Proteins

Proteins are large macromolecules constituted by chains of amino acid residues to accomplish many biological tasks required by living organisms: catalyzing reactions, DNA replication and repair, and moving molecules around. Imagining how these protein molecules are formed (i.e. folded) into three-dimensional structures lead biologists to believe that their knotting was biologically impossible but, in fact, certain proteins do contain knotted features. How and why’’ provides another of the biological mysteries catalyzing contemporary research.

Motor proteins, such as kinesins and dyneins, are responsible for several fundamental transport functions inside the cell. Disruptions of these underlying mechanisms are linked to many neurodegenerative diseases such as Alzheimer’s, Paraplegia and Amyotrophic Lateral Sclerosis (ALS). Impaired functionality of motor proteins, possibly caused due to mutations, have been linked to disruptions in intracellular transport.

When a virus infects a living cell it directs the biosynthetic resources of the cell toward transcription and translation of viral proteins, replication of viral genomes, assembly of virus particles, and release of hundreds to thousands of progeny virus particles to the extracellular environment. For well-characterized viruses one may begin to build kinetic models that predict virus growth behavior based on the dynamics of the underlying molecular processes within the infected cell.

This talk (and a related poster) describes Lie-group-theoretic techniques that can be applied in the analysis and modeling of protein conformations. Three topics are covered: (1) Conformational transitions between two known end states; (2) proper normalization of helix-helix crossing angle data in the PDB; (3) models of the conformational entropy of the ensemble of unfolded polypeptide conformations.

Synechococcus elongatus, a single celled cyanobacterium, has a remarkably precise and robust circadian clock which has been reconstituted in vitro with just three proteins. Its simplicity makes it an ideal system for understanding dynamical functions that can arise from the kinetics of multiple phosphorylations. Recent experiments and theoretical analysis will be presented along with speculations on the evolutionary origins of this clock.

Classical studies show that for many proteins, the information required for specifying the tertiary structure is contained in the amino acid sequence. However, the potential complexity of this information is truly enormous, a problem that makes defining the rules for protein folding difficult through either computational or experimental methods.

Sequence-structure relationships in proteins are highly asymmetric since
many sequences fold into relatively few structures. What is the number of
sequences that fold into a particular protein structure? Is it possible to
switch between stable protein folds by point mutations? To address these
questions we compute a directed graph of sequences and structures of
proteins, which is based on experimentally determined protein shapes. Two
thousand and sixty experimental structures from the Protein Data Bank were

Are protein motions limited because of a higher level of cooperativity than indicated by usual potentials?

We focus on the problem of determining the structure of complexes formed by the association of two proteins by searching for the global minimum of a function approximating the free energy of the complex. Solving this problem requires the combination of a number of different optimization methods. First we explore the conformational space by systematic global search based on the Fast Fourier Transform (FFT) correlation approach that evaluates the energies of billions of docked conformations on a grid.

Recent progress in obtaining docked protein complexes will be discussed.
The combination of exhaustive search, clustering and localized global
optimization can reliably find energy minima to highly nonconvex biomolecular
energy functions. Using an energy function that adds desolvation and
screened electrostatics to classical molecular mechanics potentials, the
global minimum is found very near to the observed native state. This is
demonstrated across a large number of benchmark examples.