System and methods for predicting transmembrane domains in membrane proteins and mining the genome for recognizing G-protein coupled receptors

Abstract

The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

Description

REFERENCE TO RELATED APPLICATIONS [0001] This application claims the benefit under 35 U.S.C. 119(e) of U.S. Provisional Application No. 60 / 491,334, filed on Jul. 29, 2003, the entire content of which is incorporated herein by reference.GOVERNMENT SUPPORT [0002] The invention described herein was supported, in whole or in part, by Grant Nos. NIHBRGRO1-GM625523, NIH-R29AI40567, NIH-HD36385, and other grants from other U.S. Government Agencies including the Army Research Office (ARO), the Office of Naval Research (ONR), the Department of Energy (DOE), and the National Science Foundation (NSF). The U.S. Government has certain rights in this invention.BACKGROUND OF THE INVENTION [0003] Proteins are linear polymers made up of 20 different naturally-occurring amino acids. The particular linear sequence of amino acid residues in a protein is said to define the protein's primary structure. In its natural environment, a protein folds into a three-dimensional structure determined by its primar...

AI Technical Summary

Benefits of technology

[0013] The invention provides a protocol using a hydrophobic profile based on protein sequence information and / or protein multisequence alignment information to predict transmembrane helical regions in proteins, such as multipass membrane proteins including G-Protein Coupled Receptors (GPCRs). The protocol features a coarse grain sampling methods, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting TM regions.

Problems solved by technology

Determining a protein's tertiary structure is more difficult.

However, these techniques can be time-consuming and expensive, and not all proteins are equally amenable to structural examination by these methods.

In addition, many different types of GPCRs are similar enough that they are affected by the antagonists or agonists for other types (e.g., among adrenergic, dopamine, serotonin, and histamine receptors), leading often to undesirable side effects.

This makes it difficult to develop drugs to a particular subtype without side effects resulting from cross-reactivity to other subtypes.

However, although much effort has been put into elucidating the structure of GPCRs, only a very small number of complete 3D structures of transmembrane proteins are known from experiments (e.g., bacteriorhodopsin and bovine rhodopsin).

In fact, there is no atomic-level structure available for any human GPCRs.

Consequently, design of subtype-specific drugs for GPCR targets is a very tedious empirical process, often leading to drugs with undesirable side effects.

The difficulty in obtaining three-dimensional structures for GPCRs is obtaining high-quality crystals of these membrane-bound proteins sufficient to obtain high-resolution x-ray diffraction data, and the difficulty of using NMR to determine structure on such membrane-bound systems.

For globular proteins, there have been significant advances in predicting the three-dimensional structures by using sequence homologies to families of known structures (Marti-Renom et al., 2000); however, this is not practical for GPCRs, inasmuch as a high-resolution crystal structure is available for only one GPCR, bovine rhodopsin—which has low homology (<35%) to most GPCRs of pharmacological interest.

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