Discovery of novel SOS1 inhibitors using machine learning

Overactivation of the rat sarcoma virus (RAS) signaling is responsible for 30% of all human malignancies. Son of sevenless 1 (SOS1), a crucial node in the RAS signaling pathway, could modulate RAS activation, offering a promising therapeutic strategy for RAS-driven cancers. Applying machine learning (ML)-based virtual screening (VS) on small-molecule databases, we selected a random forest (RF) regressor for its robustness and performance. Screening was performed with the L-series and EGFR-related datasets, and was extended to the Chinese National Compound Library (CNCL) with more than 1.4 million compounds. In addition to a series of documented SOS1-related molecules, we uncovered nine compounds that have an unexplored chemical framework and displayed inhibitory activity, with the most potent achieving more than 50% inhibition rate in the KRAS G12C/SOS1 PPI assay and an IC50 value in the proximity of 20 μg mL−1. Compared with the manner that known inhibitory agents bind to the target, hit compounds represented by CL01545365 occupy a unique pocket in molecular docking. An in silico drug-likeness assessment suggested that the compound has moderately favorable drug-like properties and pharmacokinetic characteristics. Altogether, our findings strongly support that, characterized by the distinctive binding modes, the recognition of novel skeletons from the carboxylic acid series could be candidates for developing promising SOS1 inhibitors

Bug mapping and fitness testing of chemically synthesized chromosome X

Debugging a genome sequence is imperative for successfully building a synthetic genome. As part of the effort to build a designer eukaryotic genome, yeast synthetic chromosome X (synX), designed as 707,459 base pairs, was synthesized chemically. SynX exhibited good fitness under a wide variety of conditions. A highly efficient mapping strategy called pooled PCRTag mapping (PoPM), which can be generalized to any watermarked synthetic chromosome, was developed to identify genetic alterations that affect cell fitness (“bugs”). A series of bugs were corrected that included a large region bearing complex amplifications, a growth defect mapping to a recoded sequence in FIP1, and a loxPsym site affecting promoter function of ATP2. PoPM is a powerful tool for synthetic yeast genome debugging and an efficient strategy for phenotype-genotype mapping