Exploring the fitness landscapes of lattice proteins
- Universitaet Wien (Austria)
- Deutsches Krebsforschungszentrum, Heidelberg (Germany)
We present methods to investigate the sequence to structure relation for proteins. We use random structures of HP-type lattice models as a coarse grained model to study generic properties of biopolymers. To circumvent the computational limitations imposed by most lattice protein folding algorithms we apply a simple and fast deterministic approximation algorithm with a tunable accuracy. We investigate ensemble properties such as the conditional probability to find structures with a certain similarity at a given distance of the underlying sequence for various alphabets. Our results suggest that the structure landscapes for lattice proteins are generally very rugged, while larger alphabets fine tune the folding process and smoothen the map. This implies a simplification for evolutionary strategies. The applied methods appear to be helpful in the study of the complex interplay between folding strategies, energy functions and alphabets. Possible implications to the investigation of evolutionary strategies or the optimization of biopolymers are discussed. 33 refs., 3 figs.
- OSTI ID:
- 549267
- Report Number(s):
- CONF-970132--
- Country of Publication:
- United States
- Language:
- English
Similar Records
Local rules for protein folding on a triangular lattice and generalized hydrophobicity in the HP model
RNA folding and combinatory landscapes
Related Subjects
BASIC STUDIES
99 GENERAL AND MISCELLANEOUS
ACCURACY
ALGORITHMS
AMINO ACID SEQUENCE
BIOLOGICAL EVOLUTION
CHEMICAL PROPERTIES
CRYSTAL LATTICES
DISTANCE
DNA SEQUENCING
ELECTRONIC STRUCTURE
FREE ENERGY
OPTIMIZATION
ORGANIC POLYMERS
PHYSICAL PROPERTIES
PROBABILITY
PROTEIN STRUCTURE
PROTEINS
STRUCTURAL MODELS
STRUCTURE-ACTIVITY RELATIONSHIPS
TOPOLOGICAL MAPPING