Combining spatial and chemical information for clustering pharmacophores.

ABSTRACT:

Background

A pharmacophore model consists of a group of chemical features arranged in three-dimensional space that can be used to represent the biological activities of the described molecules. Clustering of molecular interactions of ligands on the basis of their pharmacophore similarity provides an approach for investigating how diverse ligands can bind to a specific receptor site or different receptor sites with similar or dissimilar binding affinities. However, efficient clustering of pharmacophore models in three-dimensional space is currently a challenge.

Results

We have developed a pharmacophore-assisted Iterative Closest Point (ICP) method that is able to group pharmacophores in a manner relevant to their biochemical properties, such as binding specificity etc. The im

SUBMITTER: Zhou L 

PROVIDER: S-EPMC4290656 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature