Recent advances in machine learning and experimental biology have offered breakthrough
solutions to problems such as protein structure prediction that were long thought to be …

The COVID-19 pandemic has emphasized the need for novel drug discovery process.
However, the journey from conceptualizing a drug to its eventual implementation in clinical …

Target discovery is one of the essential steps in modern drug development, and the
identification of promising targets is fundamental for develo** first-in-class drug. A variety …

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB
PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center …

Abstract ChEMBL (https://www. ebi. ac. uk/chembl/) is a manually curated, high-quality, large-
scale, open, FAIR and Global Core Biodata Resource of bioactive molecules with drug-like …

Abstract The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb; https://www.
guidetopharmacology. org) is an open-access, expert-curated, online database that …

Predicting drug–target interaction is key for drug discovery. Recent deep learning-based
methods show promising performance, but two challenges remain: how to explicitly model …

Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical
industry and research, where it has been utilized to efficiently identify new chemical entities …

In the past, conventional drug discovery strategies have been successfully employed to
develop new drugs, but the process from lead identification to clinical trials takes more than …

Many properties of nanoparticles are governed by their shape, size, polydispersity and
surface chemistry. To apply nanoparticles in chemical sensing, medical diagnostics …