Quantification of binding affinity of glyconanomaterials with lectins
This Feature Article discusses the techniques to determine the binding affinity glyconanomaterials, which is critical for the evaluation of nanomaterials as multivalent scaffolds in enhancing carbohydrate–lectin interactions.
Sajani H. Liyanage, Mingdi Yan
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Characterization of Aptamer-Protein Complexes by X-ray Crystallography and Alternative Approaches [PDF]
Aptamers are oligonucleotide ligands, either RNA or ssDNA, selected for high-affinity binding to molecular targets, such as small organic molecules, proteins or whole microorganisms.
Levisson, M. +24 more
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Affinity of cefoperazone for penicillin-binding proteins [PDF]
Cefoperazone (T-1551, CFP) a new semisynthetic cephalosporin, has a broad spectrum of antibacterial activity. We investigated the affinity of CFP to penicillin-binding proteins (PBPs) and the inhibition of peptidoglycan synthesis by CFP. CFP had high affinities for Escherichia coli PBP-3, -1Bs, -2, and -1A, in descending order, and low affinities for ...
N, Matsubara +4 more
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Specific integrin alpha and beta chain phosphorylations regulate LFA-1 activation through affinity-dependent and -independent mechanisms [PDF]
Integrins are adhesion receptors that are crucial to the functions of multicellular organisms. Integrin-mediated adhesion is a complex process that involves both affinity regulation and cytoskeletal coupling, but the molecular mechanisms behind this ...
Susanna C. Fagerholm +11 more
core +1 more source
Current state of open source force fields in protein-ligand binding affinity predictions
In drug discovery, the in-silico prediction of binding affinity is one of the major means to prioritize compounds for synthesis. Alchemical relative binding free energy (RBFE) calculations based on molecular dynamics (MD) simulations is nowadays a ...
David F., Hahn +4 more
core +1 more source
Learning Protein-Ligand Binding Affinity with Atomic Environment Vectors
Scoring functions for the prediction of protein-ligand binding affinity have seen renewed interest in recent years when novel machine learning and deep learning methods started to consistently outperform classical scoring functions.
Andrew, Anighoro +4 more
core +1 more source
Affinity-enhanced RNA-binding domains as tools to understand RNA recognition
Understanding how the RNA-binding domains of a protein regulator are used to recognize its RNA targets is a key problem in RNA biology, but RNA-binding domains with very low affinity do not perform well in the methods currently available to characterize ...
Evangelos Christodoulou (30025) +6 more
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Reversible domain closure modulates GlnBP ligand binding affinity
Glutamine binding protein (GlnBP) is an Escherichia Coli periplasmic binding protein, which binds and carries glutamine to the inner membrane ATP-binding cassette (ABC) transporter. GlnBP binds the ligand with affinity around 0.1μM measured by isothermal
Qun Chen +13 more
doaj +2 more sources
Learning protein binding affinity using privileged information
Background Determining protein-protein interactions and their binding affinity are important in understanding cellular biological processes, discovery and design of novel therapeutics, protein engineering, and mutagenesis studies.
Wajid Arshad Abbasi +3 more
doaj +1 more source
Prediction of protein-ligand binding affinity with deep learning
The prediction of binding affinities between target proteins and small molecule drugs is essential for speeding up the drug research and design process. To attain precise and effective affinity prediction, computer-aided methods are employed in the drug ...
Yuxiao Wang +5 more
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