Empirical Scoring Functions for Affinity Prediction of Protein-ligand Complexes.

The ability to rapidly assess the quality of a protein-ligand complex in terms of its affinity is of fundamental importance for various methods of computer-aided drug design. While simple filtering or matching critieria may be sufficient in fast docking methods or at early stages of virtual screening, estimates of the actual free energy of binding are needed whenever refined docking solutions, ligand rankings or support for the optimization of hit compounds are required. If rigorous free energy calculations based on molecular simulations are impractical, such affinity estimates are provided by scoring functions.

PathOpt--a global transition state search approach: outline of algorithm.

We propose a new algorithm to determine reaction paths and test its capability for Ar12 and Ar13 clusters. Its main ingredient is a search for the local minima on a (n-1) dimensional hyperplane (n = dimension of the complete system in Cartesian coordinates) lying perpendicular to the straight line connection between initial and final states. These minima are part of possible reaction paths and are, hence, used as starting points for an uphill search to the next transition state.