Water-driven chemoselective reaction of squarate derivatives with amino acids and peptides

Here, we report a new class of highly chemoselective reactions between squarate derivatives and the amino acid cysteine or unprotected peptides with a N-terminus cysteine that proceed most efficiently in entirely aqueous solution at neutral pH. Kinetic and structural studies reveal that the presence of hydrogen bonding in water is primarily responsible for both the high yield and fast rate of the reaction.     

Studies on 2-acetylthiophene-2-furoylhydrazone complexes of 3d-bivalent metal ions

Summary Metal(II) complexes of 2-acetylthiophene-2-furoylhydrazone (HL) of the types [VO(HL)SO₄], [Cu(HL)₂Cl₂(H₂O)], [M(HL)₂Cl₂] [M=Co^II, Ni^II, or Zn^II] and [ML₂(H₂O)₂] [M=Co^II, Ni^II, Cu^II or Zn^II] have been prepared and characterized on the basis of elemental analyses, molar conductance, magnetic susceptibility, visible, e.s.r. and i.r. spectral studies. The bonding and stereochemistry of the complexes are discussed.     

Cu-catalyzed one-pot multicomponent approach for the synthesis of symmetric and asymmetric 1,4-dihydropyridine (1,4-DHP) linked 1,2,3-triazole derivatives

Abstract

Synthesis of various symmetric and asymmetric 1,4-DHP linked 1,2,3-triazole derivatives from economical and readily available starting materials via a convenient methodology in a single-pot method using CuSO₄·5H₂O as an efficient catalyst has been reported. The reaction proceeded efficiently under the optimized reaction conditions with excellent functional group compatibility providing the desired products in good yields. The method appears to be an efficient combinatorial strategy for the synthesis of new 1,4-DHP linked triazole derivatives.     

Nitrogen-doped carbon aerogel synthesis by solvothermal gelation for supercapacitor application

Journal of Solid State Electrochemistry - Nitrogen-doped mesoporous carbon aerogel having high surface area and high nitrogen content was synthesized by sol–gel method for supercapacitor...     

Identification of novel S-adenosyl-L-homocysteine hydrolase inhibitors through homology-model-based virtual screening, synthesis, and biological evaluation

The present study describes a successful application of computational approaches to identify novel Leishmania donovani (Ld) AdoHcyase inhibitors utilizing the differences for Ld AdoHcyase NAD(+) binding between human and Ld parasite. The development and validation of the three-dimensional (3D) structures of Ld AdoHcyase using the L. major AdoHcyase as template has been carried out. At the same time, cloning of the Ld AdoHcyase gene from clinical strains, its overexpression and purification have been performed. Further, the model was used in combined docking and molecular dynamics studies to validate the binding site of NAD in Ld. The hierarchical structure based virtual screening followed by the synthesis of five active hits and enzyme inhibition assay has resulted in the identification of novel Ld AdoHcyase inhibitors. The most potent inhibitor, compound 5, may serve as a "lead" for developing more potent Ld AdoHcy hydrolase inhibitors as potential antileishmanial agents.     

Robust and Semi‐Interpenetrating Hydrogels from Poly(ethylene glycol) and Collagen for Elastomeric Tissue Scaffolds

Here we present an injectable PEG/collagen hydrogel system with robust networks for use as elastomeric tissue scaffolds. Covalently crosslinked PEG and physically crosslinked collagen form semi‐interpenetrating networks. The mechanical strength of the hydrogels depends predominantely on the PEG concentration but the incorporation of collagen into the PEG network enhances hydrogel viscoelasticity, elongation, and also cell adhesion properties. Experimental data show that this hydrogel system exhibits tunable mechanical properties that can be further developed. The hydrogels allow cell adhesion and proliferation in vitro. The results support the prospect of a robust and semi‐interpenetrating biomaterial for elastomeric tissue scaffolds applications.

     

SAR monitoring of evolving compound data sets using activity landscapes

In pharmaceutical research, collections of active compounds directed against specific therapeutic targets usually evolve over time. Small molecule discovery is an iterative process. New compounds are discovered, alternative compound series explored, some series discontinued, and others prioritized. The design of new compounds usually takes into consideration prior chemical and structure-activity relationship (SAR) knowledge. Hence, historically grown compound collections represent a viable source of chemical and SAR information that might be utilized to retrospectively analyze roadblocks in compound optimization and further guide discovery projects. However, SAR analysis of large and heterogeneous sets of active compounds is also principally complicated. We have subjected evolving compound data sets to SAR monitoring using activity landscape models in order to evaluate how composition and SAR characteristics might change over time. Chemotype and potency distributions in evolving data sets directed against different therapeutic targets were analyzed and alternative activity landscape representations generated at different points in time to monitor the progression of global and local SAR features. Our results show that the evolving data sets studied here have predominantly grown around seed clusters of active compounds that often emerged early on, while other SAR islands remained largely unexplored. Moreover, increasing scaffold diversity in evolving data sets did not necessarily yield new SAR patterns, indicating a rather significant influence of "me-too-ism" (i.e., introducing new chemotypes that are similar to already known ones) on the composition and SAR information content of the data sets.