OFF-TARGET PIPELINE is a platform intended to carry out a recently introduced chemical systems biology approach for secondary target identification, but may also be useful to other applications in bioinformatics and drug discovery. Researchers can predict and compare protein functional sites, conduct structure-based docking, compute binding energy and compare electrostatic potential distribution within cavities. It also supports normalization of docking scores, information retrieval from PDB, and parsing of output files. All the afore-mentioned procedures are parallelized with significant speed gains and labor savings.

OFF-TARGET PIPELINE platform comprises:

  • SMAP, a recently introduced software for functional site detection and comparison. SMAP utilizes a novel shape descriptor, the geometric potential, that requires only the Ca atoms to represent the protein structure, thus making it both fast and suitable for use on models and low quality structures.
Due to the innate inability of SMAP to incorporate side-chain conformation into binding site comparison calculations, additional filtering steps are necessary to reduce the number of false positives. For this purpose OFF-TARGET PIPELINE provides a versatile frame, suitable for integration with:
  • docking programs (AutoDock 4, AutoDock Vina, and Surflex are currently available, but others can be added upon request)
  •  software for the evaluation of electrostatic properties of nanoscale biomolecular systems (currently APBS).

OFF-TARGET PIPELINE currently supports local execution mode and dividing of work load into individual threads running concurrently thus utilizing the CPU power to the maximum. It also supports massive submission of APBS jobs to the respective Opal-based Web-Server, in case no sufficient computer resources are available.


Evangelidis, T., Bourne, P.E., Xie, L., Xie, L.
(2012) Proceedings - 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2012  PP. 32 - 39 
doi: 10.1109/BIBMW.2012.6470348

Xie, L., Evangelidis, T., Xie, L., Bourne, P.E.
(2011) PLoS Computational Biology  7  (4)
doi: 10.1371/journal.pcbi.1002037

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