FAF-Drugs3: a web server for compound property calculation and chemical library design

Abstract

Drug attrition late in preclinical or clinical development is a serious economic problem in the field of drug discovery. These problems can be linked, in part, to the quality of the compound collections used during the hit generation stage and to the selection of compounds undergoing optimization. Here, we present FAF-Drugs3, a web server that can be used for drug discovery and chemical biology projects to help in preparing compound libraries and to assist decision-making during the hit selection/lead optimization phase. Since it was first described in 2006, FAF-Drugs has been significantly modified. The tool now applies an enhanced structure curation procedure, can filter or analyze molecules with user-defined or eight predefined physicochemical filters as well as with several simple ADMET (absorption, distribution, metabolism, excretion and toxicity) rules. In addition, compounds can be filtered using an updated list of 154 hand-curated structural alerts while Pan Assay Interference compounds (PAINS) and other, generally unwanted groups are also investigated. FAF-Drugs3 offers access to user-friendly html result pages and the possibility to download all computed data. The server requires as input an SDF file of the compounds; it is open to all users and can be accessed without registration at http://fafdrugs3.mti.univ-paris-diderot.fr.

Figure 1.

FAF-Drugs3 flow chart. Users can upload a single molecule or a compound collection. The molecules are treated following the selected filter parameters and structural alerts. Several output files can be visualized and or downloaded such as the Accepted, Rejected and Intermediate SDF files and the file containing the PAINS compounds.

Figure 2.

FAF-Drugs3 alerts identified on oral drugs. Search for the presence of structural alerts and PAINS in 778 oral drugs (i.e. the oral drugs that had clear annotation in terms of therapeutic areas). Thirty percent of drugs (in green) do not show any structural alert; 7.8% of the alerts revealed a phenol group (in blue) and 7% of the drugs are flagged as PAINS (in orange).