Chemical reaction yield is one of the most important factors for determining reaction conditions. Recently, several machine learning-based prediction models using high-throughput experiment (HTE) data sets were reported for the prediction of reaction...
Molecular structure generation is a critical problem for materials science and has attracted growing attention. The problem is challenging since it requires to generate chemically valid molecular structures. Inspired by the recent work in deep genera...
The software macHine leArning booSTEd dockiNg (HASTEN) was developed to accelerate structure-based virtual screening using machine learning models. It has been validated using datasets both from literature (12 datasets, each containing three million ...
The molecular docking simulation is a key computational tool in modern drug discovery research that its predictive performance strongly depends on the employed scoring functions. Many recent studies have shown that the application of machine learning...
In recent years there has been a growing interest in studying the differences between the chemical and biological space represented by natural products (NPs) of terrestrial and marine origin. In order to learn more about these two chemical spaces, ma...
Identification of high affinity drug-target interactions is a major research question in drug discovery. Proteins are generally represented by their structures or sequences. However, structures are available only for a small subset of biomolecules an...
Histone deacetylase 3 (HDAC3) is a potential drug target for treatment of human diseases such as cancer, chronic inflammation, neurodegenerative diseases and diabetes. Machine learning (ML) as an essential cheminformatics approach has been widely use...
Compounds with the ability to interact with multiple targets, also called promiscuous compounds, provide the basis for polypharmacological drug discovery. In recent years, a plethora of structural analogs with different promiscuity has been identifie...
Natural products play a vital role in the drug discovery and development process as an important source of reliable and novel lead structures. But the existing criteria for drug leads were usually developed for synthetic compounds and cannot be direc...
The SAR Matrix (SARM) approach was originally conceived for the systematic identification of analog series, their structural organization, and graphical structure-activity relationship (SAR) analysis. For structurally related series, SARMs also produ...