Literature DB >> 26558489

An overview of molecular fingerprint similarity search in virtual screening.

Ingo Muegge1, Prasenjit Mukherjee1.   

Abstract

INTRODUCTION: A central premise of medicinal chemistry is that structurally similar molecules exhibit similar biological activities. Molecular fingerprints encode properties of small molecules and assess their similarities computationally through bit string comparisons. Based on the similarity to a biologically active template, molecular fingerprint methods allow for identifying additional compounds with a higher chance of displaying similar biological activities against the same target - a process commonly referred to as virtual screening (VS). AREAS COVERED: This article focuses on fingerprint similarity searches in the context of compound selection for enhancing hit sets, comparing compound decks, and VS. In addition, the authors discuss the application of fingerprints in predictive modeling. EXPERT OPINION: Fingerprint similarity search methods are especially useful in VS if only a few unrelated ligands are known for a given target and therefore more complex and information rich methods such as pharmacophore searches or structure-based design are not applicable. In addition, fingerprint methods are used in characterizing properties of compound collections such as chemical diversity, density in chemical space, and content of biologically active molecules (biodiversity). Such assessments are important for deciding what compounds to experimentally screen, to purchase, or to assemble in a virtual compound deck for in silico screening or de novo design.

Keywords:  Compound acquisition; hit expansion; pharmacophore fingerprint; predictive modeling; scaffold hopping

Mesh:

Substances:

Year:  2015        PMID: 26558489     DOI: 10.1517/17460441.2016.1117070

Source DB:  PubMed          Journal:  Expert Opin Drug Discov        ISSN: 1746-0441            Impact factor:   6.098


  35 in total

1.  Quantum probability ranking principle for ligand-based virtual screening.

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2.  The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

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Journal:  Brief Bioinform       Date:  2017-07-01       Impact factor: 11.622

3.  Computer-aided drug design at Boehringer Ingelheim.

Authors:  Ingo Muegge; Andreas Bergner; Jan M Kriegl
Journal:  J Comput Aided Mol Des       Date:  2016-09-20       Impact factor: 3.686

4.  Enabling the hypothesis-driven prioritization of ligand candidates in big databases: Screenlamp and its application to GPCR inhibitor discovery for invasive species control.

Authors:  Sebastian Raschka; Anne M Scott; Nan Liu; Santosh Gunturu; Mar Huertas; Weiming Li; Leslie A Kuhn
Journal:  J Comput Aided Mol Des       Date:  2018-01-30       Impact factor: 3.686

5.  Relational graph convolutional networks for predicting blood-brain barrier penetration of drug molecules.

Authors:  Yan Ding; Xiaoqian Jiang; Yejin Kim
Journal:  Bioinformatics       Date:  2022-05-13       Impact factor: 6.931

6.  Machine learning-based chemical binding similarity using evolutionary relationships of target genes.

Authors:  Keunwan Park; Young-Joon Ko; Prasannavenkatesh Durai; Cheol-Ho Pan
Journal:  Nucleic Acids Res       Date:  2019-11-18       Impact factor: 16.971

Review 7.  Systems protobiology: origin of life in lipid catalytic networks.

Authors:  Doron Lancet; Raphael Zidovetzki; Omer Markovitch
Journal:  J R Soc Interface       Date:  2018-07       Impact factor: 4.118

8.  iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets.

Authors:  Zhen Chen; Xuhan Liu; Pei Zhao; Chen Li; Yanan Wang; Fuyi Li; Tatsuya Akutsu; Chris Bain; Robin B Gasser; Junzhou Li; Zuoren Yang; Xin Gao; Lukasz Kurgan; Jiangning Song
Journal:  Nucleic Acids Res       Date:  2022-05-07       Impact factor: 19.160

9.  Comparing structural fingerprints using a literature-based similarity benchmark.

Authors:  Noel M O'Boyle; Roger A Sayle
Journal:  J Cheminform       Date:  2016-07-05       Impact factor: 5.514

10.  Virtual Screening against Phosphoglycerate Kinase 1 in Quest of Novel Apoptosis Inhibitors.

Authors:  Jie Xia; Bo Feng; Qianhang Shao; Yuhe Yuan; Xiang Simon Wang; Naihong Chen; Song Wu
Journal:  Molecules       Date:  2017-06-21       Impact factor: 4.411

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