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Methods for the Investigation of Protein-Ligand Complexes

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Methods for the Investigation of Protein-Ligand Complexes Methods for the Investigation of Protein-Ligand Complexes Benjamin H Stauch Robinson College University of Cambridge A thesis submitted for the degree of Doctor of Philosophy June 2013 Meinen Eltern. \What we see before us is just one tiny part of the world. We get in the habit of thinking, this is the world, but that's not true at all. The real world is a much darker and deeper place than this, and much of it is occupied by jellyfish and things. We just happen to forget all that. Don't you agree? Two-thirds of earth's surface is ocean, and all we can see with the naked eye is the surface: the skin." Haruki Murakami The Wind-Up Bird Chronicle. \I may not have gone where I intended to go, but I think I have ended up where I needed to be." Douglas Adams The Long Dark Tea-Time of the Soul. Declaration This thesis is the result of my own work and includes nothing which is the outcome of work done in collaboration except where specifically indicated in the text. This thesis does not exceed the specified length limit of 60,000 words as defined by the Biology Degree Committee. This thesis has been typeset in 12pt font using LATEX according to the specifica- tions defined by the Board of Graduate Studies and the Biology Degree Committee. Acknowledgements This Ph.D. has been a long and strange journey. I owe my gratitude to many people I met on the way, and to those who were with me from the start. Although this section is therefore rather long, it is also necessarily incomplete. First and foremost, I would like to thank my supervisor John Over- ington for his leap of faith of accepting me into his group at the EBI, providing me with ideas, inspiration and criticism. Your constant sup- port and advice has made this thesis possible. Daniel Nietlispach is acknowledged for his willingness to provide su- pervision from the side of Cambridge University, and support in and understanding of complicated issues. I owe my deepest gratidude to Helke Hillebrand, Iain Mattaj, and the EMBL International Ph.D. Programme for funding and solving minor and major problems, making me feel like nothing can go wrong. Michele Cianci is thanked for his exceptional commitment, patience and support during most of the experimental work presented in this thesis. Thanks to your hospitality, my numerous trips to Hamburg have never felt like work, even though we have been clocking long hours. I must thank Bernd Simon for his support and expertise during my time in Heidelberg. It was an absolute pleasure working with you, and I like to think that you are the prime example of how EMBL really is held together. The members of my thesis advisory committee, Maja K¨ohnand Ger- ard Kleywegt, are gratefully acknowledged for their duties during my Ph.D., providing constant input and hands-on support. Teresa Carlomagno is acknowledged for accepting me into the EMBL and her supervision during my time at the EMBL Heidelberg. Importantly, my parents and my family, who were essential to me dur- ing my entire education (and before), trusting my judgment and sup- porting me in every which way. This is for you. Sophie Shephard has been a great support through many of the chal- lenges on my way, and I am sure at this stage, together with my parents and John, she will be among the five most relieved people this is coming to a conclusion. Daniel Mende and Christina Mertens have been great friends for many years. It means a lot to me to know I can always rely on you. Felix Kr¨ugerand Nenad Bartoniˇcek have been essential in making me feel at home in Cambridge, and I never had to ask them twice to help me out one of the many times I did. You guys are awesome! Also thanks to you, John and Sophie for proof-reading of this thesis. My housemates Benedetta Baldi and Tamara Steijger are credited for enduring me especially during the last phase of this thesis. Frank Thommen is acknowledged for facilitating many last-minute, non-standard, and semi-official solutions, and work-arounds. Adriana Rullmann has been a most exceptional teacher and inspiration early during my education. Without you I would probably not be here. Thanks for encouraging me to take on slightly thicker `boards'. Julien Orts, Irene Amata, John Kirpatrick, Domenico Sanfelice, Thierry Rohmer, Audron_eLapinait_e,Carmen Fernandez, Teodora Basile, Mag- dalena Rakwalska, and Stephen Fullerton are acknowledged for being great colleagues and friends during my time in Heidelberg. You made it worth it. Patr´ıciaBento, Sam Croset, Gerard van Westen, Louisa Bellis, Shaun McGlinchey, George Papadatos, Rita Santos, and the entire ChEMBL team for their welcoming me and help to settle in to Cambridge and the Genome Campus. It has been a pleasure working with you. Henning Hofmann, J¨orgZielonka, and Carten M¨unkare thanked for giving me confidence and encouraging me to pursue my ambitions, and providing me with a great environment during my master's thesis. I furthermore thank Teresa Tiffert and Robinson College, Cambridge for their support during my graduate studies here. Sander Timmer, Christine Seeliger and Steven Wilder are gratefully ackonwledged for the banter, the long hours on the ergs, the rare hours in the sun, and contributing their part in keeping me going. I must thank Angela^ Gon¸calves and Catalina Schwalie for their will- ingness to casually overlook initial dissents. Tracey Andrew and Milanka Stoijkovic are acknowledged as represen- tatives of the Ph.D. Programme. Their commitment and interest in their `subjects' has been exceptional. I am grateful to Pedro Ballester and Michael Menden for their willing- ness to discuss machine learning related matters. The Cambridge University Cycling Club, and especially Dan Ahearn, Sarah Gallagher, Jenny Haskell, and Ming-Chee Chung, are acknowl- edged for getting me away from the screen and bench, or trying to. Konrad Rudolph is thanked for last-minute support with LATEX type- setting. I want to explicitly thank my friends Karina Mayer, Jonas Brand, Isa Serma, Patrick Schubert, Swetlana Derksen, and Sina Muhler for keeping in touch, visiting, or providing accommodation during my own visits back home. Thomas Weisswange, Martin Weisel, Tim Geppert, Tim Werner, Gosia Drwal, Daniel Gottstein, Felix Reisen, and Frederik Hefke deserve a mention, too. Last but not least, I owe my gratitude to countless people at the EMBL Heidelberg, the EBI, and Cambridge University for making my time in Cambridge and Heidelberg into an experience I will keep dearly. Abstract The interaction of small molecules with biological receptors is fundamental for cellular processes and plays a central role in disease and homeostasis. In this thesis, two multi- disciplinary methods aiding the investigation of protein-ligand interactions are presented that make use of data obtained by diverse experimental techniques, Nuclear Magnetic Resonance (NMR) spectroscopy and X-ray crystallography. In the first part of the thesis, an existing NMR-based method for the determination of ligand binding modes, termed INPHARMA, is improved by incorporating a rigorous model of protein internal motion using the NMR order parameter formalism. In this approach, indirect magnetisation transfer between two competitive ligands relayed by the receptor is simulated computationally and compared to experimental NMR data. This yields a ranking of binding poses, allowing for the true ligand orientations to be selected from a pool of possible complex structures. Using Protein Kinase A (PKA) as a test system, and order parameters extracted from Molecular Dynamics simulations of two PKA-ligand complexes, it is demonstrated that the overestimation of the magnetisation transfer that had been observed when not using a motional model, can be corrected for. Additionally, a `generic' statistical characterisation of protein motional behaviour is obtained by investigating other, unrelated proteins, and applied to increase the ability of the method to discriminate true from decoy ligand orientations in the PKA system. In the second part, the empirical notion that the noble gas xenon tends to bind to ligand binding site of proteins is investigated systematically. It is found that xenon is over-represented in protein ligand binding sites of known structures within the Pro- tein Data Bank, showing dispersive interactions with aliphatic and aromatic protein moieties. A knowledge-based interaction potential for xenon is developed and used to construct a `xenon likeness score' that can discriminate xenon from water molecules and ions. The performance of a classifier based on this score is examined by cross-validation using common performance measures from the field of machine learning, indicating high discrimination power. In a prospective application, xenon binding to the N-terminal domain (NTD) of the molecular chaperone Hsp90 is predicted, and for validation, the X-ray structure of a xenon derivative of Hsp90-NTD is solved, demonstrating that xenon binding sites can be predicted with good accuracy. These findings have implications for fragment-based drug discovery, increasing both the throughput and accuracy of the INPHARMA method that is especially suited for fragment-like, weakly binding ligands, and suggesting the usefulness of adding xenon to standard fragment libraries. Contents Contentsi List of Figuresv List of Tables ix 1 Introduction1 1.1 Fragment based drug design . .2 1.1.1 Fragment library design and fragment elaboration . .4 1.1.2 Biophysical techniques for fragment identification . .7 1.1.2.1 NMR spectroscopy . .9 1.1.2.2 X-ray crystallography . 11 1.1.2.3 Surface plasmon resonance . 13 1.1.2.4 Isothermal titration calorimetry . 13 1.1.2.5 Thermal shift assay . 14 1.1.3 Computational techniques for fragment scanning .
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