AI Medical Compendium Topic

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

Models, Molecular

Showing 81 to 90 of 628 articles

Clear Filters

Conformational Space Profiling Enhances Generic Molecular Representation for AI-Powered Ligand-Based Drug Discovery.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 39206753
The molecular representation model is a neural network that converts molecular representations (SMILES, Graph) into feature vectors, and is an essential module applied across a wide range of artificial intelligence-driven drug discovery scenarios. Ho...
Artificial Intelligence Drug Discovery Ligands Models, Molecular Molecular Conformation Neural Networks, Computer
View on PubMed DOI

Predicting the Binding of Small Molecules to Proteins through Invariant Representation of the Molecular Structure.

Journal of chemical information and modeling 39197011
We present a computational scheme for predicting the ligands that bind to a pocket of a known structure. It is based on the generation of a general abstract representation of the molecules, which is invariant to rotations, translations, and permutati...
Algorithms Binding Sites Ligands Machine Learning Models, Molecular Molecular Structure Protein Binding Protein Conformation Proteins Small Molecule Libraries
View on PubMed DOI

In Silico Insights: QSAR Modeling of TBK1 Kinase Inhibitors for Enhanced Drug Discovery.

Journal of chemical information and modeling 39289178
TBK1, or TANK-binding kinase 1, is an enzyme that functions as a serine/threonine protein kinase. It plays a crucial role in various cellular processes, including the innate immune response to viruses, cell proliferation, apoptosis, autophagy, and an...
Computer Simulation Drug Discovery Humans Machine Learning Models, Molecular Protein Kinase Inhibitors Protein Serine-Threonine Kinases Quantitative Structure-Activity Relationship
View on PubMed DOI

A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

Journal of chemical information and modeling 39265103
The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the inhibitor design and RNA-related studies. However, traditional methods focus on learning RNA sequence...
Machine Learning Models, Molecular Nucleic Acid Conformation RNA Small Molecule Libraries
View on PubMed DOI

Prediction of Inhibitory Activity against the MATE1 Transporter via Combined Fingerprint- and Physics-Based Machine Learning Models.

Journal of chemical information and modeling 39254593
Renal secretion plays an important role in excretion of drug from the kidney. Two major transporters known to be highly involved in renal secretion are MATE1/2 K and OCT2, the former of which is highly related to drug-drug interactions. Among publish...
Humans Machine Learning Models, Molecular Neural Networks, Computer Organic Cation Transport Proteins
View on PubMed DOI

Toward the Integration of Machine Learning and Molecular Modeling for Designing Drug Delivery Nanocarriers.

Advanced materials (Deerfield Beach, Fla.) 39252670
The pioneering work on liposomes in the 1960s and subsequent research in controlled drug release systems significantly advances the development of nanocarriers (NCs) for drug delivery. This field is evolved to include a diverse array of nanocarriers ...
Drug Carriers Drug Delivery Systems Drug Design Humans Machine Learning Models, Molecular Nanoparticles
View on PubMed DOI

Modelling protein complexes with crosslinking mass spectrometry and deep learning.

Nature communications 39251624
Scarcity of structural and evolutionary information on protein complexes poses a challenge to deep learning-based structure modelling. We integrate experimental distance restraints obtained by crosslinking mass spectrometry (MS) into AlphaFold-Multim...
Bacillus subtilis Bacterial Proteins Cross-Linking Reagents Deep Learning Iron Mass Spectrometry Models, Molecular Protein Conformation
View on PubMed DOI

Pretrainable geometric graph neural network for antibody affinity maturation.

Nature communications 39242604
Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in silico affinity...
Antibodies Antibody Affinity Antigens Computer Simulation Deep Learning Enzyme-Linked Immunosorbent Assay Humans Models, Molecular Neural Networks, Computer Protein Binding
View on PubMed DOI

All-Atom Protein Sequence Design Based on Geometric Deep Learning.

Angewandte Chemie (International ed. in English) 39295564
Designing sequences for specific protein backbones is a key step in creating new functional proteins. Here, we introduce GeoSeqBuilder, a deep learning framework that integrates protein sequence generation with side chain conformation prediction to p...
Amino Acid Sequence Deep Learning Models, Molecular Protein Conformation Proteins Thioredoxins
View on PubMed DOI

gRNAde: A Geometric Deep Learning Pipeline for 3D RNA Inverse Design.

Methods in molecular biology (Clifton, N.J.) 39312140
Fundamental to the diverse biological functions of RNA are its 3D structure and conformational flexibility, which enable single sequences to adopt a variety of distinct 3D states. Currently, computational RNA design tasks are often posed as inverse p...
Computational Biology Deep Learning Models, Molecular Neural Networks, Computer Nucleic Acid Conformation RNA RNA, Catalytic Software
View on PubMed DOI
Popular Topics
Recent Journals