We have evaluated the prediction accuracy of three different tools, deep-learning-based AlphaFold2, AlphaFold3, and large language model-based ESMFold, utilizing the experimentally derived structures deposited in the Protein Data Bank between 2022 an...
The majority of machine learning scoring functions used in drug discovery for predicting protein-ligand binding poses and affinities have been trained on the PDBBind data set. However, it is unclear whether these new scoring functions are actually an...
Journal of the American Society for Mass Spectrometry
Nov 27, 2025
Proteogenomics integrates genomics and mass spectrometry (MS) data to understand complex biological systems, disease mechanisms, and potential biomarkers. However, the high volume and noise in MS data present computational and interpretational challe...
Journal of chemical information and modeling
Nov 26, 2025
Protein structure database search has become increasingly challenging due to the growing number of experimental and computational structures. We introduce mTM-align2, a novel two-step approach for rapid and accurate protein structure database search....
With monoclonal antibodies becoming one of the largest classes of biopharmaceuticals, it is important to have curated data to train computational models that can accelerate their design. Despite the massive amount of mutagenesis data generated on ant...
In living organisms, proteins perform key functions required for life activities by interacting to form complexes. Determining the protein complex structure is crucial for understanding and mastering biological functions. Although AlphaFold2 makes a ...
Recent advances in Artificial Intelligence have enabled multi-modal systems to model and translate diverse information spaces. Extending beyond text and vision, we introduce OneProt, a multi-modal Deep Learning model for proteins that integrates stru...
Data-independent acquisition (DIA)-based mass spectrometry is becoming an increasingly popular mass spectrometry acquisition strategy for carrying out quantitative proteomics experiments. Most of the popular DIA search engines make use of in silico g...
Proceedings of the National Academy of Sciences of the United States of America
Nov 4, 2025
Modeling the conformational heterogeneity of protein-small molecule interactions is important for understanding natural systems and evaluating designed systems but remains an outstanding challenge. We reasoned that while residue-level descriptions of...
LigPCDS (Ligand Point Cloud Data Set) is the first dataset of chemically labeled 3D point clouds of protein ligands. 3D images and structures of ligands were derived from X-ray protein crystallography experimental datasets deposited at the Protein Da...
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