Detecting Binding Affinity to Immobilized Receptor Proteins in Compound Libraries by HR-MAS STD NMR

1999 ◽  
Vol 121 (22) ◽  
pp. 5336-5337 ◽  
Author(s):  
Jens Klein ◽  
Robert Meinecke ◽  
Moriz Mayer ◽  
Bernd Meyer
Keyword(s):  
Binding Affinity ◽  
Receptor Proteins ◽  
Compound Libraries ◽  
Std Nmr ◽  
Immobilized Receptor

scholarly journals Development of 170 MHz Electrodeless Quartz-Crystal Microbalance Immunosensor with Nonspecifically Immobilized Receptor Proteins

2010 ◽  
Vol 49 (7) ◽  
pp. 07HD07 ◽  
Author(s):  
Hirotsugu Ogi ◽  
Hironao Nagai ◽  
Yuji Fukunishi ◽  
Taiji Yanagida ◽  
Masahiko Hirao ◽  
...  
Keyword(s):  
Quartz Crystal Microbalance ◽  
Quartz Crystal ◽  
Receptor Proteins ◽  
Immobilized Receptor

scholarly journals Investigating the binding affinity, molecular dynamics, and ADMET properties of 2,3-dihydrobenzofuran derivatives as an inhibitor of fungi, bacteria, and virus protein

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Ashutosh Nath ◽  
Ajoy Kumer ◽  
Fahmida Zaben ◽  
Md. Wahab Khan
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Binding Affinity ◽  
Salmonella Typhi ◽  
Potential Interaction ◽  
Virus Protein ◽  
Compound Libraries ◽  
Biological Studies ◽  
Effective Role ◽  
Active Residue

Abstract Background 2,3-Dihydrobenzofurans (DHB) have proposed as advantages structures, and used as chemical entresol to design small compound libraries. The present study illustrates to explore 2,3-dihydrobenzofurans(DHB) in comparison to selected some derivatives drugs by using molecular docking and molecular dynamics, as well as ADMET studies. The online database “Molinspiration online server” was used to detect the physicochemical pharmacokinetics and drug likeness score of DHB drugs. For estimation of molecular docking, six pathogens, such as Aspergillus niger (PDB id: 1kum), Candida albicans (3dra), Escherichia coli (6og7), Salmonella typhi (4k6l), Influenza (1ru7), and Hepatitis C (4tyd), were chosen due to close biological studies. Results From Molinspiration online server has showed that DHB did not violate the “Lipinski five rule” as drugs, leading compound for molecular docking exhibited the potential interaction to the active residue. The binding affinity of DHB2 (−7.00 kcal/mol) against 3dra was higher than DHB8 (−6.40 kcal/mol) and DHB (5.70 kcal/mol) for compounds. The results of molecular docking show that the compounds mentioned in this study are not equally effective against pathogens, such as fungi, viruses, and bacteria. However, DHB2, DHB3, and DHB 8 compounds can work against almost given pathogens which results are derived from auto dock vina in terms of binding affinity around 6.00 kcal/mol, and Fire Dock has values from about 38.0 to 42.0 kcal/mol. To explore the dynamic nature of the interaction, 50 ns molecular dynamics (MD) simulation was performed on the selected protein-DHB complexes. Thus, DHB 8 has greater potential to interact for further for fungi. Conclusion Finding from this study can play an effective role as a drug in any biological system. This study as well recommends to researchers to synthesize these DHBs for evaluation of its biological activity. Graphical abstract

scholarly journals CSConv2d: A 2-D Structural Convolution Neural Network with a Channel and Spatial Attention Mechanism for Protein-Ligand Binding Affinity Prediction

Biomolecules ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 643
Author(s):  
Xun Wang ◽  
Dayan Liu ◽  
Jinfu Zhu ◽  
Alfonso Rodriguez-Paton ◽  
Tao Song
Keyword(s):  
Ligand Binding ◽  
Binding Affinity ◽  
Spatial Attention ◽  
Kinase Inhibitors ◽  
Drug Repositioning ◽  
Attention Mechanism ◽  
Receptor Proteins ◽  
Protein Ligand Interactions ◽  
Ligand Interactions ◽  
Better Than

The binding affinity of small molecules to receptor proteins is essential to drug discovery and drug repositioning. Chemical methods are often time-consuming and costly, and models for calculating the binding affinity are imperative. In this study, we propose a novel deep learning method, namely CSConv2d, for protein-ligand interactions’ prediction. The proposed method is improved by a DEEPScreen model using 2-D structural representations of compounds as input. Furthermore, a channel and spatial attention mechanism (CS) is added in feature abstractions. Data experiments conducted on ChEMBLv23 datasets show that CSConv2d performs better than the original DEEPScreen model in predicting protein-ligand binding affinity, as well as some state-of-the-art DTIs (drug-target interactions) prediction methods including DeepConv-DTI, CPI-Prediction, CPI-Prediction+CS, DeepGS and DeepGS+CS. In practice, the docking results of protein (PDB ID: 5ceo) and ligand (Chemical ID: 50D) and a series of kinase inhibitors are operated to verify the robustness.

Antiproliferative and antiviral effects of mutated IFN-alpha with increased IFN receptor binding affinity

2011 ◽  
Vol 49 (01) ◽  
Author(s):  
MF Sprinzl ◽  
L Bührer ◽  
D Strand ◽  
G Schreiber ◽  
PR Galle ◽  
...  
Keyword(s):  
Binding Affinity ◽  
Receptor Binding ◽  
Receptor Binding Affinity ◽  
Ifn Alpha ◽  
Antiviral Effects

Enhancement of Plasminogen Binding to U937 Cells and Fibrin by Complestatin

1997 ◽  
Vol 77 (01) ◽  
pp. 137-142 ◽  
Author(s):  
Kiyoshi Tachikawa ◽  
Keiji Hasurni ◽  
Akira Endo
Keyword(s):  
Binding Site ◽  
Binding Affinity ◽  
Blood Cells ◽  
Aminocaproic Acid ◽  
U937 Cells ◽  
Biochemical Basis ◽  
Equilibrium Binding ◽  
Pharmacological Stimulation ◽  
Endogenous Fibrinolysis ◽  
Stimulation Of

SummaryPlasminogen binds to endothelial and blood cells as well as to fibrin, where the zymogen is efficiently activated and protected from inhibition by α2-antiplasmin. In the present study we have found that complestatin, a peptide-like metabolite of a streptomyces, enhances binding of plasminogen to cells and fibrin. Complestatin, at concentrations ranging from 1 to 5 μM, doubled 125I-plasminogen binding to U937 cells both in the absence and presence of lipoprotein(a), a putative physiological competitor of plasminogen. The binding of 125I-plasminogen in the presence of complestatin was abolished by e-aminocaproic acid, suggesting that the lysine binding site(s) of the plasminogen molecule are involved in the binding. Equilibrium binding analyses indicated that complestatin increased the maximum binding of 125I-plasminogen to U937 cells without affecting the binding affinity. Complestatin was also effective in increasing 125I-plasminogen binding to fibrin, causing 2-fold elevation of the binding at ~1 μM. Along with the potentiation of plasminogen binding, complestatin enhanced plasmin formation, and thereby increased fibrinolysis. These results would provide a biochemical basis for a pharmacological stimulation of endogenous fibrinolysis through a promotion of plasminogen binding to cells and fibrin.

The Role of the Initiator System in the Synthesis of Acidic Multifunctional Nanoparticles Designed for Molecular Imprinting of Proteins

2020 ◽  
Vol 65 (1) ◽  
pp. 28-41
Author(s):  
Marwa Aly Ahmed ◽  
Júlia Erdőssy ◽  
Viola Horváth
Keyword(s):  
Acrylic Acid ◽  
Binding Affinity ◽  
Molecular Imprinting ◽  
Low Temperatures ◽  
Ammonium Persulfate ◽  
Sodium Bisulfite ◽  
Multifunctional Nanoparticles ◽  
High Affinity ◽  
Initiator System

Multifunctional nanoparticles have been shown earlier to bind certain proteins with high affinity and the binding affinity could be enhanced by molecular imprinting of the target protein. In this work different initiator systems were used and compared during the synthesis of poly (N-isopropylacrylamide-co-acrylic acid-co-N-tert-butylacrylamide) nanoparticles with respect to their future applicability in molecular imprinting of lysozyme. The decomposition of ammonium persulfate initiator was initiated either thermally at 60 °C or by using redox activators, namely tetramethylethylenediamine or sodium bisulfite at low temperatures. Morphology differences in the resulting nanoparticles have been revealed using scanning electron microscopy and dynamic light scattering. During polymerization the conversion of each monomer was followed in time. Striking differences were demonstrated in the incorporation rate of acrylic acid between the tetramethylethylenediamine catalyzed initiation and the other systems. This led to a completely different nanoparticle microstructure the consequence of which was the distinctly lower lysozyme binding affinity. On the contrary, the use of sodium bisulfite activation resulted in similar nanoparticle structural homogeneity and protein binding affinity as the thermal initiation.

Destabilizing the Structural Integrity of SARS-CoV2 Receptor Proteins by Curcumin Along with Hydroxychloroquine: An Insilco Approach for a Combination Therapy

2020 ◽  
Author(s):  
Akhileshwar Srivastava ◽  
Divya Singh
Keyword(s):  
Binding Energy ◽  
Combination Therapy ◽  
Receptor Binding ◽  
Structural Integrity ◽  
Binding Domain ◽  
Receptor Binding Domain ◽  
Receptor Proteins ◽  
Main Protease ◽  
The Stability ◽  
Therapeutic Activities

Presently, an emerging disease (COVID-19) has been spreading across the world due to coronavirus (SARS-CoV2). For treatment of SARS-CoV2 infection, currently hydroxychloroquine has been suggested by researchers, but it has not been found enough effective against this virus. The present study based on in silico approaches was designed to enhance the therapeutic activities of hydroxychloroquine by using curcumin as an adjunct drug against SARS-CoV2 receptor proteins: main-protease and S1 receptor binding domain (RBD). The webserver (ANCHOR) showed the higher protein stability for both receptors with disordered score (<0.5). The molecular docking analysis revealed that the binding energy (-24.58 kcal/mol) of hydroxychloroquine was higher than curcumin (-20.47 kcal/mol) for receptor main-protease, whereas binding energy of curcumin (<a>-38.84</a> kcal/mol) had greater than hydroxychloroquine<a> (-35.87</a> kcal/mol) in case of S1 receptor binding domain. Therefore, this study suggested that the curcumin could be used as combination therapy along with hydroxychloroquine for disrupting the stability of SARS-CoV2 receptor proteins

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