Similarity search profiles as a diagnostic tool for the analysis of virtual screening calculations

An analysis method termed similarity search profiling has been developed to evaluate fingerprint-based virtual screening calculations. The analysis is based on systematic similarity search calculations using multiple template compounds over the entire value range of a similarity coefficient. In graphical representations, numbers of correctly identified hits and other detected database compounds are separately monitored. The resulting profiles make it possible to determine whether a virtual screening trial can in principle succeed for a given compound class, search tool, similarity metric, and selection criterion. As a test case, we have analyzed virtual screening calculations using a recently designed fingerprint on 23 different biological activity classes in a compound source database containing approximately 1.3 million molecules. Based on our predefined selection criteria, we found that virtual screening analysis was successful for 19 of 23 compound classes. Profile analysis also makes it possible to determine compound class-specific similarity threshold values for similarity searching.     

REPROVIS-DB: a benchmark system for ligand-based virtual screening derived from reproducible prospective applications

Benchmark calculations are essential for the evaluation of virtual screening (VS) methods. Typically, classes of known active compounds taken from the medicinal chemistry literature are divided into reference molecules (search templates) and potential hits that are added to background databases assumed to consist of compounds not sharing this activity. Then VS calculations are carried out, and the recall of known active compounds is determined. However, conventional benchmarking is affected by a number of problems that reduce its value for method evaluation. In addition to often insufficient statistical validation and the lack of generally accepted evaluation standards, the artificial nature of typical benchmark settings is often criticized. Retrospective benchmark calculations generally overestimate the potential of VS methods and do not scale with their performance in prospective applications. In order to provide additional opportunities for benchmarking that more closely resemble practical VS conditions, we have designed a publicly available compound database (DB) of reproducible virtual screens (REPROVIS-DB) that organizes information from successful ligand-based VS applications including reference compounds, screening databases, compound selection criteria, and experimentally confirmed hits. Using the currently available 25 hand-selected compound data sets, one can attempt to reproduce successful virtual screens with other than the originally applied methods and assess their potential for practical applications.