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Structural Rigidity and Protein Thermostability in Variants of Lipase A from Bacillus subtilis.

Rathi PC, Jaeger KE, Gohlke H - PLoS ONE (2015)

Bottom Line: Furthermore, we introduce a robust, local stability measure for predicting thermodynamic thermostability.Our results complement work that showed for pairs of homologous proteins that raising the structural stability is the most common way to obtain a higher thermostability.Furthermore, they demonstrate that related series of mutants with only a small number of mutations can be successfully analyzed by CNA, which suggests that CNA can be applied prospectively in rational protein design aimed at higher thermodynamic thermostability.

View Article: PubMed Central - PubMed

Affiliation: Institute of Pharmaceutical and Medical Chemistry, Heinrich-Heine-University, Düsseldorf, Germany.

ABSTRACT
Understanding the origin of thermostability is of fundamental importance in protein biochemistry. Opposing views on increased or decreased structural rigidity of the folded state have been put forward in this context. They have been related to differences in the temporal resolution of experiments and computations that probe atomic mobility. Here, we find a significant (p = 0.004) and fair (R2 = 0.46) correlation between the structural rigidity of a well-characterized set of 16 mutants of lipase A from Bacillus subtilis (BsLipA) and their thermodynamic thermostability. We apply the rigidity theory-based Constraint Network Analysis (CNA) approach, analyzing directly and in a time-independent manner the statics of the BsLipA mutants. We carefully validate the CNA results on macroscopic and microscopic experimental observables and probe for their sensitivity with respect to input structures. Furthermore, we introduce a robust, local stability measure for predicting thermodynamic thermostability. Our results complement work that showed for pairs of homologous proteins that raising the structural stability is the most common way to obtain a higher thermostability. Furthermore, they demonstrate that related series of mutants with only a small number of mutations can be successfully analyzed by CNA, which suggests that CNA can be applied prospectively in rational protein design aimed at higher thermodynamic thermostability.

No MeSH data available.


Related in: MedlinePlus

Residue-wise pi plots for medoids of the 10 clusters.Secondary structure elements as computed by the DSSP program [88, 89] are indicated on the top of the plots and are labeled: α-helix (red rectangle), β-strands (green rectangle), loop (black line).
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pone.0130289.g001: Residue-wise pi plots for medoids of the 10 clusters.Secondary structure elements as computed by the DSSP program [88, 89] are indicated on the top of the plots and are labeled: α-helix (red rectangle), β-strands (green rectangle), loop (black line).

Mentions: We thus reasoned that the (dis)similarity of unfolding pathways of BsLipA variants can be measured by Manhattan distances between their respective pi profiles. We used this distance measure for clustering the network topologies of all BsLipA variants into 10 clusters using the Partitioning Around Medoids algorithm [72] as implemented in the R program (http://www.r-project.org). This optimal number of clusters was chosen based on monitoring the change in the objective function of the clustering (the mean of the dissimilarities of all objects to their nearest medoids) as a function of the number of clusters (Figure A in S1 File) and visual inspection of cluster medoids for their dissimilarity to other medoids (residue-wise pi profiles for medoids of the 10 clusters are shown in Fig 1). A clustering in more than 10 clusters essentially created additional clusters that were very similar to other clusters. From this, the cluster distribution (frequencies of network topologies in each of the 10 clusters out of in total 2000 network topologies) for each BsLipA variant was calculated by counting the number of networks that belongs to each of the 10 clusters. A high (low) correlation between cluster distributions for two BsLipA variants then indicates that both variants unfold in a similar (different) manner. Finally, a matrix of all pairwise correlations of cluster distributions of BsLipA variants was generated.


Structural Rigidity and Protein Thermostability in Variants of Lipase A from Bacillus subtilis.

Rathi PC, Jaeger KE, Gohlke H - PLoS ONE (2015)

Residue-wise pi plots for medoids of the 10 clusters.Secondary structure elements as computed by the DSSP program [88, 89] are indicated on the top of the plots and are labeled: α-helix (red rectangle), β-strands (green rectangle), loop (black line).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493141&req=5

pone.0130289.g001: Residue-wise pi plots for medoids of the 10 clusters.Secondary structure elements as computed by the DSSP program [88, 89] are indicated on the top of the plots and are labeled: α-helix (red rectangle), β-strands (green rectangle), loop (black line).
Mentions: We thus reasoned that the (dis)similarity of unfolding pathways of BsLipA variants can be measured by Manhattan distances between their respective pi profiles. We used this distance measure for clustering the network topologies of all BsLipA variants into 10 clusters using the Partitioning Around Medoids algorithm [72] as implemented in the R program (http://www.r-project.org). This optimal number of clusters was chosen based on monitoring the change in the objective function of the clustering (the mean of the dissimilarities of all objects to their nearest medoids) as a function of the number of clusters (Figure A in S1 File) and visual inspection of cluster medoids for their dissimilarity to other medoids (residue-wise pi profiles for medoids of the 10 clusters are shown in Fig 1). A clustering in more than 10 clusters essentially created additional clusters that were very similar to other clusters. From this, the cluster distribution (frequencies of network topologies in each of the 10 clusters out of in total 2000 network topologies) for each BsLipA variant was calculated by counting the number of networks that belongs to each of the 10 clusters. A high (low) correlation between cluster distributions for two BsLipA variants then indicates that both variants unfold in a similar (different) manner. Finally, a matrix of all pairwise correlations of cluster distributions of BsLipA variants was generated.

Bottom Line: Furthermore, we introduce a robust, local stability measure for predicting thermodynamic thermostability.Our results complement work that showed for pairs of homologous proteins that raising the structural stability is the most common way to obtain a higher thermostability.Furthermore, they demonstrate that related series of mutants with only a small number of mutations can be successfully analyzed by CNA, which suggests that CNA can be applied prospectively in rational protein design aimed at higher thermodynamic thermostability.

View Article: PubMed Central - PubMed

Affiliation: Institute of Pharmaceutical and Medical Chemistry, Heinrich-Heine-University, Düsseldorf, Germany.

ABSTRACT
Understanding the origin of thermostability is of fundamental importance in protein biochemistry. Opposing views on increased or decreased structural rigidity of the folded state have been put forward in this context. They have been related to differences in the temporal resolution of experiments and computations that probe atomic mobility. Here, we find a significant (p = 0.004) and fair (R2 = 0.46) correlation between the structural rigidity of a well-characterized set of 16 mutants of lipase A from Bacillus subtilis (BsLipA) and their thermodynamic thermostability. We apply the rigidity theory-based Constraint Network Analysis (CNA) approach, analyzing directly and in a time-independent manner the statics of the BsLipA mutants. We carefully validate the CNA results on macroscopic and microscopic experimental observables and probe for their sensitivity with respect to input structures. Furthermore, we introduce a robust, local stability measure for predicting thermodynamic thermostability. Our results complement work that showed for pairs of homologous proteins that raising the structural stability is the most common way to obtain a higher thermostability. Furthermore, they demonstrate that related series of mutants with only a small number of mutations can be successfully analyzed by CNA, which suggests that CNA can be applied prospectively in rational protein design aimed at higher thermodynamic thermostability.

No MeSH data available.


Related in: MedlinePlus