In silico drug target identification, which includes
many distinct algorithms for finding disease genes
and proteins, is the first step in the drug discovery
pipeline. When the 3D structures of the targets are
available, the problem of target identification is
usually converted to finding the best interaction
mode between the potential target candidates and
small molecule probes. Pharmacophore, which is
the spatial arrangement of features essential for a
molecule to interact with a specific target receptor,
is an alternative method for achieving this goal apart
from molecular docking method. PharmMapper
server is a freely accessed web server designed to
identify potential target candidates for the given
small molecules (drugs, natural products or other
newly discovered compounds with unidentified
binding targets) using pharmacophore mapping
approach. PharmMapper hosts a large, in-house
repertoire of pharmacophore database (namely
PharmTargetDB) annotated from all the targets information
in TargetBank, BindingDB, DrugBank and
potential drug target database, including over 7000
receptor-based pharmacophore models (covering
over 1500 drug targets information). PharmMapper
automatically finds the best mapping poses of the
query molecule against all the pharmacophore
models in PharmTargetDB and lists the top N
best-fitted hits with appropriate target annotations,
as well as respective molecule’s aligned poses are
presented. Benefited from the highly efficient and
robust triangle hashing mapping method,
PharmMapper bears high throughput ability and
only costs 1 h averagely to screen the whole
PharmTargetDB. The protocol was successful in
finding the proper targets among the top 300
pharmacophore candidates in the retrospective
benchmarking test of tamoxifen. PharmMapper is
available at