Optimal bundling of transmembrane helices using sparse distance constraints

Abstract

We present a two-step approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only sparse distance constraints, such as those derived from chemical crosslinking, dipolar EPR and FRET experiments. In Step 1, using an algorithm, we developed, the conformational space of membrane protein folds matching a set of distance constraints is explored to provide initial structures for local conformational searches. In Step 2, these structures refined against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. We begin by describing the statistical analysis of the solved membrane protein structures from which the theoretical portion of the penalty function was derived. We then describe the penalty function, and, using a set of six test cases, demonstrate that it is capable of distinguishing helical bundles that are close to the native bundle from those that are far from the native bundle. Finally, using a set of only 27 distance constraints extracted from the literature, we show that our method successfully recovers the structure of dark-adapted rhodopsin to within 3.2 Å of the crystal structure.Keywords: helix packing; transmembrane helices; distance constraints; molecular refinement Integral membrane proteins are essential components of the cell membrane that participate in many important cellular processes such as energy transduction, cell signaling, mediation of senses such as vision, cell intoxication, and pathogenesis, and immune recognition. Their significance is emphasized by the fact that approximately one-third of the proteins encoded for by a typical genome are membrane proteins (Buchan et al. 2002). Furthermore, at least 70% of current pharmaceuticals are thought to act on membrane proteins (Wilson and Bergsma 2000). Despite their obvious importance, to date, the structures of fewer than 75 integral membrane proteins have been solved (see White 2003 and references therein), and this number includes redundant structures across species. This is a vast contrast to the over 25,000 soluble proteins whose structures have been solved using X-ray crystallography and NMR. Reasons for the slow progress in the structural analysis of membrane proteins include the instability of membrane proteins in environments lacking phospholipids, their tendency to aggregate and precipitate, and protein abundance, expression, and purification issues. These characteristics highlight why the application of standard structure determination methods to membrane proteins is nontrivial.Given the nature of the difficulties in generating highresolution structural data from methods such as X-ray crystallography and NMR, it is unlikely that these experimental techniques will yield a significant increase in the number of solved membrane protein structures in the near future. As an alternative approach, the focus here is on modeling transmembrane proteins using a set of s...

Simplified modeling approach suggests structural mechanisms for constitutive activation of the C5a receptor

“…It is reasonable to assume that these simplifications in modeling approach will affect the accuracy of reproducing the experimental structures of the TM regions of GPCRs. However, despite these limitations, our approach reproduced the X-ray structure of the TM region of the dark-adapted rhodopsin with an accuracy of the rms value of 2.5 Å, which is quite comparable to other approaches that used experimentally derived constraints on GPCR structures (2.9 Å 40), statistical inter-TM residue potentials (3.2 Å 41), de novo predictions by PREDICT (2.9 Å, 42) and MembStuck (3.1 Å 43), or refined threading approach (2.1 Å 44). …”

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