknowledge them here. Dear Katarina, Nataša, and Zlatko, you have always believed in me and I consider you as my second family. I am truly grateful for everything you have done for me and I could not be happier to have such friends. Thus, once again I would like to thank my best friend Katarina for a decade of friendship and all the wonderful moments we spent together from college to this day. Kate, thank you for all the love, understanding, care, and support you have given me along this path. Thanks for being such an incredible person and that you showed me how precious true friendship can be, and how much incredible value it can add to my life. Special thanks to my dear friend Nataša for all the laughter and cheerful moments in our small but at the same time always positive and joyful office in the basement of the sixth wing. I enjoyed sharing the office space with you as my colleague and a true friend. These I Table of Contents couple of years with you in my life were exciting and amazing. There is nothing better than a friend unless it is a friend with a large Milka chocolate. I want to thank my best buddy Zlatko for turning every ordinary situation into something extraordinary. Thank you for all the fruitful discussions and useful life coaching. Thanks for accepting me for who I am from the very beginning and for teaching me some of the techniques and programming which have helped to improve my skills and this dissertation. I want to express my deepest gratitude to my family for the endless support along the way, especially my parents who have always been there for me and whose love and guidance are with me in whatever I pursue. Without you, all of this would be impossible. I would like to take this opportunity to thank Jakov, Josip, Mislav, Luka, Robert, Joe, Zoran, Boris, Danijela, and all my friends and colleagues from the group in Zagreb for productive working atmosphere, helpful discussions, support, and motivation. These people have continuously encouraged me and were always willing and enthusiastic to assist in any way possible throughout the research projects. I am also grateful to my colleagues from the group in Erlangen, especially Christian Wick for excellent cooperation and hospitality. I would like to kindly thank Christof Jäger, Anna Croft, and the British Scholarship Trust for the opportunities to conduct part of my research abroad at the University of Nottingham. I want to thank my dear friends Vera, Zé, Carolina, and Ania from Nottingham for constant stimulation and support. I would like to acknowledge Željka, Nikolina, Ira, and the entire administrative staff of RBI and FAU. Last but not least, I would like to gratefully acknowledge the Croatian Science Foundation (IP-11-2013-8238) and the ERC Starting Grant (337283) for financial support. I would like to acknowledge the Cluster of Excellence: Engineering of Advanced Materials (EAM), the computing facilities of the Regionales Rechenzentrum Erlangen (RRZE), and the University Computing Centre (SRCE) for providing computational and storage resources. “I have been bent and broken, but – I hope – into a better shape.” — Charles Dickens, Great Expectations II Table of Contents Abstract Enzymes whose mechanisms involve the formation of species with unpaired electrons (free radicals) are collectively known as radical enzymes. In the last couple of years, there has been an increasing interest in radical enzymes due to the ability of these species to perform a large variety of biochemical transformations, which opens an avenue for potential industrial applications in biotechnology and enzyme engineering. Enzymes utilizing unpaired electrons on glycine residues (glycyl radical enzymes or GREs) have proven to be interesting targets for pharmaceutical applications e.g. in the synthesis of novel antibiotics. In a natural setting, GREs assume a key role in the metabolic pathways of strict and facultative anaerobes such as E. coli and other microorganisms. In this thesis, a prototypical member of the GRE family, pyruvate formate-lyase (PFL), has been systematically studied using multiscale computational modeling. This enzyme is central to the microbial anaerobic glucose metabolism, where it catalyzes the reversible conversion of pyruvate and coenzyme A (CoA) to formate and acetyl-CoA in two half- reactions by employing complex radical chemistry. Although PFL is one of the most extensively characterized GREs, several important aspects of its catalytic mechanism are still not understood. For example, the details of neither the first nor the second half-reaction have been fully characterized. The connection between the two half-reactions, in which the CoA molecule must approach the enzyme’s active site, is even more elusive. Namely, all available crystal structures in complex with CoA indicate that CoA is bound to the surface of the enzyme, some 20-30 Å away from the active site. For more than a decade, the actual entry mechanism of CoA has remained hidden due to the lack of experimental data. In the first part of this thesis, the effects of chemical modification of the enzyme (acetylation), during the first half-reaction, were investigated using molecular dynamics. This led to the identification of an entry channel for CoA, which leads from the surface of the enzyme to the active site. The channel was found to exhibit accentuated fluctuations and a higher probability of being in an open state in the acetylated (post first half-reaction) systems. This finding suggests that the structural modification of the enzyme has an important functional role, whereby the formation of the acyl-enzyme intermediate serves to initiate a subtle molecular signaling cascade that influences the protein dynamics and facilitates the entry (and the timing thereof) of CoA into the active site of PFL. III Table of Contents Using the understanding of the channel position, the reaction coordinates that connect CoA with the active site of PFL were examined using steered MD simulations and umbrella sampling. Additionally, the unrestrained dissociation dynamics of CoA from the active site were investigated. These simulations were performed on acetylated and non-acetylated model systems of PFL, aiming to investigate the possible binding and unbinding pathways of CoA, through the previously identified channel. The energetics associated with the process of CoA approaching the active site of PFL before and after the first half-reaction has been established, thus uncovering potential bound states of the coenzyme in the near vicinity of the active site. The key findings of this study reveal the presence of reactive bound states of CoA close to the active site, significant for triggering the second half-reaction and determining the overall outcomes for both acetylated and non-acetylated PFL systems. The detailed chemical aspects of PFL catalysis have been studied in the third part of this thesis by employing QM/MM calculations. In this respect, both half-reactions were investigated using the previously determined binding poses of CoA in the active site of non- acetylated and acetylated model systems. The results suggest that the progression of the first half-reaction occurs in two distinct steps. The initiation of the second half-reaction, by the abstraction of an H-atom, was found to be of key importance. On one hand, it was demonstrated that the flexibility of the active site allows for the adjustment to the newly formed species in the acetylated systems, which is crucial to lowering the barrier for the initial H-abstraction reaction. Furthermore, the H-abstraction from CoA was found to be energetically more favorable when carried by a formate radical anion rather than by the cysteinyl radical in the active site.

Load more