Physics – Condensed Matter – Statistical Mechanics
Scientific paper
2000-12-15
Physics
Condensed Matter
Statistical Mechanics
Revtex 17 pages, 10 eps figures. Proteins: Structure, Function and Genetics (in press)
Scientific paper
The prediction of the three-dimensional structures of the native state of proteins from the sequences of their amino acids is one of the most important challenges in molecular biology. An essential ingredient to solve this problem within coarse-grained models is the task of deducing effective interaction potentials between the amino acids. Over the years several techniques have been developed to extract potentials that are able to discriminate satisfactorily between the native and non-native folds of a pre-assigned protein sequence. In general, when these potentials are used in actual dynamical folding simulations, they lead to a drift of the native structure outside the quasi-native basin. In this study, we present and validate an approach to overcome this difficulty. By exploiting several numerical and analytical tools we set up a rigorous iterative scheme to extract potentials satisfying a pre-requisite of any viable potential: the stabilization of proteins within their native basin (less than 3-4 \AA$ $ cRMS). The scheme is flexible and is demonstrated to be applicable to a variety of parametrizations of the energy function and provides, in each case, the optimal potentials.
Banavar Jayanth
Maritan Amos
Micheletti Cristian
Seno Flavio
No associations
LandOfFree
Learning effective amino acid interactions through iterative stochastic techniques does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Learning effective amino acid interactions through iterative stochastic techniques, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Learning effective amino acid interactions through iterative stochastic techniques will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-510549