Prediction of burial status of transmembrane proteins (TMX).


Sikander Hayat and Yungki Park


Park, Y., Hayat, S., and Helms, V. (2007) BMC Bioinformatics, vol. 8, no. 302, doi: 10.1186/2F1471-2105-8-302. Prediction of the burial status of transmembrane residues of helical membrane proteins.


Transmembrane (TM) proteins are proteins that span the entire lipid bilayer membrane. The two major types are: Alpha helical (HMPs) and Beta barrel  (TMB) proteins. Both types play a crucial role in diverse physiological processes. For example, HMPs participate in energy generation, signal transduction, solute transfer across the membrane and maintenance of ionic and proton gradients, while TMB function include passive transport of ions and small hydrophilic molecules, membrane anchoring and a role in bacterial pathogenicity. Several studies have suggested that HMPs account for 20-30% of open reading frames of sequences genomes, while about 50% of the outer membrane (OM) mass consists of protein, either in the form of integral membrane proteins or as lipo-proteins that are anchored to the membrane.

Since it is very difficult to experimentally determine 3D structures of TMB proteins and given the fact that they perform several important functions in cell proteome of both gram-negative bacteria and eukaryotes, it is imperative to develop in silico methods for the modeling of their 3D structure. The aim of the current study is to provide additional constraints that will aid in their 3D structure prediction. To this end, we have:

  1. developed an algorithm to analytically derive a novel propensity scale for the HMP and TMB residues to be exposed to the lipid bilayer
  2. implemented TransMembrane eXposure (TMX), a novel method for predicting the burial status of HMP residues

The focus of our work is to use well established statistical learning methods to develop methods for prediction of TM residues properties. This additional information will ultimately be used to develop a method for protein 3D structure prediction. Currently, we are working on the development of the TMX webserver to make the burial status prediction mechanism available online for academic purposes.

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