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Novel molecular computational methods and their quantitative assessment

Zhang, Xin (2010) Novel molecular computational methods and their quantitative assessment. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Molecular computational methods and their efficiency estimation are discussed in this thesis.Computational simulations in biological systems help to understand biological process, drug design and many other crucial applications, thus plays more and more important roles in biological system studies. First, the new algorithm based on polymer growth strategies isintroduced. The main novel feature of this approach is the use of pre-calculated statisticallibraries of molecular fragments. A molecule is sampled by combining fragment configurationsof single residues in this study which are stored in the libraries. This method isdemonstrated to be accurate and can generate large peptides (i.e., 16 residues) in less than aminute of single-processor computing. As an application to this growth algorithm, a practicalmethod is developed to calculate absolute free energy that stages such calculation in severalsteps through growing a molecule. Significant computer time is saved by pre-calculatingfragment configurations and interactions for reuse in a variety of molecules. Then the question¡°how faster is a method than standard molecular dynamics?¡± is addressed. To quantifythe progress in the development of algorithms and forcefields used in molecular simulations,a general method for the assessment of the sampling quality is needed. I therefore developan approach for analyzing the variances in state populations, which quantifies the degree ofsampling in terms of the effective sample size (ESS). This procedure is tested in a variety ofsystems from toy models to atomistic protein simulations. At last, a simple automated procedurewas introduced to obtain approximate physical states from dynamic trajectories: thisallows samplesize estimation in systems for which physical states are not known in advance.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Zhang, Xinxiz35@pitt.eduXIZ35
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairJasnow, Davidjasnow@pitt.eduJASNOW
Committee CoChairZuckerman, Daniel Mddmmzz@pitt.eduDDMMZZ
Committee MemberDuncan, Anthony Htony@dectony.phyast.pitt.eduHAD
Committee MemberMeirovitch, Hagaihagaim@pitt.eduHAGAIM
Committee MemberLevy, Jeremyjlevy@pitt.eduJLEVY
Committee MemberSavinov,
Date: 1 October 2010
Date Type: Completion
Defense Date: 19 July 2010
Approval Date: 1 October 2010
Submission Date: 7 August 2010
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Physics
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: absolute free energy; physical states; sample size; sampling algorithm
Other ID:, etd-08072010-194718
Date Deposited: 10 Nov 2011 19:58
Last Modified: 15 Nov 2016 13:48


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