Figures
Abstract
Proteolytic enzymes have evolved several mechanisms to cleave peptide bonds. These distinct types have been systematically categorized in the MEROPS database. While a BLAST search on these proteases identifies homologous proteins, sequence alignment methods often fail to identify relationships arising from convergent evolution, exon shuffling, and modular reuse of catalytic units. We have previously established a computational method to detect functions in proteins based on the spatial and electrostatic properties of the catalytic residues (CLASP). CLASP identified a promiscuous serine protease scaffold in alkaline phosphatases (AP) and a scaffold recognizing a β-lactam (imipenem) in a cold-active Vibrio AP. Subsequently, we defined a methodology to quantify promiscuous activities in a wide range of proteins. Here, we assemble a module which encapsulates the multifarious motifs used by protease families listed in the MEROPS database. Since APs and proteases are an integral component of outer membrane vesicles (OMV), we sought to query other OMV proteins, like phospholipase C (PLC), using this search module. Our analysis indicated that phosphoinositide-specific PLC from Bacillus cereus is a serine protease. This was validated by protease assays, mass spectrometry and by inhibition of the native phospholipase activity of PI-PLC by the well-known serine protease inhibitor AEBSF (IC50 = 0.018 mM). Edman degradation analysis linked the specificity of the protease activity to a proline in the amino terminal, suggesting that the PI-PLC is a prolyl peptidase. Thus, we propose a computational method of extending protein families based on the spatial and electrostatic congruence of active site residues.
Citation: Rendón-Ramírez A, Shukla M, Oda M, Chakraborty S, Minda R, Dandekar AM, et al. (2013) A Computational Module Assembled from Different Protease Family Motifs Identifies PI PLC from Bacillus cereus as a Putative Prolyl Peptidase with a Serine Protease Scaffold. PLoS ONE 8(8): e70923. https://doi.org/10.1371/journal.pone.0070923
Editor: Vladimir N. Uversky, University of South Florida College of Medicine, United States of America
Received: May 28, 2012; Accepted: June 28, 2013; Published: August 5, 2013
Copyright: © 2013 Rendón-Ramirez et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: BJR would like to thank the Tata Institute of Fundamental Research (Department of Atomic Energy) for financial support. MO was supported in part by a Grant-in-aid for Scientific Research from the Ministry of Education, Culture, Sports, Science and Technology, Japan; (grant No. 21790431). FMG thanks the Spanish Ministerio de Ciencia e Innovacion for grant No. BFU 2007/62062, and the University of the Basque Country for grant No. IT 461-07. BA extends gratitude to the Icelandic National Research Council and the University of Iceland Research Found for supporting the project financially. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Proteolytic enzymes catalyze the cleavage of peptide bonds in proteins and are divided into several major classes based on their mechanism of catalysis [1], [2]. The MEROPS database systematically categorizes these protein families and clans to provide an integrated information source [3]. The abundance of proteolytic enzymes in biological systems results from the varied physiological conditions under which these enzymes have evolved to be effective [4].
We selected proteases with known active sites and 3D structures from each family listed in MEROPS and encapsulated their active site motifs into a single protease search module. We previously presented a bottom-up method for active site prediction (CLASP) using active site residues [5]. Subsequently, we used CLASP to quantify promiscuous activities in a wide range of proteins [6]. Here, we used CLASP to query proteins of interest for proteolytic function using this search module. Such a search module is equivalent to running a BLAST search from the MEROPS database site [7], [8].
While BLAST looks for sequence homology, CLASP detects spatial and electrostatic congruence between residues to predict similar catalytic properties in proteins. Sequence alignment techniques are known to fail to detect distant relationships since considerable divergence often resembles noise [8]. More importantly, proteins redesigned from chiseled scaffolds through exon shuffling and those resulting from convergent evolution remain beyond the scope of such methods [9]. The phenomenon of convergent evolution, first proposed in serine proteases [10], is no longer considered to be a rare event [11], [12]. Structural alignment methods have addressed some of these deficiencies, but can be misled by non-catalytic parts of the protein [13]. A recent method employs learning techniques to predict whether proteins have proteolytic activities, but has not identified any novel proteases undetected by other methods [14], [15]. CLASP unraveled a promiscuous serine protease scaffold in alkaline phosphatases (AP) [5], one of the widely studied promiscuous enzyme families [16], [17], and also a scaffold recognizing a β-lactam (imipenem) in a cold-active Vibrio AP [18], [19].
Several conserved proteases have been implicated in bacterial pathogenesis [20]. Proteases are integral components of outer membrane vesicles (OMVs), which all gram-negative bacteria shed as blebs from the cell surface [21]. We queried other proteins present in OMVs using the CLASP protease search module and found that phosphoinositide-specific phospholipase C (PI-PLC) is a Pro-X specific protease. PI-PLCs are part of the signal transduction pathways of higher organisms [22]–[24]. Prokaryotic PI-PLCs are important virulence factors that alter the signaling pathways of higher organisms [25]–[27]. We demonstrated a serine protease domain in PI-PLC from Bacillus cereus through its proteolytic activity and the inhibition of its native activity on phospholipids by serine protease inhibitors (IC50 = 0.018 mM). Edman degradation analysis demonstrated that the specificity of the protease activity was for a proline in the amino terminal, suggesting that PI-PLC is a prolyl peptidase [28].
To summarize, the distinct types of proteases categorized in the MEROPS database were used to generate a search module that could be used to query any protein with known 3D structure for the presence of a promiscuous proteolytic activity. This search module identified a serine protease scaffold in PI-PLC from Bacillus cereus, which was validated by in vitro experiments. A similar computational approach can be adopted for other enzymatic functions to extend protein families based on the spatial and electrostatic congruence of active site residues: relationships that often escape detection by sequence alignment or global structure alignment methods.
Results
We chose a set of proteases with known 3D structures and active site residues from each of the seven major classes in the MEROPS database (Table 1) [3]. We then created signatures encompassing the spatial and electrostatic properties of the catalytic residues in these proteins [5]. To maintain uniformity, we chose three residues from the active site neighborhood, including the catalytic residues (Table 2). These signatures were then used to query other proteins of interest using CLASP. Matches with low scores (less than an empirical threshold of 0.1) indicate a good spatial and electrostatic congruence, and a significant likelihood that these proteins possess proteolytic functions.
To expand our previous work on APs, we investigated the proteolytic activity of a cold-active Vibrio AP (VAP) [18] on four substrates: benzoyl-Arg-pNA, Z-GlyProArg-pNA, succinyl-AlaAlaAla-pNA, and succinyl-AlaAlaProPhe-pNA. While we detected no proteolytic activity in VAP, its native AP activity was inhibited by AEBSF (4-(2-aminoethyl) benzenesulfonyl fluoride hydrochloride) (IC50 of 0.35+/−0.05 mM (n = 6) for AEBSF at pH 7.0), but not by PMSF (phenylmethanesulfonylfluoride or phenylmethylsulfonyl fluoride). Both AEBSF and PMSF are serine protease inhibitors with similar specificity (chymotrypsin, kallikrein, plasmin, thrombin, and trypsin).
The predicted residues, deviations in distances, potential difference in cognate pairs, and scores were determined for a phosphoinositide-specific PLC (PI-PLC) (PDB id: 1PTD) from Bacillus cereus (Table 3). PI-PLC was indicated to be a serine protease because the best match was with a trypsin protein, PDBid:1A0J [29]. The residues predicted by CLASP as responsible for its protease activity coincide with the active site responsible for its native phospholipase activity (His32, Asp67, His82, and Asp274) (Fig. 1) [30]. However, there was little sequence similarity within the set of querying and queried proteins, suggesting that established sequence alignment methods would fail to detect this relationship (Table S1).
(a) Superimposed proteins. Trypsin (PDBid:1A0J) is in blue and PI-PLC (PDBid:1PTD) is in grey. After superimposition, all three atoms in both proteins lie on the same plane (Z = 0), such that His57 and His32 (colored in black) lie on the coordinate center and Asp102 and Asp67 lie on the X-Y plane (Y = 0). The active site residues of trypsin are red and those of PI-PLC, yellow. His32, Asp67, His82, and Asp274 are all part of the active site scaffold in PI-PLC [30]. (b) Distances between pairs of residues in the matches in Å. (c) Potential differences between pairs of residues in the matches. Electrostatic potential in dimensionless units of kT/e where k is Boltzmann’s constant, T is the temperature in K and e is the charge of an electron.
We tested this prediction by performing an in vitro protease assay on commercially available PI-PLC from Bacillus cereus. The protease activity of PI-PLC on the substrate protein UVI31+ [31], [32] was inhibited by the protease inhibitor leupeptin, while other inhibitors like AEBSF were unstable during a long incubation (Fig. 2A). A MALDI TOF analysis showed a clean, 13.4 kDa peak for purified UVI31+ protein (Fig. 2B), which was split into two fragments of 2.0 kDa (Fig. 2C) and 11.4 kDa (Fig. 2D) on incubation with PI-PLC. Edman degradation analysis demonstrated that the protease activity was specific for a proline following the first seven residues of the UVI31+ protein (marked by an asterisk - MAEHQLGP*IAG). This suggested that the PI-PLC is a putative prolyl peptidase. The predicted protease scaffold was tested by assaying inhibition of its phospholipase activity by the trypsin inhibitor AEBSF (IC50 = 0.018 mM). Assays were performed with the substrate in the form of large, unilamellar vesicles. The vesicles consisted of either pure phosphatidylinositol (PI) (Fig. 2E) or an equimolar mixture of PI, phosphatidylcholine (PC), phosphatidylethanolamine (PE), and cholesterol (CH) (Fig. 2F). In both cases, the maximum reaction rates decreased in a dose-dependent way in the presence of AEBSF (Fig. S1).
(A) Protease activity of PI-PLC. Substrate protein (UVI31+, lane 2) was incubated with PI- PLC (lane 3) overnight at 37°C, followed by sample analysis with 15% SDS-PAGE. Lane 1, molecular weight marker. (B) Control for UVI31+, with peak at 13.436 kDa. (C) UVI31+ treated with PI-PLC, showing fragmented peaks at 11.4 kDa and (D) another fragment of 2.0 kDa. (E) The inhibition of PI-PLC activity on phosphatidylinositol (PI) by trypsin inhibitor AEBSF. (F) The inhibition of PI-PLC activity on PI by trypsin inhibitor AEBSF in a mixture with phosphatidylcholine (PC), phosphatidylethanolamine (PE), and cholesterol (CH).
We tested the proteolytic functions and inhibition using protease inhibitors of the non-toxic Bacillus cereus phosphatidylcholine-specific phospholipase C (PC-PLC) and the closely related highly toxic C. perfringens α-toxin (CPA), which possesses an additional C-terminal domain responsible for the sphingomyelinase, hemolytic, and lethal activities [33]. CPA and PC-PLC activity on phospholipids was unaffected by trypsin inhibitors, consistent with the CLASP analysis which fails to detect a serine protease scaffold in these proteins (Table 4, 5).
CPA does have a metallo-protease motif from thermolysin PDBid:1FJO (Table 4). Remnants of a metallo-protease in the CPA protein preparation prevented direct confirmation of its proteolytic function. A metallo-protease inhibitor did not inhibit CPA activity. This lack of inhibition by a single compound is insufficient to rule out the existence of a metallo-protease scaffold.
The PC-PLC proteolytic activity could also be an artifact of metallo-protease contamination, which is difficult to remove. CLASP detects in this protein a glutamic protease motif from the Eqolisin family of peptidases, PDBid:1S2B (Table 5), which does not coincide with its native active site (Fig. 3). While this protein’s lack of inhibition by serine and metallo-protease inhibitors is consistent with CLASP analysis, mutational studies would be required to confirm the moonlighting glutamic protease scaffold [34]. Thus, the protease activities of CPA and PC-PLC remain open to debate.
The residues predicted to be responsible for the protease activity (Gln39, Glu42, and Trp43, in shades of red) does not coincide with its native active site (Trp1, His14, Asp122, HiS128, Glu146, Asp55, and His69, in shades of green). The motif is selected from a protein from the Eqolisin family of peptidases: PDBid:1S2B.
Discussion
Proteases have evolved to use different mechanisms for proteolysis [2], [3], [35]–[37]. Although most peptidases cleave peptide bonds by hydrolysis, recently a novel protease was shown to be a lyase [38], [39]. There is considerable interest in developing computational methods to identify new proteolytic enzymes and their substrates. MEROPS provides a BLAST search for any query protein [3]. Another recent method employed learning techniques to predict proteolytic activities, but found no novel proteases undetected by other methods [14], [15]. Computational methods are also used for predicting protease substrates [40]. Here, we selected proteases with known active sites and structures from each family listed in MEROPS, and encapsulated their active site motifs into a single protease search module. Using our previously described method [5], we exploited this search module to unravel proteolytic activities in phosphoinositide-specific PLC (PI-PLC) [23], [24].
The importance of proteases in organisms from all kingdoms is well established. In humans, abnormal proteolysis is linked to pathologies like cancer, stroke, heart attack, and parasite infection [41]–[43]. The complete set of known proteases present in human, chimpanzee, mouse, and rat have been incorporated into the Degradome database [44]. In plants, papain-like cysteine proteases are critical enhancers of immunity [45]. The bactericidal properties of human neutrophil elastase, a serine protease, have been exploited to design a therapeutic chimeric antimicrobial protein that targets the outer-membrane of bacteria and bolsters the innate immune defense system of grapevines against the Pierce’s disease-causing Gram-negative Xylella fastidiosa [46]. Several conserved proteases have been implicated in bacterial pathogenesis and are intricately involved in the Type III secretion system [47], quorum sensing [48], motility [49], chaperones for OMV proteins [50], and the protein quality control mechanism essential for degrading unfolded proteins [51].
Proteases are also an integral component of outer membrane vesicles (OMVs), which are shed by all Gram-negative bacteria as blebs from the cell surface [21]. OMVs from pathogenic bacteria are transported through the host plasma membrane by endocytosis [52], [53], and deliver several virulence factors that modulate the host immune system, alter host cell signaling pathways, and aid the colonization of host tissues [54], [55]. OMVs contain other proteins like alkaline phosphatase (AP), phospholipase C (PLC), and β-lactamases [56].
Previously, we detected a promiscuous serine protease scaffold in APs using CLASP [5], and a scaffold recognizing a β-lactam (imipenem) in a cold-active Vibrio AP [18], [19]. The theoretical foundation of CLASP is that the electrostatic potential difference (EPD) in cognate pairs of active site residues is conserved in proteins with the same functionality. The significance of EPD was extended to a method for enumerating possible pathways for proton abstraction in the active site [57], compute electrostatic perturbations induced by ligand binding [58], and propose a rational design-flow for directed evolution [59], [60]. Recently, we proposed a methodology for the multiple sequence alignment of related proteins with known structures using electrostatic properties as an additional discriminator and identified mutations that might be the source of functional divergence in a protein family. The active site and its close surroundings contained enough information to infer the correct phylogeny for related proteins [61]. Here, we confirmed the presence of this proteolytic scaffold in a cold-active Vibrio AP (VAP) (IC50 of 0.35+/−0.05 mM (n = 6) for AEBSF at pH 7.0). Since APs are present in OMVs, we queried other proteins present in OMVs using motifs from different proteases listed in MEROPS. CLASP analysis using the search module (Table 1 and 2) indicated that PI-PLC is a protease with Pro-X specificity (Table 3). This was validated by protease assays, mass spectrometry and by inhibition of the native phospholipase activity by the serine protease inhibitor AEBSF (IC50 = 0.018 mM). Edman degradation analysis demonstrated that the protease activity was specific for a proline in the amino terminal, suggesting that the PI-PLC is a prolyl peptidase [28]. Other endogenous proteolytic substrates of PI-PLC might be discovered by liquid chromatography–mass spectrometry-based peptidomics [62].
Enzymes that cleave phospholipids are defined by the site of cleavage as PLA (releasing the fatty acids) or PLC/PLD (releasing the polar head group) [28], [63]. In higher eukaryotes, phosphoinositide-specific PLC (PI-PLC) produces critical secondary messengers for signal transduction pathways [22], [23]. Prokaryotic PI-PLCs are important virulence factors, possibly by altering this signaling pathway [25], [26]. We experimentally demonstrated the serine protease scaffold in PI-PLC from Bacillus cereus (Fig. 2). The hypothesis concerned the origin of the diverse peptidase families and the evolutionary pressures that molded each may be reinforced by these new families of proteolytic enzymes [64].
The genus Clostridium consists of spore-forming, rod-shaped, Gram-positive bacteria, of which Clostridium perfringens is one of the most pathogenic, with hemolytic, dermonecrotic, vascular permeabilization, and platelet-aggregating properties [65]. C. perfringens strains are classified into five toxinotypes based on four typing toxins [66]. The C. perfringens α toxin (CPA), present in all five toxinotypes, is a zinc-dependent enzyme with both phospholipase C (PLC) and sphingomyelinase (SMase) activity [67]. The N-terminal domain (∼250 residues) is similar to the Bacillus cereus phosphatidylcholine-specific phospholipase C (PC-PLC) [33], [68]. The C-terminal domain has an eight-stranded anti parallel β-sandwich motif similar to eukaryotic calcium-binding C2 domains and confers toxicity on the enzyme [69], [70]. The observed protease activities of CPA and PC-PLC remain unconfirmed due to suspected metallo-protease contamination. However, CPA and PC-PLC activity on phospholipids were unaffected in the presence of trypsin inhibitors, corroborating the CLASP analysis failure to detect a serine protease scaffold in these proteins.
Another aspect of catalysis that should be modeled is the flexibility and diversity in the active site scaffold of related enzymes. For example, there are many unconventional serine proteases [36]. The group of residues that can match a particular residue from the input motif can be varied in CLASP, allowing it to model unconventional motifs. While stereochemical equivalence can be hardwired for amino acids with similar properties, there are instances where residues with different properties occupy the same sequence and spatial location and perform the same function. A well-known example is the equivalence of Ser130 and Tyr150 in Class A and C β-lactamases, respectively [71].
The lack of PI-PLC proteolytic activity on the many tested synthetic substrates, and its specificity for UVI31+ protein, indicates that one should exert caution before ruling out protease activity in an enzyme. This is particularly true when a serine protease inhibitor inhibits the native activity, confirming a serine protease-like scaffold (with the classical catalytic triad) in the active site. Serine protease inhibitors are not active on other serine-centric enzymes like serine β-lactamases, or on metallo-enzymes like CPA and PC-PLC. This establishes their specificity for the serine protease scaffold. Proteases are a unique class of enzymes with many possible substrates due to the theoretically infinite number of DNA sequences that could encode proteins with correspondingly infinite folds. Fluorogenic substrate microarrays determine protease substrate specificity using a wide range of fluorogenic protease substrates [72], [73]. Directed evolution strategies can modify the specificities [59], [74], [75]. The “poor specificity conversion” to convert chymotrypsin to trypsin is an example of the difficulty of such an endeavor [76].
We propose a computational methodology to extend protein families based on the spatial and electrostatic properties of the catalytic residues in proteases. The distinct of protease types categorized in the MEROPS database were selected to generate a search module that can query any protein with known structure for the presence of a promiscuous proteolytic activity.
Methods
1 CLASP Algorithm
The CLASP algorithm was described previously [5]. Given the active site residues from a protein with known structure, a signature encapsulating the spatial and electrostatic properties of the catalytic site is used to search for congruent matches in a query protein, generating a score which reflects the likelihood that the activity in the reference protein exists in the query protein. Adaptive Poisson-Boltzmann Solver [77] (APBS) and the PDB2PQR package [78] were used to calculate the potential difference between the reactive atoms of the corresponding proteins. The APBS parameters are set as follows: solute dielectric, 2; solvent dielectric, 78; solvent probe radius, 1.4 Å; temperature, 298 K; and ionic strength, 0. APBS writes out the electrostatic potential in dimensionless units of kT/e where k is Boltzmann’s constant, T is the temperature in K and e is the charge of an electron. All protein structures were rendered by PyMol (http://www.pymol.org/).
2 Protein, Substrate, and Reagents
PI-PLC was purchased from Sigma. Trypsin inhibitor from chicken egg white and PMSF (phenylmethylsulfonyl fluoride) were obtained from Roche.
3 Protease Assay
Each reaction mixture (30 µL total volume) contained 13 µM purified UVI31+ protein [31], [32] (14 kDa) and 0.2 units PI-PLC in 50 mM ammonium bicarbonate, and was incubated overnight at 37°C. The protein was then denatured by the addition of 7 µL SDS-denaturing solution (200 mM Tris-HCl pH 6.8, 8% SDS (w/v), 40% glycerol (v/v), 4% 2-mercaptoethanol (w/v), 50 mM EDTA pH 8.0, and 0.08% bromophenol blue (w/v) and heating at 100°C for 3 min. The sample was subjected to 15% SDS-PAGE (w/v) followed by staining with Coomassie brilliant blue. To inhibit protease activity of SAP, three different conditions were employed: (i) 0.1% SDS followed by heating at 100°C for 5 min, (ii) 1 mM PMSF, and (iii) 500 ng/mL trypsin inhibitor, before substrate addition. UVI31+ protein (13 µM) was then added as the substrate and residual enzyme activity was measured.
4 PI-PLC Assay and Inhibition Using Trypsin Inhibitors
4.1 Vesicle preparation and characterization.
The appropriate lipids - Lipids (Phosphatidylinositol/Phosphatidylethanolamine/Phophatidylcholine/Cholesterol - 40∶30∶15∶15 ratio) were mixed in organic solution and the solvent (mixture of chloroform/methanol/hydrochloric acid mixture 200/100/1, by volume) was evaporated to dryness under N2. Solvent traces were removed by evacuating the lipids for at least 2 hr. The lipids were then rehydrated in 10 mM Hepes buffer with 150 mM NaCl, pH 7.5. Large unilamellar vesicles (LUV) were prepared from the swollen lipids by extrusion and sized using 0.1 µm Nuclepore filters, as described by Ahyayauch et al. [79]. The average size of LUV was measured by quasi-elastic light scattering using a Malvern Zeta-sizer. Lipid concentration, determined by phosphate analysis, was 0.3 mM in all experiments.
4.2 Aggregation assay.
All assays were carried out at 39°C with continuous stirring in 10 mM Hepes buffer (pH 7.5) with 150 mM NaCl and 0.1% BSA for optimum catalytic activity. The enzyme concentration was 0.16 U/mL. Lipid aggregation was monitored in a Cary Varian UV-vesicle spectrometer as an increase in turbidity (absorbance at 450 nm), as described by Villar et al. [80].
5 MALDI-TOF Analysis and Edman Degradation
MALDI-TOF mass spectrometric analysis was performed using an UltraFlextreme MALDI-TOF (Bruker Daltonics, Germany). Positive ionization and linear mode were used. The experimental parameters were: laser power, 60%, voltage, 25 kV, and mass difference in linear mode with external calibration, <6100 ppm (<60.01%). The matrix was sinapinic acid. The external calibration standard consisted of insulin, ubiquitin, cytochrome C, and myoglobin. Edman degradation was performed by Intas Pharma (http://intaspharma.com/).
Supporting Information
Figure S1.
Linear regression for the inhibition of PI-PLC activity. (a) inhibition of PI-PLC activity on phosphatidylinositol (PI) by trypsin inhibitor AEBSF. (b) inhibition of PI-PLC activity on PI and phosphatidylcholine (PC), cholesterol (CH), and phosphatidylethanolamine (PE) by trypsin inhibitor AEBSF.
https://doi.org/10.1371/journal.pone.0070923.s001
(PDF)
Table S1.
Percentage identity/similarity among all proteases chosen for the search module and the PI and PC PLC from Bacillus cereus.
https://doi.org/10.1371/journal.pone.0070923.s002
(PDF)
Acknowledgments
We gratefully acknowledge Lipika Salaye for technical support. We acknowledge Deepa Saraswathi and Deepshikha Verma for the Maldi analysis, and Vandana Raghavan for providing UVI31+ protein.
Author Contributions
Conceived and designed the experiments: SC MO RM ARR FMG BA. Performed the experiments: MO RM ARR MS. Analyzed the data: SC MO RM ARR FMG BA AMD BJR. Contributed reagents/materials/analysis tools: SC MO FMG BA. Wrote the paper: SC MS MO RM ARR AMD FMG BA.
References
- 1. Walsh KA, Neurath H (1964) Trypsinogen and chymotrypsinogen as homologous proteins. Proc Natl Acad Sci USA 52: 884–889.
- 2. Rawlings ND, Barrett AJ (1993) Evolutionary families of peptidases. Biochem J 290 (Pt 1): 205–218.
- 3. Rawlings ND, Barrett AJ, Bateman A (2012) MEROPS: the database of proteolytic enzymes, their substrates and inhibitors. Nucleic Acids Res 40: D343–350.
- 4. Lopez-Otin C, Bond JS (2008) Proteases: multifunctional enzymes in life and disease. J Biol Chem 283: 30433–30437.
- 5. Chakraborty S, Minda R, Salaye L, Bhattacharjee SK, Rao BJ (2011) Active site detection by spatial conformity and electrostatic analysis-unravelling a proteolytic function in shrimp alkaline phosphatase. PLoS ONE 6: e28470.
- 6. Chakraborty S, Rao BJ (2012) A measure of the promiscuity of proteins and characteristics of residues in the vicinity of the catalytic site that regulate promiscuity. PLoS ONE 7: e32011.
- 7. Rawlings ND, Morton FR (2008) The MEROPS batch BLAST: a tool to detect peptidases and their non-peptidase homologues in a genome. Biochimie 90: 243–259.
- 8. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, et al. (1997) Gapped BLAST and PSI- BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389–3402.
- 9. Russell RB (1998) Detection of protein three-dimensional side-chain patterns: new examples of convergent evolution. J Mol Biol 279: 1211–1227.
- 10. Kraut J (1977) Serine proteases: structure and mechanism of catalysis. Annu Rev Biochem 46: 331–358.
- 11. Doolittle RF (1994) Convergent evolution: the need to be explicit. Trends Biochem Sci 19: 15–18.
- 12. Gherardini PF, Wass MN, Helmer-Citterich M, Sternberg MJ (2007) Convergent evolution of enzyme active sites is not a rare phenomenon. J Mol Biol 372: 817–845.
- 13. Holm L, Kaariainen S, Rosenstrom P, Schenkel A (2008) Searching protein structure databases with DaliLite v.3. Bioinformatics 24: 2780–2781.
- 14. Chou KC, Cai YD (2006) Prediction of protease types in a hybridization space. Biochem Biophys Res Commun 339: 1015–1020.
- 15. Shen HB, Chou KC (2009) Identification of proteases and their types. Anal Biochem 385: 153–160.
- 16. van Loo B, Jonas S, Babtie AC, Benjdia A, Berteau O, et al. (2010) An efficient, multiply promiscuous hydrolase in the alkaline phosphatase superfamily. Proc Natl Acad Sci USA 107: 2740–2745.
- 17. Brien PJ, Herschlag D (1999) Catalytic promiscuity and the evolution of new enzymatic activities. Chem Biol 6: R91–R105.
- 18. Helland R, Larsen RL, Asgeirsson B (2009) The 1.4 Å crystal structure of the large and cold-active Vibrio sp. alkaline phosphatase. Biochim Biophys Acta 1794: 297–308.
- 19. Chakraborty S, Asgeirsson B, Minda R, Salaye L, Frere JM, et al. (2012) Inhibition of a cold-active alkaline phosphatase by imipenem revealed by in silico modeling of metallo-β-lactamase active sites. FEBS Lett 586: 3710–3715.
- 20. Ingmer H, Brondsted L (2009) Proteases in bacterial pathogenesis. Res Microbiol 160: 704–710.
- 21. Kadurugamuwa JL, Beveridge TJ (1995) Virulence factors are released from Pseudomonas aeruginosa in association with membrane vesicles during normal growth and exposure to gentamicin: a novel mechanism of enzyme secretion. J Bacteriol 177: 3998–4008.
- 22. Songer JG (1997) Bacterial phospholipases and their role in virulence. Trends Microbiol 5: 156–161.
- 23. Katan M (1998) Families of phosphoinositide-specific phospholipase C: structure and function. Biochim Biophys Acta 1436: 5–17.
- 24. Goni FM, Montes LR, Alonso A (2012) Phospholipases C and sphingomyelinases: Lipids as substrates and modulators of enzyme activity. Prog Lipid Res 51: 238–266.
- 25. Camilli A, Goldfine H, Portnoy DA (1991) Listeria monocytogenes mutants lacking phosphatidylinositol-specific phospholipase C are avirulent. J Exp Med 173: 751–754.
- 26. Griffith OH, Ryan M (1999) Bacterial phosphatidylinositol-specific phospholipase C: structure, func- tion, and interaction with lipids. Biochim Biophys Acta 1441: 237–254.
- 27. Pomerantsev AP, Kalnin KV, Osorio M, Leppla SH (2003) Phosphatidylcholine-specific phospholipase C and sphingomyelinase activities in bacteria of the Bacillus cereus group. Infect Immun 71: 6591–6606.
- 28. Rosenblum JS, Kozarich JW (2003) Prolyl peptidases: a serine protease subfamily with high potential for drug discovery. Curr Opin Chem Biol 7: 496–504.
- 29. Schroder HK, Willassen NP, Smalas AO (1998) Structure of a non-psychrophilic trypsin from a cold- adapted fish species. Acta Crystallogr D Biol Crystallogr 54: 780–798.
- 30. Heinz DW, Ryan M, Bullock TL, Griffith OH (1995) Crystal structure of the phosphatidylinositol- specific phospholipase C from Bacillus cereus in complex with myo-inositol. EMBO J 14: 3855–3863.
- 31. Rout AK, Minda R, Peri D, Ramakrishnan V, Bhattacharjee SK, et al. (2010) Sequence specific 1H, 13C and 15N backbone resonance assignments of UVI31+ from Chlamydomonas reinhardtii. Biomol NMR Assign 4: 171–174.
- 32. Shukla M, Minda R, Singh H, Tirumani S, Chary KV, et al. (2012) UVI31+ is a DNA endonuclease that dynamically localizes to chloroplast pyrenoids in C. reinhardtii. PLoS ONE 7: e51913.
- 33. Titball RW, Leslie DL, Harvey S, Kelly D (1991) Hemolytic and sphingomyelinase activities of Clostridium perfringens alpha-toxin are dependent on a domain homologous to that of an enzyme from the human arachidonic acid pathway. Infect Immun 59: 1872–1874.
- 34. Jeffery CJ (2009) Moonlighting proteins–an update. Mol Biosyst 5: 345–350.
- 35. Lodola A, Branduardi D, De Vivo M, Capoferri L, Mor M, et al. (2012) A catalytic mechanism for cysteine N-terminal nucleophile hydrolases, as revealed by free energy simulations. PLoS ONE 7: e32397.
- 36. Ekici OD, Paetzel M, Dalbey RE (2008) Unconventional serine proteases: variations on the catalytic Ser/His/Asp triad configuration. Protein Sci 17: 2023–2037.
- 37. Rosenblum G, Van den Steen PE, Cohen SR, Bitler A, Brand DD, et al. (2010) Direct visualization of protease action on collagen triple helical structure. PLoS ONE 5: e11043.
- 38. Rawlings ND, Barrett AJ, Bateman A (2011) Asparagine peptide lyases: a seventh catalytic type of proteolytic enzymes. J Biol Chem 286: 38321–38328.
- 39. Tajima N, Kawai F, Park SY, Tame JR (2010) A novel intein-like autoproteolytic mechanism in autotransporter proteins. J Mol Biol 402: 645–656.
- 40. Song J, Tan H, Boyd SE, Shen H, Mahmood K, et al. (2011) Bioinformatic approaches for predicting substrates of proteases. J Bioinform Comput Biol 9: 149–178.
- 41. Koblinski JE, Ahram M, Sloane BF (2000) Unraveling the role of proteases in cancer. Clin Chim Acta 291: 113–135.
- 42. Korkmaz B, Moreau T, Gauthier F (2008) Neutrophil elastase, proteinase 3 and cathepsin G: physic- ochemical properties, activity and physiopathological functions. Biochimie 90: 227–242.
- 43. Lutgens SP, Cleutjens KB, Daemen MJ, Heeneman S (2007) Cathepsin cysteine proteases in cardio- vascular disease. FASEB J 21: 3029–3041.
- 44. Quesada V, Ordonez GR, Sanchez LM, Puente XS, Lopez-Otin C (2009) The Degradome database: mammalian proteases and diseases of proteolysis. Nucleic Acids Res 37: D239–243.
- 45. Shindo T, Misas-Villamil JC, Horger AC, Song J, van der Hoorn RA (2012) A role in immunity for Arabidopsis cysteine protease RD21, the ortholog of the tomato immune protease C14. PLoS ONE 7: e29317.
- 46. Kunkel M, Vuyisich M, Gnanakaran G, Bruening GE, Dandekar AM, et al. (2007) Rapid clearance of bacteria and their toxins: development of therapeutic proteins. Crit Rev Immunol 27: 233–245.
- 47. Jackson MW, Silva-Herzog E, Plano GV (2004) The ATP-dependent ClpXP and Lon proteases regulate expression of the Yersinia pestis type III secretion system via regulated proteolysis of YmoA, a small histone-like protein. Mol Microbiol 54: 1364–1378.
- 48. Takaya A, Tabuchi F, Tsuchiya H, Isogai E, Yamamoto T (2008) Negative regulation of quorum-sensing systems in Pseudomonas aeruginosa by ATP-dependent Lon protease. J Bacteriol 190: 4181–4188.
- 49. Tomoyasu T, Ohkishi T, Ukyo Y, Tokumitsu A, Takaya A, et al. (2002) The ClpXP ATP-dependent protease regulates flagellum synthesis in Salmonella enterica serovar typhimurium. J Bacteriol 184: 645–653.
- 50. Krojer T, Sawa J, Schafer E, Saibil HR, Ehrmann M, et al. (2008) Structural basis for the regulated protease and chaperone function of DegP. Nature 453: 885–890.
- 51. Kruger E, Witt E, Ohlmeier S, Hanschke R, Hecker M (2000) The clp proteases of Bacillus subtilis are directly involved in degradation of misfolded proteins. J Bacteriol 182: 3259–3265.
- 52. Bomberger JM, Maceachran DP, Coutermarsh BA, Ye S, O’Toole GA, et al. (2009) Long-distance delivery of bacterial virulence factors by Pseudomonas aeruginosa outer membrane vesicles. PLoS Pathog 5: e1000382.
- 53. Furuta N, Takeuchi H, Amano A (2009) Entry of Porphyromonas gingivalis outer membrane vesicles into epithelial cells causes cellular functional impairment. Infect Immun 77: 4761–4770.
- 54. Amano A, Takeuchi H, Furuta N (2010) Outer membrane vesicles function as offensive weapons in host-parasite interactions. Microbes Infect 12: 791–798.
- 55. Ellis TN, Kuehn MJ (2010) Virulence and immunomodulatory roles of bacterial outer membrane vesicles. Microbiol Mol Biol Rev 74: 81–94.
- 56. Li Z, Clarke AJ, Beveridge TJ (1998) Gram-negative bacteria produce membrane vesicles which are capable of killing other bacteria. J Bacteriol 180: 5478–5483.
- 57. Chakraborty S (2012) Enumerating pathways of proton abstraction based on a spatial and electrostatic analysis of residues in the catalytic site. PLOS ONE 7: e39577.
- 58. Chakraborty S (2013) A quantitative measure of electrostatic perturbation in holo and apo enzymes induced by structural changes. PLoS ONE 8: e59352.
- 59. Chakraborty S (2012) An automated flow for directed evolution based on detection of promiscuous scaffolds using spatial and electrostatic properties of catalytic residues. PLOS ONE 7: e40408.
- 60. Chakraborty S, Minda R, Salaye L, Dandekar AM, Bhattacharjee SK, et al. (2013) Promiscuity-based enzyme selection for rational directed evolution experiments. Methods Mol Biol 978: 205–216.
- 61. Chakraborty S., Rao B.J., Baker N., Ásgeirsson B. Structural phylogeny by profile extraction and multiple superimposition using electrostatic congruence as a discriminator. Intrinsically Disordered Proteins 1: e25463.
- 62. Lone AM, Nolte WM, Tinoco AD, Saghatelian A (2010) Peptidomics of the prolyl peptidases. AAPS J 12: 483–491.
- 63. Titball RW (1993) Bacterial phospholipases C. Microbiol Rev. 57: 347–366.
- 64. Page MJ, Di Cera E (2008) Evolution of peptidase diversity. J Biol Chem 283: 30010–30014.
- 65. Titball RW, Naylor CE, Basak AK (1999) The Clostridium perfringens alpha-toxin. Anaerobe 5: 51–64.
- 66. McDonel JL (1980) Clostridium perfringens toxins (type A, B, C, D, E). Pharmacol Ther 10: 617–655.
- 67. Sakurai J, Nagahama M, Oda M (2004) Clostridium perfringens alpha-toxin: characterization and mode of action. J Biochem 136: 569–574.
- 68. Naylor CE, Eaton JT, Howells A, Justin N, Moss DS, et al. (1998) Structure of the key toxin in gas gangrene. Nat Struct Biol 5: 738–746.
- 69. Guillouard I, Alzari PM, Saliou B, Cole ST (1997) The carboxy-terminal C2-like domain of the alpha- toxin from Clostridium perfringens mediates calcium-dependent membrane recognition. Mol Microbiol 26: 867–876.
- 70. Nagahama M, Mukai M, Morimitsu S, Ochi S, Sakurai J (2002) Role of the C-domain in the biological activities of Clostridium perfringens alpha-toxin. Microbiol Immunol 46: 647–655.
- 71. Lobkovsky E, Moews PC, Liu H, Zhao H, Frere JM, et al. (1993) Evolution of an enzyme activity: crystallographic structure at 2 Å resolution of cephalosporinase from the ampC gene of Enterobacter cloacae P99 and comparison with a class A penicillinase. Proc Natl Acad Sci USA 90: 11257–11261.
- 72. Gosalia DN, Salisbury CM, Ellman JA, Diamond SL (2005) High throughput substrate specificity profiling of serine and cysteine proteases using solution-phase fluorogenic peptide microarrays. Mol Cell Proteomics 4: 626–636.
- 73. Boulware KT, Daugherty PS (2006) Protease specificity determination by using cellular libraries of peptide substrates (CLiPS). Proc Natl Acad Sci USA 103: 7583–7588.
- 74. Zhao H, Arnold FH (1999) Directed evolution converts subtilisin E into a functional equivalent of thermitase. Protein Eng 12: 47–53.
- 75.
Cheng K, Lu F, Li M, Liang X (2010) Improvement of subtilisin-like serine alkaline protease by directed evolution for cold-adaptation. In: Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on. 1–4. doi:10.1109/ICBBE.2010.5517430.
- 76. Venekei I, Szilagyi L, Graf L, Rutter WJ (1996) Attempts to convert chymotrypsin to trypsin. FEBS Lett 383: 143–147.
- 77. Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA (2001) Electrostatics of nanosystems: appli- cation to microtubules and the ribosome. Proc Natl Acad Sci USA 98: 10037–10041.
- 78. Dolinsky TJ, Nielsen JE, McCammon JA, Baker NA (2004) PDB2PQR: an automated pipeline for the setup of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Res 32: W665–667.
- 79. Ahyayauch H, Villar AV, Alonso A, Goni FM (2005) Modulation of PI-specific phospholipase C by membrane curvature and molecular order. Biochemistry 44: 11592–11600.
- 80. Villar AV, Alonso A, Goni FM (2000) Leaky vesicle fusion induced by phosphatidylinositol-specific phospholipase C: observation of mixing of vesicular inner monolayers. Biochemistry 39: 14012–14018.