Literature DB >> 29070411

Chemical Space: Big Data Challenge for Molecular Diversity.

Mahendra Awale1, Ricardo Visini1, Daniel Probst1, Josep Arús-Pous1, Jean-Louis Reymond2.   

Abstract

Chemical space describes all possible molecules as well as multi-dimensional conceptual spaces representing the structural diversity of these molecules. Part of this chemical space is available in public databases ranging from thousands to billions of compounds. Exploiting these databases for drug discovery represents a typical big data problem limited by computational power, data storage and data access capacity. Here we review recent developments of our laboratory, including progress in the chemical universe databases (GDB) and the fragment subset FDB-17, tools for ligand-based virtual screening by nearest neighbor searches, such as our multi-fingerprint browser for the ZINC database to select purchasable screening compounds, and their application to discover potent and selective inhibitors for calcium channel TRPV6 and Aurora A kinase, the polypharmacology browser (PPB) for predicting off-target effects, and finally interactive 3D-chemical space visualization using our online tools WebDrugCS and WebMolCS. All resources described in this paper are available for public use at www.gdb.unibe.ch.

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Year:  2017        PMID: 29070411     DOI: 10.2533/chimia.2017.661

Source DB:  PubMed          Journal:  Chimia (Aarau)        ISSN: 0009-4293            Impact factor:   1.509


  9 in total

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2.  Limitations of machine learning models when predicting compounds with completely new chemistries: possible improvements applied to the discovery of new non-fullerene acceptors.

Authors:  Zhi-Wen Zhao; Marcos Del Cueto; Alessandro Troisi
Journal:  Digit Discov       Date:  2022-03-25

Review 3.  Synthetic Biology and Computer-Based Frameworks for Antimicrobial Peptide Discovery.

Authors:  Marcelo D T Torres; Jicong Cao; Octavio L Franco; Timothy K Lu; Cesar de la Fuente-Nunez
Journal:  ACS Nano       Date:  2021-02-04       Impact factor: 15.881

Review 4.  Natural Products for Drug Discovery in the 21st Century: Innovations for Novel Drug Discovery.

Authors:  Nicholas Ekow Thomford; Dimakatso Alice Senthebane; Arielle Rowe; Daniella Munro; Palesa Seele; Alfred Maroyi; Kevin Dzobo
Journal:  Int J Mol Sci       Date:  2018-05-25       Impact factor: 5.923

5.  Visualization of very large high-dimensional data sets as minimum spanning trees.

Authors:  Daniel Probst; Jean-Louis Reymond
Journal:  J Cheminform       Date:  2020-02-12       Impact factor: 5.514

6.  A visual approach for analysis and inference of molecular activity spaces.

Authors:  Samina Kausar; Andre O Falcao
Journal:  J Cheminform       Date:  2019-10-22       Impact factor: 5.514

Review 7.  Resources and computational strategies to advance small molecule SARS-CoV-2 discovery: lessons from the pandemic and preparing for future health crises.

Authors:  Natesh Singh; Bruno O Villoutreix
Journal:  Comput Struct Biotechnol J       Date:  2021-04-26       Impact factor: 7.271

8.  Exploring and mapping chemical space with molecular assembly trees.

Authors:  Yu Liu; Cole Mathis; Michał Dariusz Bajczyk; Stuart M Marshall; Liam Wilbraham; Leroy Cronin
Journal:  Sci Adv       Date:  2021-09-24       Impact factor: 14.136

Review 9.  Antimicrobial Susceptibility Testing of Antimicrobial Peptides to Better Predict Efficacy.

Authors:  Derry K Mercer; Marcelo D T Torres; Searle S Duay; Emma Lovie; Laura Simpson; Maren von Köckritz-Blickwede; Cesar de la Fuente-Nunez; Deborah A O'Neil; Alfredo M Angeles-Boza
Journal:  Front Cell Infect Microbiol       Date:  2020-07-07       Impact factor: 5.293

  9 in total

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