2 de mai. de 2011

Divulgação de palestra

Machines of life: from small proteins to large biomolecular machines
Prof. José N. Onuchic
Center for Theoretical Biological Physics
University of California at San Diego

Conferência Magna da XIX Semana da Química - 2011
LOCAL: Auditório do CCMN (Roxinho)
DATA: 06/05/2011 (sexta-feira)
HORA: 14:30


Resumo:
Globally the energy landscape of a folding protein resembles a partially
rough funnel with reduced energetic frustration. A consequence of
minimizing energetic frustration is that the topology of the native fold also
plays a major role in the folding mechanism. Some folding motifs are easier
to design than others suggesting the possibility that evolution not only
selected sequences with sufficiently small energetic frustration but also
selected more easily designable native structures. The overall structures of
the on-route and off-route (traps) intermediates for the folding of more
complex proteins are also strongly influenced by topology.
Going beyond folding, the power of reduced models to study the physics of
protein assembly, protein binding and recognition, and larger biomolecular
machines has also proven impressive. Since energetic frustration is
sufficiently small, native structure-based models, which correspond to
perfectly unfrustrated energy landscapes, have shown to be a powerful
approach to explore larger proteins and protein complexes, not only folding
but also function associated to large conformational motions. Therefore a
discussion of how global motions control the mechanistic processes in the
ribosome and molecular motors will be presented. For example, this
conceptual framework is allowing us to envisage the dynamics of molecular
motors from the structural perspective and it provides the means to make
several quantitative predictions that can be tested by experiments. For the
kinesin motor, a prototype of the biological machines in the cell,
structurebased
molecular simulations of an explicit kinesin and microtubule
structures were used to glean a number of salient features that supplement
the current experimental findings.
Supported by the NSF

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