Barak Akabayov

MolOptimizer is a user-friendly computational toolkit designed to streamline the hit-to-lead optimization process in drug discovery. MolOptimizer extracts features and trains machine learning models using a user-provided, labeled, and small-molecule dataset to accurately predict the binding values of new small molecules that share similar scaffolds with the target in focus. Hosted on the Azure web-based server, MolOptimizer emerges as a vital resource, accelerating the discovery and development of novel drug candidates with improved binding properties.

Loss of proteostasis can occur due to mutations, the formation of aggregates, or general deficiency in the correct translation and folding of proteins. These phenomena are commonly observed in pathologies, but most significantly, loss of proteostasis characterizes aging. This loss leads to the chronic activation of stress responses and has a generally deleterious impact on the organism. While finding molecules that can alleviate these symptoms is an important step toward solutions for these conditions, some molecules might be mischaracterized on the way. 4‐phenylbutyric acid (4PBA) is known for its role as a chemical chaperone that helps alleviate endoplasmic reticulum (ER) stress, yet a scan of the literature reveals that no biochemical or molecular experiments have shown any protein refolding capacity. Here, we show that 4PBA is a conserved weak inhibitor of mRNA translation, both in vitro and in cellular systems, and furthermore—it does not promote protein folding nor prevents aggregation. 4PBA possibly alleviates proteostatic or ER stress by inhibiting protein synthesis, allowing the cells to cope with misfolded proteins by reducing the protein load. Better understanding of 4PBA biochemical mechanisms will improve its usage in basic science and as a drug in different pathologies, also opening new venues for the treatment of different diseases.