Virtual screening in the identification of sirtuins' activity modulators
E Abbotto, N Scarano, F Piacente, E Millo, E Cichero… - Molecules, 2022 - mdpi.com
Sirtuins are NAD+-dependent deac (et) ylases with different subcellular localization. The
sirtuins' family is composed of seven members, named SIRT-1 to SIRT-7. Their substrates …
sirtuins' family is composed of seven members, named SIRT-1 to SIRT-7. Their substrates …
Identification of key interactions between SARS-CoV-2 main protease and inhibitor drug candidates
R Yoshino, N Yasuo, M Sekijima - Scientific reports, 2020 - nature.com
The number of cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
infection (COVID-19) has reached over 114,000. SARS-CoV-2 caused a pandemic in …
infection (COVID-19) has reached over 114,000. SARS-CoV-2 caused a pandemic in …
AI-powered virtual screening of large compound libraries leads to the discovery of novel inhibitors of Sirtuin-1
A Gryniukova, F Kaiser, I Myziuk… - Journal of Medicinal …, 2023 - ACS Publications
The discovery of new scaffolds and chemotypes via high-throughput screening is tedious
and resource intensive. Yet, there are millions of small molecules commercially available …
and resource intensive. Yet, there are millions of small molecules commercially available …
Screening for inhibitors of main protease in SARS-CoV-2: in silico and in vitro approach avoiding peptidyl secondary amides
KZ Yamamoto, N Yasuo, M Sekijima - Journal of Chemical …, 2022 - ACS Publications
In addition to vaccines, antiviral drugs are essential for suppressing COVID-19. Although
several inhibitor candidates were reported for SARS-CoV-2 main protease, most are highly …
several inhibitor candidates were reported for SARS-CoV-2 main protease, most are highly …
Mothra: Multiobjective de novo Molecular Generation Using Monte Carlo Tree Search
T Suzuki, D Ma, N Yasuo… - Journal of Chemical …, 2024 - ACS Publications
In the field of drug discovery, identifying compounds that satisfy multiple criteria, such as
target protein affinity, pharmacokinetics, and membrane permeability, is challenging …
target protein affinity, pharmacokinetics, and membrane permeability, is challenging …
Recent Advances in the Discovery of SIRT1/2 Inhibitors via Computational Methods: A Perspective
N Scarano, C Brullo, F Musumeci, E Millo, S Bruzzone… - Pharmaceuticals, 2024 - mdpi.com
Sirtuins (SIRTs) are classified as class III histone deacetylases (HDACs), a family of
enzymes that catalyze the removal of acetyl groups from the ε-N-acetyl lysine residues of …
enzymes that catalyze the removal of acetyl groups from the ε-N-acetyl lysine residues of …
[PDF][PDF] Enamine Ltd.: the science and business of organic chemistry and beyond
OO Grygorenko - European Journal of Organic Chemistry, 2021 - researchgate.net
It is my great pleasure to open this special issue dedicated to the 30th anniversary of
Enamine Ltd.–a worldwide supplier of chemical compounds and services. The company …
Enamine Ltd.–a worldwide supplier of chemical compounds and services. The company …
Sirtuin 1 inhibition: A promising avenue to suppress cancer progression through small inhibitors design
SIRT1 is a protein associated with vital cell functions such as gene regulation, metabolism,
ageing, and cellular energy restoration. Its association with the tumor suppressor protein …
ageing, and cellular energy restoration. Its association with the tumor suppressor protein …
Gargoyles: An open source graph-based molecular optimization method based on deep reinforcement learning
D Erikawa, N Yasuo, T Suzuki, S Nakamura… - ACS …, 2023 - ACS Publications
Automatic optimization methods for compounds in the vast compound space are important
for drug discovery and material design. Several machine learning-based molecular …
for drug discovery and material design. Several machine learning-based molecular …
Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning
S Nakamura, N Yasuo, M Sekijima - Communications Chemistry, 2025 - nature.com
Designing molecules with desirable properties is a critical endeavor in drug discovery.
Because of recent advances in deep learning, molecular generative models have been …
Because of recent advances in deep learning, molecular generative models have been …