Concepts of artificial intelligence for computer-assisted drug discovery

X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

Empirical scoring functions for structure-based virtual screening: applications, critical aspects, and challenges

IA Guedes, FSS Pereira, LE Dardenne - Frontiers in pharmacology, 2018 - frontiersin.org
Structure-based virtual screening (VS) is a widely used approach that employs the
knowledge of the three-dimensional structure of the target of interest in the design of new …

DeepDTA: deep drug–target binding affinity prediction

H Öztürk, A Özgür, E Ozkirimli - Bioinformatics, 2018 - academic.oup.com
Motivation The identification of novel drug–target (DT) interactions is a substantial part of the
drug discovery process. Most of the computational methods that have been proposed to …

KDEEP: Protein–Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks

J Jiménez, M Skalic, G Martinez-Rosell… - Journal of chemical …, 2018 - ACS Publications
Accurately predicting protein–ligand binding affinities is an important problem in
computational chemistry since it can substantially accelerate drug discovery for virtual …

Structure-aware interactive graph neural networks for the prediction of protein-ligand binding affinity

S Li, J Zhou, T Xu, L Huang, F Wang, H ** 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 …

Performance of machine-learning scoring functions in structure-based virtual screening

M Wójcikowski, PJ Ballester, P Siedlecki - Scientific Reports, 2017 - nature.com
Classical scoring functions have reached a plateau in their performance in virtual screening
and binding affinity prediction. Recently, machine-learning scoring functions trained on …