1 Laboratório de Biologia Molecular and 2 Laboratório de Bioinformática, EMBRAPA, Recursos Genéticos e Biotecnologia, CP 02372, CEP 70770 Brasília, DF, Brazil and 3 Department of Biology, University of California San Diego, La Jolla, CA 92093-0116, USA
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Abstract |
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Keywords: amylase inhibitor/charge compatibility/hydrogen bond net/interface forming residues/protein interactions
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Introduction |
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-Amylases (
-1,4-glucan-4-glucanohydrolases) are a family of enzymes that hydrolyze
-D-(1,4)-glucan linkages in amylose, amylopectin, glycogen and phytoglycogen and play an important role in the carbohydrate metabolism of many autotrophic and heterotrophic organisms. Heterotrophic organisms use
-amylases primarily to digest starch in their food sources. Insects such as the yellow meal worm (Tenebrio molitor) and the Mexican bean weevil (Zabrotes subfasciatus), which live in dried stored products (wheat flour and seeds of the common bean, respectively), have evolved mechanisms to overcome the effects of the proteinaceous inhibitors that are present in their food sources. Tenebrio molitor highly expresses a single amylase gene and in this manner overcomes the presence of inhibitors in wheat flour. Many insects have several
-amylases that differ in specificity, and successful utilization of a food source is dependent on the presence of an
-amylase for which there is no specific inhibitor. To gain further insight into this problem of enzymeinhibitor specificity, we purified and cloned the cDNAs of two different
-amylase inhibitors from the common bean (Phaseolus vulgaris) (Grossi de Sá and Chrispeels, 1987, 1997
; Moreno and Chrispeels, 1989
), and recently cloned the cDNA of an
-amylase from the Mexican bean weevil (Zabrotes subfasciatus), which is inhibited by
-amylase inhibitor 2 (AI-2), but not by
-amylase inhibitor 1 (AI-1) (Grossi de Sá and Chrispeels, 1997
). These two inhibitors, which share 78% amino acid identity, have the converse interaction with pancreatic porcine
-amylase (PPA): AI-1 inhibits PPA, whereas AI-2 does not (Grossi de Sá and Chrispeels, 1997
).
The availability of the crystal structure of AI-1 complexed with PPA (Bompard-Gilles et al., 1996) allowed the modeling of the structure of AI-2. The structure of Zabrotes subfasciatus
-amylase (ZSA) was modeled based on the crystal structure of Tenebrio molitor
-amylase (TMA) (Strobl et al., 1998
). Pairwise AI-1 and AI-2 with PPA and ZSA complexes were also modeled. Modeled complexes were analyzed both with and without energy minimization. For this analysis, we first identified the interface forming amino acid residues (IFR) of the four possible complexes. In addition, we identified the hydrogen bonds, ionic interactions and loss of hydrophobic surface area resulting from complex formation.
Although the data we show here fall short of explaining the specificity of the inhibition, they do provide insight into the general scheme of binding. Three new web tools, STING, HORNET and STINGPaint, efficiently determine the IFR and ionic interaction data, the hydrogen bond net, as well as aid in interpretation of the multiple sequence alignment (MSA), respectively.
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Materials and methods |
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The program STINGPaint2 (manuscript in preparation), available at http://asparagin.cenargen.embrapa.br/STING/STINGpaint2/ and also at http//:trantor.bioc.columbia.edu/arthrosoft, was used for ease of presentation by means of adequate coloring of sequence identities, hydrophobic patches, charge distribution on critical loops around the active site, as well as for annotation of conserved and calculated structural features on the aligned sequences.
Molecular modeling of AI-2 and ZSA was carried out on a Silicon Graphics ONYX R4400 VTX workstation using the program MODELLER, release 4 (Sali et al., 1993). The atomic coordinates of AI-1 (Brookhaven Protein Data code 1DHK.pdb; Bompard-Gilles et al., 1996) were used to build the three-dimensional model of AI-2. The C-terminal end of AI-2 (residues 191213 in the processed sequence) was not modeled because there were no corresponding atomic coordinates in the template structure used for this region. The model of ZSA was built using the atomic coordinates of TMA available from the Protein Data Base (code 1JAE.pdb; Strobl et al., 1998). For the building of the inhibitorenzyme complex, we assumed the same orientation of the inhibitor and the enzyme as in 1DHK.pdb. Adequate superimpositions and substitutions, accompanied by energy minimization, resulted in modeled complexes. The energy minimization procedure used the steepest descent and conjugate gradient, set to run for up to 18 000 steps, or until the maximum derivative of the energy with respect to the atomic positions was less than 0.0002 kcal/mol/Å. To ensure that atom movement is limited for a region far from the interface layer, we previously set fixed coordinates for all atoms in the subset that is far from the interface. With this procedure we gained in CPU time and also in accuracy of modeled complexes. To define subsets of atoms belonging to the interface, we used our program STING (Neshich et al., 1998
), available at http://asparagin.cenargen.embrapa.br/STING/ and also at http://honiglab.cpmc.columbia.edu/STING and http://www.pdb.bnl.gov/pdb-bin/pdbids. In STING we can define the IFR layer based on a distance set to 8.0 Å and measured between any two atoms belonging to residues in two different protein chains. Once the IFR ensemble is defined, we can easily use this definition as the subset definition in Discover-3 for fixing all but the IFR atoms. IFR atoms were allowed to adjust freely when docking was performed. In another procedure, all atoms were fixed in the vicinity of their original positions. In this procedure, we did not permit adjustments of IFR atoms to the environment encountered in the active site, except for the simple removal of steric hindrance.
The same procedure was adopted to build the model of three complexes: AI-1ZSA, AI-2PPA and AI-2ZSA. The quality of the models was checked with PROCHECK (Laskowski et al., 1993).
Hydrogen bonds were determined using our own package HORNET (available at http://asparagin.cenargen.embrapa.br/HORNET/ and also at http://trantor.bioc.columbia.edu/arthrosoft/HORNET) which specifically shows the hydrogen bond net formed between two protein chains (or protein and DNA). HORNET also shows exact listings of IFR, based on calculated buried surface area. Both graphic and textual descriptions of all inter-chain hydrogen bonds were obtained and analyzed further. We preserved interface buried water molecules. To define subsets of water molecules at the interface, we used STING's feature `Interface HOH'. The coordinates of `Interface waters' were then inserted into modeled complexes and relaxed to appropriate positions during Discover minimization.
Charge pairing was analysed using features present in STING that allow for convenient graphic presentation of all charges at the interface of complexes. Using a sequence of STING's commands: `interface on', `charges on interface' and adequate hiding of other than IFRs, as well as reading distances between charges, we were able to easily identify charge interactions at the interface.
Electrostatic potential at the interface was calculated and graphically presented using the program GRASP (Nicholls et al., 1991). Partial and full charges were used for point and complete electrostatic field descriptions at the protein surfaces.
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Results |
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The ZSA sequence alignment to TMA (Figure 1) shows the gaps introduced in the ZSA sequence at positions 211 (by removing G210 in TMA), 294 (by removing S294 in TMA), 337 (by removing Q337 and D338 in TMA) and finally at position 347 (by removing 349356 in TMA). IFRs are indicated by the symbol `#' in Figure 1
. The gaps that were introduced are all outside the region where loops form the interface between the proteins. Except for S294 in ZSA, these gaps are not crucially important for binding of the inhibitor at the active site. The structure obtained was checked by the PROCHECK program with extensive parameter analysis, and clearly showed good agreement with expected and allowed values.
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Water molecules were introduced at the interfaces of the complexes ZSAAI1, ZSAAI2 and PPAAI2. The STING-L package (command: HOH interface) was used to obtain a list of those water molecules that are found positioned between the IFRs of the two chains in the complexes. The availability of such a quick identification of water molecules in between IFR's facilitates the determination of water mediated H-bonds formed between two chains. Figure 2 shows an example of the STING-L graphical representation of two IFR areas (blue CPK for AI-1 and white CPK for PPA) with red colored water molecules between them. The water molecules visualized are those that satisfy the geometric condition of being at a 3.3 Å (maximum) distance from both chains. The output of STING-L was then used in INSIGHT to define the subset of water molecules that is inserted in all complexes. These water molecules at the interface were allowed to relax to appropriate positions during the minimization process for all docked complexes (AI-1ZSA, AI-2ZSA and AI-2PPA). In such a way, we were able to get complete information about the hydrogen bond net formed between respective IFRs, including water mediated H-bonds.
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Discussion |
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Our methodology has several specific points; with respect to steric hindrance, we know that, in general, hard body docking approaches have intrinsic limitations due to their lack of consideration of molecular flexibility, so we used a strategy with further minimization. On the other hand, approaches that include the entire molecular structure during minimization can be extremely CPU intensive (Cherfils et al., 1991; Shoichet and Kuntz, 1991; Bacon and Moult, 1992
; Cherfils and Janin, 1993
; Norel et al., 1995
) as well as producing unexpected changes in parts of the molecule far from the interface. Our methodology defines IFRs and creates a corresponding subset to be the only region allowed to change during minimization. Using our methodology the model complexes contained no steric hindrance of such magnitude that could not be removed by the energy minimization procedure. In other words, in all models built, the inhibitor could penetrate without impeding steric hindrance into the active site. In addition, as reported by Jackson and Stenberg (1995), limiting minimization to only IFRs could avoid computationally expensive minimization (by avoiding `multiple' problems) as well as a lack of consideration of solvation energy (due to in vacuo simulations). As reported by the same authors, surface area burial, as well as electrostatic desolvation, depends weakly on the precise conformation of the docked structure, indicating that the precision in the docking step is not critical as far as these two parameters are concerned.
Specificity of the inhibitor isoforms towards different -amylases may depend on the strength of the network of hydrogen bonds that forms and stabilizes the inhibitorenzyme complex. However, this study shows that the hydrogen bond net alone is not a sufficiently clear indicator to explain the known inhibitory specificity of the two amylases.
Horton and Lewis (1992) showed a strong correlation between buried surface area and measured binding strength of many protein complexes. However, in their review, Cherfils et al. (1991) noted that when compared with the rest of an enzyme's surfaces, regions involved in interaction with other molecules are neither more hydrophobic nor enriched in groups bearing an electric charge. Our own analysis shows that hydrophobic areas of the enzyme and inhibitor that are buried upon complex formation, with respect to total surface area of two proteins in isolation, are actually larger in PPAAI-2 than in PPAAI-1. One would expect that the contribution to the binding energy coming from the thermodynamically favorable process of burying of hydrophobic areas would be more extensive in the case of PPAAI-1. However, this is not the case. Nevertheless, such a positive contribution to the binding energy, originating from the burial of the hydrophobic area, is observed in the case of ZSAAI-2 (in accordance with the observed data for inhibition of ZSA by AI-2). The same trend is observed if values are calculated with respect to the total hydrophobic area of the two proteins in isolation rather that the total surface area of the two proteins in isolation (last column in Table III). It is interesting though, that some other studies have shown that the binding site is not necessarily the most hydrophobic patch among all fitted geometries (Xu et al., 1997
); this gives an additional degree of complexity to an analysis based on hydrophobicity parameters in binding specificity.
The binding energy, or more generally energetics, of proteinprotein association has been reported to be critically dependent on the hydrophobic effect (Chothia and Janin, 1975). Electrostatic interactions, on the other hand, are more involved in specificity. Binding energy results from maximization of surface burial while minimizing penalties arising from desolvation. Although many authors (Cherfils and Janin, 1993
; Connolly, 1986
) have reported the use of buried surface area and buried hydrophobic surface area as a scoring function for docking, this alone, as confirmed by our results, is not sufficient to determine specificity.
Charge complementary is essential for binding and specificity (Janin, 1995). Proteins utilize residue identity and configuration at the surface as control of the recognition of ligands by electrostatics. The high selectivity found in some complexes may originate, to a large extent, from specific electrostatic interactions governed by polar groups (Warshel, 1979
, 1986
; Xu et al., 1995
). Xu et al. (1997) has shown that electrostatics can provide not only for specificity but also contributes to binding affinity. In our case, charge compatibility of IFR in the complexes studied indicates that total net charges satisfied with complementary charges, originating from the facing surface, are identical in both complexes: PPAAI-1 and PPAAI-2, as well as in case of ZSAAI-1 and ZSAAI-2. In the former case, however, the sum of the attractive and repulsive forces between facing IFRs is +1 (in favor of attractive forces), while in the latter case, the sum is +2 (in favor of attractive forces). Thus, this parameter alone would not be sufficient to explain the existing specificity of the inhibitors for the amylases.
The electrostatic potential calculated at the interface of complexes shows some variability around the active site (data not shown). This difference becomes more pronounced if its origin is presented through point charges that are at, or just below, the interactive surface of the inhibitor. Qualitative analysis of charge distribution clearly indicates the importance of site-specific substitutions at the IFR in -amylase inhibitors, as well as in
-amylases, corroborating the structural basis of the specificity. To make a description of the charge distribution at the interface in a form more readily understandable, we used the sequence annotated by structural parameters, produced by STINGPaint2.
The sequence similarity of both inhibitors and -amylases is high, so that the general fold and specific structural elements of the modeled (ZSA and AI-2) and known (PPA and AI-1) proteins are alike. Both inhibitors show the same two-chain structure as a product of proteolytic cleavage at position Asn77 and Asn75 in AI-1 and AI-2, respectively. A significant difference between AI-1 and AI-2 is the absence of Ser34 and Tyr35 in AI-2. We judged the lack of these residues to present a serious prejudice to the hydrogen bond net, as well as to the other parameters considered in this study.
After analysis of the hydrogen bonds, electrostatic potential, steric hindrance data and charge complementarity, substitutions in AI-2 (as indicated in Figure 6) are suggested. These are mainly due to a change in hydrophobic character on this specific IFR and/or charge difference between two sequences. Also, these residues, marked with a `©' symbol, make up an ensemble that we judge to be essential for the specificity, by a combination of factors mentioned above, as well as the fact that they are also members of the IFR ensemble.
Conclusions
Specificity of -amylase inhibitors for
-amylases of different origin has been studied at the molecular level. To address this complex issue, we analyzed separately several structural parameters that participate as components of the total energy of binding. In some cases, we did find satisfactory agreement of these parameters with the known specificity of the proteinprotein interaction. However, none of the parameters was able to explain binding across all complexes studied. Obviously, the process of encoding the specificity in an enzymeinhibitor complex is multifactorial. Qualitative and weighted contributions of each of the elements examined here may enable us to explain the observed specificity. We were nevertheless able to identify single critical elements of the sequence/structure of the inhibitors that together will effectively produce the desired specificity. None of the single sites will be able to change the specificity, but will most likely influence affinity of the inhibitor to the amylase. Suggested IFR substitutions are now being tested experimentally, the result of which will measure the degree of accuracy of the analyzed parameters.
The new tools used in this studypackage STING, STINGPaint and HORNEThave been shown to be both didactic tools as well as research tools. They are easy to use and require virtually no training time.
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Acknowledgments |
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Notes |
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References |
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Received May 30, 1999; revised October 26, 1999; accepted November 22, 1999.