protein design

This paper introduces DPLM, a dynamics-aware protein language model that integrates molecular dynamics simulations with sequence data to improve predictions of protein properties.

This paper develops an optimized optogenetic system using Acr proteins to regulate endogenous gene expression in Drosophila with improved light sensitivity.

This paper evolves DNA operators to enhance protein-DNA interactions for better transcriptional control in cell-free systems.

This study uses computational methods to stabilize Plasmodium falciparum proteins, enabling reliable biophysical analysis and drug discovery.

This paper introduces DynamicsPLM, a protein language model that uses conformational ensembles to improve predictions of protein interactions, localization, and function.

The paper develops a versatile tetracycline-regulated vector system for fine-tuned gene expression in mycobacteria, enabling inducible and repressible control of gene regulation.

This paper benchmarks TCR-pMHC structure prediction tools using 70 unseen complexes and identifies the pLDDT score of the TCR CDR3 region as a key indicator of structural and functional accuracy.

This study shows that phosphorylation at S345 converts HIF-2α from a transcription factor to an RNA-binding protein, altering its function in hypoxia response.

This study identifies YIPPEE/YPEL5 as a conserved regulator of circadian rhythms by modulating PER/PER2 ubiquitination and stability, affecting circadian period length.

TcrDesign generates experimentally validated, functional, full-length TCRs using deep learning, achieving state-of-the-art performance in binding prediction and sequence generation.

This paper designs sequence-specific DNA binding proteins using deep learning, achieving a 100-fold improvement in success rates over previous methods.

The paper introduces a context-aware framework integrating text and protein language models to predict multiple antibody properties without retraining, achieving high correlation across developability properties.

This paper computationally designs a PAM-relaxed SaCas9 variant, KRH, with expanded targeting capability and enhanced editing efficiency.

The paper shows that MULTI-evolve's multimutant predictions correlate closely with additive models, suggesting its performance is not due to epistasis learning.

SPIN uses AlphaFold3 to predict host-pathogen protein interactions in plant pathogens, improving prediction reliability with a multi-metric scoring framework.

The paper improves and applies a yeast secretion and display toolkit for analyzing protein interactions and whole-cell biocatalysis.

This paper introduces a framework using protein language models to discover novel enzymes with specific functions by clustering sequence embeddings and recursively exploring functional reservoirs.

The paper uses FAMPNN to redesign SrBDH1 for increased thermostability while maintaining stereoselectivity.

The paper presents a computational workflow for designing nanobody binders against a novel cancer target, achieving sub-nanomolar affinities without experimental structure or prior antibody data.

This study shows that phosphorylation stabilizes Rb by promoting its dissociation from chromatin, revealing a mechanism linking chromatin association to protein degradation.

The paper identifies a novel Cas12a variant, BvCas12a, with high specificity and engineers variants with broader PAM compatibility and improved editing efficiency.

This paper presents a generative framework for designing intrinsically disordered proteins using protein language models, showing that large datasets are essential for accurate conformational control.

The paper identifies insertion-tolerant regions in RNA phages MS2 and PP7, enabling capsid engineering of PP7 with enhanced in vivo clearance.

This paper introduces IARA, a deep learning model that rapidly identifies optimal binding interfaces for protein binder design, reducing computational costs.

The paper develops a psychrophilic orthogonal translation system for expanding the genetic code in E. coli, showing improved efficiency and versatility compared to mesophilic and thermophilic systems.

This paper introduces a fragment-based representation for proteins that improves functional clustering and search efficiency compared to traditional methods.

The paper identifies novel SAC3-based subcomplexes of the TREX2 complex, revealing distinct RNA processing and export functions through interactions with PCID2 and other subunits.

The paper develops PHYCUT, a CRISPR/Cas9 system for multiplex genome editing in the diatom Phaeodactylum tricornutum, demonstrating its use to reduce fucosylation of secreted proteins.

This paper develops a phage-assisted evolution platform to engineer allosteric protein switches, achieving near-binary optogenetic switches with high dynamic range.

The paper describes the creation of an immobilized SUMO protease to produce the active P113 peptide without using cyanogen bromide.