Advancing drug discovery via artificial intelligence
Drug discovery and development are among the most important translational science
activities that contribute to human health and wellbeing. However, the development of a new …
activities that contribute to human health and wellbeing. However, the development of a new …
Molecular docking and structure-based drug design strategies
Pharmaceutical research has successfully incorporated a wealth of molecular modeling
methods, within a variety of drug discovery programs, to study complex biological and …
methods, within a variety of drug discovery programs, to study complex biological and …
KDEEP: Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks
Accurately predicting protein–ligand binding affinities is an important problem in
computational chemistry since it can substantially accelerate drug discovery for virtual …
computational chemistry since it can substantially accelerate drug discovery for virtual …
From machine learning to deep learning: Advances in scoring functions for protein–ligand docking
Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy
highly depends on the reliability of scoring functions (SFs). With the rapid development of …
highly depends on the reliability of scoring functions (SFs). With the rapid development of …
Forging the basis for developing protein–ligand interaction scoring functions
Z Liu, M Su, L Han, J Liu, Q Yang, Y Li… - Accounts of chemical …, 2017 - ACS Publications
Conspectus In structure-based drug design, scoring functions are widely used for fast
evaluation of protein–ligand interactions. They are often applied in combination with …
evaluation of protein–ligand interactions. They are often applied in combination with …
Scoring functions for protein-ligand binding affinity prediction using structure-based deep learning: a review
The rapid and accurate in silico prediction of protein-ligand binding free energies or binding
affinities has the potential to transform drug discovery. In recent years, there has been a …
affinities has the potential to transform drug discovery. In recent years, there has been a …
Machine‐learning scoring functions to improve structure‐based binding affinity prediction and virtual screening
QU Ain, A Aleksandrova, FD Roessler… - Wiley Interdisciplinary …, 2015 - Wiley Online Library
Docking tools to predict whether and how a small molecule binds to a target can be applied
if a structural model of such target is available. The reliability of docking depends, however …
if a structural model of such target is available. The reliability of docking depends, however …
Comparative assessment of scoring functions on an updated benchmark: 2. Evaluation methods and general results
Our comparative assessment of scoring functions (CASF) benchmark is created to provide
an objective evaluation of current scoring functions. The key idea of CASF is to compare the …
an objective evaluation of current scoring functions. The key idea of CASF is to compare the …
Improving AutoDock Vina using random forest: the growing accuracy of binding affinity prediction by the effective exploitation of larger data sets
There is a growing body of evidence showing that machine learning regression results in
more accurate structure‐based prediction of protein‐ligand binding affinity. Docking …
more accurate structure‐based prediction of protein‐ligand binding affinity. Docking …
Improved method of structure-based virtual screening via interaction-energy-based learning
N Yasuo, M Sekijima - Journal of chemical information and …, 2019 - ACS Publications
Virtual screening is a promising method for obtaining novel hit compounds in drug
discovery. It aims to enrich potentially active compounds from a large chemical library for …
discovery. It aims to enrich potentially active compounds from a large chemical library for …