Bioinformatics toolbox for exploring target mutation-induced drug resistance.

Drug resistance is increasingly among the main issues affecting human health and threatening agriculture and food security. In particular, developing approaches to overcome target mutation-induced drug resistance has long been an essential part of biological research. During the past decade, many bioinformatics tools have been developed to explore this type of drug resistance, and they have become popular for elucidating drug resistance mechanisms in a low cost, fast and effective way.

Structural and molecular dynamic studies of Pseudomonas aeruginosa OdaA reveal the regulation role of a C-terminal hinge element.

Background: Crotonase superfamily members exhibit great catalytic diversity towards various acyl-CoA substrates. A common CoA moiety binding pattern is usually observed in this family, understanding the substrate-binding mechanism would facilitate the rational engineering of crotonases for improved properties.

Methods: We applied X-ray crystallography to investigate a putative enoyl-CoA hydratase/isomerase OdaA in Pseudomonas aeruginosa.

Conformation Transition of Intracellular Part of Glucagon Receptor in Complex With Agonist Glucagon by Conventional and Accelerated Molecular Dynamics Simulations.

The inactive conformations of glucagon receptor (GCGR) are widely reported by crystal structures that support the precision structure for drug discovery of type 2 diabetes. The previous study shows that the intracellular part is open in the glucagon-bound GCGR (glu-GCGR) and closed in the apo-GCGR by accelerated molecular dynamics (aMD) simulations. However, the crystal structure of GCGR in complex with partial agonist shows that the intracellular part is closed in the inactive conformation.

Synthesis and biological evaluation of 2,4-disubstituted phthalazinones as Aurora kinase inhibitors.

A series of 2,4-disubstituted phthalazinones were synthesized and their biological activities, including antiproliferation, inhibition against Aurora kinases and cell cycle effects were evaluated. Among them, N-cyclohexyl-4-((4-(1-methyl-1H-pyrazol-4-yl)-1-oxophthalazin-2(1H)-yl) methyl) benzamide (12c) exhibited the most potent antiproliferation against five carcinoma cell lines (HeLa, A549, HepG2, LoVo and HCT116 cells) with IC values in range of 2.2-4.

Anti-inflammatory and analgesic effects of Bi-yuan-ling granules.

Bi-yuan-ling granule (BLG) is a traditional Chinese medicine compound composed mainly of baicalin and chlorogenic acid. It has been demonstrated to be clinically effective for various inflammatory diseases such as acute rhinitis, chronic rhinitis, atrophic rhinitis and allergic rhinitis. However, the underlying mechanisms of BLG against these diseases are not fully understood.

Synthesis, biological activities, and quantitative structure-activity relationship (QSAR) study of novel camptothecin analogues.

In continuation of our program aimed at the development of natural product-based pesticidal agents, three series of novel camptothecin derivatives were designed, synthesized, and evaluated for their biological activities against T. Cinnabarinus, B. brassicae, and B.

Synthesis and biological evaluation of 2,4-diaminopyrimidines as selective Aurora A kinase inhibitors.

The Aurora kinases are a family of serine/threonine kinases that interact with components of the mitotic apparatus and serve as potential therapeutic targets in oncology. Here we synthesized 15 2,4-diaminopyrimidines and evaluated their biological activities, including antiproliferation, inhibition against Aurora kinases and cell cycle effects. These compounds generally exhibited more potent cytotoxicity against tumor cell lines compared with the VX-680 control, especially compound 11c, which showed the highest cytotoxicities, with IC50 values of 0.

QSPR prediction of GC retention indices for nitrogen-containing polycyclic aromatic compounds from heuristically computed molecular descriptors.

Gas chromatographic retention indices of nitrogen-containing polycyclic aromatic compounds (N-PACs) have been predicted by quantitative structure-property relationship (QSPR) analysis based on heuristic method (HM) implemented in CODESSA. In order to indicate the influence of different molecular descriptors on retention indices and well understand the important structural factors affecting the experimental values, three multivariable linear models derived from three groups of different molecular descriptors were built. Moreover, each molecular descriptor in these models was discussed to well understand the relationship between molecular structures and their retention indices.