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Universal distribution of protein evolution rates as a consequence of protein folding physics.

ABSTRACT: The hypothesis that folding robustness is the primary determinant of the evolution rate of proteins is explored using a coarse-grained off-lattice model. The simplicity of the model allows rapid computation of the folding probability of a sequence to any folded conformation. For each robust folder, the network of sequences that share its native structure is identified. The fitness of a sequence is postulated to be a simple function of the number of misfolded molecules that have to be produced to reach a characteristic protein abundance. After fixation probabilities of mutants are computed under a simple population dynamics model, a Markov chain on the fold network is constructed, and the fold-averaged evolution rate is computed. The distribution of the logarithm of the evolution rates across distinct networks exhibits a peak with a long tail on the low rate side and resembles the universal empirical distribution of the evolutionary rates more closely than either distribution resembles the log-normal distribution. The results suggest that the universal distribution of the evolutionary rates of protein-coding genes is a direct consequence of the basic physics of protein folding.

SUBMITTER: Lobkovsky AE

PROVIDER: S-EPMC2840281 | biostudies-literature | 2010 Feb

REPOSITORIES: biostudies-literature

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Universal distribution of protein evolution rates as a consequence of protein folding physics.

Lobkovsky Alexander E AE Wolf Yuri I YI Koonin Eugene V EV

Proceedings of the National Academy of Sciences of the United States of America 20100126 7

The hypothesis that folding robustness is the primary determinant of the evolution rate of proteins is explored using a coarse-grained off-lattice model. The simplicity of the model allows rapid computation of the folding probability of a sequence to any folded conformation. For each robust folder, the network of sequences that share its native structure is identified. The fitness of a sequence is postulated to be a simple function of the number of misfolded molecules that have to be produced to ...[more]

PMID: 20133769

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Project description:The protein secretory pathway must maintain homoeostasis while producing a wide assortment of proteins in different conditions. It is also used extensively to produce many useful proteins in biotechnology. As such, secretory pathway dysfunction can be highly detrimental to the cell, resulting in the molecular basis for many human diseases, and can drastically inhibit product titers in biochemical production. Because the secretory pathway is a highly-integrated, multi-organelle system, dysfunction can happen at many levels and dissecting the root cause can be challenging. To better understand some of these dysfunctions, we measured multiple systems-level states of the cell (physiology, transcriptome, metabolism) while secreting a small protein (insulin precursor) or a large protein (?-amylase). This was carried out in the presence and absence of HAC1, a key transcription factor in maintaining secretory homeostasis. Clear trends in cellular stress were apparent across multiple data resulting from our perturbations. In particular, processes involving (1) degradation of protein / recycling amino acids, (2) overall transcription/translation repression, and (3) oxidative stress. Apparent runaway oxidative radical production was explained by a thermodynamic model that we put forward for disulfide formation in the endoplasmic reticulum. This model predicts that balancing the relative rates of protein folding and disulfide bond formation are key to easing oxidative stress. These predictions have direct implications in how to engineer a broad range of recombinant proteins for secretion and provide potential hypotheses for the root causes of several secretory-associated diseases. Yeast strains were constructed that produce and secrete (a) IP or (b) ?-amylase and were compared to yeast strains containing (c) an empty vector in both wild-type and HAC1 deletion backgrounds. These strains are named WN (WT with empty vector), WI (WT secreting IP), WA (WT secreting ?-amylase), dN (?hac1 with empty vector), dI (?hac1 secreting IP), and dA (?hac1 secreting ?-amylase). Strains were characterized in batch fermentation and samples were taken in mid-exponential phase. Triplicate fermentations were carried out for each strain.

Dataset Information

Universal distribution of protein evolution rates as a consequence of protein folding physics.

Publications

Universal distribution of protein evolution rates as a consequence of protein folding physics.

Similar Datasets

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