2 research outputs found
Molecular Dynamics of Biomolecules through Direct Analysis of Dipolar Couplings
Residual dipolar
couplings (RDCs) are important probes in structural
biology, but their analysis is often complicated by the determination
of an alignment tensor or its associated assumptions. We here apply
the maximum entropy principle to derive a tensor-free formalism which
allows for direct, dynamic analysis of RDCs and holds the classic
tensor formalism as a special case. Specifically, the framework enables
us to robustly analyze data regardless of whether a clear separation
of internal and overall dynamics is possible. Such a separation is
often difficult in the core subjects of current structural biology,
which include multidomain and intrinsically disordered proteins as
well as nucleic acids. We demonstrate the method is tractable and
self-consistent and generalizes to data sets comprised of observations
from multiple different alignment conditions
Molecular Determinants for Unphosphorylated STAT3 Dimerization Determined by Integrative Modeling
Signal
transducer and activator of transcription factors (STATs)
are proteins that can translocate into the nucleus, bind DNA, and
activate gene transcription. STAT proteins play a crucial role in
cell proliferation, apoptosis, and differentiation. The prevalent
view is that STAT proteins are able to form dimers and bind DNA only
upon phosphorylation of specific tyrosine residues in the transactivation
domain. However, this paradigm has been questioned recently by the
observation of dimers of unphosphorylated STATs (USTATs) by X-ray,
FoĢrster resonance energy transfer, and site-directed mutagenesis.
A more complex picture of the dimerization process and of the role
of the dimers is, thus, emerging. Here we present an integrated modeling
study of STAT3, a member of the STAT family of utmost importance in
cancer development and therapy, in which we combine available experimental
data with several computational methodologies such as homology modeling,
proteināprotein docking, and molecular dynamics to build reliable
atomistic models of USTAT3 dimers. The models generated with the integrative
approach presented here were then validated by performing computational
alanine scanning for all the residues in the proteināprotein
interface. These results confirmed the experimental observation of
the importance of some of these residues (in particular Leu78 and
Asp19) in the USTAT3 dimerization process. Given the growing importance
of USTAT3 dimers in several cellular pathways, our models provide
an important tool for studying the effects of pathological mutations
at the molecular and/or atomistic level, and in the rational design
of new inhibitors of dimerization