Scoring functions for docking

In the fields of computational chemistry and molecular modelling, scoring functions are mathematical functions used to approximately predict the binding affinity between two molecules after they have been docked. Most commonly one of the molecules is a small organic compound such as a drug and the second is the drug's biological target such as a protein receptor. Scoring functions have also been developed to predict the strength of intermolecular interactions between two proteins or between protein and DNA. Scoring functions are widely used in drug discovery and other molecular modelling applications. These include: Virtual screening of small molecule databases of candidate ligands to identify novel small molecules that bind to a protein target of interest and therefore are useful starting points for drug discovery De novo design (design "from scratch") of novel small molecules that bind to a protein target Lead optimization of screening hits to optimize their affinity and selectivity A potentially more reliable but much more computationally demanding alternative to scoring functions are free energy perturbation calculations. Scoring functions are normally parameterized (or trained) against a data set consisting of experimentally determined binding affinities between molecular species similar to the species that one wishes to predict. For currently used methods aiming to predict affinities of ligands for proteins the following must first be known or predicted: Protein tertiary structure – arrangement of the protein atoms in three-dimensional space. Protein structures may be determined by experimental techniques such as X-ray crystallography or solution phase NMR methods or predicted by homology modelling. Ligand active conformation – three-dimensional shape of the ligand when bound to the protein Binding-mode – orientation of the two binding partners relative to each other in the complex The above information yields the three-dimensional structure of the complex.