Abstract
BackgroundDrug discovery and chemical biology are exceedingly complex and demanding enterprises. In recent years there are been increasing awareness about the importance of predicting/optimizing the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of small chemical compounds along the search process rather than at the final stages. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses) and as such, compound collections' property profiling can be performed in silico. Clearly, these rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making.ResultsThis paper presents FAF-Drugs2, a free adaptable tool for ADMET filtering of electronic compound collections. FAF-Drugs2 is a command line utility program (e.g., written in Python) based on the open source chemistry toolkit OpenBabel, which performs various physicochemical calculations, identifies key functional groups, some toxic and unstable molecules/functional groups. In addition to filtered collections, FAF-Drugs2 can provide, via Gnuplot, several distribution diagrams of major physicochemical properties of the screened compound libraries.ConclusionWe have developed FAF-Drugs2 to facilitate compound collection preparation, prior to (or after) experimental screening or virtual screening computations. Users can select to apply various filtering thresholds and add rules as needed for a given project. As it stands, FAF-Drugs2 implements numerous filtering rules (23 physicochemical rules and 204 substructure searching rules) that can be easily tuned.
Highlights
Drug discovery and chemical biology are exceedingly complex and demanding enterprises
A compound collection may be prepared for a chemical biology project or for drug discovery, and in these cases, one may need molecules with a more "lead-like" or "druglike" profile [3,4,5]
Different experimental assays have been developed over the years to try to assess/predict ADMET properties, but in silico computations can be carried out to rapidly analyze a compound collection or prior to synthesis
Summary
Drug discovery and chemical biology are exceedingly complex and demanding enterprises. Fast methods for evaluating ADMET properties of small molecules often involve applying a set of simple empirical rules (educated guesses) and as such, compound collections' property profiling can be performed in silico These rules cannot assess the full complexity of the human body but can provide valuable information and assist decision-making. Different experimental assays have been developed over the years to try to assess/predict ADMET properties, but in silico computations can be carried out to rapidly analyze a compound collection or prior to synthesis. These calculations provide valuable information that can be further investigated experimentally [6]
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