Publications by authors named "Kalyan Palepu"
Designing binders to target undruggable proteins presents a formidable challenge in drug discovery, requiring innovative approaches to overcome the lack of putative binding sites. Recently, generative models have been trained to design binding proteins via three-dimensional structures of target proteins, but as a result, struggle to design binders to disordered or conformationally unstable targets. In this work, we provide a generalizable algorithmic framework to design short, target-binding linear peptides, requiring only the amino acid sequence of the target protein.
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- Protein-protein interactions (PPIs) are vital for many biological functions, and accurately predicting their interaction sites can aid in both experimental and computational research.
- The SaLT&PepPr pipeline utilizes a refined protein language model to predict PPI sites based only on protein sequences, showing potential advantages over structural methods despite some performance limitations compared to deep learning approaches combining structural data.
- The study successfully integrates engineered "guide" peptides with an E3 ubiquitin ligase to selectively degrade specific proteins, demonstrating effective and targeted modulation capabilities for potential applications in cancer treatment.
Background: Sleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design.
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