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Protein-protein interaction network prediction by using rigid-body docking tools: application to bacterial chemotaxis.

Matsuzaki Y, Ohue M, Uchikoga N, Akiyama Y - Protein Pept. Lett. (2014)

Bottom Line: We found that the predicted interactions were different between the results from the two tools.Large-scale PPI prediction using tertiary structures is an effective approach that has a wide range of potential applications.This method is especially useful for identifying novel PPIs of new pathways that control cellular behavior.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan. akiyama@cs.titech.ac.jp.

ABSTRACT
Core elements of cell regulation are made up of protein-protein interaction (PPI) networks. However, many parts of the cell regulatory systems include unknown PPIs. To approach this problem, we have developed a computational method of high-throughput PPI network prediction based on all-to-all rigid-body docking of protein tertiary structures. The prediction system accepts a set of data comprising protein tertiary structures as input and generates a list of possible interacting pairs from all the combinations as output. A crucial advantage of this docking based method is in providing predictions of protein pairs that increases our understanding of biological pathways by analyzing the structures of candidate complex structures, which gives insight into novel interaction mechanisms. Although such exhaustive docking calculation requires massive computational resources, recent advancements in the computational sciences have made such large-scale calculations feasible. In this study we applied our prediction method to a pathway reconstruction problem of bacterial chemotaxis by using two different rigid-body docking tools with different scoring models. We found that the predicted interactions were different between the results from the two tools. When the positive predictions from both of the docking tools were combined, all the core signaling interactions were correctly predicted with the exception of interactions activated by protein phosphorylation. Large-scale PPI prediction using tertiary structures is an effective approach that has a wide range of potential applications. This method is especially useful for identifying novel PPIs of new pathways that control cellular behavior.

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Predicted interactions among chemotaxis proteins. Predicted interactions among chemotaxis proteins by using (a) ZDOCK and (b)MEGADOCK as docking engines. The dark grey coloured cells indicate known interacting pairs based on conventional studies. Cells withdiamond marks indicate predicted interactions. Cells filled with small dots show flagella protein related combinations. Proteins related to theflagellar motor are listed on the right/bottom side. The short form of CheA is known to interact with CheZ [34] but it was not included becausethe structure was unavailable. A total of seven interactions that are not coloured dark grey were found in the STRING database [35] by(i) searching interactions associated with experimental reports or (ii) those annotated in databases (KEGG, BioCyc). The interactions are:CheY-FliG, CheY-CheW, CheB-CheW, Tsr-CheZ, Tsr-CheA, CheR-FliN, CheR-CheZ. These interactions were not considered as “correct” in this study because they have not been characterized.
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Figure 2: Predicted interactions among chemotaxis proteins. Predicted interactions among chemotaxis proteins by using (a) ZDOCK and (b)MEGADOCK as docking engines. The dark grey coloured cells indicate known interacting pairs based on conventional studies. Cells withdiamond marks indicate predicted interactions. Cells filled with small dots show flagella protein related combinations. Proteins related to theflagellar motor are listed on the right/bottom side. The short form of CheA is known to interact with CheZ [34] but it was not included becausethe structure was unavailable. A total of seven interactions that are not coloured dark grey were found in the STRING database [35] by(i) searching interactions associated with experimental reports or (ii) those annotated in databases (KEGG, BioCyc). The interactions are:CheY-FliG, CheY-CheW, CheB-CheW, Tsr-CheZ, Tsr-CheA, CheR-FliN, CheR-CheZ. These interactions were not considered as “correct” in this study because they have not been characterized.

Mentions: To explore how the current rigid-body docking based method performs on real biological data, we applied a method used in our previous studies [12][13] to reconstruct the well-known bacterial chemotaxis signaling pathway (Fig. 1). The bacterial chemotaxis pathway has been studied for several decades and most of the functional relationships among the proteins involved in this signal process have been identified, especially those involving the core part of the signaling system. However there are still uncertainties concerning how flagellar motor proteins are assembled and operate (reviewed in [17]). Also in the existing databases there are some interactions not listed in conventional network descriptions (Fig. 2).


Protein-protein interaction network prediction by using rigid-body docking tools: application to bacterial chemotaxis.

Matsuzaki Y, Ohue M, Uchikoga N, Akiyama Y - Protein Pept. Lett. (2014)

Predicted interactions among chemotaxis proteins. Predicted interactions among chemotaxis proteins by using (a) ZDOCK and (b)MEGADOCK as docking engines. The dark grey coloured cells indicate known interacting pairs based on conventional studies. Cells withdiamond marks indicate predicted interactions. Cells filled with small dots show flagella protein related combinations. Proteins related to theflagellar motor are listed on the right/bottom side. The short form of CheA is known to interact with CheZ [34] but it was not included becausethe structure was unavailable. A total of seven interactions that are not coloured dark grey were found in the STRING database [35] by(i) searching interactions associated with experimental reports or (ii) those annotated in databases (KEGG, BioCyc). The interactions are:CheY-FliG, CheY-CheW, CheB-CheW, Tsr-CheZ, Tsr-CheA, CheR-FliN, CheR-CheZ. These interactions were not considered as “correct” in this study because they have not been characterized.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4440392&req=5

Figure 2: Predicted interactions among chemotaxis proteins. Predicted interactions among chemotaxis proteins by using (a) ZDOCK and (b)MEGADOCK as docking engines. The dark grey coloured cells indicate known interacting pairs based on conventional studies. Cells withdiamond marks indicate predicted interactions. Cells filled with small dots show flagella protein related combinations. Proteins related to theflagellar motor are listed on the right/bottom side. The short form of CheA is known to interact with CheZ [34] but it was not included becausethe structure was unavailable. A total of seven interactions that are not coloured dark grey were found in the STRING database [35] by(i) searching interactions associated with experimental reports or (ii) those annotated in databases (KEGG, BioCyc). The interactions are:CheY-FliG, CheY-CheW, CheB-CheW, Tsr-CheZ, Tsr-CheA, CheR-FliN, CheR-CheZ. These interactions were not considered as “correct” in this study because they have not been characterized.
Mentions: To explore how the current rigid-body docking based method performs on real biological data, we applied a method used in our previous studies [12][13] to reconstruct the well-known bacterial chemotaxis signaling pathway (Fig. 1). The bacterial chemotaxis pathway has been studied for several decades and most of the functional relationships among the proteins involved in this signal process have been identified, especially those involving the core part of the signaling system. However there are still uncertainties concerning how flagellar motor proteins are assembled and operate (reviewed in [17]). Also in the existing databases there are some interactions not listed in conventional network descriptions (Fig. 2).

Bottom Line: We found that the predicted interactions were different between the results from the two tools.Large-scale PPI prediction using tertiary structures is an effective approach that has a wide range of potential applications.This method is especially useful for identifying novel PPIs of new pathways that control cellular behavior.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Information Science and Engineering, Tokyo Institute of Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo 152-8550, Japan. akiyama@cs.titech.ac.jp.

ABSTRACT
Core elements of cell regulation are made up of protein-protein interaction (PPI) networks. However, many parts of the cell regulatory systems include unknown PPIs. To approach this problem, we have developed a computational method of high-throughput PPI network prediction based on all-to-all rigid-body docking of protein tertiary structures. The prediction system accepts a set of data comprising protein tertiary structures as input and generates a list of possible interacting pairs from all the combinations as output. A crucial advantage of this docking based method is in providing predictions of protein pairs that increases our understanding of biological pathways by analyzing the structures of candidate complex structures, which gives insight into novel interaction mechanisms. Although such exhaustive docking calculation requires massive computational resources, recent advancements in the computational sciences have made such large-scale calculations feasible. In this study we applied our prediction method to a pathway reconstruction problem of bacterial chemotaxis by using two different rigid-body docking tools with different scoring models. We found that the predicted interactions were different between the results from the two tools. When the positive predictions from both of the docking tools were combined, all the core signaling interactions were correctly predicted with the exception of interactions activated by protein phosphorylation. Large-scale PPI prediction using tertiary structures is an effective approach that has a wide range of potential applications. This method is especially useful for identifying novel PPIs of new pathways that control cellular behavior.

Show MeSH