Literature DB >> 20425878

Rendering conventional molecular fingerprints for virtual screening independent of molecular complexity and size effects.

Britta Nisius1, Jürgen Bajorath.   

Abstract

Molecular complexity and size effects represent a known complication of fingerprint similarity searching and virtual screening that often leads to an increase in false-positive rates and a decrease in hit rates. In standard fingerprints, differences in the complexity of reference and database molecules lead to different fingerprint bit densities, which negatively affects similarity search calculations, in particular, when fingerprints of reference molecules have higher bit density than corresponding fingerprints of database compounds. In pharmaceutical research, this is the case in many practical virtual screening applications when chemically optimized reference molecules are used. Herein we introduce an intuitive computational method to make standard fingerprints such as structural keys or pharmacophore feature fingerprints independent of molecular complexity and size effects. This is achieved by applying the concept of 'balanced codes' originating in computer science. Following this approach, binary fingerprints are transformed by incorporating the complement of their bit patterns. This straightforward transformation produces fingerprint representations with characteristic bit patterns that have exactly half of their bit positions set on, corresponding to a constant bit density of 50 % for all test compounds, regardless of their complexity and size. In similarity search calculations in the presence of complexity effects of increasing magnitude, transformed structural key and pharmacophore fingerprints display consistently better performance than their unmodified counterparts and recover active compounds in cases where the original fingerprints fail.

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Year:  2010        PMID: 20425878     DOI: 10.1002/cmdc.201000089

Source DB:  PubMed          Journal:  ChemMedChem        ISSN: 1860-7179            Impact factor:   3.466


  1 in total

1.  VAE-Sim: A Novel Molecular Similarity Measure Based on a Variational Autoencoder.

Authors:  Soumitra Samanta; Steve O'Hagan; Neil Swainston; Timothy J Roberts; Douglas B Kell
Journal:  Molecules       Date:  2020-07-29       Impact factor: 4.411

  1 in total

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