A modular, highly configurable framework for easy workflow automation and data analysis
The Advantages of Workflow Automation
Real world research seldom involves a single question being answered by means of a single operation, and the fields of molecular modeling and cheminformatics are no exception. While researchers can create custom scripts to automate common procedures, this solution is less than ideal when projects demand rapid workflow prototyping, interactive data analysis, and robust, appropriately validated models. By no coincidence, these are exactly the conditions for which Schrödinger KNIME Extensions are best suited — together with the open-source KNIME interface, Schrödinger KNIME Extensions are designed to provide a powerful means for researchers to easily develop, validate, and deploy multi-step computational workflows.
KNIME has established itself as the leading open-source data pipelining tool, and provides an ideal platform for researchers looking for a way to combine best-of-breed technologies from commercial software, academic programs, and in-house code. Independent of the Schrödinger Extensions, KNIME already incorporates over 100 processing nodes for data manipulation and mining, including the complete set of analysis models from the well-known Weka data-mining environment. Additionally, it includes plug-ins that run R-scripts, giving users access to a vast library of statistical routines. Visualization of results is made possible by means of KNIME nodes that support interactive use of scatter plots, parallel coordinates, and more.
The Schrödinger nodes build upon the existing KNIME infrastructure, nearly doubling the number of available nodes, and provide access to a wealth of ligand- and structure-based tools from the Schrödinger Suite. Glide, Prime, Phase, MacroModel, Jaguar, and other programs and utilities have Schrödinger nodes that enable core functionality; please see the Features table to the right for examples.
Complex workflows can be constructed to bring molecules through a series of different programs that compute energetic and structural properties, which can then easily be combined to build models and improve the accuracy of predictions. Additionally, Schrödinger KNIME Extensions are distributed with a number of pre-configured workflows that enable a variety of sophisticated experiments. KNIME’s open architecture allows custom nodes and data types to be developed and integrated into KNIME with a very moderate amount of effort, thus enabling the incorporation of in-house applications and third-party software. KNIME’s extensible nature, combined with its easy-to-use interface and the power of Schrödinger software, make Schrödinger KNIME Extensions a powerful platform for workflow automation, model building, and data analysis.
Follow the links below to find additional resources related to KNIME:
Molecular fingerprint calculation, similarity/diversity analysis, clustering, and more using Canvas
Structure-based drug design:
High accuracy docking and scoring using Glide, as well as tools for relative binding energy predictions
Fragment-based drug design:
Fragment build-up and ligand fragmentation
Protein structure prediction:
Including rapid hydrogen-bond network optimization
Ligand structure preparation:
1D- or 2D-to-3D conversion with LigPrep, ionization and tautomeric state prediction with Epik, and more
Rapid conformational searches and general modeling tasks with MacroModel
Quantum mechanics calculations with Jaguar
ADME property prediction:
Extremely rapid prediction of over 30 ADME properties using QikProp
Data manipulation and visualization, with ongoing development to implement additional nodes in response to user feedback
Citations and Acknowledgements
Schrödinger Release 2017-1: Schrödinger KNIME Extensions, Schrödinger, LLC, New York, NY, 2017.