Luận án tiến sĩ: Nghiên cứu tính toán protein amyloid beta - Giai đoạn ban đầu tập hợp

BOSTON UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES Dissertation COMPUTATIONAL STUDY OF AMYLOID BETA PROTEIN IN IMPLICIT AND EXPLICIT SOLVENT MODELS: PROBING THE INITIAL STAGES OF AGGREGATION BOGDAN TARUS B., Boston University, 2004 Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy 2007 UMI Number: 3240642 INFORMATION TO USERS The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleed-through, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion.

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Box 1346 Ann Arbor, MI 48106-1346 Approved by First Reader £S\waÀ John E. Professor of Chemistry Second Reader LN Rosina M. Professor ¥f Chemistry To my family. Acknowledgments I would like to thank my advisor, Prof.

Straub, for his generous support and patience over my entire period of doctoral studies at Boston University. His sustained ded- ication as research advisor and enthusiastic teacher will constitute a permanent example for me. I thank all the professors on my thesis committee, Prof. Rosina Georgiadis, Prof.

Tom Keyes, Prof. Sandor Vajda and Prof. I also thank Prof. Devarajan Thiru- malai from University of Maryland for being a constant source of help and inspiration for my research.

I thank all my professors at Boston University. I would like to thank Prof. David Coker for sharing his research enthusiasm with us. I am sincerely grateful to all the colleagues I had over the years in the Straub group.

Finally, I would like to thank my family, especially my wife, Dana, for all her love and unconditioned support. 1V COMPUTATIONAL STUDY OF AMYLOID BETA PROTEIN IN IMPLICIT AND EXPLICIT SOLVENT MODELS: PROBING THE INITIAL STAGES OF AGGREGATION (Order No. ) BOGDAN TARUS Boston University Graduate School of Arts and Sciences, 2007 Major Professor: John E. Straub, Professor of Chemistry ABSTRACT It has been proposed that the amyloid đ-protein (Ađ-protein) plays a crucial role in the development of Alzheimer’s Disease (AD).

This dissertation presents the results of computa- tional studies of the initial stages of AG-protein association. The objective of this work was to determine the stability and role of the ÀØ-protein monomers and low-order oligomers as metastable intermediates on the pathway for formation of larger aggregates and fibrils. A protocol based on shape complementarity is used to generate an assortment of possible dimer structures of the A@jpo_35-protein congener. The ensemble of dimer structures are evaluated using rapidly computed estimates of the desolvation and electrostatic interaction energies to identify a putative stable dimer structure.

Using the umbrella sampling method and classical molecular dynamics, the potential of mean force (PMF) associated with the dimerization of the peptide in aqueous solution is computed. The profiles of the PMF corresponding to the formation of the two putative dimer structures are compared. Molecular dynamics trajectories originating from the two putative dimer structures are used to analyze their stability. Significant attempts are made to increase the time over which the association of the Afi9—35-protein can be simulated.

In this respect, conformations generated by the A@io_35- protein simulated using an explicit TIP3P solvent model are compared to conformations re- sulting from simulations employing one empirical and two continuum electrostatics solvent models. Inspired by recent experimental results, the dynamics of the D23-K28 “salt-bridge” V contacts are examined and critically evaluated as a possible “nucleation site” for the formation of Ø-structure characteristic of amyloid fibrils. The behavior of the AØại_ao-protein fragment is studied using molecular dynamics simula- tions employing an explicit aqueous solvent model. Special attention is paid to the VGSN(24- 27) region of the protein where experimental solid-state nuclear magnetic resonance (NMR) measurements indicate that formation of a turn may play a crucial role in stabilizing the AfØi-4a-protem in fibril structure.

The influence of two mutations, E22Q and D23N, on the thermodynamics properties of the Ai ao fragment is analyzed and related to the possible roles played by these two naturally occurring mutations in amyloidosis. vi Contents 1 Introduction 1 2 Probing the initial stage of aggregation of the A 9_3;-protein: Assessing the propensity for peptide dimerization 6 2. gà kg kg ko 7 2.3 Computational Model and Methods.1 Dimer structure generation using a docking protocol.2 Desolvation energy screening.4 Secondary Structure Analysis .4 Results and Discussion .2 Generation of dimer structures.38 Potential of Mean Force .4 Stability of dimer.5 Dynamical fluctuations in the y-dimer .6 Time dependence of secondary structure fluctuations in the homodimer 36 2.5 Summary and Conclusions .v xo 36 3 A comparative study of the structure and thermodynamics of the A{io_35- protein in different hydration models 39 vil 3. vn gà gà lv lv vn à và và và 3.38 Computational Models and Methods .1 Explicit solvent molecular dynamics.2 Implicit solvent molecular dynamics.3 Computational estimation of pK, .4 Results and analySlS.

cv ng gà gà g kg v va 3.1 Radius of gyration .2 Root-mean-square Ñuctuations.3 Lipari-Szabo generalized order parameter.5 Solvation self-energy. ch vu ng ee na 3.6 Intra-peptide hydrogen bonds .7 Computational estimation of pK, .5 Summary and Conclusions. ee Dynamics of Asp23—Lys28 salt bridge formation in Ađịo_ss monomers 41 Summary. Computational Models and Methods.

kg và và ee 4.4 Results and Discussions. ng kg kg va 4.1 Compact A(@io-35 undergoes large structural fluctuations .2 Computed values of pK, are in accord with experiments .3 Structures with intact salt-bridge D23-K28 are not the most stable 4.4 Multiple basins are populated in Àđịo ss monomer .5 Hydrogen-bonds with water increase the desolvation barrier of D23 and K28 ee 82 4.6 Burial of K28 involves a large free energy cost .7 The structure of water around residues D23 and K28 .5 Summary and Conclusions. c Q c Q k Q kg và gà va 86 The competition between the electrostatic and hydrophobic intra-peptide interactions in the AØs¡_so-protein 91 5. kg vn gà v g kg kg kg A 92 5.38 Computational Methods and Models .1 Simulation model and methods .2 Computational estimation of pK, .4 Results and analysis.

Q g gà và TT va 99 5.1 pK, values indicate weak intra-peptide electrostatic interactions .2 Inter-titratable side-chain distances .3 Intra-peptide hydrophobic contacts .4 Lys28 makes transitive contacts with the peptide backbone.5 Intra-peptide folding elements .56 Summary and Conclusions. cvva 115 Bibliography 121 Curriculum Vitae 137 1X List of Tables 41 Experimental and predicted pK, values (using the trajectories labeled T1-T5) for titratable residues in the A3,o-35-protein. The predicted pK, values are for Afio-_ss-protein structures simulated in explicit solvent model TIP3P. A value of e = 4 was used as the protein dielectric constant.1 Computational pK, values are compared with the experimental! (in parenthe- sis) pK, values for titratable residues Glu22, Asp23, and Lys28 in the A21~30- peptide.

The isolated residues and the residues in the peptide structure are similar, indicating that the pK, shifts result from weak intra-peptide electro- static interactions. c Q Q LH nu nu cà na vn g V NV k k k vUA 5.2 The number of nodes, N, and direct transitions among nodes, Ni, associated with the free energy transition disconnectivity graphs of the WT, E22Q, D23N, and K28A peptides. Na, is reduced to N—1 using the minimum-cut algorithm.? Ng nodes with free energies higher than —0.6 kcal/mol define the entropic basin. na lv kg g lv kg v kg kg va List of Figures 2.1 The distribution of the energy of interaction of the two monomers, used as the scoring function to analyze two sets of 2000 dimer decoys each.

The dimer se- lected by a method that places a relative emphasis on the burial of hydrophobic residues at the dimer interface is referred to as the “y-dimer” (a). The dimer chosen by a method that places a relative emphasis on electrostatic interactions is referred to as the “e-dimer” (b). The “desolvation energy”— corresponding to the energy change on going from separated monomeric À/Øo_ss to AZ dimeric decoy structure — was used as a measure of the degree of hydrophobic surface burial. The decoy sets were obtained using two shape complementarity proto- cols, GRAMM (a) and ZDOCK (b).

The energy of desolvation was calculated based on an atom contact energy (ACE) method.2 kcal/mol was used to compute the distribution of the interaction energy.2 The putative dimer structures derived by minimization of the functions S, (Eq.6)), corresponding to the y-dimer (a) and e-dimer (b), respectively. The side chains at the dimer interface are depicted explicitly. The green and yellow colored residues belong to monomer A (left) and those in red and orange are part of monomer B (right), .3 The distribution of the intermonomeric interaction energy plotted as a function of the atomic root-mean-square distance between each decoy structure and the structure of the y-dimer (a) and the e-dimer (b). In general, the unfavorable dimer structures are well differentiated from the most favorable structures.

The desolvation energy distribution (a) has a “funnel-like” character, indicating that structures more similar to the reference structure tend to be structures of minimal energy. The contribution of the electrostatic interaction energy determines a discontinuous distribution (b), the structure of most of the decoy dimers being very different from the structure of the e-dimer.4 The sidechain-sidechain contact matrices averaged for the ten decoy structures corresponding to the y-dimer (a) and e-dimer (b), respectively. The selection of the y-dimer is produced by a scoring function which is composed by the de- solvation energy only (a), while the e-dimer is selected by a function defined as the sum of the desolvation energy, the van der Waals and the electrostatic inter- actions (b) (see text for details). The interface of the ¿-dimer is dominated by contacts which involve hydrophobic residues, while the presence of the polar and charged residues is evident at the interface of the e-dimer.

The amino acid se- quence of the A@i9_3, monomer is Y!'EVHHQ!5KLVFF?AEDVG25°SNKGA*® TIGLM®, 6 -ỗ q. aaa ẶẼ xH 2.5 The Potential of Mean Force (PMF) is plotted for two different relative orien- tations of the monomeric peptide within the dimer. The PMF is computed as a function of the surface separation, 6 = € — €sø„;, along the distance between the centers-of-mass (DCOMs) of the two monomers, where € and £,on: are the DCOMs of the two monomers when they are at an arbitrary separation and in contact, respectively. The profile in blue corresponds to the free energy surface computed using the e-dimer as the starting structure.

The red curve is similarly computed using the y-dimer as the starting structure. The difference between the two surfaces suggests that hydrophobic interactions may be more essential to stabilization of the dimer structure than electrostatic interactions.6 The distribution of the surface buried area at the interface between the AGio_35 monomers during the molecular dynamics simulation of the dimer indicates that the set of the principal contacts at the dimer interface are maintained for the y-dimer (a), and that the e-dimer is not stable (b). A bin of 15 A? was used to compute the distribution of the interface surface area.7 The comparison of the electrostatic (red) and the hydrophobic (green) inter- action energies between the A@jo_35 monomers during the molecular dynamics simulation implies that the stability of the y-dimer is given by contacts between hydrophobic residues. In black is shown that the contribution of the fragment 15-30 plays a dominant role to the overall stability of the y-dimer.