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Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

Smith CA, Kortemme T - PLoS ONE (2011)

Bottom Line: Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space.The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA.Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

View Article: PubMed Central - PubMed

Affiliation: Graduate Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California, United States of America.

ABSTRACT
Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s) are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface), interactions between and within parts of the structure (e.g. domains) can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

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PDZ/peptide interface tolerance predictions.Shown are 5 representative examples of predictions with the generalized protocol, compared to experimental data from phage display. The Erbin V83K interface prediction involved making the indicated point mutant (V83K) to the PDZ domain prior to backrub ensemble generation (an example of a “premutated” position).
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pone-0020451-g004: PDZ/peptide interface tolerance predictions.Shown are 5 representative examples of predictions with the generalized protocol, compared to experimental data from phage display. The Erbin V83K interface prediction involved making the indicated point mutant (V83K) to the PDZ domain prior to backrub ensemble generation (an example of a “premutated” position).

Mentions: The third test dataset contains peptide sequences selected by phage display to bind to PDZ domains [15]. To determine if the generalized protocol and scripts described here produce similar results to those previously published on the PDZ-peptide dataset [35], we performed 5 representative PDZ/peptide interface specificity predictions. (For details on methodological differences between the published and current protocols, see the Methods section.) Computational and experimental sequence logos are shown in Figure 4. The correspondence to experiment is overall similar to the previous protocol [35], with the largest difference observed in the absolute frequency of amino acids, as shown in Table 1. The primary changes are reductions in the preferences for R/K at position −4 and T at position −2 for the DLG1-2 PDZ domain, as well as the preference for T at position −2 for the Erbin PDZ domain. These differences likely come from the restoration of environment dependent hydrogen bonds in the current protocol, which weakens hydrogen bonds in solvent exposed areas.


Predicting the tolerated sequences for proteins and protein interfaces using RosettaBackrub flexible backbone design.

Smith CA, Kortemme T - PLoS ONE (2011)

PDZ/peptide interface tolerance predictions.Shown are 5 representative examples of predictions with the generalized protocol, compared to experimental data from phage display. The Erbin V83K interface prediction involved making the indicated point mutant (V83K) to the PDZ domain prior to backrub ensemble generation (an example of a “premutated” position).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3138746&req=5

pone-0020451-g004: PDZ/peptide interface tolerance predictions.Shown are 5 representative examples of predictions with the generalized protocol, compared to experimental data from phage display. The Erbin V83K interface prediction involved making the indicated point mutant (V83K) to the PDZ domain prior to backrub ensemble generation (an example of a “premutated” position).
Mentions: The third test dataset contains peptide sequences selected by phage display to bind to PDZ domains [15]. To determine if the generalized protocol and scripts described here produce similar results to those previously published on the PDZ-peptide dataset [35], we performed 5 representative PDZ/peptide interface specificity predictions. (For details on methodological differences between the published and current protocols, see the Methods section.) Computational and experimental sequence logos are shown in Figure 4. The correspondence to experiment is overall similar to the previous protocol [35], with the largest difference observed in the absolute frequency of amino acids, as shown in Table 1. The primary changes are reductions in the preferences for R/K at position −4 and T at position −2 for the DLG1-2 PDZ domain, as well as the preference for T at position −2 for the Erbin PDZ domain. These differences likely come from the restoration of environment dependent hydrogen bonds in the current protocol, which weakens hydrogen bonds in solvent exposed areas.

Bottom Line: Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space.The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA.Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

View Article: PubMed Central - PubMed

Affiliation: Graduate Program in Biological and Medical Informatics, University of California San Francisco, San Francisco, California, United States of America.

ABSTRACT
Predicting the set of sequences that are tolerated by a protein or protein interface, while maintaining a desired function, is useful for characterizing protein interaction specificity and for computationally designing sequence libraries to engineer proteins with new functions. Here we provide a general method, a detailed set of protocols, and several benchmarks and analyses for estimating tolerated sequences using flexible backbone protein design implemented in the Rosetta molecular modeling software suite. The input to the method is at least one experimentally determined three-dimensional protein structure or high-quality model. The starting structure(s) are expanded or refined into a conformational ensemble using Monte Carlo simulations consisting of backrub backbone and side chain moves in Rosetta. The method then uses a combination of simulated annealing and genetic algorithm optimization methods to enrich for low-energy sequences for the individual members of the ensemble. To emphasize certain functional requirements (e.g. forming a binding interface), interactions between and within parts of the structure (e.g. domains) can be reweighted in the scoring function. Results from each backbone structure are merged together to create a single estimate for the tolerated sequence space. We provide an extensive description of the protocol and its parameters, all source code, example analysis scripts and three tests applying this method to finding sequences predicted to stabilize proteins or protein interfaces. The generality of this method makes many other applications possible, for example stabilizing interactions with small molecules, DNA, or RNA. Through the use of within-domain reweighting and/or multistate design, it may also be possible to use this method to find sequences that stabilize particular protein conformations or binding interactions over others.

Show MeSH
Related in: MedlinePlus