scholarly journals Drug-binding properties of rat α-foetoprotein. Specificities of the phenylbutazone-binding and warfarin-binding sites

1986 ◽  
Vol 239 (2) ◽  
pp. 451-458 ◽  
Author(s):  
F Hervé ◽  
K M Rajkowski ◽  
M T Martin ◽  
P Dessen ◽  
N Cittanova

Rat alpha-foetoprotein (alpha-FP) strongly binds the drugs warfarin and phenylbutazone, as does albumin; however, the binding sites for the two drugs seemed to be different. This possibility and the specificity of this/these drug-binding site(s) of rat alpha-FP were investigated by competitive protein-binding experiments with a variety of drugs, representing different pharmacological groups, and biomolecules that are strongly bound by the foetal protein and that are suspected to play a specific role during foetal development. The binding mechanisms were further investigated by using comparisons between computer-derived theoretical displacement curves and experimental points in order to distinguish different possible binding models. The results indicate: that warfarin and phenylbutazone are bound at two distinct sites on rat alpha-FP and that a negative modulatory effect is exerted between the two sites; that the degree of specificity of these two drug-binding sites is different, since the warfarin-binding site appears to be specific for the binding of coumarinic and anthranilic drugs whereas that for phenylbutazone is able to bind substances of very varied chemical structure and is more hydrophobic; that the phenylbutazone-binding site is the site that binds oestrogens that thyroid hormones and, probably, fatty acids and bilirubin are bound at (an)other site(s) but exert negative modulatory effects on phenylbutazone binding. The nature of the different binding areas of rat alpha-FP is compared with that of those already proposed for albumin. The potential risks of toxicity of such interactions between drugs and/or biomolecules on foetal development are also discussed.

Author(s):  
S.F. Hoff ◽  
A.J. Macinnis

The need for a high resolution morphological method of identifying drug binding sites has been mentioned by several authors. Electron microscopic autoradiography may identify statisically an organelle as a drug binding site, but in practice has proven unreliable. This is primarily due to the tissue preparatory procedures used in conventional electron microscopy, which denature proteins and extract many proteins and lipid components from the tissue. As the drug binding sites are denatured and/or extracted, drugs are displaced from their “receptors.” Then the drugs are either extracted or attached to an anomolous binding site created by the preparatory procedure. Sjöstrand's minimal denaturation technique is based on a sound physical-chemical rationale and was modified slightly to accommodate the drug localization procedure used in this study.It was found after many experiments that phosphotungstic acid (PTA) at pH7 had the highest specificity for the drugs used in this study and the lowest affinity for biological structures.


2017 ◽  
Author(s):  
Gregory M. Martin ◽  
Balamurugan Kandasamy ◽  
Frank DiMaio ◽  
Craig Yoshioka ◽  
Show-Ling Shyng

AbstractSulfonylureas are anti-diabetic medications that act by inhibiting pancreatic KATP channels composed of SUR1 and Kir6.2. The mechanism by which these drugs interact with and inhibit the channel has been extensively investigated, yet it remains unclear where the drug binding pocket resides. Here, we present a cryo-EM structure of the channel bound to a high-affinity sulfonylurea drug glibenclamide and ATP at 3.8Å resolution, which reveals in unprecedented details of the ATP and glibenclamide binding sites. Importantly, the structure shows for the first time that glibenclamide is lodged in the transmembrane bundle of the SUR1-ABC core connected to the first nucleotide binding domain near the inner leaflet of the lipid bilayer. Mutation of residues predicted to interact with glibenclamide in our model led to reduced sensitivity to glibenclamide. Our structure provides novel mechanistic insights of how sulfonylureas and ATP interact with the KATP channel complex to inhibit channel activity.


2020 ◽  
Author(s):  
Mohamed Fadlalla

<p>SARS CoV 2 has spread worldwide and caused a major outbreak of coronavirus disease 2019 (COVID-19). To date, no licensed drug or a vaccine is available against COVID19.</p><p>Starting from all of the resolved SARS CoV2 crystal structures, this study aims to find inhibitors for all of the SARS CoV2 proteins. To achieve this, I used PocketMatch to test the similarity of approved drugs binding sites against all of the binding sites found on SARS CoV 2 proteins. After that docking was used to confirm the results.</p><p>I found drugs that inhibit the main protease, Nsp12 and Nsp3. The discovered drugs are either in clinical trials (Sildenafil, Lopinavir, Ritonavir) or have in vitro antiviral activity (Nelfinavir, Indinavir, Amprenavir, depiqulinum , Gemcitabine, Raltitrexed, Aprepitant, montelukast, Ouabain, Raloxifene) whether against SARS CoV 2 or other viruses. In addition to this, further analysis of pockets revealed a steroidal pocket that might open the door to hypotheses on why the mortality of men is higher than women.</p><p>Many of the in silico repurposing studies test binding of the compound to the target using docking. The significance of this study adds to the similarity between the drug binding site and the target binding site. This takes into consideration the dynamic behaviour of the pocket after ligand binding.</p><div><br></div>


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Mingjian Jiang ◽  
Zhen Li ◽  
Yujie Bian ◽  
Zhiqiang Wei

Abstract Background Binding sites are the pockets of proteins that can bind drugs; the discovery of these pockets is a critical step in drug design. With the help of computers, protein pockets prediction can save manpower and financial resources. Results In this paper, a novel protein descriptor for the prediction of binding sites is proposed. Information on non-bonded interactions in the three-dimensional structure of a protein is captured by a combination of geometry-based and energy-based methods. Moreover, due to the rapid development of deep learning, all binding features are extracted to generate three-dimensional grids that are fed into a convolution neural network. Two datasets were introduced into the experiment. The sc-PDB dataset was used for descriptor extraction and binding site prediction, and the PDBbind dataset was used only for testing and verification of the generalization of the method. The comparison with previous methods shows that the proposed descriptor is effective in predicting the binding sites. Conclusions A new protein descriptor is proposed for the prediction of the drug binding sites of proteins. This method combines the three-dimensional structure of a protein and non-bonded interactions with small molecules to involve important factors influencing the formation of binding site. Analysis of the experiments indicates that the descriptor is robust for site prediction.


2020 ◽  
Author(s):  
Mohamed Fadlalla

<p>SARS CoV 2 has spread worldwide and caused a major outbreak of coronavirus disease 2019 (COVID-19). To date, no licensed drug or a vaccine is available against COVID19.</p><p>Starting from all of the resolved SARS CoV2 crystal structures, this study aims to find inhibitors for all of the SARS CoV2 proteins. To achieve this, I used PocketMatch to test the similarity of approved drugs binding sites against all of the binding sites found on SARS CoV 2 proteins. After that docking was used to confirm the results.</p><p>I found drugs that inhibit the main protease, Nsp12 and Nsp3. The discovered drugs are either in clinical trials (Sildenafil, Lopinavir, Ritonavir) or have in vitro antiviral activity (Nelfinavir, Indinavir, Amprenavir, depiqulinum , Gemcitabine, Raltitrexed, Aprepitant, montelukast, Ouabain, Raloxifene) whether against SARS CoV 2 or other viruses. In addition to this, further analysis of pockets revealed a steroidal pocket that might open the door to hypotheses on why the mortality of men is higher than women.</p><p>Many of the in silico repurposing studies test binding of the compound to the target using docking. The significance of this study adds to the similarity between the drug binding site and the target binding site. This takes into consideration the dynamic behaviour of the pocket after ligand binding.</p><div><br></div>


2014 ◽  
Vol 70 (a1) ◽  
pp. C1793-C1793
Author(s):  
Paul Rowland ◽  
Onkar SINGH ◽  
Leila Ross ◽  
Francisco Gamo ◽  
Maria Lafuente-Monasterio ◽  
...  

Malaria is a preventable and treatable disease, yet annually there are still hundreds of thousands of malaria-related deaths. The disease is caused by infection with mosquito-borne Plasmodium parasites. With hundreds of millions of cases each year there is a very high potential for drug resistance and this has compromised many existing therapies. One target under investigation is the enzyme dihydroorotate dehydrogenase (DHODH) which catalyses the rate-limiting step of pyrimidine biosynthesis and is an essential enzyme in the malaria parasite. There are currently several Plasmodium-selective DHODH inhibitors under development. To investigate the potential for drug resistance against DHODH inhibitors in vitro resistance selections were carried out using known inhibitors from different structural classes [1]. These studies identified point mutations in the drug binding site which lead to reduced sensitivity to the inhibitors, and in some cases increased sensitivity to a different inhibitor, suggesting a novel combination therapy approach to combat resistance. To help understand the significance of the inhibitor binding site mutations we determined the crystal structures of P. falciparum DHODH in complex with the inhibitors Genz-669178, IDI-6253 and IDI-6273. Co-crystallisation experiments led to a new crystal form in each case. Here we describe the crystal structures, the binding modes of the inhibitors and the great flexibility of the binding site, which is able to adjust to accommodate different inhibitor series. The structural role of the resistance mutations is also discussed.


2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Mónika Bálint ◽  
Norbert Jeszenői ◽  
István Horváth ◽  
David van der Spoel ◽  
Csaba Hetényi

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