AI Medical Compendium Topic

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

Macrocyclic Compounds

Showing 1 to 10 of 10 articles

Clear Filters

[A real-world study of paritaprevir/ritonavir-ombitasvir combined with dasabuvir in the treatment of genotype 1b chronic hepatitis C].

Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology
To recognize the efficacy and safety of paritaprevir/ritonavir-ombitasvir combined with dasabuvir (OBV/PTV/RTV+DSV) in the treatment of genotype 1b chronic hepatitis C. Patients with genotype 1b chronic hepatitis C who were admitted to the People's...

Knowledge-Based Conformer Generation Using the Cambridge Structural Database.

Journal of chemical information and modeling
Fast generation of plausible molecular conformations is central to molecular modeling. This paper presents an approach to conformer generation that makes extensive use of the information available in the Cambridge Structural Database. By using geomet...

Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4.

Journal of computer-aided molecular design
Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) offered a unique opportunity for designing and testing novel methodology for accurate docking and affinity prediction of ligands in an open and blinded manner. We participated in the beta-secret...

Macrocyclization of linear molecules by deep learning to facilitate macrocyclic drug candidates discovery.

Nature communications
Interest in macrocycles as potential therapeutic agents has increased rapidly. Macrocyclization of bioactive acyclic molecules provides a potential avenue to yield novel chemical scaffolds, which can contribute to the improvement of the biological ac...

PepExplainer: An explainable deep learning model for selection-based macrocyclic peptide bioactivity prediction and optimization.

European journal of medicinal chemistry
Macrocyclic peptides possess unique features, making them highly promising as a drug modality. However, evaluating their bioactivity through wet lab experiments is generally resource-intensive and time-consuming. Despite advancements in artificial in...

CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning.

Scientific data
Computational and machine learning approaches to model the conformational landscape of macrocyclic peptides have the potential to enable rational design and optimization. However, accurate, fast, and scalable methods for modeling macrocycle geometrie...

Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food.

ACS sensors
The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critical limitation of these traditional existing approaches is their inability to concurrently discern and...