Finding new potential acetylcholine esterase Inhibitors in SDFiles using CWM Lead Finder and PASS (Prediction of Activity Spectra for Substances)

Chemical WorkflowManager ( CWM) provides the non computer specialist a graphical user interface (GUI) to execute predefined chemistry related workflows. We provide several such predefined (and supported) workflowsas products such as CWM Lead Finderand CWMStructure Comparer. CWMproducts are ready to use ‘one-click’ workflows. CWMis not a toolbox such as most of other workflowshells. Our vision is to incorporate free scientific software (such as CDK [1], Weka [2] and others) in ready to use and supported products usable by non computer specialists using a common user interface. In the poster we present CWM Lead Finder. CWM Lead Finderreads a (in most cases rather small) SDFile containing structures with known biological activity and reads a (normally rather large) SDFile with structures of unknown activity. During execution of the workflow, the PASS (Prediction of Activity Spectra of Substances) program [3] is used to calculate prediction coefficients for around 3000 biological activities for both the structures with known and unknown' activity. These numbers are the difference between the percentage of prediction of being active (Pa) and being inactive (Pi). Using a cutoff factor the user can create a ‘biological profile’ (biological effects predicted with high probability for structures with known activity) that is further used in the workflow. Using this activity list the prediction coefficients are calculated for both the structures with known and unknown activity and afterwards are clustered. Structures from the SDFile with unknown activity that end up in clusters that contain structures with known activity have a high probability to show the same biological effects, thus are potential candidates for testing against this activity. This application answers the question: ”Which compounds are active?” The workflowgoes one step further, and helps to present the most interesting compounds. The workflowselects compounds from clusters that have the same biological profile as the ‘known’ compounds, and calculates the chemical fingerprints. We use the CDK 2 for calculating the chemical fingerprints. The fingerprints are again clustered: some clusters are a mixture of compounds of known and unknown activity, some contain only ‘known’ compounds, and other only ‘unknowns’. The most interesting clusters to look at are the ones that contain exclusively structures with unknown activity, since those structures are divers to the structures of known activity but have a high probability to show the same activity. The aim of CWM Lead Finderis to allow users that are not computer specialists or do not have in-depth know-how about prediction software to easily test their compounds for biological activity. Chemical WorkflowManager products are always predefined workflowsthat are (in the easiest case) ‘one-click’ workflows. For advanced users the CWMuser interface also allows to define new workflows, respectively modifying existing workflows. Chemical WorkflowManager is based on the new Microsoft WorkflowFoundation (WF) [4]. WF is part of .Net and therefore available for free. It provides a framework for developing workflowcentric solutions. Workflowsexecuted in Chemical WorkflowManager are tightly integrated in Microsoft SQL Server, thus allowing to run workflowsfrom the database (i.e. eliminates the problem of local files). All relevant information about the executed workflowis stored in the SQL Server database allowing easy generation of reports about how the results got obtained.