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The authors use molecular modeling to test analogs of the stearoyl-coenzyme A desaturase 1 (SCD1) inhibitor MF-438 with implications for future development of Parkinson's disease therapeutics.

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

Cancer is often caused by improper function of a few proteins, and sometimes it takes only a few proteins to malfunction to cause drastic changes in cells. Here the authors look at the genes that were mutated in patients with a type of pancreatic cancer to identify proteins that are important in causing cancer. They also determined which proteins currently lack effective treatment, and suggest that certain proteins (named KRAS, CDKN2A, and RBBP8) are the most important candidates for developing drugs to treat pancreatic cancer.

In this study, the authors investigate the crystallization kinetics of vanillin thin films from a solution or a melt, as well as how a silane coating on the glass surface affects these properties.

In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.

Polo-like kinase 1 (Plk1) is a master regulator of mitosis, initiating key steps of cell cycle regulation, and its overexpression is associated with certain types of cancer. In this study, the authors carefully designed peptides that were able to bind to Plk1 at a location that is important for its proper localization and function. Future studies could further develop these peptides to selectively target Plk1 in cancer cells and induce mitotic arrest.

The authors looked at developing a PMMA nanoparticle fabric dye that would be more sustainable compared to traditional fabric dyes. They were able to create PMMA based dyes in different colors that were also durable (i.e., did not fade quickly on fabric).

Here, seeking to better understand the roles of glycans in the receptors of active sites of neuronal cells, the authors used molecular dynamics simulations to to uncover the dynamic nature of N-glycans on membrane proteins. The authors suggest the study of theinteractions of these membrane poreins could provide future potential therapeutic targets to treat mental diseases.

With advancements in machine learning a large data scale, high throughput virtual screening has become a more attractive method for screening drug candidates. This study compared the accuracy of molecular descriptors from two cheminformatics Mordred and PaDEL, software libraries, in characterizing the chemo-structural composition of 53 compounds from the non-nucleoside reverse transcriptase inhibitors (NNRTI) class. The classification model built with the filtered set of descriptors from Mordred was superior to the model using PaDEL descriptors. This approach can accelerate the identification of hit compounds and improve the efficiency of the drug discovery pipeline.

This study examines the possibility of utilizing proteins from Drosophila melanogaster in early drug discovery. Structural and sequence analysis of five diverse Drosophila proteins and its human homologs were conducted. Drosophila proteins with high conservation of amino acids at functionally significant positions are better candidates for use as human surrogate in drug discovery efforts.