Molecular Fingerprint Recombination: Generating Hybrid Fingerprints for Similarity Searching from Different Fingerprint Types

Molecular fingerprints have a long history in computational medicinal chemistry and continue to be popular tools for similarity searching. Over the years, a variety of fingerprint types have been introduced. We report an approach to identify preferred bit subsets in fingerprints of different design and “recombine” these bit segments into “hybrid fingerprints”. These compound class‐directed fingerprint representations are found to increase the similarity search performance of their parental fingerprints, which can be rationalized by the often complementary nature of distinct fingerprint features.

[1]  Jürgen Bajorath,et al.  Development of a Fingerprint Reduction Approach for Bayesian Similarity Searching Based on Kullback-Leibler Divergence Analysis , 2009, J. Chem. Inf. Model..

[2]  Evgueni A. Haroutunian,et al.  Information Theory and Statistics , 2011, International Encyclopedia of Statistical Science.

[3]  Chris Williams,et al.  Reverse fingerprinting, similarity searching by group fusion and fingerprint bit importance , 2006, Molecular Diversity.

[4]  Jürgen Bajorath,et al.  Design and Evaluation of a Novel Class-Directed 2D Fingerprint to Search for Structurally Diverse Active Compounds , 2006, J. Chem. Inf. Model..

[5]  Andreas Bender,et al.  How Similar Are Similarity Searching Methods? A Principal Component Analysis of Molecular Descriptor Space , 2009, J. Chem. Inf. Model..

[6]  Pierre Acklin,et al.  Similarity Metrics for Ligands Reflecting the Similarity of the Target Proteins , 2003, J. Chem. Inf. Comput. Sci..

[7]  Jürgen Bajorath,et al.  Molecular similarity analysis in virtual screening: foundations, limitations and novel approaches. , 2007, Drug discovery today.

[8]  David Weininger,et al.  Stigmata: An Algorithm To Determine Structural Commonalities in Diverse Datasets , 1996, J. Chem. Inf. Comput. Sci..

[9]  Robert P. Sheridan,et al.  Chemical Similarity Using Geometric Atom Pair Descriptors , 1996, J. Chem. Inf. Comput. Sci..

[10]  Jérôme Hert,et al.  New Methods for Ligand-Based Virtual Screening: Use of Data Fusion and Machine Learning to Enhance the Effectiveness of Similarity Searching , 2006, J. Chem. Inf. Model..

[11]  Jérôme Hert,et al.  Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures , 2004, J. Chem. Inf. Model..

[12]  Jürgen Bajorath,et al.  Bit Silencing in Fingerprints Enables the Derivation of Compound Class-Directed Similarity Metrics , 2008, J. Chem. Inf. Model..

[13]  Eugen Lounkine,et al.  Improving the Search Performance of Extended Connectivity Fingerprints through Activity‐Oriented Feature Filtering and Application of a Bit‐Density‐Dependent Similarity Function , 2009, ChemMedChem.

[14]  Jürgen Bajorath,et al.  Design and Evaluation of a Molecular Fingerprint Involving the Transformation of Property Descriptor Values into a Binary Classification Scheme , 2003, J. Chem. Inf. Comput. Sci..

[15]  D. Rogers,et al.  Using Extended-Connectivity Fingerprints with Laplacian-Modified Bayesian Analysis in High-Throughput Screening Follow-Up , 2005, Journal of biomolecular screening.

[16]  P. Willett Searching techniques for databases of two- and three-dimensional chemical structures. , 2005, Journal of medicinal chemistry.

[17]  John M. Barnard,et al.  Chemical Fragment Generation and Clustering Software , 1997, J. Chem. Inf. Comput. Sci..

[18]  Hanna Geppert,et al.  Random Reduction in Fingerprint Bit Density Improves Compound Recall in Search Calculations Using Complex Reference Molecules , 2008, Chemical biology & drug design.

[19]  Jürgen Bajorath,et al.  Bayesian Similarity Searching in High-Dimensional Descriptor Spaces Combined with Kullback-Leibler Descriptor Divergence Analysis , 2008, J. Chem. Inf. Model..

[20]  P. Beroza,et al.  A rapid computational method for lead evolution: description and application to alpha(1)-adrenergic antagonists. , 2000, Journal of medicinal chemistry.

[21]  Jürgen Bajorath,et al.  Fingerprint Scaling Increases the Probability of Identifying Molecules with Similar Activity in Virtual Screening Calculations , 2001, J. Chem. Inf. Comput. Sci..

[22]  Daylight Theory Manual , 2011 .

[23]  John M. Barnard,et al.  Chemical Similarity Searching , 1998, J. Chem. Inf. Comput. Sci..

[24]  Andreas Bender,et al.  Similarity Searching of Chemical Databases Using Atom Environment Descriptors (MOLPRINT 2D): Evaluation of Performance , 2004, J. Chem. Inf. Model..

[25]  Eugen Lounkine,et al.  RelACCS‐FP: A Structural Minimalist Approach to Fingerprint Design , 2008, Chemical biology & drug design.

[26]  Brian K. Shoichet,et al.  ZINC - A Free Database of Commercially Available Compounds for Virtual Screening , 2005, J. Chem. Inf. Model..

[27]  Jürgen Bajorath,et al.  Introduction of an Information-Theoretic Method to Predict Recovery Rates of Active Compounds for Bayesian in Silico Screening: Theory and Screening Trials , 2007, J. Chem. Inf. Model..

[28]  Peter Willett,et al.  Similarity-based virtual screening using 2D fingerprints. , 2006, Drug discovery today.