Genfold: A genetic algorithm for folding protein structures using NMR restraints

GENFOLD: a genetic algorithm for folding protein structures using NMR restraints.

We report the development and validation of the program GENFOLD, a genetic algorithm that calculates protein structures using restraints obtained from NMR, such as distances derived from nuclear Overhauser effects, and dihedral angles derived from coupling constants. The program has been tested on three proteins: the POU domain (a small three-helix DNA-binding protein), bovine pancreatic trypsi...

Protein Loop Closure Using Orientational Restraints from NMR Data

Protein loops often play important roles in biological functions. Modeling loops accurately is crucial to determining the functional specificity of a protein. Despite the recent progress in loop prediction approaches, which led to a number of algorithms over the past decade, few rigorous algorithmic approaches exist to model protein loops using global orientational restraints, such as those obt...

A Hybrid Genetic Algorithm for 2D Protein Folding Simulations

Protein folding problem is one of the most interesting problem in the medical field, which consists in finding the tertiary structure for a given amino acid sequence of a protein. Protein folding is NP hard problem. In this paper, we hybridized genetic algorithm with a local search algorithm to solve 2D Protein folding problem. This kind of hybridization empower the genetic algorithm exploratio...

Topology-based models and NMR structures in protein folding simulations

Topology-based interaction potentials are simplified models that use the native contacts in the folded structure of a protein to define an energetically unfrustrated folding funnel. They have been widely used to analyze the folding transition and pathways of different proteins through computer simulations. Obviously, they need a reliable, experimentally determined folded structure to define the...

Material Characterization of Structures Using Genetic Algorithm Vibetarional Data