Several approaches have been developed for screening combinatorial libraries or collections of synthetic molecules for agonists or antagonists of protein function, each with its own advantages and limitations. In this report, we describe an experimental platform that seamlessly couples massively parallel bead-based screening of one-bead one-compound combinatorial libraries with microarray-based quantitative comparisons of the binding affinities of the many hits isolated from the bead library. Combined with other technical improvements, this technique allows the rapid identification of the best protein ligands in combinatorial libraries containing millions of compounds without the need for labor-intensive resynthesis of the hits.
Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity.
PARP inhibitors (PARPi) have received regulatory approval for the treatment of several tumors, including prostate cancer (PCa), and demonstrate remarkable results in the treatment of castration-resistant prostate cancer (CRPC) patients characterized by defects in homologous recombination repair (HRR) genes. Preclinical studies showed that DNA repair genes (DRG) other than HRR genes may have therapeutic value in the context of PARPi. To this end, we performed multiple CRISPR/Cas9 screens in PCa cell lines using a custom sgRNA library targeting DRG combined with PARPi treatment.
High-throughput combinatorial metal complex synthesis has emerged as a powerful tool for rapidly generating and screening diverse libraries of metal complexes, enabling accelerated discovery in fields such as catalysis, medicinal chemistry, and materials science. By systematically combining building blocks (BBs) under mild and efficient conditions, researchers can explore broad chemical spaces, increasing the likelihood of identifying complexes with desired properties. This method streamlines hit identification and optimisation, especially when integrated with high-throughput screening (HTS) and data-driven approaches like machine learning.
State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, China; Department of Bioengineering, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China; Wuhan Hesheng Technology Co., Ltd, Wuhan, China. Electronic address:
As a class of natural compounds ubiquitous in nature, diverse terpenoids exhibit a broad spectrum of applications in human endeavors. The efficient discovery of novel terpenoids and the establishment of a terpene library for broad utilization represent pressing challenges in terpenoid natural product research. Various microbial platforms offer abundant precursors for terpene biosynthesis from diverse sources.
Cancer remains one of the deadliest diseases worldwide, with some tumors proving difficult to treat and increasingly resistant to current therapies. Capitalizing on this, there is a need for new therapeutic agents with novel mechanisms of action. Among promising candidates, Fe(III) complexes have gained significant attention as potential chemotherapeutic agents.
