Molecular conformer generation is a fundamental task in computational chemistry. Several
machine learning approaches have been developed, but none have outperformed state-of …

Natural products (NPs) are a rich source of structurally novel molecules, and the chemical
space they encompass is far from being fully explored. Over history, NPs have represented a …

Abstract PubChem (https://pubchem. ncbi. nlm. nih. gov) is a public repository for information
on chemical substances and their biological activities, launched in 2004 as a component of …

Abstract Machine learning (ML) outperforms traditional approaches in many molecular
design tasks. ML models usually predict molecular properties from a 2D chemical graph or a …

Large-scale molecular databases play an essential role in the investigation of various
subjects such as the development of organic materials, in silico drug design, and data …

Abstract PubChem (https://pubchem. ncbi. nlm. nih. gov) is a public chemical database that
serves scientific communities as well as the general public. This database collects chemical …

The recognition process between a protein and a partner represents a significant theoretical
challenge. In silico structure-based drug design carried out with nothing more than the three …

Abstract Machine learning approaches in drug discovery, as well as in other areas of the
chemical sciences, benefit from curated datasets of physical molecular properties. However …

Background PubChem is a chemical information repository, consisting of three primary
databases: Substance, Compound, and BioAssay. When individual data contributors submit …

Background PubChem is an open repository for small molecules and their experimental
biological activity. PubChem integrates and provides search, retrieval, visualization …