Characterizing Protease Specificity: How Many Substrates Do We Need?

Calculation of cleavage entropies allows to quantify, map and compare protease substrate specificity by an information entropy based approach. The metric intrinsically depends on the number of experimentally determined substrates (data points). Thus a statistical analysis of its numerical stability is crucial to estimate the systematic error made by estimating specificity based on a limited number of substrates. In this contribution, we show the mathematical basis for estimating the uncertainty in cleavage entropies. Sets of cleavage entropies are calculated using experimental cleavage data and modeled extreme cases. By analyzing the underlying mathematics and applying statistical tools, a linear dependence of the metric in respect to 1/n was found. This allows us to extrapolate the values to an infinite number of samples and to estimate the errors. Analyzing the errors, a minimum number of 30 substrates was found to be necessary to characterize substrate specificity, in terms of amino acid variability, for a protease (S4-S4’) with an uncertainty of 5 percent. Therefore, we encourage experimental researchers in the protease field to record specificity profiles of novel proteases aiming to identify at least 30 peptide substrates of maximum sequence diversity. We expect a full characterization of protease specificity helpful to rationalize biological functions of proteases and to assist rational drug design.     

Detection of proteolytic activity by fluorescent zymogram in-gel assays

Proteases are involved in the regulation of many biological functions. This study describes a novel method for detecting protease activity by fluorescent zymogram in-gel protease assays, using SDS polyacrylamide gels copolymerized with a peptide-MCA (4-methyl-coumaryl-7-amide) substrate. This method allows simultaneous determination of protease cleavage specificity and molecular weight. Trypsin was electrophoresed in SDS polyacrylamide gels copolymerized with Boc-Gln-Ala-Arg-MCA, the gel was then incubated in assay buffer, and trypsin cleavage of the peptide-MCA substrate generated fluorescent AMC (7-amino-4-methyl-coumarin), which was subsequently detected under UV transillumination. Chymotrypsin activity was detected in gels copolymerized with Suc-Ala-Ala-Pro-Phe-MCA substrate. Selective detection of these proteases was demonstrated by the absence of trypsin activity in gels containing the chymotrypsin substrate, and the lack of chymotrypsin activity in gels containing the trypsin substrate. Detection of proteolytic activity from secretory vesicles of adrenal medulla (chromaffin granules) was observed with the trypsin substrate, Z-Phe-Arg-MCA, but not with the chymotrypsin substrate. Overall, this sensitive fluorescent zymogram in-gel protease assay method can be used for rapid determination of protease cleavage specificity and enzyme molecular weight in biological samples. This assay should be useful for many research disciplines investigating the role of the many proteases that control cellular functions.     

Substrate specificity of rhomboid intramembrane proteases is governed by helix-breaking residues in the substrate transmembrane domain

Rhomboid intramembrane proteases initiate cell signaling during Drosophila development and Providencia bacterial growth by cleaving transmembrane ligand precursors. We have determined how specificity is achieved: Drosophila Rhomboid-1 is a site-specific protease that recognizes its substrate Spitz by a small region of the Spitz transmembrane domain (TMD). This substrate motif is necessary and sufficient for cleavage and is composed of residues known to disrupt helices. Rhomboids from diverse organisms including bacteria and vertebrates recognize the same substrate motif, suggesting that they use a universal targeting strategy. We used this information to search for other rhomboid substrates and identified a family of adhesion proteins from the human parasite Toxoplasma gondii, the TMDs of which were efficient substrates for rhomboid proteases. Intramembrane cleavage of these proteins is required for host cell invasion. These results provide an explanation of how rhomboid proteases achieve specificity, and allow some rhomboid substrates to be predicted from sequence information.     

Substrate-Driven Mapping of the Degradome by Comparison of Sequence Logos

Sequence logos are frequently used to illustrate substrate preferences and specificity of proteases. Here, we employed the compiled substrates of the MEROPS database to introduce a novel metric for comparison of protease substrate preferences. The constructed similarity matrix of 62 proteases can be used to intuitively visualize similarities in protease substrate readout via principal component analysis and construction of protease specificity trees. Since our new metric is solely based on substrate data, we can engraft the protease tree including proteolytic enzymes of different evolutionary origin. Thereby, our analyses confirm pronounced overlaps in substrate recognition not only between proteases closely related on sequence basis but also between proteolytic enzymes of different evolutionary origin and catalytic type. To illustrate the applicability of our approach we analyze the distribution of targets of small molecules from the ChEMBL database in our substrate-based protease specificity trees. We observe a striking clustering of annotated targets in tree branches even though these grouped targets do not necessarily share similarity on protein sequence level. This highlights the value and applicability of knowledge acquired from peptide substrates in drug design of small molecules, e.g., for the prediction of off-target effects or drug repurposing. Consequently, our similarity metric allows to map the degradome and its associated drug target network via comparison of known substrate peptides. The substrate-driven view of protein-protein interfaces is not limited to the field of proteases but can be applied to any target class where a sufficient amount of known substrate data is available.     

Methods for mapping protease specificity

The study of protease specificity provides information on active-site structure and function, protein-protein interaction, regulation of intracellular and extracellular pathways, and evolution of protease and substrate genes. Peptide libraries that include fluorogenic and binding tags are often generated by solid-phase synthesis. Even larger explorations of cleavage site preferences employ positional scanning libraries or phage display. Microarrays enable presentation of individual peptides to proteases, DNA sequences for capture of peptide nucleic acid encoded peptides, or nanodroplets containing soluble peptide sequences. These new methods continue to inform the design of chemical inhibitors and the identification of substrates of proteases.     

Current and prospective applications of non-proteinogenic amino acids in profiling of proteases substrate specificity

Abstract Proteases recognize their endogenous substrates based largely on a sequence of proteinogenic amino acids that surrounds the cleavage site. Currently, several methods are available to determine protease substrate specificity based on approaches employing proteinogenic amino acids. The knowledge about the specificity of proteases can be significantly extended by application of structurally diverse families of non-proteinogenic amino acids. From a chemical point of view, this information may be used to design specific substrates, inhibitors, or activity-based probes, while biological functions of proteases, such as posttranslational modifications can also be investigated. In this review, we discuss current and prospective technologies for application of non-proteinogenic amino acids in protease substrate specificity profiling.     

Assessment of substrate specificity of hepatitis G virus NS3 protease by a genetic method

The RNA genome of hepatitis G virus (HGV) encodes a large polyprotein that is processed to mature proteins by viral-encoded proteases. The HGV NS3 protease is responsible for the cleavage of the HGV polyprotein at four different locations. No conserved sequence motif has been identified for the cleavage sites of the NS3 protease. To determine the substrate specificity of the NS3 protease, amino acid sequences cleaved by the NS3 protease were obtained from randomized sequence libraries by using a screening method referred to as GASP (Genetic Assay for Site-specific Proteolysis). Based on statistical analyses of the obtained cleavable sequences, a consensus substrate sequence was deduced: Gln-Glu-Thr-Leu-Val downward arrow Ser, with the scissile bond located between Val and Ser. The relevance of this peptide as a cleavable substrate was further supported by molecular modeling of the NS3 protease. Our result would provide an insight on the molecular activity of the NS3 protease and may be useful for the design of substrate-based inhibitors.     

Performance of random forest when SNPs are in linkage disequilibrium

Background

Proteases of human pathogens are becoming increasingly important drug targets, hence it is necessary to understand their substrate specificity and to interpret this knowledge in practically useful ways. New methods are being developed that produce large amounts of cleavage information for individual proteases and some have been applied to extract cleavage rules from data. However, the hitherto proposed methods for extracting rules have been neither easy to understand nor very accurate. To be practically useful, cleavage rules should be accurate, compact, and expressed in an easily understandable way.

Results

A new method is presented for producing cleavage rules for viral proteases with seemingly complex cleavage profiles. The method is based on orthogonal search-based rule extraction (OSRE) combined with spectral clustering. It is demonstrated on substrate data sets for human immunodeficiency virus type 1 (HIV-1) protease and hepatitis C (HCV) NS3/4A protease, showing excellent prediction performance for both HIV-1 cleavage and HCV NS3/4A cleavage, agreeing with observed HCV genotype differences. New cleavage rules (consensus sequences) are suggested for HIV-1 and HCV NS3/4A cleavages. The practical usability of the method is also demonstrated by using it to predict the location of an internal cleavage site in the HCV NS3 protease and to correct the location of a previously reported internal cleavage site in the HCV NS3 protease. The method is fast to converge and yields accurate rules, on par with previous results for HIV-1 protease and better than previous state-of-the-art for HCV NS3/4A protease. Moreover, the rules are fewer and simpler than previously obtained with rule extraction methods.

Conclusion

A rule extraction methodology by searching for multivariate low-order predicates yields results that significantly outperform existing rule bases on out-of-sample data, but are more transparent to expert users. The approach yields rules that are easy to use and useful for interpreting experimental data.     

Cleavage Specificity Analysis of Six Type II Transmembrane Serine Proteases (TTSPs) Using PICS with Proteome-Derived Peptide Libraries

Background

Type II transmembrane serine proteases (TTSPs) are a family of cell membrane tethered serine proteases with unclear roles as their cleavage site specificities and substrate degradomes have not been fully elucidated. Indeed just 52 cleavage sites are annotated in MEROPS, the database of proteases, their substrates and inhibitors.

Methodology/Principal Finding

To profile the active site specificities of the TTSPs, we applied Proteomic Identification of protease Cleavage Sites (PICS). Human proteome-derived database searchable peptide libraries were assayed with six human TTSPs (matriptase, matriptase-2, matriptase-3, HAT, DESC and hepsin) to simultaneously determine sequence preferences on the N-terminal non-prime (P) and C-terminal prime (P’) sides of the scissile bond. Prime-side cleavage products were isolated following biotinylation and identified by tandem mass spectrometry. The corresponding non-prime side sequences were derived from human proteome databases using bioinformatics. Sequencing of 2,405 individual cleaved peptides allowed for the development of the family consensus protease cleavage site specificity revealing a strong specificity for arginine in the P1 position and surprisingly a lysine in P1′ position. TTSP cleavage between R↓K was confirmed using synthetic peptides. By parsing through known substrates and known structures of TTSP catalytic domains, and by modeling the remainder, structural explanations for this strong specificity were derived.

Conclusions

Degradomics analysis of 2,405 cleavage sites revealed a similar and characteristic TTSP family specificity at the P1 and P1′ positions for arginine and lysine in unfolded peptides. The prime side is important for cleavage specificity, thus making these proteases unusual within the tryptic-enzyme class that generally has overriding non-prime side specificity.     

PROSPER: An Integrated Feature-Based Tool for Predicting Protease Substrate Cleavage Sites

The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s). Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database) with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate sequence using machine learning techniques. It is freely available at http://lightning.med.monash.edu.au/PROSPER/.     

A lead discovery strategy driven by a comprehensive analysis of proteases in the peptide substrate space

We present here a comprehensive analysis of proteases in the peptide substrate space and demonstrate its applicability for lead discovery. Aligned octapeptide substrates of 498 proteases taken from the MEROPS peptidase database were used for the in silico analysis. A multiple‐category naïve Bayes model, trained on the two‐dimensional chemical features of the substrates, was able to classify the substrates of 365 (73%) proteases and elucidate statistically significant chemical features for each of their specific substrate positions. The positional awareness of the method allows us to identify the most similar substrate positions between proteases. Our analysis reveals that proteases from different families, based on the traditional classification (aspartic, cysteine, serine, and metallo), could have substrates that differ at the cleavage site (P1–P1′) but are similar away from it. Caspase‐3 (cysteine protease) and granzyme B (serine protease) are previously known examples of cross‐family neighbors identified by this method. To assess whether peptide substrate similarity between unrelated proteases could reliably translate into the discovery of low molecular weight synthetic inhibitors, a lead discovery strategy was tested on two other cross‐family neighbors—namely cathepsin L2 and matrix metallo proteinase 9, and calpain 1 and pepsin A. For both these pairs, a naïve Bayes classifier model trained on inhibitors of one protease could successfully enrich those of its neighbor from a different family and vice versa, indicating that this approach could be prospectively applied to lead discovery for a novel protease target with no known synthetic inhibitors.     

3C-like protease of rabbit hemorrhagic disease virus: identification of cleavage sites in the ORF1 polyprotein and analysis of cleavage specificity.

Rabbit hemorrhagic disease virus, a positive-stranded RNA virus of the family Caliciviridae, encodes a trypsin-like cysteine protease as part of a large polyprotein. Upon expression in Escherichia coli, the protease releases itself from larger precursors by proteolytic cleavages at its N and C termini. Both cleavage sites were determined by N-terminal sequence analysis of the cleavage products. Cleavage at the N terminus of the protease occurred with high efficiency at an EG dipeptide at positions 1108 and 1109. Cleavage at the C terminus of the protease occurred with low efficiency at an ET dipeptide at positions 1251 and 1252. To study the cleavage specificity of the protease, amino acid substitutions were introduced at the P2, P1, and P1' positions at the cleavage site at the N-terminal boundary of the protease. This analysis showed that the amino acid at the P1 position is the most important determinant for substrate recognition. Only glutamic acid, glutamine, and aspartic acid were tolerated at this position. At the P1' position, glycine, serine, and alanine were the preferred substrates of the protease, but a number of amino acids with larger side chains were also tolerated. Substitutions at the P2 position had only little effect on the cleavage efficiency. Cell-free expression of the C-terminal half of the ORF1 polyprotein showed that the protease catalyzes cleavage at the junction of the RNA polymerase and the capsid protein. An EG dipeptide at positions 1767 and 1768 was identified as the putative cleavage site. Our data show that rabbit hemorrhagic disease virus encodes a trypsin-like cysteine protease that is similar to 3C proteases with regard to function and specificity but is more similar to 2A proteases with regard to size.     

Phage display substrate: a blind method for determining protease specificity

Phage display substrate enables rapid determination of protease specificity by exposing vast numbers of recombinant peptides to a given protease. Peptides released through specific cleavage are amplified in an expression system. Phage display substrate has been widely exploited and developed further. The number of proteases (from various sources) characterized by this approach testifies to its power. To conserve their advantage over chemical methods, however, phage libraries must be constructed accordingly. The current phenomenal progress in genomics steadily increases the number of protease to be studied. Phage display substrate should prove a powerful method to exploit this wealth of new knowledge.     

Molecular and enzymatic characterization of the porcine endogenous retrovirus protease

The protease of the porcine endogenous retrovirus (PERV) subtypes A/B and C was recombinantly expressed in Escherichia coli as proteolytically active enzyme and characterized. The PERV Gag precursor was also recombinantly produced and used as the substrate in an in vitro enzyme assay in parallel with synthetic nonapeptide substrates designed according to cleavage site sequences identified in the PERV Gag precursor. The proteases of all PERV subtypes consist of 127 amino acid residues with an M(r) of 14,000 as revealed by determining the protease N and C termini. The PERV proteases have a high specificity for PERV substrates and do not cleave human immunodeficiency virus (HIV)-specific substrates, nor are they inhibited by specific HIV protease inhibitors. Among the known retroviral proteases, the PERV proteases resemble most closely the protease of the murine leukemia retrovirus.     

Amino acid preferences for a critical substrate binding subsite of retroviral proteases in type 1 cleavage sites

The specificities of the proteases of 11 retroviruses representing each of the seven genera of the family Retroviridae were studied using a series of oligopeptides with amino acid substitutions in the P2 position of a naturally occurring type 1 cleavage site (Val-Ser-Gln-Asn-Tyr Pro-Ile-Val-Gln; the arrow indicates the site of cleavage) in human immunodeficiency virus type 1 (HIV-1). This position was previously found to be one of the most critical in determining the substrate specificity differences of retroviral proteases. Specificities at this position were compared for HIV-1, HIV-2, equine infectious anemia virus, avian myeloblastosis virus, Mason-Pfizer monkey virus, mouse mammary tumor virus, Moloney murine leukemia virus, human T-cell leukemia virus type 1, bovine leukemia virus, human foamy virus, and walleye dermal sarcoma virus proteases. Three types of P2 preferences were observed: a subgroup of proteases preferred small hydrophobic side chains (Ala and Cys), and another subgroup preferred large hydrophobic residues (Ile and Leu), while the protease of HIV-1 preferred an Asn residue. The specificity distinctions among the proteases correlated well with the phylogenetic tree of retroviruses prepared solely based on the protease sequences. Molecular models for all of the proteases studied were built, and they were used to interpret the results. While size complementarities appear to be the main specificity-determining features of the S2 subsite of retroviral proteases, electrostatic contributions may play a role only in the case of HIV proteases. In most cases the P2 residues of naturally occurring type 1 cleavage site sequences of the studied proteases agreed well with the observed P2 preferences.     

Proteases from human immunodeficiency virus and avian myeloblastosis virus show distinct specificities in hydrolysis of multidomain protein substrates.

The virally encoded proteases from human immunodeficiency virus (HIV) and avian myeloblastosis virus (AMV) have been compared relative to their ability to hydrolyze a variant of the three-domain Pseudomonas exotoxin, PE66. This exotoxin derivative, missing domain I and referred to as LysPE40, is made up of a 13-kilodalton NH2-terminal translocation domain II connected by a segment of 40 amino acids to enzyme domain III of the toxin, a 23-kilodalton ADP-ribosyltransferase. HIV protease hydrolyzes two peptide bonds in LysPE40, a Leu-Leu bond in the interdomain region and a Leu-Ala bond in a nonstructured region three residues in from the NH2-terminus. Neither of these sites is cleaved by the AMV enzyme; hydrolysis occurs, instead, at an Asp-Val bond in another part of the interdomain segment and at a Leu-Thr bond in the NH2-terminal region of domain II. Synthetic peptides corresponding to these cleavage sites are hydrolyzed by the individual proteases with the same specificity displayed toward the protein substrate. Peptide substrates for one protease are neither substrates nor competitive inhibitors for the other. A potent inhibitor of HIV type 1 protease was more than 3 orders of magnitude less active toward the AMV enzyme. These results suggest that although the crystallographic models of Rous sarcoma virus protease (an enzyme nearly identical to the AMV enzyme) and HIV type 1 protease show a high degree of similarity, there exist structural differences between these retroviral proteases that are clearly reflected by their kinetic properties.     

Activity based fingerprinting of proteases using FRET peptides

We have successfully developed a protease assay using fluorescence resonance energy transfer based peptide libraries, which allows not only general detection of enzymatic activities, but more importantly substrate fingerprinting of proteases from different classes. The method allows the generation of substrate fingerprints of a protease from both the nonprime and prime sites. Therefore, it is well suited for profiling of major metalloproteases such as thermolysin and MMPs. We envisage that this method will provide a useful tool in the emerging field of Catalomics for high-throughput studies of proteases.     

High throughput substrate specificity profiling of serine and cysteine proteases using solution-phase fluorogenic peptide microarrays

Proteases regulate numerous biological processes with a degree of specificity often dictated by the amino acid sequence of the substrate cleavage site. To map protease/substrate interactions, a 722-member library of fluorogenic protease substrates of the general format Ac-Ala-X-X-(Arg/Lys)-coumarin was synthesized (X=all natural amino acids except cysteine) and microarrayed with fluorescent calibration standards in glycerol nanodroplets on glass slides. Specificities of 13 serine proteases (activated protein C, plasma kallikrein, factor VIIa, factor IXabeta, factor XIa and factor alpha XIIa, activated complement C1s, C1r, and D, tryptase, trypsin, subtilisin Carlsberg, and cathepsin G) and 11 papain-like cysteine proteases (cathepsin B, H, K, L, S, and V, rhodesain, papain, chymopapain, ficin, and stem bromelain) were obtained from 103,968 separate microarray fluorogenic reactions (722 substrates x 24 different proteases x 6 replicates). This is the first comprehensive study to report the substrate specificity of rhodesain, a papain-like cysteine protease expressed by Trypanasoma brucei rhodesiense, a parasitic protozoa responsible for causing sleeping sickness. Rhodesain displayed a strong P2 preference for Leu, Val, Phe, and Tyr in both the P1=Lys and Arg libraries. Solution-phase microarrays facilitate protease/substrate specificity profiling in a rapid manner with minimal peptide library or enzyme usage.     

Intramembrane Proteolysis of Mgm1 by the Mitochondrial Rhomboid Protease Is Highly Promiscuous Regarding the Sequence of the Cleaved Hydrophobic Segment

Rhomboids are a family of intramembrane serine proteases that are conserved in bacteria, archaea, and eukaryotes. They are required for numerous fundamental cellular functions such as quorum sensing, cell signaling, and mitochondrial dynamics. Mitochondrial rhomboids form an evolutionarily distinct class of rhomboids. It is largely unclear how their activity is controlled and which substrate determinants are responsible for recognition and cleavage. We investigated these requirements for the mitochondrial rhomboid protease Pcp1 and its substrate Mgm1. In contrast to several other rhomboid proteases, Pcp1 does not require helix-breaking amino acids in the cleaved hydrophobic region of Mgm1, termed ‘rhomboid cleavage region’ (RCR). Even transmembrane segments of inner membrane proteins that are normally not processed by Pcp1 become cleavable when put in place of the authentic RCR of Mgm1. We further show that mutational alterations of a highly negatively charged region located C-terminally to the RCR led to a strong processing defect. Moreover, we show that the determinants required for Mgm1 processing by mitochondrial rhomboid protease are conserved during evolution, as PARL (the human ortholog of Pcp1) showed similar substrate requirements. These results suggest a surprising promiscuity of the mitochondrial rhomboid protease regarding the sequence requirements of the cleaved hydrophobic segment. We propose a working hypothesis on how the mitochondrial rhomboid protease can, despite this promiscuity, achieve a high specificity in recognizing Mgm1. This hypothesis relates to the exceptional biogenesis pathway of Mgm1.