Development and prospects of predicting drug polymorphs technology / 药学学报

Most chemical medicines have polymorphs. The difference of medicine polymorphs in physicochemical properties directly affects the stability, efficacy, and safety of solid medicine products. Polymorphs is incomparably important to pharmaceutical chemistry, manufacturing, and control. Meantime polymorphs is a key factor for the quality of high-end drug and formulations. Polymorph prediction technology can effectively guide screening of trial experiments, and reduce the risk of missing stable crystal form in the traditional experiment. Polymorph prediction technology was firstly based on theoretical calculations such as quantum mechanics and computational chemistry, and then was developed by the key technology of machine learning using the artificial intelligence. Nowadays, the popular trend is to combine the advantages of theoretical calculation and machine learning to jointly predict crystal structure. Recently, predicting medicine polymorphs has still been a challenging problem. It is expected to learn from and integrate existing technologies to predict medicine polymorphs more accurately and efficiently.

Deep learning in drug design and discovery / 药学学报

Among various technologies used in drug design and discovery, deep learning is still in its infancy. Recently, deep learning approaches have been rapidly developed and applied to address various problems in drug discovery, including generation of virtual compound library, prediction of compound activity, metabolism and toxicity, and prediction of organic synthesis routes. Compared with the traditional machine learning methods, the prediction power of deep learning did not show significant improvement. However, proactively learning and automatically feature extraction bring advantages for deep learning approaches. Compared to first principle-based computational chemistry methods, deep learning can not be generalized because it depends on large-scale and high-quality annotated data sets. But its molecular representation with single-atom atomic environment vectors could be useful for computational chemists. As an emerging technology, deep learning, especially the unsupervised learning method that does not rely on large datasets with labels, is gradually improving. It is expected that someday deep learning method will become practical for drug discovery.

Theoretically nanoscale study on ionization of muscimol nano drug in aqueous solution

In the present work, acid dissociation constant (pKa) values of muscimol derivatives were calculated using the Density Functional Theory (DFT) method. In this regard, free energy values of neutral, protonated and deprotonated species of muscimol were calculated in water at the B3LYP/6-31G(d) basis sets. The hydrogen bond formation of all species had been analyzed using the Tomasi's method. It was revealed that the theoretically calculated pKa values were in a good agreement with the existing experimental pKa values, which were determined from capillary electrophoresis, potentiometric titration and UV-visible spectrophotometric measurements.

No presente trabalho, calculou-se a constante de dissociação do ácido (pKa) dos derivados de muscimol, utilizando-se o método da teoria do funcional de densidade (DFT). Com esse objetivo, calcularam-se os valores das espécies neutra, protonada e desprotonada do muscimol em água em base B3LYP/6-31G(d). A formação da ligação de hidrogênio de todas as espécies foi analisada utilizando o método de Tomasi. Demonstrou-se que os valores de pKa calculados teoricamente estavam em boa concordância com os valores experimentais disponíveis, determinados por eletroforese capilar, titulação potenciométrica e medidas por espectrofotometria UV-visível.

Application of computational chemistry in determination of absolute configuration of natural products / 国际药学研究杂志

The presentation of chemical and biological properties of natural products is directly related to its absolute configuration. To have a comprehensive understanding of natural products, it is important to determine the absolute configuration of natural products. The traditional methods for the determination of absolute configuration are limited in some cases. With the development in computational technology and quantum chemistry theory, the spectroscopic properties of natural products, such as optical rotatory dispersion(ORD), circular dichroism(CD) and nuclear magnetic resonance(NMR) , can be calculated with accuracy. The combination of theoretical and experimental spectroscopy provides a new insight for determining the absolute configuration. Recently, computational chemistry has become a powerful tool, and in this review we presents its application in the determination of absolute configuration of natural products, which provides a guideline for readers in choosing an appropriate method when facing a particular case.

Theoretical indications on the relationship between pyrogallol[4]arenes dynamics of assembling and geometry / Indicios teóricos entre la relación dinámica de ensamblaje y geometría de pirogalol[4]arenos / Indícios teóricos sobre a relação entre dinâmica de montagem e geometria de pirogalol[4]arenos

Los pirogalol[4]arenos son macrociclos con gran potencial como bloques de construcción de nanocápsulas. Los dímeros precursores del 2,8,14,20-tetrametilpirogalol[4]areno y del 2,8,14,20-tetrafenilpirogalol[4]areno se estudiaron teóricamente para obtener entendimiento acerca de la dinámica de ensamble de estos compuestos. Las curvas de energía potencial a lo largo del ángulo de torsión del enlace R-pirogalol)CH-(R-pirogalol) de los dímeros han sido calculadas al nivel de teoría B3LYP/6-311G(d,p). Se encontró que las barreras de energía para rotación libre en torno al enlace seleccionado son 0.00133 Hartrees para el dímero con sustituyentes alquílicos y 0.77879 Hartrees para aquél con sustituyentes arílicos. Estos valores implican que la rotación libre en torno al enlace seleccionado es permitida para el primer dímero pero es prohibida para el segundo. Puesto que las orientaciones del sustituyente y el anillo de pirogalol en torno a este enlace posiblemente determinan la geometría de la estructura final, parece razonable proponer que el pirogalol[4]areno con sustituyentes alquílicos más probablemente adoptará una geometría de corona, mientras que el pirogalol[4]areno con sustituyentes arílicos mas probablemente adoptará una geometría de silla. Estas previsiones están en acuerdo con evidencia experimental la cual demuestra que la geometría de los pirogalol[4]arenos es dependiente del tipo de sustituyentes presentes en ellos.

O pyrogalol [4]arenes são macrocycles com grande potencial como blocos de construção da nanocapsules. Os dímeros precursores de 2,8,14,20-tetrametilpirogalol[4]arene e 2,8,14,20-tetrafenilpirogalol[4]arene foram estudados teoricamente para obter uma compreensão sobre a dinâmica do monte destes compostos. As curvas de energia potencial ao longo do ângulo de torção da link R-pkogdol)CH-(R-pirogalol) dos dímeros foram calculados ao nível da teoria B3LYP/ 6-311G(d,p). Verificou que as barreiras de energia da rotação livre em torno do link selecionado é 0,00133 Hartrees para ao dímero com substituintes alquil e 0,77879 Hartrees para que com substituintes aril. Esses valores implicam que a livre rotação em torno da link seleccionado é permitido para o primeiro dímero mas é proibida para o segundo. Uma vez que a orientação dos substituintes e o anel de pyrogalol em torno deste link possivelmente determinar a geometria da estrutura final, parece razoável sugerir que o pyrogalol[4]arene com substituintes alquil mais provavelmente vai ter uma geometria da copa, enquanto o pyrogalol[4]arene com substituintes resíduo mais provavelmente irá ter uma geometría de cadeira. Estas previsões estão de acordo com evidências experimentais que demonstram que a geometria do pyrogalol[4]arenes é dependente do tipo de substituintes presentes nos mesmos.

Pyrogallol[4]arenes are macrocycles with high potential as building blocks for nanocapsules. We theoretically studied the dimeric precursors of 2,8,14,20-tetramethylpyrogaUol[4]arene and 2,8,10,14-tetraphenylpyrogallol[4] arene to understand the dynamics of assembly of these compounds, and calculated the potential energy curves along the torsion angle of the (R-pyrogallol)CH-(R-pyrogallol) dimeric bond at the B3LYP/6-311G(d,p) level of theory. We found that the energy barriers for free rotation around the selected bond are 0.00133 Hartrees for the alkyl-substituted dimer and 0.77879 Hartrees for the aryl-substituted dimer. These values imply that the free rotation around the selected bond exists for the first dimer but not for the second one. Because the orientation of the substituent and the pyrogallol ring around this bond are likely to determine the geometry of the final structure, we propose that the alkyl-substituted compound will most likely adopt a crown-shaped geometry whereas the aryl-substituted compound will adopt a chair-shaped geometry. These predictions concur with experimental evidence, which shows that the geometry of pyrogallol[4]arenes depends on the substituents attached to them.