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PASS specifications


Unique identifier OMICS_18393
Alternative name Prediction of Activity Spectra for Substances
Software type Package/Module
Interface Graphical user interface
Restrictions to use License purchase required
Input data A 2D structural formula of chemical compound.
Input format MOL, SD
Output data Some pharmacotherapeutic effects, biochemical mechanisms, toxicity, metabolism, gene regulation expression, transporter-related activities.
Operating system Mac OS, Windows
Computer skills Medium
Version 11.4.12
Stability Stable
Maintained Yes


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  • person_outline Marc Nicklaus <>

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Publications for Prediction of Activity Spectra for Substances

PASS in publications

PMCID: 4189283
PMID: 25298685
DOI: 10.4103/0973-1296.139809

[…] states, tautomers, stereochemistries and ring conformations. the energy minimized compounds were subjected to biological activity prediction based on their structural orientation using pass (prediction of activity spectra for substances) tool.[], the pass prediction results also showed that these compounds have anti-pulmonary hypertension property. based on the results of in vitro, […]

PMCID: 2680638
PMID: 19468330
DOI: 10.3390/ijms10041628

[…] with the human organism has been elucidated through absorption, distribution, metabolism and excretion data derived by adme boxes [] and the human toxicological effects by toxboxes [] and by pass (prediction of activity spectra for substances) []., the epi suite has been applied as the primary tool for generating physico-chemical endpoints []. this software package includes a variety […]

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PASS institution(s)
Laboratory of Structure-Function Based Drug Design, V.N. Orekhovich Institute of Biomedical Chemistry of the Russian Academy of Medical Sciences, Moscow, Russia; Computer Chemistry Center and Institute for Organic Chemistry, University of Erlangen-Nurnberg, Erlangen, Germany; Laboratory of Medicinal Chemistry, Center for Cancer Research, National Cancer Institute, National Institutes of Health, NCI-Frederick, Frederick, MD, USA
PASS funding source(s)
Supported by the U.S. Civil Research and Development Foundation (Grant # RC1-2064).

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