| PackageDescription | Computer Aided Drug Discovery (CADD) Pipeline
This package is part of the mgltools set of Python libraries which
provide an infrastructure for the analysis of protein structures and
their docking of chemical compounds.
.
The Computer Aided Drug Discovery (CADD) Pipeline is a workflow
environment designed to support molecular dyanmics simulations
and virtual screening experiments for in silico drug discovery,
with a special focus on supporting the use of the Relaxed
Complex Scheme. It includes web based access to applications
such as NAMD, AutoDock, PDB2PQR, APBS, MGLToos and couples them
in a flexible and scalable fashion through cloud computing.
It is developed as a standalone application, using Vision
(https://www.nbcr.net/pub/wiki/index.php?title=MGLTools#Vision) as
the backend engine for visual programming and workflow execution.
The scientific applications are made accessible through CADD using
Opal Web services (https://www.nbcr.net/pub/wiki/index.php?title=Opal)
for scalable and distributed computation.
.
The workflow components of the CADD pipeline are currently released
as Vision networks packaged for specific processes in a modular
fashion. These modules may be coupled at ease for more complex
processes. In the future, they may also be accessible from workflow
repositories such as MyExperiment.org, and from AutoDockTools. The Opal
services used in the CADD workflow may be accessed using programmatic
access, the Opal Server Dashboard or other workflow clients such as
Kepler, VisTrails or Taverna through Opal plugins available at Opal
Sourceforge website (http://opal.nbcr.net).
.
Features
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* Automatic launching of NAMD simulation on TeraGrid and NBCR resources,
including experimental support for migration of simulation between
resources.
* Selection of representative snapshots/conformations from MD simulations
using clustering tools such as QR factorization from VMD and Ptraj from
Amber.
* Support of Virtual Screening using AutoDock, AutoDock Vina
* Support of Relaxed Complex Scheme based Virtual Screening and Rescoring
* Visualization and analysis of Virtual Screening hits |