Elsevier

Drug Discovery Today

Volume 10, Issue 9, 1 May 2005, Pages 663-671
Drug Discovery Today

Review
In silico strategies for modeling membrane transporter function

https://doi.org/10.1016/S1359-6446(05)03429-XGet rights and content

Transporter proteins facilitate the transfer of solutes across the cell membrane and have an intricate role in drug absorption, distribution and excretion. Because of their substrate promiscuity, several transporters represent viable pharmacological targets for enhancing drug absorption, preventing drug toxicity or facilitating localized tissue delivery. However, the slow emergence of high-resolution structures for these proteins has hampered the intelligent design of transporter substrates. Nonetheless, currently available functional, as well as structural, data provide an attractive scaffold for generating fusion models that merge substrate-based SARs and protein-based homology structures. The resultant models offer features that extend single modality paradigms in predictive function.

Section snippets

Comparative modeling

The primary amino acid sequences of many transporters are known and solution of their secondary structures is facilitated by bioinformatics tools, such as hydropathy plotting, and, preferably, by a combination of experimental verification methods, such as N-glycosylation analysis or epitope insertion scanning [3, 4]. Although only a few transporter proteins have been analyzed by X-ray crystallography and afforded high-resolution 3D information, new structures are emerging at a steady rate,

Ligand-based methods

In silico approaches based on molecular level transporter models could be used to predict ligand- and inhibitor-binding modes, thus representing a useful tool in the discovery of novel transporter substrates. Although comparative models can be generated successfully for membrane proteins with seven or 12 TMDs, this approach is not yet feasible for proteins without a suitable TMD template. In these cases, techniques that do not require knowledge of transporter structure can be applied, such as

Combination in silico approaches

In silico methods represent one of numerous useful tools to study the transport mechanism and substrate affinity requirements of membrane transporters. It efficiently fills the gap between our knowledge of atomic level transporter structural mechanisms and in vitro transporter properties derived by biochemical experiments. This type of hybrid approach will eventually lead to the discovery of safer and more efficient drugs by targeting transporters or, in the case of efflux pumps, avoiding them

Future perspectives

Clearly, the future of transporter modeling will lie in the realm of combination in silico approaches. The grouping of QSAR and homology modeling techniques has been pioneered in the receptor pharmacology area and could now be applied to transporter families. Furthermore, the emergence of expression systems and HTS methods has enabled the collection of functional data on many transporter homologues and orthologues. The era of modeling individual transporters will now give way to comparative

References (61)

  • ChangG.

    Structure of MsbA from Vibrio cholera: a multidrug resistance ABC transporter homolog in a closed conformation

    J. Mol. Biol.

    (2003)
  • LeeJ.Y.

    Projection structure of P-glycoprotein by electron microscopy. Evidence for a closed conformation of the nucleotide binding domains

    J. Biol. Chem.

    (2002)
  • CampbellJ.D.

    Molecular modeling correctly predicts the functional importance of Phe594 in transmembrane helix 11 of the multidrug resistance protein, MRP1 (ABCC1)

    J. Biol. Chem.

    (2004)
  • HolmL. et al.

    Database algorithm for generating protein backbone and side-chain co-ordinates from a C alpha trace application to model building and detection of co-ordinate errors

    J. Mol. Biol.

    (1991)
  • HuangM.

    Inhibition of nucleoside transport by p38 MAPK inhibitors

    J. Biol. Chem.

    (2002)
  • BaringhausK.H.

    Substrate specificity of the ileal and the hepatic Na+/bile acid cotransporters of the rabbit. II. A reliable 3D QSAR pharmacophore model for the ileal Na+/bile acid cotransporter

    J. Lipid Res.

    (1999)
  • JahnigF. et al.

    Modeling of the structure of bacteriorhodopsin. A molecular dynamics study

    J. Mol. Biol.

    (1992)
  • XiangZ. et al.

    Extending the accuracy limits of prediction for side-chain conformations

    J. Mol. Biol.

    (2001)
  • Salas-BurgosA.

    Predicting the three-dimensional structure of the human facilitative glucose transporter Glut1 by a novel evolutionary homology strategy: insights on the molecular mechanism of substrate migration, and binding sites for glucose and inhibitory molecules

    Biophys. J.

    (2004)
  • GottschalkK.E.

    Structure prediction of small transmembrane helix bundles

    J. Mol. Graph. Model.

    (2004)
  • GottschalkK.E.

    A structural model of EmrE, a multi-drug transporter from Escherichia coli.

    Biophys. J.

    (2004)
  • RomanD.L.

    Interactions of antidepressants with the serotonin transporter: a contemporary molecular analysis

    Eur. J. Pharmacol.

    (2003)
  • GeldenhuysW.J.

    Molecular modeling studies on the active binding site of the blood–brain barrier choline transporter

    Bioorg. Med. Chem. Lett.

    (2004)
  • GrisshammerR. et al.

    Overexpression of integral membrane proteins for structural studies

    Q. Rev. Biophys.

    (1995)
  • ZhangE.Y.

    Topology scanning and putative three-dimensional structure of the extracellular binding domains of the apical sodium-dependent bile acid transporter (SLC10A2)

    Biochemistry

    (2004)
  • LeachA.R.

    Molecular Modelling. Principles and Applications

    (2001)
  • LaskowskiR.A.

    PROCHECK: a program to check the stereochemical quality of protein structures

    J. Appl. Crystallogr.

    (1993)
  • HuangY.

    Structure and mechanism of the glycerol-3-phosphate transporter from Escherichia coli

    Science

    (2003)
  • AlmqvistJ.

    Homology modeling of the human microsomal glucose 6-phosphate transporter explains the mutations that cause the glycogen storage disease type Ib

    Biochemistry

    (2004)
  • KarplusM. et al.

    Molecular dynamics simulations of biomolecules

    Nat. Struct. Biol.

    (2002)
  • Cited by (0)

    View full text