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Molecular similarity and diversity in chemoinformatics: From theory to applications

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Abstract

This review is dedicated to a survey on molecular similarity and diversity. Key findings reported in recent investigations are selectively highlighted and summarized. Even if this overview is mainly centered in chemoinformatics, applications in other areas (pharmaceutical and medical chemistry, combinatorial chemistry, chemical databases management, etc.) are also introduced. The approaches used to define and descript the concepts of molecular similarity and diversity in the context of chemoinformatics are discussed in the first part of this review. We introduce, in the second and third parts, the descriptions and analyses of different methods and techniques. Finally, current applications and problems are enumerated and discussed in the last part.

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Abbreviations

AAB:

Advanced Algorithm Builder

ADMET:

absorption, distribution, metabolism, excretion and toxicity

ANN:

Artificial Neural Networks

BCUT:

Burden CAS University of Texas (topological descriptors)

CART:

Classification And Regression Tree

CAS:

Chemical Abstract Service (American Chemical Society)

CLIP program:

Candidate Ligand Identification Program

CODESSA:

COmprehensive DEscriptors for Structural and Statistical Analysis

CoMFA:

Comparative Molecular Field Analysis

CoMSIA:

Comparative Molecular Similarity Indices Analysis

CPU:

Central Processor Unit

CSA:

Cluster Significance Analysis

CSS:

Common SubStructure

DARC:

Description, Acquisition, Restitution, Computer-aided design

DF:

Density Function

DISSIM:

Statistical module to calculate the DISSIMilarity index

DMC:

Dynamic Mapping of Consensus positions

DNA:

Desoxirribo Nucleic Acid

DRAGON:

Software for the calculation of molecular descriptors

FREL:

Fragments Reduced to an Environment that is Limited

FM:

Fragmental Methods

FO:

Focus

GETAWAY:

GEometry; Topology and Atom-Weights AssemblY

GMLC:

Gaussian Maximum Likelihood Classification

GTM:

Generative Topographic Mapping

HIV:

Human Immunodeficiency Virus

HTS:

High Throughput Screening

HTSS:

Hierarchic Tree Substructure Search Systems

HOMO-LUMO:

Highest Occupied Molecular Orbital – Lowest Unoccupied Molecular Orbital

IR:

InfraRed

IUPAC:

International Union of Pure and Applied Chemistry

KNN:

K-Nearest Neighbors

LaSSI:

Latent Semantic Structure Indexing

LDA:

Linear Discriminant Analysis

MACCS:

Substructure search system from CambridgeSoft Corporation

MaP:

Mapping Property distributions of molecular surfaces

MDDR:

MDL Drug Data Report

MEP:

Molecular electrostatic Potential

MCSS:

Maximal Common Sub-Structure

MQS:

Molecular Quantum Similarity

NMC:

Nearest Mean Classifier

PCA:

Principal Component Analysis

Pm:

molecular Property characteristic

QQSPR or Q2SPR:

Quantum Quantitative Structure-Property Relationship

QSAR:

Quantitative Structure-Activity Relationship

QSPR:

Quantitative Structure-Property Relationship

QSCD:

Quantized Surface Complementarity Diversity

RDF:

Radial Distribution Function

RMS:

Root Mean Square

S4:

Substructure search software (Beilstein Institute of Organic Chemistry & Softron Ltd)

SIMCA:

Soft Independent Modeling of Class Analogy

SMILES:

Simplified Molecular Input Line Entry Specification

SVM:

Support Vector Machines

ToPD:

Total Pharmacophore Diversity

UV:

UltraViolet

WLN:

Wiswesser Line Notation

WHIM:

Weighted Holistic Invariant Molecular

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  1. ITODYS, Université Paris 7 – Denis Diderot, CNRS UMR-7086, 1 rue Guy de la Brosse, 75005, Paris, France

    Ana G. Maldonado, J. P. Doucet, Michel Petitjean & Bo-Tao Fan

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Maldonado, A.G., Doucet, J.P., Petitjean, M. et al. Molecular similarity and diversity in chemoinformatics: From theory to applications. Mol Divers 10, 39–79 (2006). https://doi.org/10.1007/s11030-006-8697-1

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