Highlights•A few newly introduced molecular descriptors were discussed.•Various
computational approaches to calculate the descriptors are listed.•We described several …

The primary goal of rational drug discovery is the identification of selective ligands which act
on single or multiple drug targets to achieve the desired clinical outcome through the …

In modern drug discovery, the combination of chemoinformatics and quantitative structure–
activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling …

Background: Virtual Screening (VS) has emerged as an important tool in the drug
development process, as it conducts efficient in silico searches over millions of compounds …

In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges
as a transformative force, bridging the realms of biology and technology. This paper …

The discovery of bioactive molecules is an expensive and time-consuming process and new
strategies are continuously searched for in order to optimize this process. Virtual Screening …

Here we report PPB2 as a target prediction tool assigning targets to a query molecule based
on ChEMBL data. PPB2 computes ligand similarities using molecular fingerprints encoding …

In the last decade, machine learning and artificial intelligence applications have received a
significant boost in performance and attention in both academic research and industry. The …

Abstract Machine-learning (ML)-based scoring functions (MLSFs) have gradually emerged
as a promising alternative for protein–ligand binding affinity prediction and structure-based …

Drug repurposing provides a non-laborious and less expensive way for finding new human
medicines. Computational assessment of bioactivity profiles shed light on the hidden …