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2,040 papers
Stable constitutive expression of host-derived BiP was associated with prolonged late-stage GLP-1–Fc accumulation in the producer population examined, and these kinetics are compatible with a model in which the timing of ER chaperone supply influences the maintenance of productive output.
Although CSF protein levels did not correlate with proteinuria or perinatal outcomes, spot urine proteinuria is a significant predictor of preeclampsia, FGR, and the need for NICU admission.
A5 is developed, a fluorogenic substrate for aldehyde dehydrogenase 2 (ALDH2) that exhibits high isoform selectivity and a >240-fold signal enhancement over the standard NADH assay, and enables quantitative imaging of ALDH2 activity across multiple biological scales.
LT16 outperformed existing antiandrogens by fully antagonizing clinical AR mutations and effectively suppressing castration- and enzalutamide-resistant LNCaP cells proliferation in vitro and in vivo, positioning it as a promising and innovative therapeutic for advanced PCa.
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PepBAN is introduced, a deep learning framework for modeling PepPI predictions that effectively learns the pattern of pairwise local interactions, enables the identification of key residues participating in the peptide-protein interactions, and offers an intuitive approach to interpret the underlying mechanisms of PepP...
PepPCBench enables a robust evaluation of PFNN-based methods and supports their continued development for peptide-protein structure prediction, and highlights the influence of peptide length, conformational flexibility, and training set similarity on prediction accuracy.
CarsiDock-Cov is presented, a new paradigm distinguishing itself as the first deep learning (DL)-guided approach for covalent docking, offering an automated and efficient solution that shows considerable promise for accelerating covalent drug discovery and design.
EpiMII is presented, a Graph Neural Network model for MHC-II epitope design, which learns from the structural features of epitopes to predict their sequences, potentially contributing to vaccine development.
CovalentLab is introduced, an interactive computational platform that integrates ligand-based and warhead-based strategies into a unified workflow for the rational design of covalent ligands and enables the prediction and ranking of nine classes of covalent-binding residues in proteins according to their reactivity.
This study established a unified model (NRIGN) based on the deep graphic architecture to discriminate agonists and antagonists targeting 26 successful or in-clinical-trial NR targets and achieves an excellent prediction accuracy and is robust enough to be applied in various real-world scenarios.
RAPiDock is presented, an all-atom diffusion model that predicts peptide–protein binding patterns across 92 amino acid types, enabling high-throughput virtual screening for advancing therapeutic peptide design and serve as a powerful tool for high-throughput virtual screening with structural precision.
Abstract Cyclic peptides represent a highly promising class of biopharmaceutical scaffolds. The screening of cyclic peptides against protein targets can be greatly facilitated using computational approaches, especially molecular docking. However, it remains a crucial challenge to accurately predict protein–cyclic pepti...
Proof of concept for watermarking AI-generated proteins while preserving biological function.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
Scientists are using AlphaFold to strengthen a photosynthesis enzyme for resilient, heat-tolerant crops.
Explore how AlphaFold has accelerated science and fueled a global wave of biological discovery.
AlphaFold has revealed the structure of a key protein behind heart disease
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