Applications of weighting and chirality strategies for distance geometry algorithms to an enterotoxin peptide analog

Significant improvements are made to a recent algorithm that finds molecular conformations using distance geometry on nuclear magnetic resonance data. Weighting factors for the nearest approximation of the distance matrix to a data matrix are allowed to vary between iterations of the algorithm. These changes are proportional to the error of the distance between atoms in the configuration and the nuclear magnetic resonance data bounds. The weight changes increase the rate of convergence by an order of magnitude. Penalty functions are proposed to ensure the correct chirality. Numerical results for these modifications and subsequent energy calculations using CHARMm are given for an analog of the heat stable (ST) enterotoxin peptide STh produced byE. coli in humans.