De novo design of peptide binders to conformationally diverse targets with contrastive language modeling.

Designing binders to target undruggable proteins presents a formidable challenge in drug discovery. In this work, we provide an algorithmic framework to design short, target-binding linear peptides, requiring only the amino acid sequence of the target protein. To do this, we propose a process to generate naturalistic peptide candidates through Gaussian perturbation of the peptidic latent space of the ESM-2 protein language model and subsequently screen these novel sequences for target-selective interaction activity via a contrastive language-image pretraining (CLIP)-based contrastive learning architecture.

Programmable Protein Stabilization with Language Model-Derived Peptide Guides.

Dysregulated protein degradation via the ubiquitin-proteasomal pathway can induce numerous disease phenotypes, including cancer, neurodegeneration, and diabetes. Stabilizing improperly ubiquitinated proteins via target-specific deubiquitination is thus a critical therapeutic goal. Building off the major advances in targeted protein degradation (TPD) using bifunctional small-molecule degraders, targeted protein stabilization (TPS) modalities have been described recently.

PepMLM: Target Sequence-Conditioned Generation of Therapeutic Peptide Binders via Span Masked Language Modeling.

Target proteins that lack accessible binding pockets and conformational stability have posed increasing challenges for drug development. Induced proximity strategies, such as PROTACs and molecular glues, have thus gained attention as pharmacological alternatives, but still require small molecule docking at binding pockets for targeted protein degradation. The computational design of protein-based binders presents unique opportunities to access "undruggable" targets, but have often relied on stable 3D structures or structure-influenced latent spaces for effective binder generation.

Assessing the effectiveness of mitochondrial COI and 16S rRNA genes for DNA barcoding of farmland spiders in China.

DNA barcoding has been widely used to identify and discover new species in a wide range of taxa. In order to assess the effectiveness of COI (cytochrome C oxidase subunit I) and 16S (16S ribosomal RNA) in the discrimination of spiders, we have generated 289 barcodes for a total of 56 farmland spider species from 14 different families for the first time in China. Our results reveal that the standard barcoding marker COI can be used to distinguish the farmland spiders both in species and family level by NJ tree-based method, despite the absence of a barcode gap between the intra- and inter-specific genetic divergences.