Bulky, flexible molecules such as peptides and peptidomimetics are often used as lead
compounds during the drug discovery process. Pathophysiological events, eg, the formation …

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 …

The development and validation of a new knowledge-based scoring function (DrugScore) to
describe the binding geometry of ligands in proteins is presented. It discriminates efficiently …

Empirical scoring functions to calculate binding affinities of protein–ligand complexes have
been calibrated based on experimental structure and affinity data collected from public and …

Empirical scoring functions provide estimates of the free energy of protein− ligand binding in
situations when atomic-scale simulations are intractable, for example, in virtual high …

We have developed an iterative knowledge-based scoring function (ITScore) to describe
protein–ligand interactions. Here, we assess ITScore through extensive tests on native …

The development of a new knowledge-based scoring function (DrugScore) and its power to
recognize binding modes close to experiment, to predict binding affinities, and to identify 'hot …

Novel scoring functions that predict the affinity of a ligand for its receptor have been
developed. They were built with several statistical tools (partial least squares, genetic …

Scoring functions have been widely used to assess protein–ligand binding affinity in
structure-based drug discovery. However, currently commonly used scoring functions face …

A central problem in de novo drug design is determining the binding affinity of a ligand with
a receptor. A new scoring algorithm is presented that estimates the binding affinity of a …