Chemoinformatics as a Theoretical Chemistry Discipline

Abstract

Here, chemoinformatics is considered as a theoretical chemistry discipline complementary to quantum chemistry and force-field molecular modeling. These three fields are compared with respect to molecular representation, inference mechanisms, basic concepts and application areas. A chemical space, a fundamental concept of chemoinformatics, is considered with respect to complex relations between chemical objects (graphs or descriptor vectors). Statistical Learning Theory, one of the main mathematical approaches in structure-property modeling, is briefly reviewed. Links between chemoinformatics and its "sister" fields - machine learning, chemometrics and bioinformatics are discussed.

A renaissance of neural networks in drug discovery

“…94 Representation learning provided by deep multi-layer ANNs will play an increasingly important role in computational drug discovery. [97][98][99] However, the question of molecular descriptors used to capture the important properties of molecules is still a relatively poorly answered one. Despite the large number and variety of molecular descriptors, none can be guaranteed to have universal applicability and provide optimal solutions to all problems arising in drug discovery.…”

Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge

“…350 Da or less (39,40). Such new compound discovery and annotation efforts are big data challenges which represent the chemical sciences in the purest sense, and form the basis for the nascent fields of chemography (41) and cheminformatics (42,43). Figure 1C contains a histogram of the number of chemical abstracts indexed by the CAPlus system which is accessed through SciFinder.…”

Quimioinformática: Uma Introdução

“…Além disso, pode aumentar a eficiência do processo de pesquisa e desenvolvimento, pois diminui resíduos gerados, visto que compostos mais improváveis de terem sucesso são descartados antes de seguirem para ensaios experimentais. 43,135 Um fluxograma de aplicação da quimioinformática para o planejamento de moléculas de interesse encontra-se representado na Figura 4. Dados biológicos de compostos químicos provenientes de estudos experimentais (fase 0) estão sempre sendo publicados em artigos científicos e/ou depositados em repositórios de dados (fase 1).…”