Drug combinations, offering increased therapeutic efficacy and reduced toxicity, play an
important role in treating multiple complex diseases. Yet, our ability to identify and validate …

Structure-based virtual screening is an important tool in early stage drug discovery that
scores the interactions between a target protein and candidate ligands. As virtual libraries …

Covalent modification is commonly used to tune the channel size and functionality of 2D
membranes. However, common synthesis strategies used to produce such modifications are …

In the space of only a few years, deep generative modeling has revolutionized how we think
of artificial creativity, yielding autonomous systems which produce original images, music …

The goal of structure-based drug discovery is to find small molecules that bind to a given
target protein. Deep learning has been used to generate drug-like molecules with certain …

Rich data and powerful machine learning models allow us to design drugs for a specific
protein target\textit {in silico}. Recently, the inclusion of 3D structures during targeted drug …

A fundamental problem in drug discovery is to design molecules that bind to specific
proteins. To tackle this problem using machine learning methods, here we propose a novel …

Molecular descriptors are widely employed to present molecular characteristics in
cheminformatics. Various molecular-descriptor-calculation software programs have been …

Emergent resistance to all clinical antibiotics calls for the next generation of therapeutics.
Here we report an effective antimicrobial strategy targeting the bacterial hydrogen sulfide …

Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with
high affinity and specificity to pre-determined protein targets. In this paper, we formulate …