Design of a knowledge-based force field for off-lattice simulations of protein structure

Prediction of protein structure from amino-acid sequence still continues to be an unsolved problem of theoretical molecular biology. One approach to solve it is to construct an appropriate (free) energy function that recognizes the native structures of some selected proteins (whose native structures are known) as the ones distinctively lowest in (free) energy and then to carry out a search of the lowest-energy structure of a new protein. In order to reduce the complexity of the problem and the cost of energy evaluation, the so-called united-residue representation of the polypeptide chain is often applied, in which each amino-acid residue is represented by only a few interaction sites. Once the global energy minimum of the simplified chain has been found, the all-atom structure can easily and reliably be constructed. The search of the lowest-energy structure is usually carried out by means of Monte Carlo methods, though use of more efficient global-optimization methods, especially those of deformation of original energy surface is potentially promising. Monte Carlo search of the conformational space can be accelerated greatly, if the chain is superposed on a discrete lattice (the on-lattice approach). On the other hand, the on-lattice approach prohibits the use of many efficient global-optimization methods, because they require both energy and its space derivatives. The on-lattice methods in which the chain is embedded in the continuous 3D space are, therefore, also worth developing. In this paper we summarize the work on the design and implementation of an off-lattice united-residue force field that is underway in our group, in cooperation with Professor HA. Scheraga of Cornell University, U.S.A.