A New Version of DADAS (Distance Analysis in Dihedral Angle Space) and Its Performance

Abstract

Among the computational algorithms to determine solution structures of proteins, the minimization of a variable target function in the dihedral angle space with the first derivative has been widely applied with its success at generating unbiased structures. The program called DADAS (Distance Analysis in Dihedral Angle Space, sometimes called DISMAN) has been extended to include additional tools, besides the rapid first derivative calculation and the variable target function: a rapid second derivative calculation, effective Metropolis Monte Carlo sampling and simulated annealing based on the Monte Carlo simulation. The new version of DADAS, called DADAS90, has some advantages, as compared with the older one, of flexibility to design new hybrid algorithms consisting of the mentioned tools and the possibility to manipulate the target function minimization from short range to long range information. The performance of each of the tools and their combination has been tested with respect to the convergence to the exact structure with the use of simulated data sets of distance constraints. The points on how to apply the program to an actual system with a limited amount of NMR data on distance and angle constraints have been also studied.