Literature DB >> 10361729

Pharmacophore fingerprinting. 1. Application to QSAR and focused library design.

M J McGregor1, S M Muskal.   

Abstract

A new method of rapid pharmacophore fingerprinting (PharmPrint method) has been developed. A basis set of 10,549 three-point pharmacophores has been constructed by enumerating several distance ranges and pharmacophoric features. Software has been developed to assign pharmacophoric types to atoms in chemical structures, generate multiple conformations, and construct the binary fingerprint according to the pharmacophores that result. The fingerprint is used as a descriptor for developing a quantitative structure-activity relationship (QSAR) model using partial least squares. An example is given using sets of ligands for the estrogen receptor (ER). The result is compared with previously published results on the same data to show the superiority of a full 3D, conformationally flexible approach. The QSAR model can be readily interpreted in structural/chemical terms. Further examples are given using binary activity data and some of our novel in-house compounds, which show the value of the model when crossing compound classes.

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Year:  1999        PMID: 10361729     DOI: 10.1021/ci980159j

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  14 in total

1.  Descriptors you can count on? Normalized and filtered pharmacophore descriptors for virtual screening.

Authors:  Andrew C Good; Sung-Jin Cho; Jonathan S Mason
Journal:  J Comput Aided Mol Des       Date:  2004 Jul-Sep       Impact factor: 3.686

Review 2.  Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling.

Authors:  Linlin Zhao; Heather L Ciallella; Lauren M Aleksunes; Hao Zhu
Journal:  Drug Discov Today       Date:  2020-07-11       Impact factor: 7.851

Review 3.  Big Data and Artificial Intelligence Modeling for Drug Discovery.

Authors:  Hao Zhu
Journal:  Annu Rev Pharmacol Toxicol       Date:  2019-09-13       Impact factor: 13.820

4.  BiasNet: A Model to Predict Ligand Bias Toward GPCR Signaling.

Authors:  Jason E Sanchez; Govinda B Kc; Julian Franco; William J Allen; Jesus David Garcia; Suman Sirimulla
Journal:  J Chem Inf Model       Date:  2021-08-16       Impact factor: 6.162

5.  Are 2D fingerprints still valuable for drug discovery?

Authors:  Kaifu Gao; Duc Duy Nguyen; Vishnu Sresht; Alan M Mathiowetz; Meihua Tu; Guo-Wei Wei
Journal:  Phys Chem Chem Phys       Date:  2020-04-29       Impact factor: 3.676

Review 6.  Applications of artificial intelligence to drug design and discovery in the big data era: a comprehensive review.

Authors:  Neetu Tripathi; Manoj Kumar Goshisht; Sanat Kumar Sahu; Charu Arora
Journal:  Mol Divers       Date:  2021-06-10       Impact factor: 2.943

7.  Capturing nature's diversity.

Authors:  Mauro Pascolutti; Marc Campitelli; Bao Nguyen; Ngoc Pham; Alain-Dominique Gorse; Ronald J Quinn
Journal:  PLoS One       Date:  2015-04-22       Impact factor: 3.240

8.  Spectrophores as one-dimensional descriptors calculated from three-dimensional atomic properties: applications ranging from scaffold hopping to multi-target virtual screening.

Authors:  Rafaela Gladysz; Fabio Mendes Dos Santos; Wilfried Langenaeker; Gert Thijs; Koen Augustyns; Hans De Winter
Journal:  J Cheminform       Date:  2018-03-07       Impact factor: 5.514

9.  Implementation of multiple-instance learning in drug activity prediction.

Authors:  Gang Fu; Xiaofei Nan; Haining Liu; Ronak Y Patel; Pankaj R Daga; Yixin Chen; Dawn E Wilkins; Robert J Doerksen
Journal:  BMC Bioinformatics       Date:  2012-09-11       Impact factor: 3.169

10.  Exploring protein hotspots by optimized fragment pharmacophores.

Authors:  Dávid Bajusz; Warren S Wade; Grzegorz Satała; Andrzej J Bojarski; Janez Ilaš; Jessica Ebner; Florian Grebien; Henrietta Papp; Ferenc Jakab; Alice Douangamath; Daren Fearon; Frank von Delft; Marion Schuller; Ivan Ahel; Amanda Wakefield; Sándor Vajda; János Gerencsér; Péter Pallai; György M Keserű
Journal:  Nat Commun       Date:  2021-05-27       Impact factor: 14.919

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