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        <identifier>oai:www.ideals.illinois.edu:2142/14582</identifier>
        <datestamp>2023-07-10</datestamp>
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        <thesis xmlns="http://www.ndltd.org/standards/metadata/etdms/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.ndltd.org/standards/metadata/etdms/1.1/ http://www.ndltd.org/standards/metadata/etdms/1.1/etdms11.xsd http://purl.org/dc/elements/1.1/ http://www.ndltd.org/standards/metadata/etdms/1.1/etdmsdc.xsd">
          <dc:contributor>Oono, Yoshitsugu</dc:contributor>
          <dc:contributor>Chemla, Yann R.</dc:contributor>
          <dc:contributor>Oono, Yoshitsugu</dc:contributor>
          <dc:contributor>Schulten, Klaus J.</dc:contributor>
          <dc:contributor>Vishveshwara, Smitha</dc:contributor>
          <dc:creator>Rajan, Aruna</dc:creator>
          <dc:date>2010-01-06T16:13:13Z</dc:date>
          <dc:date>2010-01-06T16:13:13Z</dc:date>
          <dc:date>2010-01-06T16:13:13Z</dc:date>
          <dc:date>2009-12</dc:date>
          <dc:description>Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now
possible due to advances in computer technology. Soon, trajectories long enough to probe
dynamics over many milliseconds will become available. Since these timescales match the
physiological timescales over which many small proteins fold, all atom MD simulations of protein
folding are now becoming popular. To distill features of such large folding trajectories,
we must develop methods that can both compress trajectory data to enable visualization,
and that can yield themselves to further analysis, such as the finding of collective coordinates
and reduction of the dynamics. Conventionally, clustering has been the most popular
MD trajectory analysis technique, followed by principal component analysis (PCA). Simple
clustering used in MD trajectory analysis suffers from various serious drawbacks, namely,
(i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and
(iii) since it does not take into account interrelationships amongst data points, the separation
of data into clusters can often be artificial. Usually, partitions generated by clustering
techniques are validated visually, but such validation is not possible for MD trajectories of
protein folding, as the underlying structural transitions are not well understood. Rigorous
cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions
in which MD trajectories reside, while still preserving their salient features. PCA has
often been used for dimension reduction and while it is computationally inexpensive, being
a linear method, it does not achieve good data compression. In this thesis, I propose a
different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves
superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS
by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding
trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make
comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS.
The three villin headpiece trajectories showed great structural heterogeneity. Apart from
a few trivial features like early formation of secondary structure, no commonalities between
trajectories were found. There were no units of residues or atoms found moving in concert
across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative
to the plane formed by helices 2 and 3 was observed towards the end of the folding process
in all trajectories, when nearly all native contacts had been formed. However, the transition
occurred through a different series of steps in all trajectories, indicating that it may not be
a common transition in villin folding. The trajectories showed competition between local
structure formation/hydrophobic collapse and global structure formation in all trajectories.
Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core
inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it
showed no flipping transition. All the other trajectories get trapped in hydrophobically
collapsed states. The NLE residues were found to be buried deeply into the core, compared
to the corresponding lysines in the villin headpiece, thereby making the core tighter and
harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a
fast folder as experiments suggest. The tightness of the hydrophobic core may be a very
important factor in the folding of larger proteins. It is likely that chaperones like GroEL act
to undo the tight hydrophobic core of proteins, after most secondary structure elements have
been formed, so that global rearrangement is easier. I conclude by presenting facts about
chaperone-protein complexes and propose further directions for the study of protein folding.</dc:description>
          <dc:description>Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2009-11-20T14:29:24Z
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University of Illinois Theses &amp; Dissertations (ID: 1)
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          <dc:identifier>http://hdl.handle.net/2142/14582</dc:identifier>
          <dc:language>en</dc:language>
          <dc:rights>Copyright 2009 Aruna Rajan</dc:rights>
          <dc:subject>protein folding</dc:subject>
          <dc:subject>molecular dynamics simulations</dc:subject>
          <dc:subject>non-metric multidimensional scaling</dc:subject>
          <dc:subject>principal component analysis</dc:subject>
          <dc:subject>clustering</dc:subject>
          <dc:subject>villin headpiece</dc:subject>
          <dc:subject>norleucine mutant</dc:subject>
          <dc:title>Analysis of Molecular Dynamics Simulations of Protein Folding</dc:title>
          <degree>
            <department>Physics</department>
            <departmentCode>1244</departmentCode>
            <discipline>Physics</discipline>
            <disciplineCode>0240</disciplineCode>
            <grantor>University of Illinois at Urbana-Champaign</grantor>
            <level>Dissertation</level>
            <name>Ph.D.</name>
            <program>PHD:Physics -UIUC</program>
            <programCode>10KS0240PHD</programCode>
          </degree>
        </thesis>
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