The
Dokholyan group focuses primarily on understanding protein dynamics,
more specifically
on how induced changes in protein folding and aggregation lead to disease.
One prominent example of this is the hypothesized misfolding of superoxide
dismutase associated with the neurodegenerative disease Amyotrophic Lateral
Sclerosis (ALS), also known as Lou Gehrig’s disease. The lab is
currently pursuing two specific approaches: I. Molecular Etiology of ALS
Mutations in the dimeric enzyme superoxide dismutase (SOD1) have been
linked to familial (hereditary) cases of ALS. Formation of toxic SOD1
aggregates is associated with both sporadic and familial ALS. The Dokholyan
group aims to uncover the origin of mutant SOD1 toxicity at the molecular
level by using a combination of computational and experimental approaches.
Approximately 10% of ALS patients suffer from a familial form of ALS.
Because the SOD1 mutations in these patients are thought to cause SOD1
aggregation, the Dokholyan lab plans to (i) determine whether these
mutations facilitate aggregation by altering the balance between native
and misfolded states (ii) determine the effect of refolding factors
(chaperones) on mutant SOD1 folding, and (iii) reconstruct the SOD1
aggregates computationally. The Dokholyan group plans to identify the
structure of SOD1 aggregates using Discrete Molecular Dynamics (DMD),
a tool for rapid simulations of simplified protein models. Determining
the structure of SOD1 aggregates is critical for designing small molecules
that can prevent or reverse the formation of these toxic aggregates. II. The Protein Folding Problem
A fundamental goal of molecular biophysics is to understand the relationship
between protein sequence and structure, also known as the ‘protein
folding problem.’ Solving this problem is critical for making
accurate protein structure/function predictions. In order to address
this problem computationally, it is necessary to develop an inter-atomic
interaction potential. The Dokholyan group is developing a hierarchy
of interaction models, from simplified coarse-grained models to more
detailed ones, and determining their interaction parameters. These
interaction models are then used to perform simulations of protein
models using a range of molecular dynamics simulations methodologies
designed to accommodate the interaction models. The advantage of
this approach is its modularity; instead of solving the much more
difficult
problem of finding a native state by spanning the whole protein folding
time scale, one can separate the time scale out into slow and fast
events in protein folding and treat them with different methodologies.
Selected Publications:
Sharma S, Ding F, Dokholyan NV. (2007) Multiscale modeling of nucleosome dynamics. Biophys J. 92:1457-70.
Serohijos AW, Chen Y, Ding F, Elston TC, Dokholyan NV. (2006) A structural model reveals energy transduction in dynein. Proc Natl Acad Sci U S A. 103:18540-5.
Sharma S, Ding F, Nie H, Watson D, Unnithan A, Lopp J, Pozefsky D, Dokholyan NV. (2006) iFold: a platform for interactive folding simulations of proteins. Bioinformatics. 22:2693-4.
Ding F, Dokholyan NV. (2006) Emergence of protein fold families through rational design. PLoS Comput Biol. 2:e85.
Khare SD, Ding F, Gwanmesia KN, Dokholyan NV. (2005) Molecular origin
of polyglutamine aggregation in neurodegenerative diseases. PLoS
Comput Biol 1:e30.
Ding
F, Jha RK, Dokholyan NV. (2005) Scaling behavior and structure
of denatured proteins. Structure 13:1047-54.
Ding
F, Buldyrev SV, Dokholyan NV (2005) Folding Trp-cage
to NMR resolution native structure using a coarse-grained protein
model. Biophys J 88:147-155. |
