High-throughput and virtual screening are important components of modern drug discovery
research. Typically, these screening technologies are considered distinct approaches, as …

Computational tools to search chemical structure databases are essential to finding leads
early in a drug discovery project. Similarity methods are among the most diverse and most …

Inspired by natural language processing techniques, we here introduce Mol2vec, which is
an unsupervised machine learning approach to learn vector representations of molecular …

This review is dedicated to a survey on molecular similarity and diversity. Key findings
reported in recent investigations are selectively highlighted and summarized. Even if this …

This perspective describes Auto-QChem, an automatic, high-throughput and end-to-end
DFT calculation workflow that computes chemical descriptors for organic molecules …

Classifying proteins into functionally distinct families based only on primary sequence
information remains a difficult task. We describe here a method to generate a large data set …

A unifying principle of rational drug design is the use of either shape similarity or
complementarity to identify compounds expected to be active against a given target. Shape …

Abstract The Uses of Objects Task is a widely used creativity test. The test is usually scored
by humans, which introduces subjectivity and individual variance into creativity scores. Here …

Chemical databases are becoming a powerful tool in drug discovery. Database searches
based on possible requirements for biological activity can identify compounds that might be …

The multitude of potential drug targets emerging from genome sequencing demands new
approaches to drug discovery. A chemogenomics strategy, which involves the generation of …