Machine‐learning scoring functions for structure‐based drug lead optimization
Molecular docking can be used to predict how strongly small‐molecule binders and their
chemical derivatives bind to a macromolecular target using its available three‐dimensional …
chemical derivatives bind to a macromolecular target using its available three‐dimensional …
OnionNet-2: a convolutional neural network model for predicting protein-ligand binding affinity based on residue-atom contacting shells
One key task in virtual screening is to accurately predict the binding affinity (△ G) of protein-
ligand complexes. Recently, deep learning (DL) has significantly increased the predicting …
ligand complexes. Recently, deep learning (DL) has significantly increased the predicting …
A comprehensive survey of prospective structure-based virtual screening for early drug discovery in the past fifteen years
H Zhu, Y Zhang, W Li, N Huang - International Journal of Molecular …, 2022 - mdpi.com
Structure-based virtual screening (SBVS), also known as molecular docking, has been
increasingly applied to discover small-molecule ligands based on the protein structures in …
increasingly applied to discover small-molecule ligands based on the protein structures in …
A review of mathematical representations of biomolecular data
Recently, machine learning (ML) has established itself in various worldwide benchmarking
competitions in computational biology, including Critical Assessment of Structure Prediction …
competitions in computational biology, including Critical Assessment of Structure Prediction …
Assessment of the generalization abilities of machine-learning scoring functions for structure-based virtual screening
In structure-based virtual screening (SBVS), it is critical that scoring functions capture protein–
ligand atomic interactions. By focusing on the local domains of ligand binding pockets, a …
ligand atomic interactions. By focusing on the local domains of ligand binding pockets, a …
True accuracy of fast scoring functions to predict high-throughput screening data from docking poses: the simpler the better
VK Tran-Nguyen, G Bret, D Rognan - Journal of Chemical …, 2021 - ACS Publications
Hundreds of fast scoring functions have been developed over the last 20 years to predict
binding free energies from three-dimensional structures of protein-ligand complexes …
binding free energies from three-dimensional structures of protein-ligand complexes …
VAD-MM/GBSA: a variable atomic dielectric MM/GBSA model for improved accuracy in protein–ligand binding free energy calculations
The molecular mechanics/generalized Born surface area (MM/GBSA) has been widely used
in end-point binding free energy prediction in structure-based drug design (SBDD) …
in end-point binding free energy prediction in structure-based drug design (SBDD) …
SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors
In drug discovery, rapid and accurate prediction of protein–ligand binding affinities is a
pivotal task for lead optimization with acceptable on-target potency as well as …
pivotal task for lead optimization with acceptable on-target potency as well as …
A consistent scheme for gradient-based optimization of protein–ligand poses
F Flachsenberg, A Meyder, K Sommer… - Journal of Chemical …, 2020 - ACS Publications
Scoring and numerical optimization of protein–ligand poses is an integral part of docking
tools. Although many scoring functions exist, many of them are not continuously …
tools. Although many scoring functions exist, many of them are not continuously …
Improving docking-based virtual screening ability by integrating multiple energy auxiliary terms from molecular docking scoring
Virtual Screening (VS) based on molecular docking is an efficient method used for retrieving
novel hit compounds in drug discovery. However, the accuracy of the current docking …
novel hit compounds in drug discovery. However, the accuracy of the current docking …