A computational framework to empower probabilistic protein design.

ABSTRACT:

Motivation

The task of engineering a protein to perform a target biological function is known as protein design. A commonly used paradigm casts this functional design problem as a structural one, assuming a fixed backbone. In probabilistic protein design, positional amino acid probabilities are used to create a random library of sequences to be simultaneously screened for biological activity. Clearly, certain choices of probability distributions will be more successful in yielding functional sequences. However, since the number of sequences is exponential in protein length, computational optimization of the distribution is difficult.

Results

In this paper, we develop a computational framework for probabilistic protein design following the structural paradigm. We formulate th

SUBMITTER: Fromer M 

PROVIDER: S-EPMC2718646 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature