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Order out of disorder: working cycle of an intrinsically unfolded chaperone.

ABSTRACT: The redox-regulated chaperone Hsp33 protects organisms against oxidative stress that leads to protein unfolding. Activation of Hsp33 is triggered by the oxidative unfolding of its own redox-sensor domain, making Hsp33 a member of a recently discovered class of chaperones that require partial unfolding for full chaperone activity. Here we address the long-standing question of how chaperones recognize client proteins. We show that Hsp33 uses its own intrinsically disordered regions to discriminate between unfolded and partially structured folding intermediates. Binding to secondary structure elements in client proteins stabilizes Hsp33's intrinsically disordered regions, and this stabilization appears to mediate Hsp33's high affinity for structured folding intermediates. Return to nonstress conditions reduces Hsp33's disulfide bonds, which then significantly destabilizes the bound client proteins and in doing so converts them into less-structured, folding-competent client proteins of ATP-dependent foldases. We propose a model in which energy-independent chaperones use internal order-to-disorder transitions to control substrate binding and release.

SUBMITTER: Reichmann D

PROVIDER: S-EPMC3376891 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Order out of disorder: working cycle of an intrinsically unfolded chaperone.

Reichmann Dana D Xu Ying Y Cremers Claudia M CM Ilbert Marianne M Mittelman Roni R Fitzgerald Michael C MC Jakob Ursula U

Cell 20120301 5

The redox-regulated chaperone Hsp33 protects organisms against oxidative stress that leads to protein unfolding. Activation of Hsp33 is triggered by the oxidative unfolding of its own redox-sensor domain, making Hsp33 a member of a recently discovered class of chaperones that require partial unfolding for full chaperone activity. Here we address the long-standing question of how chaperones recognize client proteins. We show that Hsp33 uses its own intrinsically disordered regions to discriminate ...[more]

PMID: 22385960

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Project description:The focus of the computational structural biology community has taken a dramatic shift over the past one-and-a-half decades from the classical protein structure prediction problem to the possible understanding of intrinsically disordered proteins (IDP) or proteins containing regions of disorder (IDPR). The current interest lies in the unraveling of a disorder-to-order transitioning code embedded in the amino acid sequences of IDPs/IDPRs. Disordered proteins are characterized by an enormous amount of structural plasticity which makes them promiscuous in binding to different partners, multi-functional in cellular activity and atypical in folding energy landscapes resembling partially folded molten globules. Also, their involvement in several deadly human diseases (e.g. cancer, cardiovascular and neurodegenerative diseases) makes them attractive drug targets, and important for a biochemical understanding of the disease(s). The study of the structural ensemble of IDPs is rather difficult, in particular for transient interactions. When bound to a structured partner, an IDPR adapts an ordered conformation in the complex. The residues that undergo this disorder-to-order transition are called protean residues, generally found in short contiguous stretches and the first step in understanding the modus operandi of an IDP/IDPR would be to predict these residues. There are a few available methods which predict these protean segments from their amino acid sequences; however, their performance reported in the literature leaves clear room for improvement. With this background, the current study presents 'Proteus', a random forest classifier that predicts the likelihood of a residue undergoing a disorder-to-order transition upon binding to a potential partner protein. The prediction is based on features that can be calculated using the amino acid sequence alone. Proteus compares favorably with existing methods predicting twice as many true positives as the second best method (55 vs. 27%) with a much higher precision on an independent data set. The current study also sheds some light on a possible 'disorder-to-order' transitioning consensus, untangled, yet embedded in the amino acid sequence of IDPs. Some guidelines have also been suggested for proceeding with a real-life structural modeling involving an IDPR using Proteus.

Dataset Information

Order out of disorder: working cycle of an intrinsically unfolded chaperone.

Publications

Order out of disorder: working cycle of an intrinsically unfolded chaperone.

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