Acetylcholinesterase Inhibitory Activity of Modified Lupane, Oleanane, and Ursane A-seco-Triterpenoids.

A series of new lupane, ursane, and oleanane type triterpenic A-seco-derivatives containing bromo-, azido-, alkyne-, 1H-tetrazol-5-yl-, 5-methyloxazol-2-yl-, N-(4-(4-methylpiperazin-1-yl)but-2-yn-1-yl), and a carbonyl group at C2, C24, C28, C30 positions has been synthesized. The bioactivity was evaluated by Ellman's method, and the results showed that most of the compounds displayed moderate acetylcholinesterase inhibitory activities in vitro. Among them, A-seco-derivatives of 28-oxo-allobetuline and betulinic acid with bromo- and azido-groups exhibited the most potent inhibitory activity against AChE. Extra experiments showed methyl 2-cyano-3,4-seco-dibromo- and 2-cyano-3,4-seco-diazido-derivatives of betulinic acid as mixed-type inhibitors, with Ki values as low as Ki =0.18 µM and Ki =0.21 µM, respectively.

Chiral Polymers from Norbornenes Based on Renewable Chemical Feedstocks.

Optically active polymers are of great interest as materials for dense enantioselective membranes, as well as chiral stationary phases for gas and liquid chromatography. Combining the versatility of norbornene chemistry and the advantages of chiral natural terpenes in one molecule will open up a facile route toward the synthesis of diverse optically active polymers. Herein, we prepared a set of new chiral monomers from cis-5-norbornene-2,3-dicarboxylic anhydride and chiral alcohols of various natures. Alcohols based on cyclic terpenes ((-)-menthol, (-)-borneol and pinanol), as well as commercially available alcohols (S-(-)-2-methylbutanol-1, S-(+)-3-octanol), were used. All the synthesized monomers were successfully involved in ring-opening metathesis polymerization, affording polymers in high yields (up to 96%) and with molecular weights in the range of 1.9 × 105-5.8 × 105 (Mw). The properties of the metathesis polymers obtained were studied by TGA and DSC analysis, WAXD, and circular dichroism spectroscopy. The polymers exhibited high thermal stability and good film-forming properties. Glass transition temperatures for the prepared polymers varied from -30 °C to +139 °C and, therefore, the state of the polymers changed from rubbery to glassy. The prepared polymers represent a new attractive platform of chiral polymeric materials for enantioselective membrane separation and chiral stationary phases for chromatography.

Gas-Transport and the Dielectric Properties of Metathesis Polymer from the Ester of exo-5-Norbornenecarboxylic Acid and 1,1'-Bi-2-naphthol.

Polymers from norbornenes are of interest for applications in opto- and microelectronic (low dielectric materials, photoresists, OLEDs). Norbornenes with ester motifs are among the most readily available norbornene derivatives. However, little is known about dielectric properties and the gas-transport of polynorbornenes from such monomers. Herein, we synthesized a new metathesis polymer from exo-5-norbornenecarboxylic acid and 1,1'-bi-2-naphthol. The designed monomer was obtained via a two-step procedure in a good yield. This norbornene derivative with a rigid and a bulky binaphthyl group was successfully polymerized over the 1st generation Grubbs catalyst, affording high-molecular-weight products (Mw ≤ 1.5·106) in yields of 94-98%. The polymer is amorphous and glassy (Tg = 161 °C), and it shows good thermal stability. Unlike most, polyNBi is a classic low-permeable glassy polymer. The selectivity of polyNBi was higher than that of polyNB. Being less permeable than polyNB, polyNBi unexpectedly showed a lower value of dielectric permittivity (2.7 for polyNBi vs. 5.0 for polyNB). Therefore, the molecular design of polynorbornenes has great potential to obtain polymers with desired properties in a wide range of required characteristics. Further tuning of the gas separation efficiency can be achieved by attaching an appropriate substituent to the ester and aryl group.

Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough.

The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. The approach combines signal processing and noise removal methods with an ensemble of fine-tuned deep learning networks and enables COVID detection on coughs. We have also developed and deployed a mobile application that uses a symptoms checker together with voice, breath, and cough signals to detect COVID-19 infection. The application showed robust performance on both openly sourced datasets and the noisy data collected during beta testing by the end users.

Recommender Systems in Antiviral Drug Discovery.

Recommender systems (RSs), which underwent rapid development and had an enormous impact on e-commerce, have the potential to become useful tools for drug discovery. In this paper, we applied RS methods for the prediction of the antiviral activity class (active/inactive) for compounds extracted from ChEMBL. Two main RS approaches were applied: collaborative filtering (Surprise implementation) and content-based filtering (sparse-group inductive matrix completion (SGIMC) method). The effectiveness of RS approaches was investigated for prediction of antiviral activity classes ("interactions") for compounds and viruses, for which some of their interactions with other viruses or compounds are known, and for prediction of interaction profiles for new compounds. Both approaches achieved relatively good prediction quality for binary classification of individual interactions and compound profiles, as quantified by cross-validation and external validation receiver operating characteristic (ROC) score >0.9. Thus, even simple recommender systems may serve as an effective tool in antiviral drug discovery.