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020 ▼a 9781392849439
035 ▼a (MiAaPQ)AAI13903210
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 540
1001 ▼a Lincoff, James A.
24510 ▼a Development and Application of a Novel Enhanced Sampling Method and Bayesian Analysis for Characterizing Intrinsically Disordered Proteins.
260 ▼a [S.l.]: ▼b University of California, Berkeley., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 109 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
500 ▼a Advisor: Head-Gordon, Teresa.
5021 ▼a Thesis (Ph.D.)--University of California, Berkeley, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a Intrinsically disordered proteins (IDPs) are a class of proteins with wide-ranging significance in signaling and disease that do not adopt a dominant folded structure as monomers. Rather, the structures of IDPs in solution are best described as ensembles of conformational states that may range from being fully random coil to partially ordered. This structural plasticity of IDPs is theorized to facilitate regulation of their interaction with other species, as in signal transduction or aggregation of IDPs into ordered fibrils. Characterizing the structural ensembles of IDPs in the free, solvated state is key to understanding the mechanisms of these interactions, and correspondingly the role an IDP species plays in signaling or disease. The rapid interconversion between conformational states, however, complicates the experimental study of IDPs because most experimental signals report highly averaged information. Computational modeling with validation through comparison to experiment has therefore been a main approach to characterizing IDP structure and dynamics. The focus of my dissertation is on the development of new methods for computational study of IDPs, facilitating better and less expensive de novo generation of IDP structural ensembles and improving the metrics used to evaluate the degree of agreement between a simulated ensemble and a set of experimental data. Despite vast improvements in computational power and efficiency, molecular dynamics (MD) simulations of IDPs for generating conformational ensembles are still limited by the expense of calculations. In Chapter 2 I present the development of a new enhanced sampling method-temperature cool walking (TCW)-and comparison of its performance against a standard method-temperature replica exchange (TREx). The TCW method accelerates the rate of convergence to the equilibrium conformational ensemble with increased sampling acceleration relative to TREx at greatly reduced computational cost. The second major limitation in MD is the accuracy of the force field. Most classical fixed charge force fields were parameterized using data from folded proteins, and have been thought to be biased to overly collapsed and structured conformations. This has motivated the development of IDP-tailored force fields that sample greater disorder, at the potential expense of the ability to model stabilizing interactions between an IDP and its binding partners. In Chapter 3, I assess to what degree the shortcomings assigned to standard force fields may be due to insufficient sampling by characterizing the performance of standard and newly modified force fields on the Alzheimer's peptide amyloid-棺 using both TREx and TCW. We find that with improved sampling, standard and modified force fields produce similar structural ensembles, suggesting that both are appropriate for simulation of the disordered state. In Chapter 4 I present preliminary results building off of this work by characterizing the performance of a polarizable force field modeling a synthetic peptide that demonstrates complete loss of helical content with increasing temperature. Inclusion of polarization effects has been thought to be key for accurate modeling of such multicomponent systems, especially when there is a shift in the electrostatic environment as is the case for the unfolding peptide. Our early results, while limited by current lack of convergence for tests using the polarizable force field and needing further confirmation, match that expectation by finding early evidence of greater response to temperature by the polarizable force field than fixed charge comparators. The last work presented here is in the development of new methods for calculating the degree of agreement between a simulated IDP ensemble and experimental data. Backcalculation of experimental data from structure can be very imprecise, motivating the development in Chapter 5 of scoring formalisms that account for variable uncertainties in both back-calculation and experiment for diverse experimental data types. In summary, the methods described in this dissertation seek to improve computational study of IDPs by facilitating better, less expensive generation of IDP ensembles and producing more informative metrics for evaluating their agreement with experiment.
590 ▼a School code: 0028.
650 4 ▼a Chemical engineering.
650 4 ▼a Biophysics.
650 4 ▼a Chemistry.
690 ▼a 0542
690 ▼a 0786
690 ▼a 0485
71020 ▼a University of California, Berkeley. ▼b Chemical Engineering.
7730 ▼t Dissertations Abstracts International ▼g 81-05B.
773 ▼t Dissertation Abstract International
790 ▼a 0028
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492440 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK