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Computer Simulations of Structure-Activity Relationships for hERG Channel Blockers
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
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2011 (English)In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 50, no 27, 6146-6156 p.Article in journal (Refereed) Published
Abstract [en]

The hERG potassium channel is of major pharmaceutical importance, and its blockade by various compounds, potentially causing serious cardiac side effects, is a major problem in drug development. Despite the large amounts of existing biochemical data on blockade of hERG by drugs and druglike compounds, relatively little is known regarding the structural basis of binding of blockers to the channel. Here, we have used a recently developed homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations yield a remarkably good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships in terms of a number of key interactions. Two main interaction regions of the channel are thus identified with implications for further mutagenesis experiments and design of new compounds.

Place, publisher, year, edition, pages
2011. Vol. 50, no 27, 6146-6156 p.
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-156474DOI: 10.1021/bi200173nISI: 000292430600018OAI: oai:DiVA.org:uu-156474DiVA: diva2:431954
Available from: 2011-07-27 Created: 2011-07-25 Last updated: 2017-12-08Bibliographically approved
In thesis
1. Computational Modelling of Ligand Complexes with G-Protein Coupled Receptors, Ion Channels and Enzymes
Open this publication in new window or tab >>Computational Modelling of Ligand Complexes with G-Protein Coupled Receptors, Ion Channels and Enzymes
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Accurate predictions of binding free energies from computer simulations are an invaluable resource for understanding biochemical processes and drug action. The primary aim of the work described in the thesis was to predict and understand ligand binding to several proteins of major pharmaceutical importance using computational methods.

We report a computational strategy to quantitatively predict the effects of alanine scanning and ligand modifications based on molecular dynamics free energy simulations. A smooth stepwise scheme for free energy perturbation calculations is derived and applied to a series of thirteen alanine mutations of the human neuropeptide Y1 G-protein coupled receptor and a series of eight analogous antagonists. The robustness and accuracy of the method enables univocal interpretation of existing mutagenesis and binding data. We show how these calculations can be used to validate structural models and demonstrate their ability to discriminate against suboptimal ones. Site-directed mutagenesis, homology modelling and docking were further used to characterize agonist binding to the human neuropeptide Y2 receptor, which is important in feeding behavior and an obesity drug target.  In a separate project, homology modelling was also used for rationalization of mutagenesis data for an integron integrase involved in antibiotic resistance.

Blockade of the hERG potassium channel by various drug-like compounds, potentially causing serious cardiac side effects, is a major problem in drug development. We have used a homology model of hERG to conduct molecular docking experiments with a series of channel blockers, followed by molecular dynamics simulations of the complexes and evaluation of binding free energies with the linear interaction energy method. The calculations are in good agreement with experimental binding affinities and allow for a rationalization of three-dimensional structure-activity relationships with implications for design of new compounds. Docking, scoring, molecular dynamics, and the linear interaction energy method were also used to predict binding modes and affinities for a large set of inhibitors to HIV-1 reverse transcriptase. Good agreement with experiment was found and the work provides a validation of the methodology as a powerful tool in structure-based drug design. It is also easily scalable for higher throughput of compounds.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. 61 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1105
Keyword
computer simulations, molecular dynamics, ligand binding, free energy perturbation, linear interaction energy, binding free energy, homology modelling, structure prediction, alanine scanning, site-directed mutagenesis, hERG, GPCR, neuropeptide Y, HIV-1 reverse transcriptase, integron integrase
National Category
Theoretical Chemistry Structural Biology Biochemistry and Molecular Biology
Research subject
Molecular Biotechnology
Identifiers
urn:nbn:se:uu:diva-212103 (URN)978-91-554-8823-9 (ISBN)
Public defence
2014-01-31, B42, BMC, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2014-01-10 Created: 2013-12-05 Last updated: 2014-01-24
2. Advances in Ligand Binding Predictions using Molecular Dynamics Simulations
Open this publication in new window or tab >>Advances in Ligand Binding Predictions using Molecular Dynamics Simulations
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Biochemical processes all involve associations and dissociations of chemical entities. Understanding these is of substantial importance for many modern pharmaceutical applications. In this thesis, longstanding problems with regard to ligand binding are treated with computational methods, applied to proteins of key pharmaceutical importance. Homology modeling, docking, molecular dynamics simulations and free-energy calculations are used here for quantitative characterization of ligand binding to proteins. By combining computational tools, valuable contributions have been made for pharmaceutically relevant areas: a neglected tropical disease, an ion channel anti-drug-target, and GPCR drug-targets.

We report three compounds inhibiting cruzain, the main cysteine protease of the protozoa causing Chagas’ disease. The compounds were found through an extensive virtual screening study and validated with experimental enzymatic assays. The compounds inhibit the enzyme in the μM-range and are therefore valuable in further lead optimization studies.

A high-resolution crystal structure of the BRICHOS domain is reported, together with molecular dynamics simulations and hydrogen-deuterium exchange mass spectrometry studies. This work revealed a plausible mechanism for how the chaperone activity of the domain may operate.

Rationalization of structure-activity relationships for a set of analogous blockers of the hERG potassium channel is given. A homology model of the ion channel was used for docking compounds and molecular dynamics simulations together with the linear interaction energy method employed for calculating the binding free-energies.

The three-dimensional coordinates of two GPCRs, 5HT1B and 5HT2B, were derived from homology modeling and evaluated in the GPCR Dock 2013 assessment. Our models were in good correlation with the experimental structures and all of them placed among the top quarter of all models assessed. 

Finally, a computational method, based on molecular dynamics free-energy calculations, for performing alanine scanning was validated with the A2A adenosine receptor bound to either agonist or antagonist. The calculated binding free-energies were found to be in good agreement with experimental data and the method was subsequently extended to non-alanine mutations. With extensive experimental mutation data, this scheme is a valuable tool for quantitative understanding of ligand binding and can ultimately be used for structure-based drug design.

Place, publisher, year, edition, pages
Uppsala: Uppsala universitet, 2014. 51 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1172
Keyword
free-energy perturbation, molecular dynamics, ligand binding, free-energy perturbation, linear interaction energy, binding free-energy, homology modeling, virtual screening, alanine scanning, amino acid mutagenesis, hERG, GPCR, adenosine receptor, serotonin receptor, BRICHOS, cruzain
National Category
Theoretical Chemistry Biological Sciences
Identifiers
urn:nbn:se:uu:diva-230777 (URN)978-91-554-9020-1 (ISBN)
Public defence
2014-10-15, B41, BMC, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2014-09-23 Created: 2014-08-29 Last updated: 2015-01-23

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