Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter

Membrane transporters are critical modulators of drug pharmacokinetics, efficacy, and safety. One example is the proton-dependent oligopeptide transporter PepT1, also known as SLC15A1, which is responsible for the uptake of the β-lactam antibiotics and various peptide-based prodrugs. In this study,...

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Main Authors: Newstead, S, Samsudin, F, Parker, J, Sansom, M, Fowler, P
Format: Journal article
Published: Cell Press 2016
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author Newstead, S
Samsudin, F
Parker, J
Sansom, M
Fowler, P
author_facet Newstead, S
Samsudin, F
Parker, J
Sansom, M
Fowler, P
author_sort Newstead, S
collection OXFORD
description Membrane transporters are critical modulators of drug pharmacokinetics, efficacy, and safety. One example is the proton-dependent oligopeptide transporter PepT1, also known as SLC15A1, which is responsible for the uptake of the β-lactam antibiotics and various peptide-based prodrugs. In this study, we modeled the binding of various peptides to a bacterial homolog, PepTSt, and evaluated a range of computational methods for predicting the free energy of binding. Our results show that a hybrid approach (endpoint methods to classify peptides into good and poor binders and a theoretically exact method for refinement) is able to accurately predict affinities, which we validated using proteoliposome transport assays. Applying the method to a homology model of PepT1 suggests that the approach requires a high-quality structure to be accurate. Our study provides a blueprint for extending these computational methodologies to other pharmaceutically important transporter families.
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spelling oxford-uuid:cf9297be-e847-4ef8-b12d-04c748c5d5dc2022-03-27T07:43:37ZAccurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide TransporterJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:cf9297be-e847-4ef8-b12d-04c748c5d5dcSymplectic Elements at OxfordCell Press2016Newstead, SSamsudin, FParker, JSansom, MFowler, PMembrane transporters are critical modulators of drug pharmacokinetics, efficacy, and safety. One example is the proton-dependent oligopeptide transporter PepT1, also known as SLC15A1, which is responsible for the uptake of the β-lactam antibiotics and various peptide-based prodrugs. In this study, we modeled the binding of various peptides to a bacterial homolog, PepTSt, and evaluated a range of computational methods for predicting the free energy of binding. Our results show that a hybrid approach (endpoint methods to classify peptides into good and poor binders and a theoretically exact method for refinement) is able to accurately predict affinities, which we validated using proteoliposome transport assays. Applying the method to a homology model of PepT1 suggests that the approach requires a high-quality structure to be accurate. Our study provides a blueprint for extending these computational methodologies to other pharmaceutically important transporter families.
spellingShingle Newstead, S
Samsudin, F
Parker, J
Sansom, M
Fowler, P
Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter
title Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter
title_full Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter
title_fullStr Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter
title_full_unstemmed Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter
title_short Accurate Prediction of Ligand Affinities for a Proton-Dependent Oligopeptide Transporter
title_sort accurate prediction of ligand affinities for a proton dependent oligopeptide transporter
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