AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Proteins

Showing 371 to 380 of 1862 articles

Clear Filters

Efficient and accurate large library ligand docking with KarmaDock.

Nature computational science
Ligand docking is one of the core technologies in structure-based virtual screening for drug discovery. However, conventional docking tools and existing deep learning tools may suffer from limited performance in terms of speed, pose quality and bindi...

Uncovering new families and folds in the natural protein universe.

Nature
We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover nearly all proteins that are known, including thos...

Protein remote homology detection and structural alignment using deep learning.

Nature biotechnology
Exploiting sequence-structure-function relationships in biotechnology requires improved methods for aligning proteins that have low sequence similarity to previously annotated proteins. We develop two deep learning methods to address this gap, TM-Vec...

Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15.

Proteins
We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were obtained using the D-I-TASSER and DMFold-Multimer algorithms, respectively. For monomer structure pred...

Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination.

International journal of biological macromolecules
Proteins play a crucial role in many biological processes, where their interaction with other proteins are integral. Abnormal protein-protein interactions (PPIs) have been linked to various diseases including cancer, and thus targeting PPIs holds pro...

The current role and evolution of X-ray crystallography in drug discovery and development.

Expert opinion on drug discovery
INTRODUCTION: Macromolecular X-ray crystallography and cryo-EM are currently the primary techniques used to determine the three-dimensional structures of proteins, nucleic acids, and viruses. Structural information has been critical to drug discovery...

Biomolecular NMR in the AI-assisted structural biology era: Old tricks and new opportunities.

Biochimica et biophysica acta. Proteins and proteomics
Over the last 40 years nuclear magnetic resonance (NMR) spectroscopy has established itself as one of the most versatile techniques for the characterization of biomolecules, especially proteins. Given the molecular size limitations of NMR together wi...

Deep learning-based method for predicting and classifying the binding affinity of protein-protein complexes.

Biochimica et biophysica acta. Proteins and proteomics
Protein-protein interactions (PPIs) play a critical role in various biological processes. Accurately estimating the binding affinity of PPIs is essential for understanding the underlying molecular recognition mechanisms. In this study, we employed a ...

Transferring From Textual Entailment to Biomedical Named Entity Recognition.

IEEE/ACM transactions on computational biology and bioinformatics
Biomedical Named Entity Recognition (BioNER) aims at identifying biomedical entities such as genes, proteins, diseases, and chemical compounds in the given textual data. However, due to the issues of ethics, privacy, and high specialization of biomed...

Streamlining Large Chemical Library Docking with Artificial Intelligence: the PyRMD2Dock Approach.

Journal of chemical information and modeling
The present contribution introduces a novel computational protocol called PyRMD2Dock, which combines the Ligand-Based Virtual Screening (LBVS) tool PyRMD with the popular docking software AutoDock-GPU (AD4-GPU) to enhance the throughput of virtual sc...