Open access peer-reviewed chapter

Trypsins: Structural Characterization and Inhibition Focus in Insects

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Yaremis Beatriz Meriño-Cabrera and Maria Goreti de Almeida Oliveira

Submitted: 11 November 2021 Reviewed: 12 January 2022 Published: 06 March 2022

DOI: 10.5772/intechopen.102632

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Edited by Sajjad Haider, Adnan Haider and Angel Catalá

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Serine proteases are considered the main class of protein digestive enzymes present in the midgut of many lepidopteran species and are the focus of the review in this chapter. Among them, trypsin and chymotrypsin are the most studied and participate in a great diversity of physiological processes that include, in addition to digestion, activation of specific proteins, such as in the coagulation cascades, in the immune system of insects and plants, in the development and production of biologically active peptides, in signal transduction, hormone activation, and development. In this chapter, a review was made of the structural characteristics of trypsins, specifically of Lepidoptera insects, main experimental and theoretical techniques for the study of their function and structure, and interaction with other proteins and ligands as protease inhibitors. Finally, it was described how this type of hydrolases can be a focus of inhibition in pests to the detriment of the development and death of the target insect. Until now, the main strategies of agricultural crop management, especially of large crops, consist of the use of inorganic pesticides and transgenic cultivars containing Bacillus thuringiensis toxins. Therefore, new and ecologically friendly strategies are necessary, such as the use of protease inhibitors.


  • 3D structure of trypsin
  • catalytic triad
  • inhibitor protein
  • larvae
  • pest

1. Introduction

Enzymes have extraordinary catalytic power, often greater than synthetic or inorganic catalysts. They have a high degree of specificity for their respective substrates, accelerate chemical reactions, and act in aqueous solutions under mild temperature and pH conditions. Few non-biological catalysts have this set of properties. Except for a small group of catalytic RNA molecules, all enzymes are proteins. Enzymes are at the heart of every biochemical process. Acting in organized sequences, they catalyze each of the reactions of the hundreds of steps that degrade nutrient molecules, that conserve and transform chemical energy, and that build biological macromolecules from elementary precursors [1, 2].

One type of enzyme is the proteases or peptidases, molecules that promote cleavage through the hydrolysis of peptide bonds present in proteins and polypeptides, transforming them into a smaller amino acid or polypeptide residues [3]. The term protease appeared in the German literature of physiological chemistry in the latter part of the nineteenth century about proteolytic enzymes and was used as a general term embracing all the hydrolases that act on proteins or further degrade the fragments of them [4].

Proteolytic cleavage of peptide bonds is one of the most frequent and important enzymatic modifications of proteins. Historically, enzymatic proteolysis has generally been associated with protein digestion and early drew the attention of physiologists and biochemists who were interested in the process of protein digestion in animals and humans [5]. Hence, the digestive proteases of the pancreatic and gastric secretions are among the best-characterized enzymes, and the current knowledge of protein structure and enzyme function has been derived from a study of these proteases. Investigations of the kinetics, specificity, and inhibition, together with detailed analyses of their amino acid sequence and X-ray structure, have led to the identification of the components and geometry of their active sites, and from these, the mechanism of action of these digestive proteases was deduced [6]. As a result, it became evident that proteases can be classified into families, members of each family having similar structures and mechanisms of action.

Proteases are classified according to the Enzyme Commission of the International Union of Biochemistry and Molecular Biology (IUBMB) within group 3 (hydrolases), subgroup 4. They are also classified based on three criteria: (1) type of reaction catalyzed, (2) chemical nature of the catalytic site, and (3) evolutionary relationship according to structure [7].

Proteases are subdivided into two main groups, the exopeptidases, and the endopeptidases, depending on their site of action. The exopeptidases cleave peptide bonds close to the amino or carboxy-terminal group in the substrate, while endopeptidases cleave peptide bonds far from the terminal group of the protein substrate [5, 8].

Insect digestive proteases are classified based on the functional group present in the active site into serine, cysteine, aspartyl, and metalloproteases [5, 8, 9]. Serine proteases have a serine residue at their active center, while aspartyl proteases have two aspartic acid units at their catalytic center. Cysteine-proteases have an amino acid cysteine, and metalloproteases have a metal ion in their catalytic mechanism [8]. Some insects often have multiple digestive proteases in their intestinal tract, belonging to different or the same mechanic group, although they usually use one principal type in their digestive function [10, 11].

Serine proteases are considered the main class of digestive protein enzymes present in the midgut of many lepidopteran species [9] and are the review focus in this chapter. Among them, trypsin and chymotrypsin are the most studied and participate in a great diversity of physiological processes that include, in addition to digestion, activation of specific proteins, such as in the coagulation cascades, in the immune system of insects and plants, in the development and production of biologically active peptides, in signal transduction, hormone activation, and development [12, 13, 14].

Serine proteases belong to the largest gene families in the animal kingdom, are widely distributed in nature, and are found in all assemblies of cellular life, as well as in several viral genomes, indicating vital participation in the metabolism of these organisms [14]. In insects, a study with Helicoverpa armigera demonstrated the existence of at least 28 different genes belonging to the serine-proteases family whose products are expressed in the gut [15]; Furthermore, a proteomic analysis of the gut of the soybean pest Anticarsia gemmatalis where proteases were characterized by LC/MS, 54 expressed antigens were found for gut protease, suggesting multiple important isoforms involved in the digestion process and other functions in the larval gut [16].

In Ref. [8] it is described that serine proteases are generally active at neutral and alkaline pH, with a pH optimum between 7.0 and 11.0. They have broad specificity, including amidase and esterase activities. The molecular mass of serine proteases is generally in the range of 18–35 kDa [17, 18]. However, several organisms have serine proteases with higher molecular masses, such as Melolontha melolontha (Coleoptera: εelolonthidae), whose molecular mass for two trypsin-like enzymes is 56 and 63 kDa [19]. The isoelectric point of serine proteases is generally in the pH range 4.0 and 6.0 [16, 20].

The catalytic function of serine proteases is realized through the action of the catalytic triad (Serine 195 reactive, Histidine 57, and Aspartic acid 102 to trypsin bovine). The degree and type of substrate specificity are determined by the nature of the active center region [21]. When residues in the catalytic triad are altered, separately or together, large changes in the enzyme turnover rate (Kcat) occur, changing the enzyme mechanism, with little effect on KM. The residues of the triad act in perfect synergism and contribute to an optimized catalytic activity [22]. Serine proteases generally act in a two-step hydrolysis reaction, where a covalently linked intermediate, acyl-enzyme, is formed.

This acylation is followed by the deacylation, a process in which a water-mediated nucleophilic attack occurs, resulting in hydrolysis of the peptide. The nucleophilic attack of the hydroxyl group of the serine residue 195 on the carboxylic carbon atom of the peptide bond, catalyzed by the histidine residue, which acts as a base, leads to the formation of a tetrahedral intermediate and an imidazole ion. The intermediate decomposes via acid-base catalysis by the action of the polarized groups of aspartate and histidine into an acyl-enzyme intermediate, an imidazole base, and an amine. This mechanism involves close contact between the tetrahedral intermediate and the imidazole ion, which inhibits proton release to the solvent medium before acid-base catalysis, regenerating the active enzyme and releasing the degradation product [24]. Each step occurs through the formation of a tetrahedral intermediate, whose structure resembles a high-energy transition state in both reactions. This mechanism is capable of accelerating the speed of peptide bond hydrolysis more than 109-fold compared with the uncatalyzed reaction [14, 23, 24, 25].

The ratio between the speed of acylation and deacylation depends on the type of substrate used. For an amide substrate, the velocity of acylation is slower than for deacylation, and for an ester substrate, can be one to three times faster. Therefore, in the amidase activity, the acylation step is slow and deacylation fast, while in esterase enzymes the acylation step is fast and the deacylation step is slow, and the slow step is the limiting step in hydrolysis [26].


2. Trypsin-like enzymes in insects

The occurrence of different digestive enzymes in the insect alimentary canal is usually associated with the chemical composition of the ingested diet. However, the theory of dietary adaptation should not disregard phylogenetic aspects in determining the type (not quantity) of enzymes present in the insect gut. The possibility that insects possess a wide variety of digestive enzymes, whose relative amounts present may change in response to diet, is considered. This change could occur during an individual’s feeding or result from the adaptation of a taxonomic group of insects to a particular diet, resulting in the presence of enzymes whose activities are permanently greater than others [27].

In Ref. [28] it was demonstrated that the intestinal proteolytic profile changes during larval development of Anticarsia gemmatalis caterpillars, the activity of cysteine proteases is more intense in the first instar. On the contrary, the serine proteases showed major activities in the late stages of the larval phase. Furthermore, Zymogram analysis and protein identification by liquid chromatography–mass spectrometry indicated serine protease as the main protease class expressed in the fifth instar.

Protein digestion in lepidopterans is performed mainly by serine proteases, the increase in the structural and functional diversity of genes that code for this sub-subclass can be attributed to the insect’s response machinery to circumvent of protease inhibitors (PIs). Therefore, these constitutively expressed proteins represent an adaptive advantage [16].

Trypsins (EC are serine proteases and are considered the most important digestive proteases of most insects. Trypsins are involved in the initial phase of protein digestion and are characterized by containing a catalytic triad consisting of the amino acid residues Hys, Asp, and Ser; in A. gemmatalis trypsin are Ser 229, Hys 85, and Asp 132 [16, 29, 30].

Every trypsin-like serine protease has a preference for substrates with a basic residue at P1, Lys, or Arg. This is mainly caused by the presence of a negatively charged Asp 189 at the bottom of the S1 pocket (numbering used in chymotrypsinogen). The architecture of the S1 site among these proteases is highly conserved. A striking difference is found at position 190, which can be an Ser or Ala, and serves as an identification point for subfamilies [31]. The nomenclature for substrate amino acid residues is Pn, …, P2, P1, P1′, P2′, …, Pn′, where P1-P1’ denotes the hydrolyzed bond. Sn, …, S2, S1, S1′, S2′, …, Sn′ denotes the corresponding binding subsites of the enzyme [22].

Insect trypsins have similar primary specificity; except Lepidoptera, these proteases hydrolyze more efficiently substrates containing Arg than Lys at the P1 position [32, 33]. Lepidopteran trypsins have higher specificity for Lys-containing substrates than for Arg-containing substrates. Protease inhibitors produced by plants present a region known as the reactive site, which interacts with its target enzyme. The sequence alignment of several plant protease inhibitors indicated that the reactive sites of most of these inhibitors have a Lys residue at the P1 position [32]. The presence of a Lys at the P1 site in the reactive site is a survival strategy, as these inhibitors would act by inhibiting the trypsins of most insects that preferentially hydrolyze Arg at this position [30, 34].

Trypsins isolated from the midgut of various insects typically exhibit molecular mass between 20 and 35 kDa and optimal activity at alkaline pH [17, 18]. Trypsins from lepidopterans typically exhibit higher pH optimum corresponding to the high pH value of the midgut contents. Most lepidopteran serine proteinases sequences do not contain lysine residues. The lysine residue at position 188 is conserved in mammalian and dipteran trypsins. However, in Lepidoptera, this residue is replaced by arginine. It has been suggested that this substitution is a necessary adaptation for the stability of the enzyme in the gut of these insects, where the pH value is very high, associated with the need for the digestive enzymes to remain protonated [15, 35]; However, the presence of lysine in the sequence of the digestive trypsins of Sesamia nonagroides and Helicoverpa armigera has already been described [36].

Although the primary specificity of trypsins from most insects is similar to that of vertebrates, and they show sequence homology in the catalytic site region, their properties contrast in several respects. Insect trypsins, in most cases, are unstable at acidic pH, exhibit different sensitivities to inhibitors, and typically contain fewer cysteine pairs in their sequences than do vertebrate trypsins [37].

In vertebrates, calcium prevents the aggregation of enzyme molecules, protecting it from autolysis and denaturation by heat, inducing a conformational change in its structure to a more compact form, which is necessary for catalytic activity [38]. According to the literature, insect trypsins are not influenced in their tryptic activity by calcium ions, which has been demonstrated in several studies on serine proteases from various insects such as Spodoptera litura (Lepidoptera) [39], in Helicoverpa armigera (Lepidoptera) [40]; soluble and membrane trypsin-like proteins of Musca domestica (Diptera) [41]; trypsin of Spodoptera littoralis (Lepidoptera) [42], and in Ref. [11] Pilon and coworkers analyzed the trypsins of A. gemmatalis (Lepidoptera), verifying that trypsins found in these insects are not stabilized or activated by calcium ions.

The autolysis of insect trypsins typically differs from that of mammalian trypsins. The stabilization of mammalian trypsins depends on calcium binding to the binding motif in their structure; this motif is not present in the sequences of insect trypsins. The autocatalytic sites in mammalian trypsins (Lys 61-Ser 62, Arg 117-Val 118, and Lys 145-Ser 146) are not conserved in insects, having their cleavage sites [33]. However, several authors found that the trypsins of the studied insects suffered a drop in tryptic activity on the substrate BApNA in the presence of EDTA, a result that led the authors to suggest that calcium maybe, in some way, acting on the enzymes of these insects [19, 43, 44].

The processing and secretion mechanisms of insect trypsins also appear to include aspects that differ from other animals. There is evidence that the soluble form of insect trypsin is derived from a membrane-bound form [45]. The presence of trypsin in the soluble form whose kinetic and physical properties were identical to the microvillar membrane-associated form in M. domestica [46] led the authors to propose a mechanism of trypsin secretion, where trypsin is synthesized in the midgut cells of insects in the active form but associated with the vesicle membrane, which will be processed in the microvilli becoming soluble before being secreted [45].

Through immunolocalization studies, trypsins also were detected in more than one form in the gut of Spodoptera frugiperda (Lepidoptera) [47]. Trypsins were observed associated with the microvillar membrane of midgut cells, the membrane of secretory vesicles, and within the microvilli. A secretion model was proposed, where trypsin is synthesized bound to the membrane via a hydrophobic anchor peptide. Subsequently, the enzyme would be processed in the Golgi complex and transported in secretory vesicles. These vesicles migrate through the microvilli and either before or after fusing with the microvillar membrane are released into the intestinal lumen in the form of double- or single-membrane vesicles, respectively. The double-membrane vesicles fuse to form a single membrane. The trypsin present on the luminal surface of these vesicles is then solubilized by limited proteolysis or by the dissolution of the vesicles due to the highly alkaline pH of the midgut contents. Remnant membranes, with some trypsin bound, are finally incorporated into the peritrophic membrane [48].

In A. gemmatalis, a study provided evidence of the presence of membrane-bound trypsin-like proteases in midgut preparations of the velvet bean caterpillar, a key soybean pest in warm climates, and the likely occurrence of members of other protease families [43]. The detection of proteolytic activity in the insoluble fraction from the midgut of A. gemmatalis, after treatment with Triton X-100 and centrifugation at 100,000 g, indicates the occurrence of membrane-bound proteases that may be least partially transferred to the peritrophic membrane [43].


3. Methodologies and techniques for the study of digestives trypsin-like enzyme of lepidoptera larvae

3.1 In vitro

3.1.1 Gel-filtration chromatography

Gel-filtration chromatography is performed on a Superose 12 HR10/30 column (10 mm × 30 cm) in an FPLC system equilibrated with 0.1 M Tris-HCl pH 7.5 and 0.1 M NaCl. A flow rate of 0.5 mL/min is used and fractions of 1.5 mL, collected in each tube, and before collection, 1.5 M Phomic acid is added to keep the collected samples at pH 3.0. The sample applied to the gel-filtration column is the enzyme extract obtained from the intestines of the insect larvae. The enzymatic activity of each fraction collected in the chromatographs is monitored using L-BApNA as substrate. For calibration of the Superose 12 HR10/30 column, the following molecular mass standards are used: Blue Dextran (2 × 106 Da), amylase (205,000 Da), alcohol dehydrogenase (150,000 Da), BSA (66,000 Da), ovalbumin (45,000 Da), chymotrypsinogen (25,000 Da), cytochrome C (12,327 Da), aprotinin (6500 Da), which are applied to the column; and the retention time and Kav obtained for each standard applied, through these data, it is possible to calculate the molecular mass ranges of the samples of interest.

3.1.2 Ion exchange chromatography

The samples after gel-filtration chromatography are dialyzed, in membranes with a cutoff of 12,000–14,000 Da, 150 times against 5 mM Tris–HCl pH 7.5 buffer, and subsequently applied (10 mL per run) to the ion exchange column. Ion exchange chromatography is performed on a Mono-Q HR 5/5 column (5 mm × 5 cm). Equilibrated with 0.1 M Tris–HCl pH 7.5 and eluted with a NaCl gradient. A flow rate of 1 mL/min is used and 1.5 ml fractions are collected. The enzyme activity of each fraction is monitored using L-BApNA as substrate.

3.1.3 Affinity chromatography

Affinity chromatography by column HiTrap Benzamidine is an efficient method for partial purification of trypsin-like proteases and has been used in other studies getting similar results [11, 18]. The efficiency of the method may be due to the fact that the benzamidine is a potent competitive inhibitor of trypsin-like proteases that occupies the S1 subsite (site of specificity) of the enzyme; benzamidine is stabilized by hydrophobic interactions in its hydrophobic pocket and electrostatic interactions between the amidine group and carboxyl group belonging to the residue aspartic acid present in the bottom of the S1 site [11, 49].

The samples, after gel-filtration or ion-exchange chromatography, have their pH set to 7.5 and were applied (5 mL) to affinity chromatography. This chromatography is done on a HiTrap Benzamidine column equilibrated with 0.1 M Tris-HCl, pH 7.5, and eluted with 10–3 M HCl. A flow rate of 0.5 mL/min is used, and 1.5 mL fractions are collected. The enzymatic activity of each fraction is monitored, using L-BApNA as substrate.

3.1.4 Enzyme activity

The amidase activity is carried out according to the method already described [50], using sample (extract of the intestate or enriched trypsin fraction after chromatography), chromogenic substrate L-BApNA at a final concentration of 0.5 mM, and 0.1 M Tris-HCl buffer, pH 8.2. The initial velocities are determined by the formation of the product p-nitroanilide, by measuring its absorbance at 410 nm as a function of time (120 s), using for the calculations of the molar extinction coefficient of 8800 M−1 × cm−1 for the product. The experiment is performed in triplicates.

3.1.5 Determination of protein concentration

The determination of the total protein concentration of the samples is estimated by the method described [51], using a 0.2 mg/mL BSA solution to obtain a standard curve for quantification.

3.1.6 SDS-PAGE

The efficiency of the purification method was also confirmed by the results of SDS-PAGE with a reduction of protein species in the purified sample compared with the crude extract. Electrophoresis is performed by the method already described [51]. Using a 12.5% polyacrylamide gel in the presence of SDS (0.1%), the experiment is performed at a constant voltage of 100 V for 1 h20 at room temperature. The gel is stained by silver or Coomassie blue staining. The molecular mass standard used is purchased from Invitrogen (“BenchMark ™ Protein Ladder”).

3.1.7 Zymogram

Zymogram is performed using 12.5% SDS-PAGE containing 0.1% copolymerized gelatin. Electrophoresis occurred at 50 V at 4°C, and the gel was subsequently incubated in 2.5% (v/v) Triton X-100 for 1 h at room temperature and under stirring to remove SDS. After incubation, the gels are washed and again incubated with 0.1 M Tris-HCl buffer, pH 8.0, for 2 h at 37°C. The activity is revealed by staining with “Coomassie Blue” R-250 (0.25%).

3.2 In silico methods

The interaction between PIs and insect trypsin-like enzymes is an example of ligand-macromolecule recognition, required in the plant defense process. The understanding of these recognition mechanisms is one of the central aspects for the success in the discovery of new promissory compounds. The characterization of binding mode between inhibitor and protease can be obtained from several methods, among them the in silico studies that allow the reduction of time and costs, specifically docking-molecular analyzes allow to identify the binding conformation and affinity quantification [52]. Below we will show the main methodologies.

3.2.1 Molecular modeling

Molecular modeling encompasses all the computational techniques used to simulate the behavior of molecules. These techniques are widely used in the fields of computational chemistry and drug development to study biological systems and can therefore be applied to the discovery of enzyme inhibitors. Comparative protein modeling

Functional characterization of protein sequences is a frequent problem in the biological field. It is now well established that knowledge of molecular structure is a powerful tool to understand, control, and alter functions of biomolecules. Although three-dimensional structures of proteins can be determined by X-ray crystallography and nuclear magnetic resonance (NMR), these experiments demand time and large quantities of proteins in self-purify and have some limitations. The NMR technique is difficult to apply to large proteins (greater than 250 amino acid residues), or very flexible proteins, while X-ray crystallography depends on obtaining crystals with good diffraction ability, a process performed by trial and error, and solving the phase problem [53]. However, protein sequences can be determined much more easily by using molecular biology and protein sequencing techniques. Therefore, in cases where the structure cannot be determined experimentally, homology modeling can often produce a useful three-dimensional model of a target sequence based on its similarity to a protein with a known structure used as a template protein [54].

The principle of molecular homology modeling is based on the fact that throughout evolution the structures of proteins are more conserved than their sequence [53, 55]. The biological evolution of proteins has some rules such as homology between amino acid residue sequence implies structural and functional similarity; homologous proteins have conserved internal regions (mainly consisting of secondary structure elements: α-helices and β-sheets); structural changes between homologous proteins occur in the loop regions [55]. Furthermore, proteins are grouped into a limited number of three-dimensional families making it possible to model the proteins of interest if there is a member of the family that already has its structure determined. A model built by comparative modeling needs that at least one 3D structure of the family in question has been elucidated by experimental techniques. Another important point is the identity between the sequences (target and template), this value should be above 25% so that the generated model can be reliable [53, 56]. Homology molecular modeling features four main steps: the search for homologous protein sequences, the alignment of the sequences, the construction and optimization of the models, and finally, the evaluation and validation of the generated structures [56]. Phyre2 and protein modeling

The Phyre2 system is a combination of software created and written in several languages by a researcher’s group in London, England. The system runs on a Linux program with an approximately 300-core CPU. The Phyre2 server can be used in several ways, depending on the user’s research focus. The most commonly used facility is the prediction of the 3D structure of a single submitted protein sequence [57].

The Phyre and Phyre2 servers predict the three-dimensional structure of a protein sequence using the principles and techniques of homology modeling. A protein sequence of interest (the target) can be modeled with reasonable accuracy using a sequence far removed from the known structure (the template) since the relationship between the target and template can be discerned through sequence alignment. Currently, the most powerful and accurate methods for detecting and aligning remotely related sequences rely on profiles or hidden Markov models (HMMs). These profiles/HMMs capture the mutational propensity of each position in an amino acid residue sequence based on mutations observed in related sequences and can be thought of as an “evolutionary fingerprint” of a specific protein (Figure 1) [57, 58].

Figure 1.

Normal-mode Phyre2 pipeline showing algorithmic stages taken to the Phyre2 web portal for protein modeling, prediction, and analysis. Stage numbers are shown in circles, and elements within a stage are surrounded by a dashed box. Stage 1 (gathering homologous sequences): A query sequence is scanned against the specially curated nr20 (no sequences with >20% mutual sequence identity) protein sequence database with HHblits. The resulting multiple-sequence alignment is used to predict secondary structure with PSIPRED and both the alignment and secondary structure prediction combined into a query hidden Markov model. Stage 2 (fold library scanning): This is scanned against a database of HMMs of proteins of known structure. The top-scoring alignments from this search are used to construct crude backbone-only models. Stage 3 (loop modeling): Indels in these models are corrected by loop modeling. Stage 4 (side-chain placement): amino acid side chains are added to generate the final Phyre2 model [58].

Typically, the amino acid residue sequences of a representative set of all known three-dimensional protein structures are compiled, and these sequences are processed by scanning into a large protein sequence database. The result is a database of profiles or HMMs, one for each known 3D structure. A user sequence of interest is processed in a similar way to form a profile/HMM. This user profile is verified in the profile database using profile-profile or HMM-HMM alignment techniques. These alignments can also take into account predicted or known secondary structure element patterns and can be scored using various statistical models [57, 58].

3.2.2 Quality and validation of three-dimensional protein models

The quality of the generated models depends mainly on the existence of appropriate templates, i.e., with good resolution, high coverage, and high identity. For close homologs, the most commonly used programs in most cases generate resolutive models with RMSD (root mean square deviation) of approximately 2 Å from the experimental structure. Generally, a sequence identity above 35% is sufficient to produce good models for proteins above approximately 100 amino acid residues, and as the similarity between target and template decreases, the model error increases [59].

Among the programs used for validation of stereochemical features of protein structures is the PROCHECK program, which uses selected stereochemical information from high-quality structures to provide an overall assessment of the structure and to highlight regions that need refinement.

The program can be used independently of experimental data and applied to structures already published or to structures generated by comparative modeling. The program also analyzes the torsion angles of the main (phi and psi) and side chains of the molecule informing the bad contacts and planarity of peptide bonds [60]. One of the most well-known output files generated by the program is the Ramachandran plot that presents a correlation between the torsional angles of the main chain. Analysis of the rotation of these angles led to the identification of allowed and disallowed regions where collisions between atoms occur [60].

Another widely used program for validation is ProSa, a tool that relies on a statistical analysis of all protein structures deposited in the PDB. Soluble protein structures whose z-scores, a score used by the program to evaluate the quality of three-dimensional protein models, depart from the averages obtained for experimentally determined structures are uncommon and usually stem from various structural errors. This tool uses a knowledge-based function of the Potential of Mean Force type, which describes the preferred geometries of a given sequence of amino acid residues by statistically analyzing the interaction geometries between atoms of structures deposited in the PDB [61].

3.2.3 Molecular docking

Understanding the mechanisms of protein-ligand molecular recognition is one of the central aspects for the discovery and planning of new compounds. Obtaining an accurate and automated description of the molecular recognition process, using computational methodologies, can allow the reduction of the time and high costs involved in the development of new drugs [62].

Among these methodologies, receptor-ligand docking has contributed significantly to advances in drug development and is employed in the refinement and optimization of previously identified prototype compounds, virtual database screening, and estimation of protein-ligand binding affinities. The molecular docking methodology aims to predict the binding orientation of two molecules forming a stable complex and to estimate the binding affinity between them. Therefore, the success of the technique is measured by comparing the predicted results with binding modes determined by X-ray crystallography of the complexes and affinity measurements determined in vitro assays [62].

To perform molecular docking, basically, three steps are required: definition of the structure of the target molecule, location of the binding site, and prediction of the binding mode and affinity of a ligand using specific algorithms. The structure can be obtained by X-ray crystallography, NMR techniques, or computationally predicted by comparative modeling as described earlier. The application of these models for docking is already well established and represents an important alternative when experimental structures are not yet available [63].

The prediction of binding mode and affinity is performed using search algorithms and evaluation functions, two main aspects that differentiate docking programs. Search algorithms are used to sample the possible orientations of the ligands bound to the protein target, considering translational, rotational, and conformational degrees of freedom (which evaluate the dihedral angles associated with simple covalent bonds).

Evaluation functions can be divided into three main classes: force-field-based functions, empirical functions, and knowledge-based functions. Force-field-based functions use a force field to calculate the binding energy between the ligand and the protein target. Empirical functions use empirical and semiempirical methods whose coefficients have been pre-optimized based on experimental results of receptor-ligand structures and their respective inhibition constants. Knowledge-based functions also use experimental data but use crystallographic structures to describe the receptor-ligand interaction geometries, instead of using data from the inhibition constants. Through statistical analysis of these geometries, “Mean Force Potentials” are derived, which evaluate the change in free energy as a function of interatomic coordinates. Because of the errors associated with these three-class evaluation functions, newer programs are using combinations of these functions to produce consensus functions, which appear to increase the quality of the results [64].

3.2.4 Protein-protein docking

Protein–protein docking has immense applications (Figure 2). It is particularly important in predicting metabolic pathways, macromolecular interactions, and macromolecular assemblies. Due to the difficulty in determining macromolecular assemblies experimentally, computational prediction of possible binding modes is one of the main goals of this type of docking [64]. Protein-protein docking simulates molecular recognition and is the most complex docking task. This is because the number of degrees of freedom is enormous, and it is not a possibility to do an exhaustive search of the conformational space. This is why many docking algorithms treat proteins as rigid bodies [65].

Figure 2.

Protein-protein docking, the receptor protein in blue surface and ligand protein in red surface. The docking study is determined the interface region (yellow), i.e., the residues of amino acids of the receptor and ligand that participate in the interaction or formation of the protein-protein complex, these residues (hot-spots) can serve to design new molecules with an inhibitory character, for example, in the case of the study of the trypsin-inhibitor complex.

The Cluspro 2.0 server could be employed for protein-protein docking. This server performs rigid body docking and generates 109 complexes by performing rotation and translation movements of one protein (“ligand”) relative to another (“receptor”, held fixed). Docking conformations are classified according to the properties of their clusters. To rank the docking conformations, the program considers the pairwise interaction potential, the solvation energy, as well as the van der Waals (attraction and repulsion) and electrostatic contributions.


4. Trypsin-inhibition focus for the pest control

Insects represent one of the most important biotic stresses in agriculture worldwide. They are responsible for reducing crop yields, despite the use of chemical pesticides. These not only cause yield losses directly due to herbivore attack but also indirectly by acting as vectors for various plant pathogens. The estimated losses in crops around the world, without the use of pesticides or other non-chemical control strategies, reach about 70% of production, representing a loss of US$ 400 billion to the agricultural sector [66].

In the attempt to control the attack of insects on cultivars, new methods have been sought that are not based on agrochemical strategies. Although today the methods of pest control still concentrate primarily on the use of these substances, the high cost of developing new products whose formulations must suit pests that are increasingly resistant to their use, the unacceptable environmental consequences, and consumer pressure against this practice have caused a revolution in pest control in modern agriculture [67].

Thus, the study of molecules that can help in the control of herbivorous insects is very important. Until now, the main strategies of agricultural crop management, especially of large crops, consisted of the use of inorganic pesticides and transgenic cultivars containing Bacillus thuringiensis toxins. However, in addition to the damage caused to the environment and human health by inorganic insecticides, several insects of agronomic importance have developed resistance to these molecules.

For example, the frequent applications of diamide-type insecticides have already selected resistant individuals of important lepidopteran pests, in several locations around the world, since the beginning of their use 10 years ago [68]. Moreover, the other, more sustainable control method, based on the expression of Bt toxins, also suffers similar problems as insecticides. There have already been reported cases of Bt resistance since 1990, from Plutella xylostella (Lepidoptera: Plutellidae) larvae that required dosages of the dispel toxin (Abbott Laboratories North Chicago, OL), e.g., one of the first Bt toxin formulations for field spraying; 2x higher than susceptible populations to be controlled at acceptable levels [69]. In the following years, reports of resistance involving Bt insecticides and transgenic cultivars containing Bt toxin variants began to emerge in several other parts of the globe as well [70]. For these reasons, searches for new, preferably more sustainable, molecules have been ongoing in science.

Among possible new molecules are plant-derived protease inhibitors (PIs). Until the early 1980s, it was known that molecules that reduced the activity of proteolytic enzymes, the PIs, were present in plant tissues. It was then, in 1992, that Dr. Terry Green, a postdoctoral fellow at the University of Washington, showed that tomato and potato plants accumulated large amounts of protease inhibitors when exposed to herbivory by the potato beetle, Leptinotarsa Decemliata (Coleoptera: Chrysomelidae). From this moment on, the IPs and digestive proteases of herbivorous insects became the target of the study of many researchers. Several works show that chronic exposure of insects, mainly those of the order Lepidoptera, to plant-derived protease inhibitors such as SKTI (Soybean Kunitz Trypsin Inhibitor), SBBI (Soybean Bowman-Birk Inhibitor), APTI (Adenanthera pavonina Trypsin Inhibitor), ILTI (Inga Laurina Trypsin Inhibitor) showed negative effects on the larval cycle of these herbivores (Figure 3). These adverse effects include reduced weight, survival, and delayed larval cycle [17, 29, 71, 72, 73, 74, 75]. However, the use of these molecules so far in agriculture has not proven effective, mainly due to the long exposure period required to cause effective control rates. In this regard, even efforts to express exogenous IPs constitutively (e.g., as is done with Bt toxins) in plants have not proven effective yet, since the initial attempt in 1987, when researchers expressed an inhibitor found in peas (Cowpea Trypsin Inhibitor) in tobacco (Nicotiana tabacum) leaves and observed that several orders of insects adapted quickly, returning to normal weight in a short period of time [76].

Figure 3.

APTI (Adenanthera pavonina trypsin inhibitor) and ILTI (Inga Laurina trypsin inhibitor) are an example of protein inhibitors of lepidoptera trypsins.

The commonly accepted mode of action of IPs in herbivores is that these molecules inhibit digestive proteases in the gut, resulting in a deficiency of free amino acids and consequently slowing the larval cycle and reducing survival and fecundity [77]. However, the effect of IPs may be more complex than just reducing proteolytic activity in the gut. It has been shown that feedback mechanisms in response to IPs lead to hyperproduction of proteases to compensate for the activity of the inhibited enzymes. The nutritional stress imposed by this mechanism, which needs to divert amino acids important for insect development, slows development and reduces survival [78].

The main mechanisms of adaptation to IPs by herbivores so far recorded involve the following strategies: overexpression of the target protease, expression of proteases insensitive to the IP, and degradation of the molecule by endogenous proteolytic cleavage [79]. Thus, although naturally produced protease inhibitors are supplanted by the high gene plasticity of herbivores, these molecules are undoubtedly a defense mechanism against insects and thus a valuable target for the development of new insecticides. Plant tissues have a suboptimal protein content. Thus, nitrogen often becomes the limiting factor in the nutrition of many if not most phytophagous insects. Efficient hydrolysis of plant proteins to obtain essential amino acids is crucial for the survival of herbivores.

Indeed, for these molecules to be efficient against herbivores, more complex studies using more current bioinformatics tools, omics, and protease kinetics can be used to further explore and understand the mechanisms of adaptations to IPs. It is known that the set of proteolytic enzymes present in the midgut of herbivores can be composed of serine, threonine, cysteine, aspartic, and metalloproteases [80]. However, in the case of insects of the order Lepidoptera, the vast majority use protein digestion systems based on serine-proteases, trypsin-like, and chymotrypsin-like [81]. In addition, different isoforms of serine-proteases are known to be present in the gut of the same species. These different isoforms assist in the complex mechanism of insect response to IPs [76]. Insect trypsins share similar, but not identical, specificities with vertebrate trypsins. For example, some insect trypsins, unlike those of mammals, are calcium-stabilized and others not [11].

The mechanisms of response to IPs in herbivorous insects are not yet fully understood, and therefore protease inhibitors with characteristics that can prevent the insect from supplanting the effect of these molecules may generate more promising results. To date, much of the work testing the anti-insect effects of IPs has used molecules extracted and purified from plants [76]. However, due to the long periods of close association/interaction between insects and plants, possibly the mechanisms of herbivores are more prepared to counteract these kinds of molecules. Therefore, exposing herbivores to protease inhibitors that were not closely evolved, such as mammalian IPs and designed peptides, may elevate the anti-insect effects of these molecules. In Spodoptera gregaria larvae (Lepidoptera: Noctuidae) exposed to inhibitors of the pacifastin multidomain fam¬ily (115 kDa), e.g., (inhibitors of non-vegetable origin) was shown further growth suppression than plant inhibitors early in the insect cycle. However, the effect was gradually supplanted by the herbivores, which normalized their growth by the end of the cycle. Possibly, due to the high number of residues of the pacifastin IPs, a high amount of cleavage sites may be present, causing them to undergo endogenous proteolysis in the midgut.

Several works unravel the mechanisms behind the interactions between protease inhibitors (natural or otherwise) and proteases in the digestive tract of herbivorous insects, mainly the soybean caterpillar Anticarsia gemmatalis. Until then, much information has been generated regarding the specificities of A. gemmatalis proteases, mainly cysteine-proteases and serine-proteases. In 2005, trypsin-like enzymes from the gut of A. gemmatalis were purified and characterized. They showed the potential effect of several protease inhibitors on the activity of these enzymes. Inhibitors of serine proteases, including Benzamidine, TLCK, PMSF, and BPTI, reduced the activity of purified trypsins by more than 50% at relatively low concentrations in the micromolar and millimolar range [44]. And in the reference [11] the in vivo effects of synthetic trypsin inhibitors such as Benzamidine were evaluated.

Benzamidine was able to reduce protein digestibility, which affects the survival and formation of A. gemmatalis adults. The reference [11] evaluated the effect of this inhibitor throughout the insect cycle and concluded that although it caused an increase in the larval cycle and a higher percentage of mortality, most larvae were able to adapt to the inhibitor by remodeling the amount and type of enzyme present during digestion of the artificial diet. In addition, negative effects of other protease inhibitors on A. gemmatalis, mainly the organic ones [29, 30], were shown. Peptide protease inhibitors have also been tested, which were developed from molecular minimization using docking-molecular techniques in developing insects of the order Lepidoptera [81]. Even after molecule minimization, the conserved domains of trypsin IPs were able to reduce survival and important biological parameters of A. gemmatalis and S. cosmioides. An important work opened the vision for another approach in the attempt to use protease inhibitors in herbivore control.

Smaller, rationally designed molecules, based on enzyme kinetics and bioinformatics results, can help in the development of molecules that present better levels of control [82]. Besides generating increased molar concentration of protease inhibitors in the gut lumen and presenting higher stability than the conventionally tested PIs. In addition, protease inhibitor molecules without close association with the herbivore are less likely to find adaptation mechanisms. Transgenic plants can also be generated by generating proteins based on tandem sequences of previously tested peptides.


5. Conclusion

We concluded that the trypsin enzymes are serine proteases and are considered the most important digestive proteases of most insects. Trypsins are involved in the initial phase of protein digestion and are characterized by containing a catalytic triad consisting of the amino acid residues Hys, Asp, and Ser; in A. gemmatalis trypsin is Ser 229, Hys 85, and Asp 132. In the gut, insects exhibit the potential expression of various trypsin isoforms, but the proteolytic metabolism can be targeted by protease inhibitors, such as SKTI, ILTI, ApTI, BPTI, which offer possibilities for the development of novel biorational-based insect control approaches in silico methodologies such as molecular modeling and docking. The action of the protease inhibitors on the development of Lepidoptera larvae shows that these inhibitors influence larval survival, indicating that these proteins may have great toxic potential.



The authors would like to thank the National Council for Scientific and Technological Development (Conselho Nacional de Desenvolvimento Científico e Tecnológico—CNPq), the Brazilian Federal Agency for the Support and Evaluation of Graduate Education (Coordenação de Aperfeiçoamento de Pessoal de Ensino Superior—CAPES), and the Protection Foundation for Research in Minas Gerais (Fundação de Amparo à pesquisa de Minas Gerais, FAPEMIG).


Conflict of interest

The authors declare no conflict of interest.


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Written By

Yaremis Beatriz Meriño-Cabrera and Maria Goreti de Almeida Oliveira

Submitted: 11 November 2021 Reviewed: 12 January 2022 Published: 06 March 2022