Journal of chemical information and modeling
Oct 31, 2025
Accurate in silico prediction of protein-ligand binding affinity is essential for efficient hit identification in large molecular libraries. Commonly used structure-based methods such as docking often fail to rank compounds effectively, and free ener...
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...
The growing interest in using peptide molecules as therapeutic agents, driven by their high selectivity and efficacy, has become a significant trend in the pharmaceutical industry. However, their oral administration remains challenging due to their l...
Adverse drug events represent a key challenge in public health, especially concerning drug safety profiling and drug surveillance. Drug-drug interactions represent one of the most popular types of adverse drug events. Most computational approaches to...
α-Helical domains are widespread and versatile, yet typically fail under low mechanical load because backbone hydrogen bonds unzip sequentially, limiting their use in force-bearing nanomaterials and molecular devices. We present an AI-guided strategy...
Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical data, which, in addition to being limited to known chemical enti...
Proceedings of the National Academy of Sciences of the United States of America
Oct 16, 2025
Rapid and accurate estimation of protein-ligand binding affinities is crucial for early-stage drug discovery, yet hindered by a trade-off between the accuracy of gold-standard physics-based methods and the speed of simpler empirical scoring functions...
Proceedings of the National Academy of Sciences of the United States of America
Oct 16, 2025
Deep learning has advanced our ability to assess the effects that individual mutations have on protein function; however, predicting the complex interplay between two or more mutations remains challenging. Here, we seek to address this challenge by b...
BACKGROUND: The identification of protein-protein interaction (PPI) plays a crucial role in understanding the mechanisms of complex biological processes. Current research in predicting PPI has shown remarkable progress by integrating protein informat...
Journal of chemical information and modeling
Oct 14, 2025
Pose prediction of ligands to proteins remains a central challenge of structure-based drug design. Although data leakage and generalizability concerns remain, data-driven methods for pose prediction (i.e., based on deep learning and diffusion) now ro...
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