Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions
New drug production, from target identification to marketing approval, takes over 12 years
and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the …
and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the …
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 …
Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization
M Kadukova, S Grudinin - Journal of computer-aided molecular design, 2017 - Springer
We present a novel optimization approach to train a free-shape distance-dependent protein-
ligand scoring function called Convex-PL. We do not impose any functional form of the …
ligand scoring function called Convex-PL. We do not impose any functional form of the …
Application of machine learning techniques to predict binding affinity for drug targets: a study of cyclin-dependent kinase 2
G Bitencourt-Ferreira, A Duarte da Silva… - Current medicinal …, 2021 - ingentaconnect.com
Background: The elucidation of the structure of cyclin-dependent kinase 2 (CDK2) made it
possible to develop targeted scoring functions for virtual screening aimed to identify new …
possible to develop targeted scoring functions for virtual screening aimed to identify new …
Predicting Protein-Ligand Binding Structure Using E (n) Equivariant Graph Neural Networks
Drug design is a costly and time-consuming process, often taking more than 12 years and
costing up to billions of dollars. The COVID-19 pandemic has signified the urgent need for …
costing up to billions of dollars. The COVID-19 pandemic has signified the urgent need for …
Docking of small molecules to farnesoid X receptors using AutoDock Vina with the Convex-PL potential: lessons learned from D3R Grand Challenge 2
M Kadukova, S Grudinin - Journal of computer-aided molecular design, 2018 - Springer
Abstract The 2016 D3R Grand Challenge 2 provided an opportunity to test multiple protein–
ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many …
ligand docking protocols on a set of ligands bound to farnesoid X receptor that has many …
Protein–ligand docking using FFT based sampling: D3R case study
D Padhorny, DR Hall, H Mirzaei, AB Mamonov… - Journal of computer …, 2018 - Springer
Fast Fourier transform (FFT) based approaches have been successful in application to
modeling of relatively rigid protein–protein complexes. Recently, we have been able to …
modeling of relatively rigid protein–protein complexes. Recently, we have been able to …
Perspective on the SAMPL and D3R blind prediction challenges for physics-based free energy methods
N Tielker, L Eberlein, O Beckstein… - Free Energy Methods …, 2021 - ACS Publications
Solvation and binding thermodynamics of a drug-like molecule is quantified by the
respective free energy (FE) change that governs physical properties like log P/log D and …
respective free energy (FE) change that governs physical properties like log P/log D and …
Monte Carlo on the manifold and MD refinement for binding pose prediction of protein–ligand complexes: 2017 D3R Grand Challenge
Manifold representations of rotational/translational motion and conformational space of a
ligand were previously shown to be effective for local energy optimization. In this paper we …
ligand were previously shown to be effective for local energy optimization. In this paper we …
Applications of the NRGsuite and the molecular docking software FlexAID in computational drug discovery and design
LP Morency, F Gaudreault, R Najmanovich - … Drug Discovery and Design, 2018 - Springer
Docking simulations help us understand molecular interactions. Here we present a hands-
on tutorial to utilize FlexAID (Flex ible A rtificial I ntelligence D ocking), an open source …
on tutorial to utilize FlexAID (Flex ible A rtificial I ntelligence D ocking), an open source …