AI Medical Compendium Journal:
Current medicinal chemistry

Showing 11 to 20 of 30 articles

Evidence from Machine Learning, Diagnostic Hub Genes in Sepsis and Diagnostic Models based on Xgboost Models, Novel Molecular Models for the Diagnosis of Sepsis.

Current medicinal chemistry
BACKGROUND: Systemic multi-organ dysfunction resulting from dysregulated immune responses in the host triggered by microbial infection or other factors is a major cause of death in sepsis, and secretory pathways play an important role in it.

Recent Advances in Protein Folding Pathway Prediction through Computational Methods.

Current medicinal chemistry
The protein folding mechanisms are crucial to understanding the fundamental processes of life and solving many biological and medical problems. By studying the folding process, we can reveal how proteins achieve their biological functions through spe...

Computational Protein Design - Where it goes?

Current medicinal chemistry
Proteins have been playing a critical role in the regulation of diverse biological processes related to human life. With the increasing demand, functional proteins are sparse in this immense sequence space. Therefore, protein design has become an imp...

Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.

Current medicinal chemistry
BACKGROUND: The idea of scoring function space established a systems-level approach to address the development of models to predict the affinity of drug molecules by those interested in drug discovery.

Application of Machine Learning Technology in the Prediction of ADME- Related Pharmacokinetic Parameters.

Current medicinal chemistry
BACKGROUND: As an important determinant in drug discovery, the accurate analysis and acquisition of pharmacokinetic parameters are very important for the clinical application of drugs. At present, the research and development of new drugs mainly obta...

Recent Applications of Artificial Intelligence in Early Cancer Detection.

Current medicinal chemistry
Cancer is a deadly disease that is often caused by the accumulation of various genetic mutations and pathological alterations. The death rate can only be reduced when it is detected in the early stages, because cancer treatment when the tumor has not...

The Impact of Crystallographic Data for the Development of Machine Learning Models to Predict Protein-Ligand Binding Affinity.

Current medicinal chemistry
BACKGROUND: One of the main challenges in the early stages of drug discovery is the computational assessment of protein-ligand binding affinity. Machine learning techniques can contribute to predicting this type of interaction. We may apply these tec...