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Surface tension and viscosity are both measures of how "sticky" a liquid is, but are they related? The authors here investigate the surface tension and viscosity of mixtures of water with different concentrations of agar agar, flour, or detergent. Surprisingly, they find that the least viscous mixtures had the strongest surface tensions, indicating that the two properties are not linked.

Elevated acetylcholinesterase (AChE) activity contributes to cognitive decline and neurodegenerative diseases such as Alzheimer’s, motivating the search for more effective inhibitors with better bioavailability. This study used computational methods to design novel, non-toxic AChE inhibitors.

The authors looked at whether they could induce the formation of new neurons from astrocytes via the upregulation of a microRNA (miR-124a). They found that upregulation of miR-124a started transdifferentiation of neurons, but was not enough to lead to full conversion of astrocytes to neurons.

The authors looked at four members of the tetracycline antibiotic family/class against four different species of bacteria.

The authors computationally screened potential ALDH1 inhibitors, for use as potential cancer therapeutics.

The authors describe the design and testing of new guide RNAs targeting the DMPK gene, which is responsible for myotonic dystrophy.

Predicting antibody structures and antibody-antigen complexes using AlphaFold

Microscopic beauty is hiding in common kitchen ingredients - even vanillin flavoring can be turned into mesmerizing artwork by crystallizing the vanillin and examining it under a polarizing microscope. Wang and Pang explore this hidden beauty by determining the optimal conditions to grow crystalline vanillin films and by creating computer simulations of chemical interactions between vanillin molecules.

Here, seeking to address the growing threat of multidrug-resistant bacteria (MDR). the authors used in silico virtual screening to target MDR Pseudomonas aeruginosa. They considered a key protein in its biosynthesis and virtually screened 20,000 candidates and 30 derivatives of brequinar. In the end, they identified a possible candidate with the highest degree of potential to inhibit the pathogen's lipid A synthesis.

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.