A recently published PLOS Computational Biology article by the Torres lab has been the featured method article on the front page of the journal.
The article entitled “Large-Scale Chemical Similarity Networks for Target Profiling of Compounds Identified in Cell-Based Chemical Screens” highlights how the Torres lab, spearheaded by graduate student Yu-Chen (Ben) Lo, has developed CSNAP (Chemical Similarity Network Analysis Pulldown), a new computational target identification method that utilizes chemical similarity networks for large-scale chemotype recognition and drug target profiling.
The CSNAP method is freely available and can be accessed from the CSNAP web server.
Graduate student Yu-Chen (Ben) Lo (right) spearheaded the development of CSNAP.
“Determining the targets of compounds identified in cell-based high-throughput chemical screens is a critical step for downstream drug development and understanding of compound mechanism of action. However, current computational target prediction approaches like chemical similarity database searches are limited to single or sequential ligand analyses, which limits their ability to accurately deconvolve a large number of compounds that often have chemically diverse structures.” Prof. Torres said. “We have developed a new computational drug target prediction method, called CSNAP that is based on chemical similarity networks. By clustering diverse chemical structures into distinct sub-networks corresponding to chemotypes, we show that CSNAP improves target prediction accuracy and consistency over a board range of drug classes. We further coupled CSNAP to a mitotic database and successfully determined the major mitotic drug targets of a diverse compound set identified in a cell-based chemical screen. We demonstrate that CSNAP can easily integrate with diverse knowledge-based databases for on/off target prediction and post-target validation, thus broadening its applicability for identifying the targets of bioactive compounds from a wide range of chemical screens.”
The front page of PLOS Computational Biology can be viewed here.
VIsit the Torres Lab homepage here.