Solvent viscosity dependence of the protein folding dynamics

Solvent viscosity has been frequently adopted as an adjustable parameter in various computational studies (e.g., protein folding simulations) with implicit solvent models. A common approach is to use low viscosities to expedite simulations. While using viscosities lower than that of aqueous is unphysical, such treatment is based on observations that the viscosity affects the kinetics (rates) in a well-defined manner as described by Kramers' theory. Here, we investigate the effect of viscosity on the detailed dynamics (mechanism) of protein folding. On the basis of a simple mathematical model, we first show that viscosity may indeed affect the dynamics in a complex way. By applying the model to the folding of a small protein, we demonstrate that the detailed dynamics is affected rather pronouncedly especially at unphysically low viscosities, cautioning against using such viscosities. In this regard, our model may also serve as a diagnostic tool for validating low-viscosity simulations. It is also suggested that the viscosity dependence can be further exploited to gain information about the protein folding mechanism.     

Resin-immobilized CuO and Cu nanocomposites for alcohol oxidation

Resin immobilized stable, spherical CuO nanoparticles prepared in the presence of cyclodextrin (CD) act as catalysts for liquid phase alcohol oxidation in air. The catalytic activity of the CuO nanocomposites and its green chemistry approach make it superior to the related resin-bound Cu(0) nanocomposite. The effect of alcohol chain length and electron-donating or -withdrawing groups influence product yield. The nanocomposites exhibit good reusability, simple workup procedure, and a straightforward approach to aldehyde formation.     

Dye Degradation and Sulfur Oxidation of Methyl Orange and Thiophenol via Newly Designed Nanocomposite GQDs/NiSe-NiO Photocatalyst Under Homemade LED Light

Photocatalytic processes triggered by graphene-based photocatalysts under solar light have sparked interest as a new sort of instrument for solar chemical synthesis. Herein we investigated self-assembled graphene quantum dots (GQDs)/NiSe-NiO composite photocatalyst for organic transformation as well as dye degradation. The synthesized GQDs/NiSe-NiO composite photocatalyst has an excellent suitable band gap, high molar extinction coefficient, low toxicity and chemical/thermal stability. The GQDs/NiSe-NiO composite photocatalyst emerges as a new standard for sulfur oxidation and dye degradation reactions under homemade LED light with high yield.     

Interaction of DNA bases with silver nanoparticles: assembly quantified through SPRS and SERS

Colloidal silver nanoparticles were prepared by reducing silver nitrate with sodium borohydride. The synthesized silver particles show an intense surface plasmon band in the visible region. The work reported here describes the interaction between nanoscale silver particles and various DNA bases (adenine, guanine, cytosine, and thymine), which are used as molecular linkers because of their biological significance. In colloidal solutions, the color of silver nanoparticles may range from red to purple to orange to blue, depending on the degree of aggregation as well as the orientation of the individual particles within the aggregates. Transmission electron microscopy (TEM), X-ray diffraction (XRD), and absorption spectroscopy were used to characterize the assemblies. DNA base-induced differential silver nanoparticle aggregation was quantified from the peak separation (relates to color) of surface plasmon resonance spectroscopy (SPRS) and the signal intensity of surface-enhanced Raman scattering (SERS), which rationalize the extent of silver-nucleobase interactions.     

Molecular graph convolutions: moving beyond fingerprints

Molecular “fingerprints” encoding structural information are the workhorse of cheminformatics and machine learning in drug discovery applications. However, fingerprint representations necessarily emphasize particular aspects of the molecular structure while ignoring others, rather than allowing the model to make data-driven decisions. We describe molecular graph convolutions, a machine learning architecture for learning from undirected graphs, specifically small molecules. Graph convolutions use a simple encoding of the molecular graph—atoms, bonds, distances, etc.—which allows the model to take greater advantage of information in the graph structure. Although graph convolutions do not outperform all fingerprint-based methods, they (along with other graph-based methods) represent a new paradigm in ligand-based virtual screening with exciting opportunities for future improvement.     

Radiometric Sterility Test for Radiopharmaceuticals

A radiometric system originally developed for testing of blood samples obtained from patients suffering from bacteraemia has been adapted for sterility testing of radiopharmaceuticals. Radiometric sterility tests on 202 batches of 19 different radio-pharmaceutical injections were performed and compared with the conventional sterility test method. This technique is more sensitive and rapid than the conventional method.

The radiometric method can be used for injectable radiopharmaceuticals of the radionuclides ³⁵S, ⁵¹Cr, ⁵⁷Co, ⁵⁸Co, ⁵⁹Fe, ⁸²Br, ⁸⁶Rb, ^99mTc, ^113mIn, ¹²³I and ¹⁶⁹Yb. The method is not applicable to iodine-131 labelled radiopharmaceuticals owing to the interference of volatile and radioactive xenon-131m. In the case of neohydrin-203Hg it is necessary to carry out the test after removal of the radioactive material by filtration through a microbe retaining filter.     

Essential oil composition of aerial parts of Cyclospermum leptophyllum (Pers.) Sprague ex Britton and P. Wilson

The essential oil of Cyclospermum leptophyllum (Pers.) Sprague ex Britton and P. Wilson syn. Apium leptophyllum (Pers.) F. Muell. Ex Benth., family Apiaceae (Umbellifereae), was analysed by GC and GC-MS. The essential oil showed the presence of thymohydroquinone dimethyl ether (50.7%), thymol methyl ether (11.2%), γ-terpinene (10.4%), p-cymene (9.5%) and carvacrol methyl ether (5.9%), along with trans-ocimene, β-pinene, germacrene D, cumin aldehyde, α-humulene, β-myrcene, sabinene, limonene, β-phellandrene, caryophyllene oxide, α-pinene and α-thujene as minor constituents. To the best of our knowledge, this is the first study of the essential oil composition of C. leptophyllum collected from India.     

Error bounds on the SCISSORS approximation method

The SCISSORS method for approximating chemical similarities has shown excellent empirical performance on a number of real-world chemical data sets but lacks theoretically proven bounds on its worst-case error performance. This paper first proves reductions showing SCISSORS to be equivalent to two previous kernel methods: kernel principal components analysis and the rank-k Nystro?m approximation of a Gram matrix. These reductions allow the use of generalization bounds on these techniques to show that the expected error in SCISSORS approximations of molecular similarity kernels is bounded in expected pairwise inner product error, in matrix 2-norm and Frobenius norm for full kernel matrix approximations and in root-mean-square deviation for approximated matrices. Finally, we show that the actual performance of SCISSORS is significantly better than these worst-case bounds, indicating that chemical space is well-structured for chemical sampling algorithms.     

Comparison of denitrification between Paracoccus sp. and Diaphorobacter sp

Denitrification was compared between Paracoccus sp. and Diaphorobacter sp. in this study, both of which were isolated from activated sludge of a denitrifying reactor. Denitrification of both isolates showed contrasting patterns, where Diaphorobacter sp. showed accumulation of nitrite in the medium while Paracoccus sp. showed no accumulation. The nitrate reduction rate was 1.5 times more than the nitrite reduction in Diaphorobacter sp., as analyzed by the resting state denitrification kinetics. Increasing the nitrate concentration in the medium increased the nitrite accumulation in Diaphorobacter sp., but not in Paracoccus sp., indicating a branched electron transfer during denitrification. Diaphorobacter sp. was unable to denitrify efficiently at high nitrate concentrations from 1 M, but Paracoccus sp. could denitrify even up to 2 M nitrate. Paracoccus sp. was found to be an efficient denitrifier with insignificant amounts of nitrite accumulation, and it could also denitrify high amounts of nitrate up to 2 M. Efficient denitrification without accumulation of intermediates like nitrite is desirable in the removal of high nitrates from wastewaters. Paracoccus sp. is shown to suffice this demand and could be a potential organism to remove high nitrates effectively.     

Acylation of Grignard reagents mediated by N-methylpyrrolidone: a remarkable selectivity for the synthesis of ketones

An efficient user-friendly method of acylation of Grignard reagents to selectively synthesize ketones is presented, which is assisted by simple amides such as NMP, or DMF. The present chemoselective method tolerates a variety of functional groups such as ketone, ester, nitrile and other functional groups.