AI Medical Compendium Journal:
Combinatorial chemistry & high throughput screening

Showing 61 to 68 of 68 articles

Classification of Human Pregnane X Receptor (hPXR) Activators and Non-Activators by Machine Learning Techniques: A Multifaceted Approach.

Combinatorial chemistry & high throughput screening
The Human Pregnane X Receptor (hPXR) is a regulator of drug metabolising enzymes (DME) and efflux transporters (ET). The prediction of hPXR activators and non-activators has pharmaceutical importance to predict the multiple drug resistance (MDR) and ...

A novel machine learning method for cytokine-receptor interaction prediction.

Combinatorial chemistry & high throughput screening
Most essential functions are associated with various protein-protein interactions, particularly the cytokine-receptor interaction. Knowledge of the heterogeneous network of cytokine- receptor interactions provides insights into various human physiolo...

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

Combinatorial chemistry & high throughput screening
The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties o...

Artificial Neural Network Methods Applied to Drug Discovery for Neglected Diseases.

Combinatorial chemistry & high throughput screening
Among the chemometric tools used in rational drug design, we find artificial neural network methods (ANNs), a statistical learning algorithm similar to the human brain, to be quite powerful. Some ANN applications use biological and molecular data of ...

QSAR Analysis of Some Antagonists for p38 map kinase Using Combination of Principal Component Analysis and Artificial Intelligence.

Combinatorial chemistry & high throughput screening
Quantitative relationships between structures of a set of p38 map kinase inhibitors and their activities were investigated by principal component regression (PCR) and principal componentartificial neural network (PC-ANN). Latent variables (called com...

A Study of Applications of Machine Learning Based Classification Methods for Virtual Screening of Lead Molecules.

Combinatorial chemistry & high throughput screening
The ligand-based virtual screening of combinatorial libraries employs a number of statistical modeling and machine learning methods. A comprehensive analysis of the application of these methods for the diversity oriented virtual screening of biologic...

Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

Combinatorial chemistry & high throughput screening
The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this ...

Classification models of HCV NS3 protease inhibitors based on support vector machine (SVM).

Combinatorial chemistry & high throughput screening
Inhibition of the hepatitis C virus (HCV) non-structural protein 3 (NS3) serine protease by molecule inhibitors is an attractive strategy for the treatment of hepatitis C. We built four classification models based on a dataset of 413 HCV NS3 protease...