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Mechanistic Insights Into Proteins Association Through Molecular Dynamics

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Mechanistic Insights Into Proteins Association Through Molecular Dynamics This document is downloaded from DR‑NTU (https://dr.ntu.edu.sg) Nanyang Technological University, Singapore. Mechanistic insights into proteins association through molecular dynamics Chua, Khi Pin 2017 Chua, K. P. (2017). Mechanistic insights into proteins association through molecular dynamics. Doctoral thesis, Nanyang Technological University, Singapore. http://hdl.handle.net/10356/73025 https://doi.org/10.32657/10356/73025 Downloaded on 08 Oct 2021 05:59:21 SGT Mechanistic Insights Into Proteins Association Through Molecular Dynamics Khi Pin Chua Interdisciplinary Graduate School NTU Institute for Health Technologies 2017 Mechanistic Insights Into Proteins Association Through Molecular Dynamics Khi Pin Chua Interdisciplinary Graduate School NTU Institute for Health Technologies A thesis submitted to the Nanyang Technological University in partial fulfilment of the requirement for the degree of Doctor of Philosophy 2017 i Acknowledgments I would like to express the utmost gratitude to my supervisor, Associate Professor Chew Lock Yue for his guidance throughout the four years of my doctoral study. He has been the biggest source of motivation for me. His insistence in doing science the right way is an inspiration to all of us in the lab. Additionally, I would like to thank my co-supervisor, Associate Professor Mu Yuguang for steering me in the right direction when I was lost. His experience in the molecular dynamics field has been one of the main factors I learnt so much during the past four years. Other than that, I would like to thank my mentor, Associate Professor Konstantin Pervushin for giving me valuable feedbacks in the projects I have done during our meetings. The feedbacks were crucial in polishing my works. My sincere thanks also go to my collaborators Assistant Professor Miao Yansong, Associate Professor Ali Miserez, Sun He and Hiew Shu Hui. I have learnt from them the nuances of experimental biology during our interdisciplinary collaborations. I would also like to take this chance to thank my labmates for the useful discussions during group meetings and for all the fun we had going out for group dinner. I could not have gone through the thesis without their supports. I am extremely grateful to my family who has supported me unconditionally throughout the thesis. They have provided me moral and emotional support when I had doubt in this journey. Lastly, I would like to thank my friends for the social life I needed besides working in the lab. And the friend who had the patience to listen to a nerdy scientists' random science facts and his struggles with life. Contents Acronyms iv List of Figures v List of Tables ix 1 Overview and Main Methodology 1 1.1 Basic Structures of Proteins and Protein Folding Problem . 1 1.2 Proteins' Aggregation and Gelation . 5 1.3 Protein-protein Recognition . 7 2 Methodology and Literatures Review 9 2.1 Molecular Dynamics . 9 2.2 Applications of Molecular Dynamics on Protein-protein Interactions . 14 2.2.1 Amylin (IAPP) Aggregation . 14 2.2.2 Prion Fragment: PrP106-126 Aggregation . 16 2.2.3 Peptides Gelation . 19 2.2.4 Protein-protein Complexes: Recognition of Polyprolines . 22 2.3 Aims and Objectives . 24 3 Replica Exchange Molecular Dynamics Simulation of Cross-Fibrillation of IAPP and PrP106-126 26 3.1 Introduction . 26 3.2 Simulation Details and Analysis Methods . 28 3.3 Results . 31 3.3.1 REMD Diagnostic Tests . 31 3.3.2 Secondary Structures Propensity and Contact's Probability . 32 3.3.3 Dihedral Principal Component Analysis . 35 3.3.4 β-sheets Formation . 40 3.4 Discussion and Conclusion . 43 3.5 Supplementary Information . 47 3.5.1 Comparison of dPCA Energy Landscape at Three Lowest Tem- peratures . 47 3.5.2 The Evolution of into Structure E . 47 3.5.3 DSSP Plot for 315 K Ensemble . 50 3.5.4 Dynamical Reweighting using MBAR . 50 3.5.5 Structures from Conformational Clustering . 53 3.5.6 Constant Temperature Molecular Dynamics with Amber99SB- ILDN . 55 4 Towards a Mechanistic Understanding of Peptides Gelation using Sequences from Sucker Ring Teeth Proteins 56 4.1 Introduction . 56 4.2 Methods . 58 4.2.1 Martini Coarse-grained Model . 58 ii CONTENTS iii 4.2.2 Bias Exchange Well-tempered Metadynamics (WT-BEMD) . 59 4.3 Results . 62 4.3.1 Coarse-grained Simulations using MARTINI Model . 62 4.3.2 Convergence of Metadynamics Simulation . 67 4.3.3 Metadynamics: Difference in Free Energy Landscape . 70 4.3.4 Metadynamics: Multi-dimensional Free Energy Clustering Anal- ysis . 71 4.4 Discussion . 76 4.5 Supplementary Figures . 79 5 Binding Analysis of Profilin-Polyproline Complex 81 5.1 Introduction . 81 5.2 Methods . 84 5.2.1 Homology Modelling and Molecular Dynamics . 84 5.2.2 MM/PBSA Binding Energy Analysis . 86 5.3 Results . 88 5.4 Discussions . 93 5.4.1 Stability of AtPRF3-Polyprolines Complexes and Extended N- terminal α-helix . 93 5.4.2 CH-π and Electrostatic Interactions . 94 5.4.3 MM/PBSA Binding Free Energy . 96 5.5 Supplementary Information . 98 6 Conclusion and Future Outlook 102 7 List of Publications 107 8 References 108 Acronyms iv Acronyms Aβ Amyloid Beta protein. AtPRF Arabidopsis Thaliana Profilin. BEMD Bias-exchange Metadynamics. CD Circular Dichroism. dPCA Dihedral Principal Component Analysis. FH1 Formin Homology Domain 1. hIAPP Human Islet Amyloid Polypeptide. IDP Intrinsically disordered protein. MD Molecular Dynamics. METAD Metadynamics. MM/PBSA Molecular Mechanics/Poisson Boltzmann Surface Area. NMR Nuclear Magnetic Resonance. PDB Protein Data Bank. PMF Potential mean force. PolyP Poly-prolines. PP-II Poly-prolines Type II. PrP Prion Protein. PrP106-126 Prion protein fragment (residue 106 to residue 126). REMD Replica-exchange Molecular Dynamics. RMSD Root-mean-square Deviation. SASA Solvent-accessible Surface Area. SH2/SH3 Src Homology Domain 2/3. SRT Sucker Ring Teeth. VdW Van der Waal. WT-BEMD Well-tempered Bias-exchange Metadynamics. List of Figures 1 Illustrations of a/an (a) α-helix. (b) Anti-parallel β-sheets. (c) Parallel β-sheets. Figure (a) was generated by author using PyMOL.1 Figures (b) and (c) were obtained from the Internet from Wikimedia Common Repository.2, 3 ................................ 3 2 Figure shows a protofibril of amyloid beta (Aβ solved experimentally. Generated using PyMOL using structure 2BEG from Protein Data Bank (PDB).1, 4 ............................... 5 3 (a) Structure of SH3 with a proline-rich peptide (PDB code:1PRL).5 (b) Structure of a hemoglobin heterotetramer (PDB code:1C7C).6 Figures were generated by the author using PyMOL.1 .............. 8 4 (a) Crystal structure of full length human amylin (hIAPP). (b) NMR structure of anti-parallel β-sheets structures of hIAPP20-29 (SNNF- GAILS). Figures are generated by author using PyMOL.1, 7, 8 . 15 5 (a) Solution NMR structure of human prion protein (PDB Code:1QLX).9 Structures shown are for residue 125 to residue 228. (b) X-ray crystal structure of dimeric prion.10 Figure generated by author using PyMOL.1 18 6 Crystal structure of the N-terminal domain of silk fibroin from Bombyx mori. Figure generated by author using PyMOL.1, 11 . 21 7 Test for validity of REMD simulation. (A) Sufficient overlaps are found between the potential energy distribution of all the temperatures used in the simulation. Note that each color represents the distribution from a single temperature. (B) Random walk in the temperature space for all replicas (y-axis). Colors indicate temperature ensembles, ranging from lowest temperature (blue) to highest temperature (red). (C) The aver- age coil propensity at different temperatures are similar for ten periods during the simulation. (D) Average turn propensity which has been evaluated in a similar fashion as (C). (E) Evolution of secondary struc- tures for the 315 K ensemble. (F) An estimate of the conformational entropy of the protein complex in bound state by the quasi-harmonic method. 32 8 Propensity of the different secondary structures adopted by PrP106-126 and IAPP during the 100-600 ns period. The gray bar indicated by CS separates the two chains. Index 106-126 is PrP106-126 while index 1-37 is IAPP. 33 9 Frequency of contacts formed by (A) PrP106-126 towards IAPP and (B) IAPP towards PrP106-126. (C) Mean distance between residues of IAPP and PrP106-126. All contacts and distances were calculated by including only the heavy atoms. 35 10 Contour plot of the relative free energy landscape determined from dPCA using the first and second principal components of REMD simula- tion at 315K. Note that the color bar represents the relative free energy (kJ mol−1), which is evaluated from the population of conformations obtained by determining the frequency of the conformation within a grid of the energy landscape. 36 v LIST OF FIGURES vi 11 (A-F) Representative structures for six minima in the dPCA relative free energy landscape. Note that red color is used for IAPP, while blue color is used for PrP106-126. Yellow spheres indicate the N-termini. Figures were generated with PyMOL. (G-H) Representative structure from the 9th cluster determined from conformational clustering. (I) Secondary structures determined by DSSP for A-G. Z is the initial configuration of the system. Yellow indicates β-sheets, gold indicates β-bridge, orange indicates 3-10 helix and cyan indicates α-helix. 37 12 (1-8)Snapshots containing inter-chain β-sheets structures. Figures were generated using PyMOL. (9) Secondary structures determined by DSSP for structures 1-8. The definition of colors and representation of struc- tures are identical to those given in Figure 11. 41 S1 Comparison of the dPCA energy landscape for the three lowest temper- atures ensembles. 47 S2 Snapshots of the different stages described in the structural evolution of PrP106-126 and IAPP complex.
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