The first step in the process of reducing risk is naturally their analysis. Risk analysis is largely seen as a process of defining threats, likelihood of occurring of these factors, and impact if they appear, thus determining the risks and their severity. The paper shows how it operates.
Properties of a simple model of polypeptide chains were studied by the means of the Monte Carlo method. The chains were built on the (310) hybrid lattice. The residues interacted with long-range potential. There were two kinds of residues: hydrophobic and hy- drophilic forming a typical helical pattern -HHPPHPP-. Short range potential was used to prefer helical conformations of the chain. It was found that at low temperatures the model chain formes dense and partially ordered structures (non-unique). The presence of the local potential led to an increase of helicity. The effect of the interplay between the two potentials was studied. After the collapse of the chain further annealing caused rearrangement of helical structures. Dynamic properties of the chain at low temperature depended strongly on the local chain ordering.
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 H.A. Scheraga of Cornell University, U.S.A.
A high coordination lattice model was used to represent the protein chain. Lattice points correspond to amino-acid side groups. A complicated force field was designed in order to reproduce a protein-like behavior of the chain. Long-distance tertiary restraints were also introduced into the model. The Replica Exchange Monte Carlo method was applied to find the lowest energy states of the folded chain and to solve the problem of multiple minima. In this method, a set of replicas of the model chain was simulated independently in different temperatures with the exchanges of replicas allowed. The model chains, which consisted of up to 100 residues, were folded to structures whose root-mean-square deviation (RMSD) from their native state was between 2.5 and 5 A. Introduction of restrain based on the positions of the backbone hydrogen atoms led to an improvement in the number of successful simulation runs. A small improvement (about 0.5 A) was also achieved in the RMSD of the folds. The proposed method can be used for the refinement of structures determined experimentally from NMR data.
A high coordination lattice discretization of protein conformational space is described. The model allows discrete representation of polypeptide chains of globular proteins and small macromolecular assemblies with an accuracy comparable to the accuracy of crystallographic structures. Knowledge based force Held, that consists of sequence specific short range interactions, cooperative model of hydrogen bond network and tertiary one body, two body and multibody interactions, is outlined and discussed. A model of stochastic dynamics for these protein models is also described. The proposed method enables moderate resolution tertiary structure prediction of simple and small globular proteins. Its applicability in structure prediction increases significantly when evolutionary information is exploited or/and when sparse experimental data are available. The model responds correctly to sequence mutations and could be used at early stages of a computer aided protein design and protein redesign. Computational speed, associated with the discrete structure of the model, enables studies of the long time dynamics of polypeptides and proteins and quite detailed theoretical studies of thermodynamics of nontrivial protein models.