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The proton-coupled amino acid transporter hPAT1 has recently gained much interest due to its ability to transport small drugs thereby allowing their oral administration. A three-dimensional quantitative structure-activity relationship (3D QSAR) study has been performed on its natural and synthetic substrates employing comparative molecular similarity indices analysis (CoMSIA) to investigate the structural requirements for substrates and to derive a predictive model that may be used for the design of new prodrugs. The cross-validated CoMSIA models have been derived from a training set of 40 compounds and the predictive ability of the resulting models has been evaluated against a test set of 10 compounds. Despite the relatively narrow range of binding affinities (K(i) values) reliable statistical models with good predictive power have been obtained. The best CoMSIA model in terms of a proper balance of all statistical terms and the overall contribution of individual properties has been obtained by considering steric, hydrophobic, hydrogen bond donor and acceptor descriptors (q(cv)(2)=0.683, r(2)=0.958 and r(PRED)(2)=0.666). The 3D QSAR model provides insight in the interactions between substrates and hPAT1 on the molecular level and allows the prediction of affinity constants of new compounds. A pharmacophore model has been generated from the training set by means of the MOE (molecular operating environment) program. This model has been used as a query for virtual screening to retrieve potential new substrates from the small-molecule, 'lead-like' databases of MOE. The affinities of the compounds were predicted and 11 compounds were identified as possible high-affinity substrates. Two selected compounds strongly inhibited the hPAT mediated l-[(3)H]proline uptake into Caco-2 cells constitutively expressing the transport protein., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

The H(+)/peptide cotransporters PEPT1 and PEPT2 have gained considerable interest in pharmaceutical sciences as routes for drug delivery. It is, therefore, of interest to develop uncommon artificial substrates for the two carriers. This study was initiated to investigate the binding affinity of 2-aminothiazole-4-acetic acid (ATAA) conjugates with amino acids to PEPT1 and PEPT2. The 2-aminothiazole-4-acetic acid derivatives have been synthesised and tested for their affinity to PEPT1 and PEPT2. The K(i) values were compared with in silico predicted values from CoMSIA models. C-terminal ATAA-Xaa conjugates proved to be low to medium inhibitors of the [(14)C]Gly-Sar uptake at both carrier systems whereas N-terminal Xaa-ATAA conjugates exhibited medium to high affinity. A promising candidate for further functionalisation is Val-ATAA which shows extraordinary high affinity to PEPT1.

The H(+)/peptide cotransporter PEPT2 is expressed in a variety of organs including kidney, lung, brain, mammary gland, and eye. PEPT2 substrates are di- and tripeptides as well as peptidomimetics, such as beta-lactam antibiotics. Due to the presence of PEPT2 at the bronchial epithelium, the aerosolic administration of peptide-like drugs might play a major role in future treatment of various pulmonary and systemic diseases. Moreover, PEPT2 has a significant influence on the in vivo disposition and half-life time of peptide-like drugs within the body, particularly in kidney and brain. PEPT2 is known to have similar but not identical structural requirements for substrate recognition and transport compared to PEPT1, its intestinal counterpart. In this review we compiled available affinity constants of 352 compounds, measured at different mammalian tissues and expression systems and compare the data whenever possible with those of PEPT1.

The renal type H(+)/peptide cotransporter PEPT2 has a substantial influence on the in vivo disposition of dipeptides and tripeptides as well as peptide-like drugs within the body, particularly in kidney, lung, and the brain. The comparative molecular similarity indices analysis (CoMSIA) method was applied to identify those regions in the substrate structures that are responsible for recognition and for differences in affinity. We have developed a comprehensive 3D quantitative structure-activity relationship (3D-QSAR) model based on 83 compounds that is able to explain and predict the binding affinities of new PEPT2 substrates. This 3D-QSAR model possesses a high predictive power (q(2) = 0.755; r(2) = 0.893). An additional 3D-QSAR model based on the same compounds was generated and correlated with affinity data of the intestinal H(+)/peptide cotransporter PEPT1. By comparing the CoMSIA contour plots, differences in selectivity between the intestinal and the renal type peptide carrier become evident.

The utilization of the membrane transport protein PEPT1 as a drug delivery system is a promising strategy to enhance the oral bioavailability of drugs. Since very little is known about the substrate binding site of PEPT1, computational methods are a meaningful tool to gain a more detailed insight into the structural requirements for substrates. Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies using the comparative molecular similarity indices analysis (CoMSIA) method were performed on a training set of 98 compounds. Affinity constants of beta-lactam antibiotics and tripeptides were determined at Caco-2 cells. A statistically reliable model of high predictive power was obtained (q(2) = 0.828, r(2) = 0.937). The results derived from CoMSIA were graphically interpreted using different field contribution maps. We identified those regions which are crucial for the interaction between peptidomimetics and PEPT1. The new 3D-QSAR model was used to design a new druglike compound mimicking a dipeptide. The predicted K(i) value was confirmed experimentally.

The interaction of the antibacterial phosphonodipeptide alafosfalin with mammalian H(+)/peptide cotransporters was studied in Caco-2 cells, expressing the low-affinity intestinal type peptide transporter 1 (PEPT1), and SKPT cells, expressing the high-affinity renal type peptide transporter 2 (PEPT2). Alafosfalin strongly inhibited the uptake of [(14)C]glycylsarcosine with K(i) values of 0.19 +/- 0.01 mm and 0.07 +/- 0.01 mm for PEPT1 and PEPT2, respectively. Saturation kinetic studies revealed that in both cell types alafosfalin affected only the affinity constant (K(t)) but not the maximal velocity (V(max)) of glycylsarcosine (Gly-Sar) uptake. The inhibition constants and the competitive nature of inhibition were confirmed in Dixon-type experiments. Caco-2 cells and SKPT cells were also cultured on permeable filters: apical uptake and transepithelial apical to basolateral flux of [(14)C]Gly-Sar across Caco-2 cell monolayers were reduced by alafosfalin (3 mm) by 73%. In SKPT cells, uptake of [(14)C]Gly-Sar but not flux was inhibited by 61%. We found no evidence for an inhibition of the basolateral to apical uptake or flux of [(14)C]Gly-Sar by alafosfalin. Alafosfalin (3 mm) did not affect the apical to basolateral [(14)C]mannitol flux. Determined in an Ussing-type experiment with Caco-2 cells cultured in Snapwells trade mark, alafosfalin increased the short-circuit current through Caco-2 cell monolayers. We conclude that alafosfalin interacts with both H(+)/peptide symporters and that alafosfalin is actively transported across the intestinal epithelium in a H(+)-symport, explaining its oral availability. The results also demonstrate that dipeptides where the C-terminal carboxyl group is substituted by a phosphonic function represent high-affinity substrates for mammalian H(+)/peptide cotransporters.

The utilization of the carrier protein PEPT1 for the absorption of peptidomimetic drug molecules is a promising strategy for oral drug administration and increasing bioavailability. In the absence of structural information on the binding mode of substrates to PEPT1, a computational study was conducted to explore the structural requirements for substrates and to derive a predictive model that may be used for the design of novel orally active drugs. A comparative molecular field analysis (CoMFA) and a comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 79 dipeptide-type substrates for which affinity data had been collected in a single test system under the same conditions. These studies produced models with conventional r(2) and cross-validated coefficient (q(2)) values of 0.901 and 0.642 for CoMFA and 0.913 and 0.776 for CoMSIA. The models were validated by an external test set of 19 dipeptides and dipeptide derivatives. CoMSIA contour maps were used to identify the recognition elements that are relevant for the binding of PEPT1 substrates. The 3D QSAR models provide an insight in the interactions between substrates and PEPT1 on the molecular level and allow the prediction of affinity constants of new compounds.