Advances in 2D fingerprint similarity searching

Similarity searching is one of the premier approaches for computational hit identification. Fingerprints are bit string representations of molecular structure and properties and rather simplistic search tools. Nevertheless, they are widely used and often surprisingly successful in drug discovery applications.

Herein we discuss recent research efforts that have helped to better understand fingerprint search performance, design new fingerprints and search strategies, or modify standard fingerprints for specific applications. Key publications of the past ∼ 20 years are covered and major emphasis is put on reviewing fingerprint studies published during the past 5 years.

The reader is provided with an overview of the state-of-the-art fingerprint design and search strategies developed. It will be possible to rationalize opportunities and limitations of 2D fingerprint similarity searching. Take home messages: Fingerprint search calculations are more complex than it might appear at first glance and susceptible to complications that are often overlooked in practical applications. Fingerprint search performance typically only depends on relatively small subsets of bit positions. Recently, different fingerprint engineering strategies have been applied to 'tune' existing fingerprints in a compound class-directed manner. Fingerprints have substantial scaffold hopping potential, despite the simplicity of their design.