Introduction Modern drug discovery is generally accessed by useful information from
previous large databases or uncovering novel data. The lack of biological and/or chemical …

Enzyme engineering aims to improve or install a new function in biocatalysts for applications
ranging from chemical synthesis to biomedicine. For decades, computational techniques …

The generation of candidate hit molecules with the potential to be used in cancer treatment
is a challenging task. In this context, computational methods based on deep learning have …

In December 2019, an infectious disease was detected in Wuhan, China, caused by a new
pathogenic coronavirus, named SARS-CoV-2. It spread very rapidly, and on March 11th of …

We introduce the concept of fragment localized molecular orbitals (FLMOs), which are
Hartree–Fock molecular orbitals localized in specific fragments constituting a molecular …

In this work, we develop a method for generating targeted hit compounds by applying deep
reinforcement learning and attention mechanisms to predict binding affinity against a …

Designing hybrid molecules with dual functions is one approach to improve the therapeutic
efficacy of combination treatment. We have previously conjugated phthalazine and bis …

In this study, we introduce the Framework for Optimized Customizable User-Informed
Synthesis (FOCUS), a generative machine learning model tailored for drug discovery …

We introduce the concept of Kohn–Sham fragment localized molecular orbitals (KS-FLMOs),
which are Kohn–Sham molecular orbitals (MOs) localized in specific fragments constituting …

Since the discovery of dicoumarol (a coumarin-based anticoagulant) in 1940, coumarins
have been found to possess a range of biological activities such as antimicrobial, anti …