Results 51 to 60 of about 5,903,465 (247)

A brief review of protein–ligand interaction prediction

Computational and Structural Biotechnology Journal, 2022
The task of identifying protein–ligand interactions (PLIs) plays a prominent role in the field of drug discovery. However, it is infeasible to identify potential PLIs via costly and laborious in vitro experiments.
Lingling Zhao, Yan Zhu, Junjie Wang, Naifeng Wen, Chunyu Wang, Liang Cheng   +5 more
doaj   +1 more source

GDGRU-DTA: Predicting Drug-Target Binding Affinity based on GNN and Double GRU

Data Mining and Machine Learning, 2022
The work for predicting drug and target affinity(DTA) is crucial for drug development and repurposing. In this work, we propose a novel method called GDGRU-DTA to predict the binding affinity between drugs and targets, which is based on GraphDTA, but we consider that protein sequences are long sequences, so simple CNN cannot capture the context ...
Zhijian Lyu, Shaohua Jiang, Yigao Liang, Min Gao   +3 more
openaire   +3 more sources

Identification of a Shiga toxin A‐derived peptide internalized into Gb3 receptor‐bearing cells via interaction with the Shiga toxin B subunit

FEBS Letters, EarlyView.
The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi, João C. Encarnação, Valeria Napolitano, Grzegorz Dubin, Grzegorz Popowicz, Karl Andersson, U. Helena Danielson   +6 more
wiley   +1 more source

Investigating transcription factor dynamics in health and disease using FRAP

FEBS Letters, EarlyView.
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj, Carolina Vazquez Garzon, Jose Joaquin Velasco, Janine N. Post   +3 more
wiley   +1 more source

Development of novel ligands influencing neurotransmission in the central nervous system [PDF]

, 2007
The development of novel drugs targeting GPCRs is of particular interest since modulation of subfamilies of this receptor class highly influences neurotransmission in the central nervous system.
Sasse, Britta Caroline
core  

DCI-SiteDTA: drug-target affinity prediction based on binding sites detection and site-aware dual cross-interaction block

BMC Bioinformatics
Background Predicting the binding affinity between drugs and proteins is crucial for accelerating drug discovery. However, traditional research methods typically treat binding site detection and affinity prediction as two separate tasks, lacking ...
Jinyang Zhang, Xingyang Li, Bo Wei, Yuni Zeng   +3 more
doaj   +1 more source

Conserved binding mode but diverse interfaces of MreC‐PBP2 interactions

FEBS Letters, EarlyView.
The crystal structure of abMreC reveals a conserved two β‐barrel architecture and provides structural insights into its role within the bacterial elongasome. The abMreC–abPBP2 complex model identifies the molecular basis of MreC‐mediated PBP2 recognition, contributing to the regulation of peptidoglycan synthesis.
Hyunseok Jang, Hyo Been Jin, Chang Min Kim, So Yeon Lee, Hyun Ho Park   +4 more
wiley   +1 more source

DTA+VAE: Drug Target Affinity prediction with SELFIES String via variational autoencoder and Transformer6 protein model [PDF]

, 2023
A crucial step in drug discovery is identifying drug-target interactions. Over the years, there have been many computational methods to determine whether a drug and a target will interact or not.
Patel, Yakin
core   +1 more source

LEP-AD: language embedding of proteins and attention to drugs predicts drug-target interactions

Journal of Cheminformatics
Introduction Predicting drug–target interactions remains a significant challenge in drug development and lead optimization. Recent advances have leveraged machine learning algorithms to model drug–target interactions from molecular and sequence data ...
Reem Alsulami, Robert Lehmann, Anuj Daga, Sumeer A. Khan, Raik Grünberg, Ahmed Abogosh, David Gomez Cabrero, Stefan T. Arold, Robert Hoehndorf, Jesper Tegner, Narsis A. Kiani   +10 more
doaj   +1 more source

An epithelial GPR35 isoform supports tumor‐associated transcriptional and metabolic phenotypes

FEBS Letters, EarlyView.
GPR35 generates two functionally distinct isoforms with previously unresolved roles. GPR35‐short mediates immune‐cell chemotaxis, while GPR35‐long is enriched in colorectal cancer epithelium, where it supports increased metabolism, proliferation, and tumor‐associated transcriptional programs.
Jørgen D. Rønneberg, Martine Hjeltnes, Josephine Krieger, Joshua E. Elias, Maria Stensland, Kristian Holm, Xiaojun Jiang, Chuki Khangsar, Tuula A. Nyman, Arthur Kaser, Johannes R. Hov, Tom H. Karlsen, Nicole C. Kaneider, Frode L. Jahnsen, Georg Schneditz   +14 more
wiley   +1 more source