Advancing drug discovery: Thiadiazole derivatives as multifaceted agents in medicinal chemistry and pharmacology.

In this dispensation of rapid scientific and technological advancements, significant efforts are being made to curb health-related diseases. Research discoveries have highlighted the value of heterocyclic compounds, particularly thiadiazole derivatives, due to their diverse pharmacological activities. These compounds play a crucial role in therapeutic medicine and the development of effective drugs. Thiadiazoles are five-membered heterocyclic compounds consisting of one sulfur and two nitrogen atoms. This review explores advanced synthesis techniques, including the use of heterogeneous catalysts, microwave-assisted methods, ultrasound-assisted synthesis, solvent-free processes, multicomponent reactions, copper-catalyzed aerobic oxidative annulation, intramolecular cyclization, click-chemistry supported synthesis, and alkali-promoted, transition-metal-free mediated synthesis. These methods enhance the diversity and potential applications of thiadiazole compounds. Furthermore, this study provides up-to-date information on the key pharmacological activities of thiadiazole derivatives, highlighting their potential in therapeutic medicine for drug development. The structure-activity relationship (SAR) is also discussed to better understand their interactions and safety in biological systems. This work aims to expand on the reported chemistry and pharmacological potential of the thiadiazole moiety to validate their efficacy as promising pharmacophores in drug design and development.

Pooled multicolour tagging for visualizing subcellular protein dynamics.

Imaging-based methods are widely used for studying the subcellular localization of proteins in living cells. While routine for individual proteins, global monitoring of protein dynamics following perturbation typically relies on arrayed panels of fluorescently tagged cell lines, limiting throughput and scalability. Here, we describe a strategy that combines high-throughput microscopy, computer vision and machine learning to detect perturbation-induced changes in multicolour tagged visual proteomics cell (vpCell) pools. We use genome-wide and cancer-focused intron-targeting sgRNA libraries to generate vpCell pools and a large, arrayed collection of clones each expressing two different endogenously tagged fluorescent proteins. Individual clones can be identified in vpCell pools by image analysis using the localization patterns and expression level of the tagged proteins as visual barcodes, enabling simultaneous live-cell monitoring of large sets of proteins. To demonstrate broad applicability and scale, we test the effects of antiproliferative compounds on a pool with cancer-related proteins, on which we identify widespread protein localization changes and new inhibitors of the nuclear import/export machinery. The time-resolved characterization of changes in subcellular localization and abundance of proteins upon perturbation in a pooled format highlights the power of the vpCell approach for drug discovery and mechanism-of-action studies.

Discovery of Molecular Glue Degraders via Isogenic Morphological Profiling.

Molecular glue degraders (MGDs) are small molecules that degrade proteins of interest via the ubiquitin-proteasome system. While MGDs were historically discovered serendipitously, approaches for MGD discovery now include cell-viability-based drug screens or data mining of public transcriptomics and drug response datasets. These approaches, however, have target spaces restricted to the essential proteins. Here we develop a high-throughput workflow for MGD discovery that also reaches the nonessential proteome. This workflow begins with the rapid synthesis of a compound library by sulfur(VI) fluoride exchange chemistry coupled to a morphological profiling assay in isogenic cell lines that vary in levels of the E3 ligase CRBN. By comparing the morphological changes induced by compound treatment across the isogenic cell lines, we were able to identify FL2-14 as a CRBN-dependent MGD targeting the nonessential protein GSPT2. We envision that this workflow would contribute to the discovery and characterization of MGDs that target a wider range of proteins.