Catalytic hydrogenation is an important process used for the production of everything from foods to fuels. Current heterogeneous implementations of this process utilize metals as the active species. Until recently, catalytic heterogeneous hydrogenation over a metal-free solid was unknown; implementation of such a system would eliminate the health, environmental, and economic concerns associated with metal-based catalysts. Here, we report good hydrogenation rates and yields for a metal-free heterogeneous hydrogenation catalyst as well as its unique hydrogenation mechanism. Catalytic hydrogenation of olefins was achieved over defect-laden h- BN ( dh -BN) in a reactor designed to maximize the defects in h- BN sheets. Good yields (>90%) and turnover frequencies (6 × 10 –5 –4 × 10 –3 ) were obtained for the hydrogenation of propene, cyclohexene, 1,1-diphenylethene, ( E )- and ( Z )-1,2-diphenylethene, octadecene, and benzylideneacetophenone. Temperature-programmed desorption of ethene over processed h -BN indicates the formation of a highly defective structure. Solid-state NMR (SSNMR) measurements of dh -BN with high and low propene surface coverages show four different binding modes. The introduction of defects into h- BN creates regions of electronic deficiency and excess. Density functional theory calculations show that both the alkene and hydrogen-bond order are reduced over four specific defects: boron substitution for nitrogen (B N ), vacancies (V B and V N ), and Stone–Wales defects. SSNMR and binding-energy calculations show that V N are most likely the catalytically active sites. This work shows that catalytic sites can be introduced into a material previously thought to be catalytically inactive through the production of defects.
In this paper we review the current status of high-performance computing applications in the general area of drug discovery. We provide an introduction to the methodologies applied at atomic and molecular scales, followed by three specific examples of implementation of these tools. The first example describes in silico modeling of the adsorption of small molecules to organic and inorganic surfaces, which may be applied to drug delivery issues. The second example involves DNA translocation through nanopores with major significance to DNA sequencing efforts. The final example offers an overview of computer-aided drug design, with some illustrative examples of its usefulness.
Colchicine is a well-known compound with strong antiproliferative activity that has had limited use in chemotherapy because of its toxicity. In order to create more potent anticancer agents, a series of novel colchicine derivatives have been obtained by simultaneous modification at C7 (amides and sulfonamides) and at C10 (methylamino group) positions and characterized by spectroscopic methods. All the synthesized compounds have been tested in vitro to evaluate their cytotoxicity toward A549, MCF-7, LoVo, LoVo/DX and BALB/3T3 cell lines. Additionally, the activity of the studied compounds was investigated using computational methods involving molecular docking of the colchicine derivatives to β-tubulin. The majority of the obtained derivatives exhibited higher cytotoxicity than colchicine, doxorubicin or cisplatin against tested cancer cell lines. Furthermore, molecular modeling studies of the obtained compounds revealed their possible binding modes into the colchicine binding site of tubulin.
Biomining of valuable metals using a target specific approach promises increased purification yields and decreased cost. Target specificity can be implemented with proteins/peptides, the biological molecules, responsible from various structural and functional pathways in living organisms by virtue of their specific recognition abilities towards both organic and inorganic materials. Phage display libraries are used to identify peptide biomolecules capable of specifically recognizing and binding organic/inorganic materials of interest with high affinities. Using combinatorial approaches, these molecular recognition elements can be converted into smart hybrid biomaterials and harnessed for biotechnological applications. Herein, we used a commercially available phage-display library to identify peptides with specific binding affinity to molybdenite (MoS2) and used them to decorate magnetic NPs. These peptide-coupled NPs could capture MoS2 under a variety of environmental conditions. The same batch of NPs could be re-used multiple times to harvest MoS2, clearly suggesting that this hybrid material was robust and recyclable. The advantages of this smart hybrid biomaterial with respect to its MoS2-binding specificity, robust performance under environmentally challenging conditions and its recyclability suggests its potential application in harvesting MoS2 from tailing ponds and downstream mining processes.
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