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Computational study of microtubule stability and associated chemotherapeutic agents by Ahmed Taha Abd Elfattah Taha Ayoub A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy. Department of Chemistry University of Alberta (cid:13)c Ahmed Taha Abd Elfattah Taha Ayoub, 2015 Abstract Microtubules are cellular structures that are crucial to many cellular functions including mainte- nance of cell shape, vesicular transport, and cell division. The dynamic instability of microtubules is the basic feature which enables them to do their cellular functions. Their pivotal role in cell division makes them an important therapeutic target for cancer chemotherapeutic treatment. In this thesis, I have studied two major biological problems connected to microtubules: virtual screen- ing for novel microtubule stabilizing agents, and energetic analysis of tubulin inter-dimer binding energies within microtubules. Inthevirtualscreeningprojectalibraryof33millionchemicalcompoundswasscreenedagainst availablemicrotubulestabilizingagentsusingsimilarityfingerprintsandstructure-baseddrugdesign techniquesarrivingatanovelscaffoldpredictedtobindatthetaxolbindingsite. Thisnovelscaffold shed light on the mechanism of antitumor action of lankacidin antibiotics, due to sharing a high degree of similarity, and was tested and partly confirmed computationally and experimentally. In the microtubule energetic analysis project, various quantum chemical descriptors were tested and parameterized for the prediction of hydrogen bond energies. These descriptors and parameters wereusedinanalyzingthestrengthofhydrogenbondsacrossthelongitudinalinter-dimerinterfaces through which tubulin dimers join head-to-tail to form protofilaments, and across the lateral inter- dimer interface through which protofilaments align side-by-side to form microtubule cylinders. As a continuation to this study, a molecular dynamics simulation of a complete microtubule was run, followed by a complete analysis and breakdown of MM/GBSA (Molecular Mechanics/Generalized Born-Surface Area) binding energies at lateral and longitudinal inter-dimer interfaces enabling thorough analysis of the contribution of each residue, domain, subunit, and dimer to the stability of a microtubule cylinder and shedding light on the driving force for microtubule disassembly and other important phenomena. ii Preface Some of the research conducted for this thesis forms part of an international research collaboration with Dr. K. Arakawa from Hiroshima University, Japan, T. Craddock from Nova Southeastern University, Florida and R. Ahmed from the University of Alberta, with Professor J.A. Tuszynski being the lead collaborator at the University of Alberta. In Chapter 3, isolation of lankacidin antibiotics was conducted by K. Arakawa, fluorescence quenching experiments were conducted by R. Ahmed, and computational predictions, research concept, hypothesis and plan of experiments were done by myself with the help of R. Ahmed, M. Klobukowski and J. Tuszynski. Chapter 2 of this thesis has been published as A. T. Ayoub, M. Klobukowski, and J. Tuszynski, “Similarity-based virtual screening for microtubule stabilizers reveals novel antimitotic scaffold,” Journal of Molecular Graphics and Modelling, vol. 44, 188-196, 2013. I was responsible for the simulations, modelling, data processing and analysis as well as the manuscript composition. M. Klobukowski and J. Tuszynski were the supervisory authors and were involved with concept for- mation and manuscript composition. Chapter 4 of this thesis has been published as A. T. Ayoub, J. Tuszynski, and M. Klobukowski, “Estimating hydrogen bond energies: comparison of methods,” Theoretical Chemistry Accounts, vol. 133, issue 8, 1520-1527, 2014. I was responsible for the calculations, data processing and anal- ysis as well as the manuscript composition. J. Tuszynski and M. Klobukowski were the supervisory authors and were involved with concept formation and manuscript composition. Chapter5ofthisthesishasbeenpublishedasA.T.Ayoub,T.J.A.Craddock,M.Klobukowski, and J. Tuszynski, “Analysis of the strength of interfacial hydrogen bonds between tubulin dimers using quantum theory of atoms in molecules,” Biophysical Journal, vol. 107, issue 3, 740-750, 2014. I was responsible for model building, simulations, data processing and analysis as well as the manuscript composition. T. Craddock assisted in model building and manuscript composition. M. Klobukowski and J. Tuszynski were the supervisory authors and were involved with concept formation and manuscript composition. Chapter 6 of this thesis has been published as A. T. Ayoub, M. Klobukowski, J. Tuszynski, “DetailedPer-residueEnergeticAnalysisExplainstheDrivingForceforMicrotubuleDisassembly,” PLOSComputationalBiology,vol. 11,issue6,e1004313,2015. Iwasresponsibleformodelbuilding, simulations, data processing and analysis as well as the manuscript composition. J. Tuszynski and M. Klobukowski were the supervisory authors and were involved with concept formation and manuscript composition. iii To my mother, my father, wife, kids and my beloved country Egypt iv Acknowledgements The work I have done throughout my PhD studies could not have been possible without the help and support of Mariusz Klobukowski, my research supervisor. He has always been friendly and helpful. He was always a good listener instilling enthusiasm and determination in his students. I also would like to extend my gratitude to the members of my group: Tao Zeng, Amelia Fitzsimons, Cassandra Churchill, Meagan Oakley, Dylan Hennessey and Miriam Van Hoeve. The open personality, professional attitude and immediate assistance of Jack Tuszynski, my research co-supervisor, was a privilege to me. He was always there when needed and despite his busy schedule, he would always respond and help almost instantly. His research group was very active and productive. I extend my acknowledgement to the entire group including: Philip Winter, Rabab Ahmed, Sara Omar, Md. Ashrafuzzaman, Niloofar Nayebi, Marc St. George, Chih-Yuan Tseng, Douglas Friesen, Mark Healey, Jonathan Mane, Khalid Barakat, Kamlesh Sahu, Travis Craddock, Peter Ghaly, and Holly Friedman. I deeply thank my friends with whom I spent great time in Edmonton, especially my friend and brother Muhammad Al-Araby Salem. I also thank Mohammed Darwish, Haitham El-Sikhry, Mohammed Kaasem, Khalid Said Albadawy, Ahmed S. Abdelfattah, Abdelrahman Askar, and Ahmed El-Kadi. Many thanks to all of my friends who represented the best company away from my homeland. To my beloved wife, Hebatalla Elnaka, I really cannot thank you enough. You have done your best taking care of the family and the kids and, most importantly, you managed to endure my busy and sometimes crazy work schedule. You are the best wife in the world. To my loving and caring Mother Atayat, your constant prayers and wishes have been my best companioninmyresearchlife. IwishIcouldrepayyourdebtsonedaythoughI’msureIcannot. My mother-in-law, Hanan, was exceptionally supportive and her constant prayers cannot be forgotten. I extend my gratitude to my Dad, siblings, and honorable relatives. ThankyouallforallthehelpandsupportthroughoutmylifeandthroughoutmyPhDprogram. I will always remember you. v Contents 1 Introduction 1 1.1 Cancer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Mitosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.3 Microtubules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Computational Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4.1 Molecular Mechanics Force Fields. . . . . . . . . . . . . . . . . . . . . . . . . 5 1.4.2 Molecular Dynamics Simulations . . . . . . . . . . . . . . . . . . . . . . . . . 8 1.4.3 Energy Calculations with MM/PB(GB)SA Algorithm . . . . . . . . . . . . . 11 1.4.4 Quantum Theory of Atoms in Molecules . . . . . . . . . . . . . . . . . . . . . 13 1.5 Scope of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2 Similarity-Based Virtual Screening for Microtubule Stabilizers Reveals Novel Antimitotic Scaffold 16 2.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3 Computational Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 2.3.1 Filtering PubChem Compound Library . . . . . . . . . . . . . . . . . . . . . 17 2.3.2 Preparing Receptor for Docking . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3.3 Rescoring the best hits using MM/PBSA . . . . . . . . . . . . . . . . . . . . 20 2.3.4 Prediction of Physicochemical Properties . . . . . . . . . . . . . . . . . . . . 21 2.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.4.1 Results of Virtual Screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.4.2 Results of Rescoring via MM/PBSA . . . . . . . . . . . . . . . . . . . . . . . 25 2.4.3 Results of Physicochemical Predictions . . . . . . . . . . . . . . . . . . . . . . 28 2.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 3 Unravelling the Mechanism of Action of Antitumor Lankacidin 31 3.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 3.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 3.3.1 Computational Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 vi 3.3.2 Isolation of Lankacidin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.3.3 Fluorescence Quenching Assays . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.3.4 Determination of Kinetic Parameters . . . . . . . . . . . . . . . . . . . . . . . 34 3.4 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.4.1 Computational Predictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.4.2 Fluorescence Quenching Assays . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.5 Discussion and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 4 Estimating Hydrogen Bond Energies: Comparison of Methods 38 4.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 4.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.4.1 Performance of Descriptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.4.2 Effect of Dispersion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 5 Analysis of the Strength of Interfacial Hydrogen Bonds between Tubulin Dimers Using Quantum Theory of Atoms in Molecules 47 5.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 5.2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 5.3 Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5.3.1 Energy Calculation using AIM Approach . . . . . . . . . . . . . . . . . . . . 49 5.3.2 Molecular Dynamics Simulations . . . . . . . . . . . . . . . . . . . . . . . . . 50 5.3.3 Quantum Mechanical Calculations . . . . . . . . . . . . . . . . . . . . . . . . 52 5.4 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 5.4.1 Longitudinal Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 5.4.2 Lateral B Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 5.4.3 Lateral A Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 6 Detailed Per-residue Energetic Analysis Explains the Driving force for Micro- tubule Disassembly 64 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 6.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 6.2.1 Building the Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 6.2.2 Parameterization and Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . 67 6.2.3 Trajectory Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 6.3 Results and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 6.3.1 Molecular Dynamics Equilibration . . . . . . . . . . . . . . . . . . . . . . . . 69 vii 6.3.2 Lateral Energetics in the GDP-Model . . . . . . . . . . . . . . . . . . . . . . 69 6.3.3 Lateral Energetics in the GTP-Model . . . . . . . . . . . . . . . . . . . . . . 71 6.3.4 Longitudinal Energetics in the GDP-Model . . . . . . . . . . . . . . . . . . . 73 6.3.5 Longitudinal Energetics in the GTP-Model . . . . . . . . . . . . . . . . . . . 74 6.3.6 Energy Profile Explains the MT Disassembly Mechanism . . . . . . . . . . . 75 6.3.7 Energy Distribution around the Microtubule Ring . . . . . . . . . . . . . . . 78 6.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 7 Conclusion and Future Work 82 Bibliography 85 viii List of Tables 2.1 Binding energies of the five novel hits . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.2 Binding energies in the fifth modification/redocking run . . . . . . . . . . . . . . . . 25 2.3 Experimental binding constants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 2.4 Extrapolated binding energies of novel hits . . . . . . . . . . . . . . . . . . . . . . . 28 2.5 Predicted physicochemical properties of the novel hits . . . . . . . . . . . . . . . . . 29 4.1 Linear fitting parameters at B3LYP/TZVP . . . . . . . . . . . . . . . . . . . . . . . 41 4.2 Linear fitting parameters of improved OWBO descriptor . . . . . . . . . . . . . . . . 43 4.3 Case studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.4 Linear fitting parameters at different levels of theory . . . . . . . . . . . . . . . . . . 46 5.1 Cutting bonds for QM/MM interface . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 5.2 Energy of hydrogen bonds in the LongAB interface . . . . . . . . . . . . . . . . . . . 55 5.3 Energy of hydrogen bonds in the LatB interface . . . . . . . . . . . . . . . . . . . . . 57 5.4 Energy of hydrogen bonds in the LatA interface . . . . . . . . . . . . . . . . . . . . . 61 ix List of Figures 1.1 Animal cell cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Microtubule structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Lennard-Jones potential . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.4 A map of the electron density gradient vector field . . . . . . . . . . . . . . . . . . . 13 2.1 Structures of microtubule stabilizing agents . . . . . . . . . . . . . . . . . . . . . . . 18 2.2 Filtration scheme . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.3 Quantitative improvement of binding energies . . . . . . . . . . . . . . . . . . . . . . 24 2.4 Ligand poses in taxol binding site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 2.5 RMSD equilibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.6 Linear regression plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.1 Structure of lankacidin C and lankacidinol A . . . . . . . . . . . . . . . . . . . . . . 32 3.2 Effect of lankacidin C on fluorescence of the porcine cytoskeleton tubulin. . . . . . . 35 3.3 Effect of lankacidinol A on fluorescence of the porcine cytoskeleton tubulin . . . . . 36 3.4 Effect of lankacidin C on fluorescence of purified recombinant TUB-BI . . . . . . . . 36 3.5 Effect of lankacidinol A on fluorescence of purified recombinant TUB-BI . . . . . . . 37 4.1 Regression plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.2 Improvement of OWBO descriptor performance . . . . . . . . . . . . . . . . . . . . . 43 5.1 Microtubule lattice and interfaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5.2 Major hydrogen bonds at the longitudinal interface . . . . . . . . . . . . . . . . . . . 56 5.3 Relative orientation of the two adjacent heterodimers . . . . . . . . . . . . . . . . . . 58 5.4 Major hydrogen bonds in the LatB system . . . . . . . . . . . . . . . . . . . . . . . . 59 5.5 Major hydrogen bonds in the LatA system. . . . . . . . . . . . . . . . . . . . . . . . 62 6.1 Model of MT structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 6.2 Tubulin subsystems used for MM/GBSA Calculations . . . . . . . . . . . . . . . . . 68 6.3 Equilibration Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 6.4 Domain contributions to overall energy . . . . . . . . . . . . . . . . . . . . . . . . . . 72 6.5 Energetic contributions of residues . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 6.6 Energy profiles at longitudinal inter-dimer interface. . . . . . . . . . . . . . . . . . . 76 x

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“Similarity-based virtual screening for microtubule stabilizers reveals novel antimitotic scaffold,”. Journal of Cassandra Churchill, Meagan Oakley, Dylan Hennessey and Miriam Van Hoeve. The open Many microtubule stabilizers have been introduced so far that work by disrupting the dynamic.
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