Abstract.
One of the main challenges in computational protein
design (CPD) is the huge size of the protein sequence and
conformational space that has to be computationally
explored. Recently, we showed that state-of-the-art combinatorial
optimization technologies based on Cost Function Network (CFN)
processing allow speeding up provable rigid backbone protein design
methods by several orders of magnitudes. Building up on this, we
improved and injected CFN technology into the well-established CPD
package Osprey to allow all Osprey CPD algorithms to
benefit from associated speedups. Because Osprey
fundamentally relies on the ability of
to produce conformations in increasing order of energy, we defined new
strategies combining CFN lower bounds, with new side-chain
positioning-based branching scheme. Beyond the speedups obtained in
the new
-CFN
combination, this novel branching scheme enables a much faster
enumeration of suboptimal sequences, far beyond what is reachable
without it. Together with the immediate and important speedups
provided by CFN technology, these developments directly benefit to all
the algorithms that previously relied on the DEE/
combination inside Osprey and make it possible to solve
larger CPD problems with provable algorithms.