Deep Drug–Target Binding Affinity Prediction Base on Multiple Feature Extraction and Fusion [PDF]
ACS OmegaZepeng Li +3 more
doaj +2 more sources
Drug-Target Binding Affinity Prediction Using Transformers [PDF]
, 2021 Abstract Drug discovery is generally difficult, expensive, and low success rate. One of the essential steps in the early stages of drug discovery and drug repurposing is identifying drug-target interactions. Binding affinity indicates the strength of drug-target pair interactions.
Mahsa Saadat +3 more
openaire +1 more source
GraphDTA: Predicting drug–target binding affinity with graph neural networks [PDF]
Bioinformatics, 2019 Abstract The development of new drugs is costly, time consuming, and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs.
Thin Nguyen +5 more
openaire +3 more sources
Multilevel Attention Models for Drug Target Binding Affinity Prediction [PDF]
Neural Processing Letters, 2021 Drug-Target Binding Affinity (DTBA) prediction is one class of Drug-Target Interaction problem (DTI), where the focus is to predict the binding strength of a drug-target pair. Several machine learning approaches have been developed for this purpose. However, almost all rely on the use of increasingly sophisticated inputs to improve the obtained results
openaire +1 more source
CSatDTA: Prediction of Drug-Target Binding Affinity Using Convolution Model with Self-Attention. [PDF]
Int J Mol Sci, 2022 Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug–target affinity is crucial.
Ghimire A, Tayara H, Xuan Z, Chong KT.
europepmc +2 more sources
Drug-target affinity prediction using applicability domain based on data density
, 2021 In the pursuit of research and development of drug discovery, the computational prediction of the target affinity of a drug candidate is useful for screening compounds at an early stage and for verifying the binding potential to an unknown target.
Shunya, Sugita, Masahito, Ohue
core +1 more source
WideDTA: prediction of drug-target binding affinity
CoRR, 2019 Motivation: Prediction of the interaction affinity between proteins and compounds is a major challenge in the drug discovery process. WideDTA is a deep-learning based prediction model that employs chemical and biological textual sequence information to predict binding affinity.
Hakime Öztürk +2 more
openaire +2 more sources
Multiplexed Small Molecule Ligand Binding Assays by Affinity Labeling and DNA Sequence Analysis
, 2021 Small molecule binding assays to target proteins are a core component of drug discovery and development. While a number of assay formats are available, significant drawbacks still remain in cost, sensitivity, and throughput.
Krusemark, Casey J. +3 more
core +1 more source
Optimized hydrophobic interactions and hydrogen bonding at the target-ligand interface leads the pathways of drug-designing. [PDF]
PLoS ONE, 2010 Weak intermolecular interactions such as hydrogen bonding and hydrophobic interactions are key players in stabilizing energetically-favored ligands, in an open conformational environment of protein structures.
Rohan Patil +5 more
doaj +1 more source
Journal of Cheminformatics, 2022 Motivation Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-target (DT) pairs with low binding ...
Junjie Wang +4 more
doaj +1 more source