Crystallographic analysis reveals a unique lidocaine binding site on human serum albumin

Hein, Kim L.; Kragh‐Hansen, Ulrich; Morth, J. Preben; Jeppesen, Martin D.; Otzen, Daniel E.; Møller, Jesper; Nissen, Poul

doi:10.1016/j.jsb.2010.03.014

Cited by 103 publications

(61 citation statements)

References 34 publications

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“…The only crystallographic analysis of HSA complexed with a basic drug, lidocaine, revealed a superficially placed binding site in subdomain IB, different than fatty acids and acidic drugs binding sites. Lidocaine binding is due mainly to cation- interactions between the phenyl ring and Arg 114, stabilized by electrostatic interactions (46). The presence of a large number of positively charged residuals in the binding site and the lack of hydrophobic interactions is considered as the main reason for the low binding affinity of lidocaine.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Structure – Pharmacokinetics Relationships for Plasma Protein Binding of Basic Drugs

Zhivkova

2017

J Pharm Pharm Sci

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Purpose. Binding of drugs to plasma proteins is a common physiological occurrence which may have a profound effect on both pharmacokinetics and pharmacodynamics. The early prediction of plasma protein binding (PPB) of new drug candidates is an important step in drug development process. The present study is focused on the development of quantitative structure -pharmacokinetics relationship (QSPkR) for the negative logarithm of the free fraction of the drug in plasma (pf u ) of basic drugs. Methods. A dataset includes 220 basic drugs, which chemical structures are encoded by 176 descriptors. Genetic algorithm, stepwise regression and multiple linear regression are used for variable selection and model development. Predictive ability of the model is assessed by internal and external validation. Results. A simple, significant, interpretable and predictive QSPkR model is constructed for pf u of basic drugs. It is able to predict 59% of the drugs from an external validation set within the 2-fold error of the experimental values with squared correlation coefficient of prediction 0.532, geometric mean fold error (GMFE) 1.94 and mean absolute error (MAE) 0.17. Conclusions. PPB of basic drugs is favored by the lipophilicity, the presence of aromatic C-atoms (either non-substituted, or involved in bridged aromatic systems) and molecular volume. The fraction ionized as a base f B and the presence of quaternary Catoms contribute negatively to PPB. A short checklist of criteria for high PPB is defined, and an empirical rule for distinguishing between low, high and very high plasma protein binders is proposed based. This rule allows correct classification of 69% of the very high binders, 71% of the high binders and 91% of the low binders in plasma.

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Section: Discussionmentioning

confidence: 99%

Quantitative Structure – Pharmacokinetics Relationships for Plasma Protein Binding of Basic Drugs

Zhivkova

2017

J Pharm Pharm Sci

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“…Indeed, 60% of the drugs, containing aaaC atoms, have fu<0.1. On the other hand, the presence of aromatic rings is a prerequisite for hydrophobic, van der Waals, CH-π and π-π interactions in the binding sites of plasma proteins [27,28], and the same interactions may be involved in the binding with transport proteins and metabolizing enzymes. Descriptor SdssC_acnt encodes the number of C-atom connected with two simple and one double bond.…”

Section: Methodsmentioning

confidence: 99%

Quantitative Structure–pharmacokinetics Modeling of the Unbound Clearance for Neutral Drugs

Zhivkova

2018

Int J Curr Pharm Sci

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Objective: Prediction of pharmacokinetic behaviour of new candidate drugs is an important step in drug design. Clearance is a key pharmacokinetic parameter, controlling drug exposure in the body. It depends on numerous factors and is frequently restricted by plasma protein binding. The study is focused on the development of quantitative structure-pharmacokinetic relationship (QSPkR) for the unbound clearance (CLu Methods:The dataset consisted of 117 neutral drugs, divided into training set (n = 94) and external test set (n = 23). Chemical structures were encoded by 113 theoretical descriptors. Genetic algorithm and step-wise multiple linear regression were applied for model development. The model was evaluated by cross-validation in the training set and external test set.) of neutral drugs.Results: Significant, predictive and interpretable QSPkR model was developed with explained variance r 2 = 0.617, cross-validated correlation coefficient q 2 LOO-CV = 0.554, external test set predictive coefficient r 2 pred = 0.656, and root mean square error in prediction RMSEP = 1.89. The model was able to predict CLu Conclusion:The model reveals the main molecular features governing CL for 56% of the drugs in the external test set within the 2-fold error of experimental values.u of neutral drugs. CLu Keywords: QSPkR, Clearance, Unbound clearance, In silico modelling, Prediction of ADME is favoured by lipophilicity, the presence of fused aromatic rings, ester groups, dihydropyridine moieties and nine-member ring systems, while polarity, molecular size and strong electron withdrawing atoms and groups as substituents in aromatic rings affect negatively CL

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“…These four residues are conserved in albumins from mammals. A copious amount of X-ray crystallographic studies have been carried out on HSA [44][45][46][47][48][49][50][51][52][53], with structural information on other serum albumins having become available recently [54,55]. Inspection of these structures reveals that the MBS is consistently only present in fatty acid-free preparations [33] (Figure 1c).…”

Section: +mentioning

confidence: 99%

“…In (d), the four zinc-binding residues are shown with thin lines, and some residues forming the two halves of the FA2 binding pocket are shown as sticks, with the resolved part of a myristate molecule shown in space-filling mode. (c) MBS residues in a selection of X-ray structures with and without (pdb 4G03, 2BXH, 4F5V (rabbit SA), 3V09 (rabbit SA), 3JRY, 1E78, 1AO6, 4K71 (HSA in complex with the Fc receptor) [45,50,51,53,54,55]) bound fatty acids (decanoate (1E7E), dodecanoate (1E7F), myristate (3SQJ, 1E7G), palmitate (1E7H), stearate (1E7I), oleate (1GNI), arachidonate (1GNJ) [47,48]). The overlay was generated by aligning the backbone atoms of residues His247, Gly248, and Asp249 in Swiss pdb viewer v. 3.7.…”

Section: Ffa-mediated Alterations In Plasma Zinc Speciation: Implicatmentioning

confidence: 99%

Fatty Acid-Mediated Inhibition of Metal Binding to the Multi-Metal Site on Serum Albumin: Implications for Cardiovascular Disease

Blindauer

Khazaipoul²,

Yu³

et al. 2016

CTMC

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(2016) Fatty acid-mediated inhibition of metal binding to the multi-metal site on serum albumin : implications for cardiovascular disease. Current Trends in Medicinal Chemistry, 16. Permanent WRAP URL:http://wrap.warwick.ac.uk/78963 Copyright and reuse:The Warwick Research Archive Portal (WRAP) makes this work by researchers of the University of Warwick available open access under the following conditions. Copyright © and all moral rights to the version of the paper presented here belong to the individual author(s) and/or other copyright owners. To the extent reasonable and practicable the material made available in WRAP has been checked for eligibility before being made available.Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.Publisher's statement: © Bentham Science Publishers. http://dx.doi.org/10.2174/1568026616666160216155927 A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Abstract: Human serum albumin (HSA) is the major protein in blood plasma and is responsible for circulatory transport of a range of small molecules including fatty acids, metal ions and drugs. We previously identified the major plasma Zn 2+ transport site on HSA and revealed that fatty-acid binding (at a distinct site called the FA2 site) and Zn 2+ binding are interdependent via an allosteric mechanism. Since binding affinities of long-chain fatty acids exceed those of plasma Zn 2+ , this means that under certain circumstances the binding of fatty acid molecules to HSA is likely to diminish HSA Zn 2+ -binding, and hence affects the control of circulatory and cellular Zn 2+ dynamics. This relationship between circulatory fatty acid and Zn 2+ dynamics is likely to have important physiological and pathological implications, especially since it has been recognised that Zn 2+ acts as a signalling agent in many cell types. Fatty acid levels in the blood are dynamic, but most importantly, chronic elevation of plasma fatty acid levels is associated with some metabolic disorders and disease states -including myocardial infarction and other cardiovascular diseases. In this article, we briefly review the metalbinding properties of albumin and highlight the importance of their interplay with fatty acid binding. We also consider the impact of this dynamic link upon levels and speciation of plasma Zn 2+ , its effect upon cellular Zn 2+ homeostasis and its relevance to cardiovascular and circulatory processes in health and disease.

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Crystallographic analysis reveals a unique lidocaine binding site on human serum albumin

Cited by 103 publications

References 34 publications

Quantitative Structure – Pharmacokinetics Relationships for Plasma Protein Binding of Basic Drugs

Quantitative Structure – Pharmacokinetics Relationships for Plasma Protein Binding of Basic Drugs

Quantitative Structure–pharmacokinetics Modeling of the Unbound Clearance for Neutral Drugs

Fatty Acid-Mediated Inhibition of Metal Binding to the Multi-Metal Site on Serum Albumin: Implications for Cardiovascular Disease

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