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PASS Overview

latest revision May 30, 2010

Pipeline Pilot PASS Component

 

PASS predicts with high accuracy (>80%)  up to 3750 biological activities for your compounds. As input you only need the 2D structure. Since it is trained against a huge number of activities it can be used for many different projects. This is one of the most successful programs giving you early indications if your compounds might be useful. This is a very easy tool for in silico screening

A typical example:

PASS was trained on a special set of compounds. There were 5000 compounds containing 200 hits. With PASS 50 structures were selected, 25 were hits. Assume one test is 1 dollar. If the distribution of the hits would be equal in the database of 5000, you need to spend 5000/200*25 = 625 dollars to find 25 hits. With PASS you would need 50 dollars. This is a saving of 625/50 = 1250%!

Why should you use PASS?

  • Analyze your dataset:
    • drug versus non-drug like (see reference Anzali et.al.)
    • cluster the dataset using the PASS parameters or the MNA descriptor keys
    • select compounds that belong to an activity class

All you require is the structure in the form of a MOL or SDFile. The prediction goes very fast. Calculation of biological activity spectra for 10,000 compounds on an ordinary IBM PC takes about 5 min. So you can do it for large data sets. 

The training set includes at the moment ca. 205'873 substances with more than 5462 biological effects. PASS predicts simultaneously the probabilities of presence (Pa)/absence (Pi). PASS Pro is open; therefore the user can add to the training set some new biologically active compounds and new activities. Mean accuracy of prediction in LOO cross-validation is ~95%.

 

PASS Metabolite
PharmaExpert

Go an read about applications of PASS in R&D.

 

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