Literature DB >> 11300855

Chemography: the art of navigating in chemical space.

T I Oprea1, J Gottfries.   

Abstract

Combinatorial chemistry needs focused molecular diversity applied to the druglike chemical space (drugspace). A drugspace map can be obtained by systematically applying the same conventions when examining the chemical space, in a manner similar to the Mercator convention in geography: Rules are equivalent to dimensions (e.g., longitude and latitude), while structures are equivalent to objects (e.g., cities and countries). Selected rules include size, lipophilicity, polarizability, charge, flexibility, rigidity, and hydrogen bond capacity. For these, extreme values were set, e.g., maximum molecular weight 1500, calculated negative logarithm of the octanol/water partition between -10 and 20, and up to 30 nonterminal rotatable bonds. Only S, N, O, P, and halogens were considered as elements besides C and H. Selected objects include a set of "satellite" structures and a set of representative drugs ("core" structures). Satellites, intentionally placed outside drugspace, have extreme values in one or several of the desired properties, while containing druglike chemical fragments. ChemGPS (chemical global positioning system) is a tool that combines these predefined rules and objects to provide a global drugspace map. The ChemGPS drugspace map coordinates are t-scores extracted via principal component analysis (PCA) from 72 descriptors that evaluate the above-mentioned rules on a total set of 423 satellite and core structures. Global ChemGPS scores describe well the latent structures extracted with PCA for a set of 8599 monocarboxylates, a set of 45 heteroaromatic compounds, and for 87 alpha-amino acids. ChemGPS positions novel structures in drugspace via PCA-score prediction, providing a unique mapping device for the druglike chemical space. ChemGPS scores are comparable across a large number of chemicals and do not change as new structures are predicted, making this tool a well-suited reference system for comparing multiple libraries and for keeping track of previously explored regions of the chemical space.

Entities:  

Year:  2001        PMID: 11300855     DOI: 10.1021/cc0000388

Source DB:  PubMed          Journal:  J Comb Chem        ISSN: 1520-4766


  61 in total

1.  Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.

Authors:  Iwona E Weidlich; Yuri Pevzner; Benjamin T Miller; Igor V Filippov; H Lee Woodcock; Bernard R Brooks
Journal:  J Comput Chem       Date:  2014-11-03       Impact factor: 3.376

2.  Discriminant and quantitative PLS analysis of competitive CYP2C9 inhibitors versus non-inhibitors using alignment independent GRIND descriptors.

Authors:  Lovisa Afzelius; Collen M Masimirembwa; Anders Karlén; Tommy B Andersson; Ismael Zamora
Journal:  J Comput Aided Mol Des       Date:  2002-07       Impact factor: 3.686

3.  Design of chemical space networks using a Tanimoto similarity variant based upon maximum common substructures.

Authors:  Bijun Zhang; Martin Vogt; Gerald M Maggiora; Jürgen Bajorath
Journal:  J Comput Aided Mol Des       Date:  2015-09-29       Impact factor: 3.686

4.  Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds.

Authors:  Pavel Sidorov; Helena Gaspar; Gilles Marcou; Alexandre Varnek; Dragos Horvath
Journal:  J Comput Aided Mol Des       Date:  2015-11-12       Impact factor: 3.686

5.  An automated PLS search for biologically relevant QSAR descriptors.

Authors:  Marius Olah; Cristian Bologa; Tudor I Oprea
Journal:  J Comput Aided Mol Des       Date:  2004 Jul-Sep       Impact factor: 3.686

6.  ChemMine. A compound mining database for chemical genomics.

Authors:  Thomas Girke; Li-Chang Cheng; Natasha Raikhel
Journal:  Plant Physiol       Date:  2005-06       Impact factor: 8.340

7.  Megavariate analysis of environmental QSAR data. Part I--a basic framework founded on principal component analysis (PCA), partial least squares (PLS), and statistical molecular design (SMD).

Authors:  Lennart Eriksson; Patrik L Andersson; Erik Johansson; Mats Tysklind
Journal:  Mol Divers       Date:  2006-06-13       Impact factor: 2.943

Review 8.  A cheminformatic toolkit for mining biomedical knowledge.

Authors:  Gus R Rosania; Gordon Crippen; Peter Woolf; David States; Kerby Shedden
Journal:  Pharm Res       Date:  2007-03-24       Impact factor: 4.200

9.  Atypical cytostatic mechanism of N-1-sulfonylcytosine derivatives determined by in vitro screening and computational analysis.

Authors:  Fran Supek; Marijeta Kralj; Marko Marjanović; Lidija Suman; Tomislav Smuc; Irena Krizmanić; Biserka Zinić
Journal:  Invest New Drugs       Date:  2007-09-27       Impact factor: 3.850

10.  Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment.

Authors:  Alexandre Beautrait; Vincent Leroux; Matthieu Chavent; Léo Ghemtio; Marie-Dominique Devignes; Malika Smaïl-Tabbone; Wensheng Cai; Xuegang Shao; Gilles Moreau; Peter Bladon; Jianhua Yao; Bernard Maigret
Journal:  J Mol Model       Date:  2008-01-03       Impact factor: 1.810

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.