Recent breakthroughs in protein structure prediction have opened new avenues for genome-wide drug discovery, yet existing virtual screening methods remain computationally prohibitive. We present DrugCLIP, a contrastive learning framework that achieves ultrafast and accurate virtual screening, up to 10 million times faster than docking, while consistently outperforming various baselines on in silico benchmarks. In wet-lab validations, DrugCLIP achieved a 15% hit rate for norepinephrine transporter, and structures of two identified inhibitors were determined in complex with the target protein. For thyroid hormone receptor interactor 12, a target that lacks holo structures and small-molecule binders, DrugCLIP achieved a 17.5% hit rate using only AlphaFold2-predicted structures. Finally, we released GenomeScreenDB, an open-access database providing precomputed results for ~10,000 human proteins screened against 500 million compounds, pioneering a drug discovery paradigm in the post-AlphaFold era.

Background: The Begonia species are common shade plants that are mostly found in southwest China. They have not been well studied despite their medicinal and decorative uses because gene penetration, decreased adaptability, and restricted availability are all caused by frequent interspecific hybridization. Result: To understand the patterns of mutation in the chloroplast genomes of different species of Begonia, as well as their evolutionary relationships, we collected seven Begonia species in China and sequenced their chloroplast genomes. Begonia species exhibit a quadripartite structure of chloroplast genomes (157,634 − 169,694 bp), consisting of two pairs of inverted repeats (IR: 26,529 − 37,674 bp), a large single copy (LSC: 75,477 − 86,500 bp), and a small single copy (SSC: 17,861 − 18,367 bp). 128–143 genes (comprising 82–93 protein-coding genes, 8 ribosomal RNAs, and 36–43 transfer RNAs) are found in the chloroplast genomes. Based on comparative analyses, this taxon has a relatively similar genome structure. A total of six substantially divergent DNA regions (trnT-UGU-trnL-UAA, atpF-atpH, ycf4-cemA, psbC-trnS-UGA, rpl32-trnL-UAG, and ccsA-ndhD) are found in the seventeen chloroplast genomes. These regions are suitable for species identification and phylogeographic analysis. Phylogenetic analysis shows that Begonia species that were suited to comparable environments grouped in a small clade and that all Begonia species formed one big clade in the phylogenetic tree, supporting the genus’ monophyly. In addition, positive selection sites were discovered in eight genes (rpoC1, rpoB, psbE, psbK, petA, rps12, rpl2, and rpl22), the majority of which are involved in protein production and photosynthesis. Conclusion: Using these genome resources, we can resolve deep-level phylogenetic relationships between Begonia species and their families, leading to a better understanding of evolutionary processes. In addition to enhancing species identification and phylogenetic resolution, these results demonstrate the utility of complete chloroplast genomes in phylogenetically and taxonomically challenging plant groupings.

The genus Bletilla is a small genus of only five species distributed across Asia, including B. chartacea, B. foliosa, B. formosana, B. ochracea and B. striata, which is of great medicinal importance. Furthermore, this genus is a member of the key tribe Arethuseae (Orchidaceae), harboring an extremely complicated taxonomic history. Recently, the monophyletic status of Bletilla has been challenged, and the phylogenetic relationships within this genus are still unclear. The plastome, which is rich in both sequence and structural variation, has emerged as a powerful tool for understanding plant evolution. Along with four new plastomes, this work is committed to exploring plastomic markers to elucidate the phylogeny of Bletilla. Our results reveal considerable plastomic differences between B. sinensis and the other three taxa in many aspects. Most importantly, the specific features of the IR junction patterns, novel pttRNA structures and codon aversion motifs can serve as useful molecular markers for Bletilla phylogeny. Moreover, based on maximum likelihood and Bayesian inference methods, our phylogenetic analyses based on two datasets of Arethuseae strongly imply that Bletilla is non-monophyletic. Accordingly, our findings from this study provide novel potential markers for species identification, and shed light on the evolution of Bletilla and Arethuseae.