Asymmetric Synthesis of Triphenylmethanes via Organocatalytic Regio- and Enantioselective Friedel-Crafts Alkylation of Aniline Derivatives.

Herein, we described a highly regio- and enantioselective Friedel-Crafts alkylation of aniline derivatives with generated -quinone methides enabled by chiral phosphoric acid, furnishing a wide range of enantioenriched triarylmethanes bearing three similar benzene rings in high yields (up to 98%) with excellent stereoselectivities (up to 98% ee). Furthermore, the large-scale reactions and diversified transformations of product demonstrate the practicality of the protocol. Density functional theory calculations elucidate the origin of the enantioselectivity.

Enantioselective Peroxidation of -alkynyl imines enabled by chiral BINOL calcium phosphate.

Herein, we report a catalytic enantioselective addition of -alkynyl imines with hydroperoxides catalyzed by chiral BINOL calcium phosphate, affording a broad range of enantioenriched α-peroxy propargylamines in good yields (80-99%) with high enantioselectivities (up to 94% ee). The protocol is characterized by mild conditions, easy accessibility and good practicability.

Virtual Screening for Type II B Inhibitors of B-Raf Kinase.

Background: B-RafV600E kinase was identified as an important target in current cancer treatment, and the type II B inhibitors show good qualities in preclinical studies. Therefore, it is very important to discover novel II B inhibitors of B-RafV600E kinase.

Methods: In order to discover novel II B inhibitors of B-RafV600E kinase, virtual screening against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3DQSAR model and binding free energy (ΔGbind) calculation studies.

Virtual screening of B-Raf kinase inhibitors: A combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy calculation studies.

B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines.

An Investigation of Molecular Docking and Molecular Dynamic Simulation on Imidazopyridines as B-Raf Kinase Inhibitors.

In the recent cancer treatment, B-Raf kinase is one of key targets. Nowadays, a group of imidazopyridines as B-Raf kinase inhibitors have been reported. In order to investigate the interaction between this group of inhibitors and B-Raf kinase, molecular docking, molecular dynamic (MD) simulation and binding free energy (ΔGbind) calculation were performed in this work.

A Combined Pharmacophore Modeling, 3D QSAR and Virtual Screening Studies on Imidazopyridines as B-Raf Inhibitors.

B-Raf kinase is an important target in treatment of cancers. In order to design and find potent B-Raf inhibitors (BRIs), 3D pharmacophore models were created using the Genetic Algorithm with Linear Assignment of Hypermolecular Alignment of Database (GALAHAD). The best pharmacophore model obtained which was used in effective alignment of the data set contains two acceptor atoms, three donor atoms and three hydrophobes.

Correction: Xie, H.; et al. 3D QSAR studies, pharmacophore modeling and virtual screening on a series of steroidal aromatase inhibitors. Int. J. Mol. Sci. 2014, 15, 20927-20947.

A number of sentences in the first paragraph of the introduction of [28] were copied verbatim from [21,22,25,29]. Although [21,22,25] were cited in the text, [29] was omitted and it was not made sufficiently clear that direct quotations were used. The authors wish to apologize to the authors of [21,22,25,29] and to the readers of the journal for any inconvenience.

3D QSAR studies, pharmacophore modeling and virtual screening on a series of steroidal aromatase inhibitors.

Aromatase inhibitors are the most important targets in treatment of estrogen-dependent cancers. In order to search for potent steroidal aromatase inhibitors (SAIs) with lower side effects and overcome cellular resistance, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of SAIs to build 3D QSAR models. The reliable and predictive CoMFA and CoMSIA models were obtained with statistical results (CoMFA: q² = 0.