Results 41 to 50 of about 5,508,972 (143)

Dual modality feature fused neural network integrating binding site information for drug target affinity prediction

npj Digital Medicine
Accurately predicting binding affinities between drugs and targets is crucial for drug discovery but remains challenging due to the complexity of modeling interactions between small drug and large targets.
Hao-Huai He, Guan-Xing Chen, Zhen-Chao Tang, C. Chen   +3 more
semanticscholar   +1 more source

3DProtDTA: the deep learning model for drug-target affinity prediction based on the residue-level protein graphs

bioRxiv, 2022
Accurate prediction of the drug-target affinity (DTA) in silico is of critical importance for modern drug discovery. Computational methods of DTA prediction, applied in the early stages of drug development, are able to speed it up and cut its cost ...
T. Voitsitskyi, Roman Stratiichuk, Ihor Koleiev, Leonid Popryho, Zakhar Ostrovsky, Pavel Henitsoi, Ivan Khropachev, Volodymyr Vozniak, Roman Zhytar, Diana Nechepurenko, S. Yesylevskyy, Alan Nafiev, S. Starosyla   +12 more
semanticscholar   +1 more source

Discovering the Biological Target of 5-epi-Sinuleptolide Using a Combination of Proteomic Approaches

Marine Drugs, 2017
Sinuleptolide and its congeners are diterpenes with a norcembranoid skeleton isolated from the soft coral genus Sinularia. These marine metabolites are endowed with relevant biological activities, mainly associated with cancer development.
Elva Morretta, Roberta Esposito, Carmen Festa, Raffaele Riccio, Agostino Casapullo, Maria Chiara Monti   +5 more
doaj   +1 more source

Drug-Target Residence Time Affects in Vivo Target Occupancy through Multiple Pathways

, 2019
The drug discovery and development process is greatly hampered by difficulties in translating in vitro potency to in vivo efficacy. Recent studies suggest that the long-neglected drug-target residence time parameter complements classical drug affinity ...
Bruce D. Hammock (65754), Kin Sing Stephen Lee (7339106), Connie J. Ng (7339109), Christophe Morisseau (362750), Karen M. Wagner (495920), Sean D. Kodani (5895083), Debin Wan (1996066), Jun Niu (323242), Jun Yang (2084), Hua Dong (241097)   +9 more
core   +1 more source

GEFA: early fusion approach in drug-target affinity prediction

, 2022
GEFA: early fusion approach in drug-target affinity ...
Thin Nguyen (13097583), Truyen Tran (13098360), Thao Minh Le (13097496), Tri Nguyen (13917915)   +3 more
core  

AffinityVAE: A multi-objective model for protein-ligand affinity prediction and drug design

, 2023
In the prediction of protein-ligand affinity, the traditional methods require a large amount of computing resources, and have certain limitations in predicting and simulating the structural changes.
Yu, X, Han, K, Wang, M, Li, W, Luo, Y, Wang, C, Jin, Q   +6 more
core   +1 more source

ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding

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, NaiFeng Wen, Chunyu Wang, Lingling Zhao, Liang Cheng   +4 more
doaj   +1 more source

MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network

BMC Genomics
Drug development is a time-consuming and costly endeavor, and utilizing computer-aided methods to predict drug-target affinity (DTA) can significantly accelerate this process. The key to accurate DTA prediction lies in selecting appropriate computational
Zhanwei Hou, Yi-Jun Li, Haixia Zhai, Jun-Wei Luo, Yulian Ding, Yi Pan   +5 more
semanticscholar   +1 more source

Optimization of drug–target affinity prediction methods through feature processing schemes

Bioinform., 2023
Motivation Numerous high-accuracy drug–target affinity (DTA) prediction models, whose performance is heavily reliant on the drug and target feature information, are developed at the expense of complexity and interpretability.
Xiaoqing Ru, Quan Zou, Chen Lin
semanticscholar   +1 more source

Emerging paradigms in anti-infective drug design. [PDF]

, 2014
The need for new drugs to treat microbial infections is pressing. The great progress made in the middle part of the twentieth Century was followed by a period of relative inactivity as the medical needs relating to infectious disease in the wealthier ...
Croft, Simon L, Barrett, Michael P., Barrett, Michael P, Croft, Simon L.   +3 more
core   +1 more source