Desenhos de estruturas químicas correlacionam-se com propriedades biológicas: MIA-QSAR

Cormanich, Rodrigo A.; Nunes, Cleiton Antônio; Freitas, Matheus P.

doi:10.1590/s0100-40422012000600017

Cited by 8 publications

(2 citation statements)

References 12 publications

(17 reference statements)

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“…After selecting the best methodology, we studied other properties for the 40 selected molecules, such as ionization potential, electron affinity, electronic transitions, molecular volume and area. Properties such as dipole, volume and area are useful descriptors to relate the molecular structure and activity . Volume was calculated through a method in which a probe the same size as the solvent molecule (in this case water) is used to build a mesh around the molecule.…”

Section: Methodsmentioning

confidence: 99%

Quantum‐chemistry descriptors for photosensitizers based on macrocycles

et al. 2017

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Studies on the synthesis, structure, spectroscopy and photodynamics of macrocycles such as porphyrin, phthalocyanine, and chlorin have increased in importance in the last decades. This interest is mainly due to their catalytic, spectrophotometric, magnetic, and electrochemical properties, which enable these compounds to be employed in many different applications. [1][2][3][4][5][6] In combination with experimental approaches, theoretical studies based on quantum mechanics are useful for the comprehension of electronic structure and environmental effects. [2,[7][8][9][10][11][12][13][14][15][16][17][18] There are two main methodologies that aim to increase the efficiency for energy transfer appliances: complexation with different metallic ions and the addition of (a) polar/(un)charged substituents. Both methodologies are able to avoid the aggregation and/or enhance the substrate interaction while maintaining or even improving photochemical properties.[2,7-9,19-33]One of the first ab initio studies for porphyrins [34] was performed through the MO-LCGO-SCF method, described by Roothaan. [35][36][37] Since then, the number of ab initio studies for these macrocycles has grown significantly, particularly concerning the calculations based on density functional theory (DFT), due to its good relation and cost/accuracy ratio. [2,8,9,[17][18][19][20][21][22][23]25,26,28,29,31,[38][39][40][41][42][43][44][45][46][47] DFT studies of most porphyrins and phthalocyanines have employed B3LYP functio nal; [2,8,9,25,28,[38][39][40]48] nevertheless, other functionals such as BLYP, [8,29,49] VWN-B-P, [26] and BHandHLYP [8] have also been used. T. E. Shubina and T. Clark [25] performed a methodological study for porphyrins complexed to Fe(III) and Co(II), which indicated that B3LYP and OLYP functionals are excellent choices for studying these macrocycles. Time-dependent Hartree-Fock, [26,38,[41][42][43] ZINDO/S, [38,42] configuration interaction, [41,42] and CASSCF/CASPT2Phthalocyanines, porphyrins, and chlorins have been widely studied as photosensitizers. Both experimental and computational strategies are employed in order to propose new and more active molecules derived from those macrocycles. In this context, there are two main strategies used: (i) the addition of different substituents and (ii) the complexation of the macrocycle with different metallic ions. In this work, we present selected descriptors based on quantum chemistry calculations for forty macrocycles, including some approved drugs. We have found that density functional theory is a suitable methodology to study the large sets of molecules when applying the B3LYP/LanL2DZ methodology for geometry optimization and TD-OLYP/6-31G(d) for absorption spectrum. The inclusion of solvent effects by means of continuum model is important in order to obtain the accurate electronic data. We have verified that by bonding charged or polar substituents to the macrocycle, it is possible to enhance water solvation as well as to improve spectroscopic properties because molecular orbital...

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Section: Methodsmentioning

confidence: 99%

Quantum‐chemistry descriptors for photosensitizers based on macrocycles

et al. 2017

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“…Nas últimas duas décadas, foram publicados artigos de revisão sobre QSAR/QSPR, 14,15 artigos abordando metodologias de QSAR/ QSPR, [16][17][18][19][20] e de suas aplicações, [21][22][23][24] além de revisões sobre modelagem molecular [25][26][27][28] em língua portuguesa. Contudo, não existe até o presente momento nenhum artigo científico que apresente a quimioinformática ao público acadêmico e científico em português.…”

Section: E Posteriormente Journal Of Chemical Information and Computerunclassified

Quimioinformática: Uma Introdução

Alves¹,

Braga²,

Muratov³

et al. 2017

Quim. Nova

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publicado na web em 08/11/2017 CHEMINFORMATICS: AN INTRODUCTION. Cheminformatics is an interdisciplinary field between chemistry and informatics, which has evolved considerably since its inception in the 1960s. Initially, the cheminformatics community dealt primarily with practical and technical aspects of chemical structure representation, manipulation, and processing, while modern research explores a new role: the exploration and interpretation of large chemical databases and the discovery of new compounds with desired activity and safety profiles. Despite the recent release of several hallmark reviews addressing methods and application of cheminformatics written in Portuguese, so far there are no scientific articles presenting cheminformatics research to the Brazilian scientific community yet. To address this gap, we aim to introduce the field of cheminformatics to both students and researchers in a simple and didactic way by narrating important historical facts and contextualizing information within the scope of various applications.Keywords: cheminformatics; QSAR; chemical similarity; structure representation, property prediction; virtual screening. INTRODUÇÃOA quimioinformática é uma ciência interdisciplinar que utiliza recursos das ciências da computação e informação para resolver problemas da química.1 O termo quimioinformática foi cunhado por Frank Brown em 1998, definindo-a como "mistura de recursos de informação para transformar dados em informação e informação em conhecimento, no intuito de tomar decisões melhores e mais rápidas na área de identificação e otimização de compostos líderes".2 Em uma definição mais abrangente, em 1999, Greg Paris, então pesquisador da companhia farmacêutica Novartis, definiu a quimioinformática como "um termo genérico que engloba a concepção, criação, organização, gestão, recuperação, análise, disseminação, visualização e utilização de informação química". Sciences (1975Sciences ( -2005, chegando no nome atual em 2005 (http://pubs.acs.org/toc/jcisd8/current). Nesse intervalo, várias áreas que hoje compõem a quimioinformática foram se consolidando como (i) representação, visualização, manipulação e processamento de estruturas químicas, (ii) organização de bases de dados de estruturas químicas e (iii) estudos das relações quantitativas entre estrutura e atividade/propriedade (QSAR/QSPR, do inglês, quantitative structure-activity/property relationships). 5O campo da quimioinformática evoluiu bastante, passando de aspectos práticos e técnicas de representação, manipulação e processamento de estruturas químicas individuais até o seu papel primordial na atualidade: exploração de bases de dados químicas e descoberta de novos compostos com atividade e/ou propriedade desejadas. Ao se explorar bases de dados é possível extrair várias informações que auxiliam na compreensão do comportamento de determinado grupo de compostos e é possível gerar modelos computacionais que são utilizados para predizer a atividade de moléculas que carecem de dados experimentais, ou seja, dados de ensai...

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