Protein side-chain placement using CLP
Constraint logic programming (CLP) techniques can be used in protein side-chain placement, an important sub-task in comparative modelling. In a simple formulation values for domain variables represent rotamer side-chain conformations, and constraints represent atomic clashes. These constraints can be visualised using a "rotamer contact map", and observations made with this visualisation tool have been used to develop a strategy that overcomes limitations present in CLP caused by over-constrained residues. Null rotamers provide a mechanism that can automatically identify over-constrained residues. The use of null rotamers makes possible an iterative modelling strategy where, at each iteration, a CLP program is generated automatically; each program representing successively tighter packing constraints corresponding to larger atomic radii. Different CLP enumeration heuristics have been evaluated for use with this side-chain placement method, and it has been tested with several different rotamer libraries; a backbone-dependent rotamer library, when used with first-fail enumeration heuristics, was shown to be the most successful. Side-chain conformations predicted by this CLP method compare favourably against those predicted using other side-chain placement methods. The CLP method has been applied to two modelling problems. The first involved building models of class II MHC molecules in order to increase the utility of a peptide threading program. This program uses an allele's known or modelled 3D structure with a heuristic scoring function to predict peptides that are likely to bind to it - thus using CLP to model class II MHC alleles increases the program's utility. The second application used the CLP method to build structures of ribosome inactivating proteins (RIPs). These models were built using CLP together with comparative modelling approaches, and a model of bouganin, a recently identified wild RIF protein, has been built to help design engineered therapeutic proteins.