Computational approaches streamlining drug discovery
AV Sadybekov, V Katritch - Nature, 2023 - nature.com
Computer-aided drug discovery has been around for decades, although the past few years
have seen a tectonic shift towards embracing computational technologies in both academia …
have seen a tectonic shift towards embracing computational technologies in both academia …
Rings in clinical trials and drugs: present and future
J Shearer, JL Castro, ADG Lawson… - Journal of medicinal …, 2022 - ACS Publications
We present a comprehensive analysis of all ring systems (both heterocyclic and
nonheterocyclic) in clinical trial compounds and FDA-approved drugs. We show 67% of …
nonheterocyclic) in clinical trial compounds and FDA-approved drugs. We show 67% of …
A practical guide to large-scale docking
Abstract Structure-based docking screens of large compound libraries have become
common in early drug and probe discovery. As computer efficiency has improved and …
common in early drug and probe discovery. As computer efficiency has improved and …
Integrating QSAR modelling and deep learning in drug discovery: the emergence of deep QSAR
Quantitative structure–activity relationship (QSAR) modelling, an approach that was
introduced 60 years ago, is widely used in computer-aided drug design. In recent years …
introduced 60 years ago, is widely used in computer-aided drug design. In recent years …
Deep generative molecular design reshapes drug discovery
Recent advances and accomplishments of artificial intelligence (AI) and deep generative
models have established their usefulness in medicinal applications, especially in drug …
models have established their usefulness in medicinal applications, especially in drug …
Accelerating high-throughput virtual screening through molecular pool-based active learning
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 …
scores the interactions between a target protein and candidate ligands. As virtual libraries …
Exploration of ultralarge compound collections for drug discovery
WA Warr, MC Nicklaus, CA Nicolaou… - Journal of Chemical …, 2022 - ACS Publications
Designing new medicines more cheaply and quickly is tightly linked to the quest of exploring
chemical space more widely and efficiently. Chemical space is monumentally large, but …
chemical space more widely and efficiently. Chemical space is monumentally large, but …
Defining levels of automated chemical design
One application area of computational methods in drug discovery is the automated design of
small molecules. Despite the large number of publications describing methods and their …
small molecules. Despite the large number of publications describing methods and their …
Sample efficient reinforcement learning with active learning for molecular design
Reinforcement learning (RL) is a powerful and flexible paradigm for searching for solutions
in high-dimensional action spaces. However, bridging the gap between playing computer …
in high-dimensional action spaces. However, bridging the gap between playing computer …
AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection
Protein-ligand docking is a computational method for identifying drug leads. The method is
capable of narrowing a vast library of compounds down to a tractable size for downstream …
capable of narrowing a vast library of compounds down to a tractable size for downstream …