Results 61 to 70 of about 160,727 (166)
Prediction of Drug-Target Affinity Using Attention Neural Network
International Journal of Molecular SciencesStudying drug-target interactions (DTIs) is the foundational and crucial phase in drug discovery. Biochemical experiments, while being the most reliable method for determining drug-target affinity (DTA), are time-consuming and costly, making it challenging to meet the current demands for swift and efficient drug development. Consequently, computational
Tang, Xin, Lei, Xiujuan, Zhang, Yuchen
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DGDTA: dynamic graph attention network for predicting drug–target binding affinity
BMC Bioinformatics, 2023 AbstractBackgroundObtaining accurate drug–target binding affinity (DTA) information is significant for drug discovery and drug repositioning. Although some methods have been proposed for predicting DTA, the features of proteins and drugs still need to be further analyzed. Recently, deep learning has been successfully used in many fields.
Haixia Zhai +5 more
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Molecular cloning and expression of novel fibroblast growth factor-2 conjugated with immunodominant domains of pseudomonas exotoxin [PDF]
, 2015 Angiogenesis is very important in cancer growth and metastasis. Basic fibroblast growth factor (bFGF) as one of the most important angiogenesis factors is an attractive target for cancer vaccine.
Farazmandfar, T. +6 more
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Associative learning mechanism for drug‐target interaction prediction
CAAI Transactions on Intelligence Technology, 2023 As a necessary process of modern drug development, finding a drug compound that can selectively bind to a specific protein is highly challenging and costly.
Zhiqin Zhu +5 more
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Characterization of HSP90 isoforms in transformed bovine leukocytes infected with Theileria annulata [PDF]
, 2016 HSP90 chaperones are essential regulators of cellular function, as they ensure the appropriate conformation of multiple key client proteins. Four HSP90 isoforms were identified in the protozoan parasite Theileria annulata.
Calder, Ewen D.D. +8 more
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DTITR: End-to-end drug–target binding affinity prediction with transformers
Computers in Biology and Medicine, 2022 The accurate identification of Drug-Target Interactions (DTIs) remains a critical turning point in drug discovery and understanding of the binding process. Despite recent advances in computational solutions to overcome the challenges of in vitro and in vivo experiments, most of the proposed in silico-based methods still focus on binary classification ...
Nelson R.C. Monteiro +2 more
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Target identification strategies in plant chemical biology [PDF]
, 2014 The current needs to understand gene function in plant biology increasingly require more dynamic and conditional approaches opposed to classic genetic strategies.
Dejonghe, Wim, Russinova, Eugenia
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BMC Bioinformatics, 2021 Background The study of drug–target interactions (DTIs) affinity plays an important role in safety assessment and pharmacology. Currently, quantitative structure–activity relationship (QSAR) and molecular docking (MD) are most common methods in research ...
Xian-rui Wang +4 more
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Structure based de novo design of IspD inhibitors as anti-tubercular agents [PDF]
, 2012 Tuberculosis is one of the leading contagious diseases, caused by Mycobacterium tuberculosis. Despite improvements in anti-tubercular agents, it remains one of the most prevalent infectious diseases worldwide, responsible for a total of 1.6 million ...
Abhay T. Sangamwar +4 more
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Drug–Target Affinity Prediction Based on Cross-Modal Fusion of Text and Graph
Applied SciencesDrug–target affinity (DTA) prediction is a critical step in virtual screening and significantly accelerates drug development. However, existing deep learning-based methods relying on single-modal representations (e.g., text or graphs) struggle to fully ...
Jucheng Yang, Fushun Ren
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