Development of a QSAR Model for Binding of Tripeptides and Tripeptidomimetics to the Human Intestinal Di-/Tripeptide Transporter hPEPT1

Structure-based model profiles affinity constant of drugs with hPEPT1 for rapid virtual screening of hPEPT1's substrate

The human proton-coupled peptide transporter (hPEPT1) with broad substrates is an important route for improving the pharmacokinetic performance of drugs. Thus, it is essential to predict the affinity constant between drug molecule and hPEPT1 for rapid virtual screening of hPEPT1's substrate during lead optimization, candidate selection and hPEPT1 prodrug design. Here, a structure-based in silico model for 114 compounds was constructed based on eight structural parameters. This model was built by the multiple linear regression method and satisfied all the prerequisites of the regression models. For the entire data set, the r(2) and adjusted r(2) values were 0.74 and 0.72, respectively. Then, this model was used to perform substrate/non-substrate classification. For 29 drugs from DrugBank database, all were correctly classified as substrates of hPEPT1. This model was also used to perform substrate/non-substrate classification for 18 drugs and their prodrugs; this QSAR model also can distinguish between the substrate and non-substrate. In conclusion, the QSAR model in this paper was validated by a large external data set, and all results indicated that the developed model was robust, stable, and can be used for rapid virtual screening of hPEPT1's substrate in the early stage of drug discovery.

The tandem chain extension aldol reaction used for synthesis of ketomethylene tripeptidomimetics targeting hPEPT1

The rationale for targeting the human di-/tripeptide transporter hPEPT1 for oral drug delivery has been well established by several drug and prodrug cases. The aim of this study was to synthesize novel ketomethylene modified tripeptidomimetics and to investigate their binding affinity for hPEPT1. Three related tripeptidomimetics of the structure H-Phe-ψ[COCH(2)]-Ser(Bz)-X(aa)-OH were synthesized applying the tandem chain extension aldol reaction, where amino acid derived β-keto imides were stereoselectively converted to α-substituted γ-keto imides. In addition, three corresponding tripeptides, composed of amide bonds, were synthesized for comparison of binding affinities. The six investigated compounds were all defined as high affinity ligands (K(i)-values <0.5 mM) for hPEPT1 by measuring the concentration dependent inhibition of apical [(14)C]Gly-Sar uptake in Caco-2 cells. Consequently, the ketomethylene replacement for the natural amide bond and α-side chain modifications appears to offer a promising strategy to modify tripeptidic structures while maintaining a high affinity for hPEPT1.

Bioavailability through PepT1: the role of computer modelling in intelligent drug design

In addition to being responsible for the majority of absorption of dietary nitrogen, the mammalian proton-coupled di- and tri-peptide transporter PepT1 is also recognised as a major route of drug delivery for several important classes of compound, including beta-lactam antibiotics and angiotensin-converting enzyme inhibitors. Thus there is considerable interest in the PepT1 protein and especially its substrate binding site. In the absence of a crystal structure, computer modelling has been used to try to understand the relationship between PepT1 3D structure and function. Two basic approaches have been taken: modelling the transporter protein, and modelling the substrate. For the former, computer modelling has evolved from early interpretations of the twelve transmembrane domain structure to more recent homology modelling based on recently crystallised bacterial members of the major facilitator superfamily (MFS). Substrate modelling has involved the proposal of a substrate binding template, to which all substrates must conform and from which the affinity of a substrate can be estimated relatively accurately, and identification of points of potential interaction of the substrate with the protein by developing a pharmacophore model of the substrates. Most recently, these two approaches have moved closer together, with the attempted docking of a substrate library onto a homology model of the human PepT1 protein. This article will review these two approaches in which computers have been applied to peptide transport and suggest how such computer modelling could affect drug design and delivery through PepT1.

Targeting drug transporters - combining in silico and in vitro approaches to predict in vivo

Transporter proteins are expressed throughout the human body in different vital organs. They play an important role to various extents in determining absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties of therapeutic molecules. Over the past decade, numerous drug transporters have been cloned and considerable progress has been made toward understanding the molecular characteristics of individual transporters. In this chapter several in vitro and in silico techniques are described with applications to understand transporter behavior. These include employing new techniques to rapidly identify novel ligands for transporters. Ultimately these methods should lead to a greater overall appreciation of the role of transporters in vivo.

A quantitative structure-activity relationship for translocation of tripeptides via the human proton-coupled peptide transporter, hPEPT1 (SLC15A1)

The human intestinal proton-coupled peptide transporter, hPEPT1 (SLC15A1), has been identified as an absorptive transporter for both drug substances and prodrugs. An understanding of the prerequisites for transport has so far been obtained from models based on competition experiments. These models have limited value for predicting substrate translocation via hPEPT1. The aim of the present study was to investigate the requirements for translocation via hPEPT1. A set of 55 tripeptides was selected from a principal component analysis based on VolSurf descriptors using a statistical design. The majority of theses tripeptides have not previously been investigated. Translocation of the tripeptides via hPEPT1 was determined in a MDCK/hPEPT1 cell-based translocation assay measuring substrate-induced changes in fluorescence of a membrane potential-sensitive probe. Affinities for hPEPT1 of relevant tripeptides were determined by competition studies with [14C]Gly-Sar in MDCK/hPEPT1 cells. Forty tripeptides were found to be substrates for hPEPT1, having K(m)(app) values in the range 0.4-28 mM. Eight tripeptides were not able to cause a substrate-induced change in fluorescence in the translocation assay and seven tripeptides interacted with the probe itself. The conformationally restricted tripeptide Met-Pro-Pro was identified as a novel high-affinity inhibitor of hPEPT1. We also discovered the first tripeptide (Asp-Ile-Arg) that was neither a substrate nor an inhibitor of hPEPT1. To rationalise the requirements for transport, a quantitative structure-activity relationship model correlating K(m)(app) values with VolSurf descriptors was constructed. This is, to our knowledge, the first predictive model for the translocation of tripeptides via hPEPT1.

Pharmaceutical and pharmacological importance of peptide transporters

Peptide transport is currently a prominent topic in membrane research. The transport proteins involved are under intense investigation because of their physiological importance in protein absorption and also because peptide transporters are possible vehicles for drug delivery. Moreover, in many tissues peptide carriers transduce peptidic signals across membranes that are relevant in information processing. The focus of this review is on the pharmaceutical relevance of the human peptide transporters PEPT1 and PEPT2. In addition to their physiological substrates, both carriers transport many β-lactam antibiotics, valaciclovir and other drugs and prodrugs because of their sterical resemblance to di- and tripeptides. The primary structure, tissue distribution and substrate specificity of PEPT1 and PEPT2 have been well characterized. However, there is a dearth of knowledge on the substrate binding sites and the three-dimensional structure of these proteins. Until this pivotal information becomes available by X-ray crystallography, the development of new drug substrates relies on classical transport studies combined with molecular modelling. In more than thirty years of research, data on the interaction of well over 700 di- and tripeptides, amino acid and peptide derivatives, drugs and prodrugs with peptide transporters have been gathered. The aim of this review is to put the reports on peptide transporter-mediated drug uptake into perspective. We also review the current knowledge on pharmacogenomics and clinical relevance of human peptide transporters. Finally, the reader's attention is drawn to other known or proposed human peptide-transporting proteins.

QSAR models for the human H(+)/peptide symporter, hPEPT1: affinity prediction using alignment-independent descriptors

A data set comprising the major known chemical classes of hPEPT1 ligands was compiled from the literature. For these compounds, alignment-independent descriptors (VolSurf, GRIND/Almond, and MOE) were computed. Using hierarchical partial least-squares projection to latent structures (H-PLS), a one-component model with r2 = 0.77 and q2 = 0.75 was obtained. The model satisfied a set of rigorous validation criteria and performed well in the prediction of an external test set. Mechanistic interpretation of the model reveals polarity properties to be the dominant factors in determining hPEPT1 affinity, with hydrophobic interactions contributing to a lesser extent. The model is superior to previously reported models due to its combination of quality and speed. Accordingly, it is suitable for ligand-based virtual screening, such as QSAR-based database mining.

Artificial neural network models for prediction of intestinal permeability of oligopeptides

BACKGROUND

Oral delivery is a highly desirable property for candidate drugs under development. Computational modeling could provide a quick and inexpensive way to assess the intestinal permeability of a molecule. Although there have been several studies aimed at predicting the intestinal absorption of chemical compounds, there have been no attempts to predict intestinal permeability on the basis of peptide sequence information. To develop models for predicting the intestinal permeability of peptides, we adopted an artificial neural network as a machine-learning algorithm. The positive control data consisted of intestinal barrier-permeable peptides obtained by the peroral phage display technique, and the negative control data were prepared from random sequences.

RESULTS

The capacity of our models to make appropriate predictions was validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). The training and test set statistics indicated that our models were of strikingly good quality and could discriminate between permeable and random sequences with a high level of confidence.

CONCLUSION

We developed artificial neural network models to predict the intestinal permeabilities of oligopeptides on the basis of peptide sequence information. Both binary and VHSE (principal components score Vectors of Hydrophobic, Steric and Electronic properties) descriptors produced statistically significant training models; the models with simple neural network architectures showed slightly greater predictive power than those with complex ones. We anticipate that our models will be applicable to the selection of intestinal barrier-permeable peptides for generating peptide drugs or peptidomimetics.

Design, Synthesis, and Evaluation of Tripeptidic Promoieties Targeting the Intestinal Peptide Transporter hPEPT1

The human intestinal proton coupled di/tri-peptide transporter hPEPT1 promotes the oral bioavailability of several drug compounds. The strategy behind the present work is that by linking a suitable di- or tripeptidic promoiety to a drug substance, by a hydrolysable ester bond, it may give rise to a prodrug that targets hPEPT1. 29 tripeptides were designed based on known structural requirements for substrates binding hPEPT1. Serine, homoserine, or threonine was incorporated in the tripeptide as hydroxy group donors in order for them to be linked to carboxylic drug substances. Optimisation of the promoiety included a study of 14 unnatural tripeptides whose diversity was expressed by VolSurf descriptors. A total of 29 tripeptides was synthesised by solid phase peptide synthesis and a standard Fmoc protocol. The affinity of the tripeptides to hPEPT1 was determined by measuring the inhibition of [(14)C]Gly-Sar in mature Caco-2 cell monolayers which resulted in K(i) values ranging from 0.22 to 25 mM or above. Translocation through the intestinal membrane, mediated by hPEPT1, was measured by recording the membrane potential relative to that induced by the known substrate Gly-Sar. The change in membrane potential is caused by influx of protons due to the co-transport of substrates and protons by hPEPT1 and is, as such, an indication of translocation. A K(i) value of 0.30 mM combined with efficient translocation indicated that H-Phe-Ser-Ala-OH is a suitable lead promoiety for targeted hPEPT1 prodrug design.

In vitro evaluation of N-methyl amide tripeptidomimetics as substrates for the human intestinal di-/tri-peptide transporter hPEPT1

Oral absorption of tripeptides is generally mediated by the human intestinal di-/tri-peptide transporter, hPEPT1. However, the bioavailability of tripeptides is often limited due to degradation in the GI-tract by various peptidases. The aim of the present study was to evaluate the general application of N-methyl amide bioisosteres as peptide bond replacements in tripeptides in order to decrease degradation by peptidases and yet retain affinity for and transport via hPEPT1. Seven structurally diverse N-methyl amide tripeptidomimetics were selected based on a principal component analysis of structural properties of 6859 N-methyl amide tripeptidomimetics. In vitro extracellular degradation of the selected tripeptidomimetics as well as affinity for and transepithelial transport via hPEPT1 were investigated in Caco-2 cells. Decreased apparent degradation was observed for all tripeptidomimetics compared to the corresponding natural tripeptides. However, affinity for and transepithelial transport via hPEPT1 were only seen for Gly-Sar-Sar, AsnPsi[CONCH(3)]PhePsi[CONCH(3)]Trp, and Gly-Sar-Leu. This implies that tripeptidomimetics originating from tripeptides with neutral side chains are more likely to be substrates for hPEPT1 than tripeptidomimetics with charged side chains. The results of the present study indicate that the N-methyl amide peptide bond replacement approach for increasing bioavailability of tripeptidomimetic drug candidates is not generally applicable to all tripeptides. Nevertheless, retained affinity for and transport via hPEPT1 were shown for three of the evaluated N-methyl amide tripeptidomimetics.