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Common structural elements in 'scorpion-toxin' type proteins. P NarayananDepartment of Life Sciences, University of Mumbai, Mumbai, India., India
Correspondence Address: Source of Support: None, Conflict of Interest: None PMID: 0010734329 Keywords: Amino Acid Sequence, Animal, Protein Folding, Proteins, chemistry,Scorpion Venoms,
Animal and insects use their venom and toxin components for offence and defence and for several biological functions (e.g. as digestive proteases). The peptide venom toxins (neuro-, cardio- and cytotoxins) are low molecular mass molecules. Hence they are of potential molecular probes in elucidating the molecular mechanisms of signal transmission and transduction at the pre- and postsynaptic neuronal terminals, in addition to their pharmacological and medicinal uses. While their mode of action at the synaptic terminals is of importance in our understanding of the structure and function of ligand-gated channels, they are of importance as molecular tools in molecular (genetic) engineering and therapeutic agents in medicine. A rational approach towards molecular (genetic) engineering, namely, the design of altered molecules to suit desired requirements, rests on the availability of the three-dimensional structures (tertiary structures) of proteins that are to be 'engineered'. Physical techniques that are available, to date, to determine the three-dimensional structures are - single-crystal X-ray diffraction and multi-dimensional NMR spectroscopic methods. The bottleneck encountered in molecular engineering is due to the difficulty and delay in obtaining the tertiary structure data of macromolecules by these experimental methods, due to inherent constraints and operational restraints. Single-crystalline state of matter is a prerequisite for initiating X-ray diffraction studies, while the size (mass) of the molecule is the limiting factor in NMR spectroscopic methods. In addition, operational constraints make the existing experimental techniques of macromolecular structure determination a challenging and time-consuming process. The primary structure (amino acid sequence) data of proteins are obtainable faster and in a more 'routine' way than their tertiary structure (protein folding) data. Therefore, prediction of tertiary structures of proteins from their amino acid sequence data is an alternative approach to molecular engineering. This approach, though highly complex and challenging route, is an attractive and desirable one for multiple reasons - (i) to realize the full potential of rapidly growing gene sequence data, (ii) for rational molecular design, (iii) for molecular (protein) engineering (genetically altered proteins) and for (iv) de novo synthesis (design) of proteins. The task of predicting the tertiary structure of a protein, a priori, from its amino acid sequence data, is not at all that simple and straightforward. This is because protein folding is a highly cooperative process, involving secondary and tertiary structural interactions[1]. Prediction of secondary structure elements (helices, sheets and loops) of proteins from their amino acid sequence data, and then try to extend the predicted structural data towards predicting the tertiary structures of proteins is one of the often-employed methods[2] (and vide: literature). However, these empirical procedures are met with limited success, due to inherent limitations, although there is a proliferation of such prediction methods[3],[4],[5]. The reason is - topologies (structural motifs, domains etc), and not amino acid sequence homologies, are better conserved in protein folding. Structure prediction, in essence, should aim at pattern matching and it is, therefore, more meaningful to identify proteins by structural motifs and shapes and align the amino acid sequence data to fit these topologies[6], [7]. The complexity of the structure prediction problem can be minimized in certain classes of proteins, where the natural structural (geometrical) constraints strongly influence the tertiary folding interactions. This has been attempted with reasonable success in the prediction of the repertoire of conformation of hypervariable loop (for a given amino acid sequence) in immunoglobulins, on the basis of comparative studies of known antibody structures[8], [9]. Disulphide-containing peptides and proteins belong to other class of molecules, where natural structural constraints (S-S bonds) influence the protein folding. A disulphide bridge (S-S bond) moiety contains both secondary and tertiary structure features and such S-S moieties may circumvent (or minimize) the cooperative process in tertiary folding, in those structures where S-S bonds have a decisive influence in the folding process. In such classes of structures, simplification of structure prediction problem can be achieved by incorporating the "knowledge" about the disulphide-bonded moieties into the structure prediction methods. Neuro-, cardio- and cytotoxins of snake venoms, all scorpion venom toxins, sea snail and sea anemone toxins and some of the insect toxins and defensins are disulphide-containing peptides, which can be addressed under the "special" classes in structure prediction and modeling procedures. Simplification in the structure prediction procedures is possible, in the case of disulphide-containing proteins by incorporating (i) "knowledge" governing the packing interactions between and among various structural elements[10], [11] and (ii) "knowledge" of the role and hierarchy of the S-S bridges in these structures. The empirical "knowledge" for "modeling" tertiary structures of disulphide-containing proteins from their primary structure data is: 1) Residues that become buried in the interior of a solvent close-pack. Close packing and exclusion of water and burial of hydrophobic groups are the major determinants of protein folding. 2) Packing interactions stabilize folding and, therefore, tend to be conserved in protein folding processes. 3) Hydrophobicity is the major factor stabilizing higher order interactions (ligand-ligand interactions). 4) Secondary structures found in proteins interact in a manner that (gives maxim van der Waals energy) induces no appreciable steric strain. 5) Structural motifs, modules and topologies play a central role in protein folding. 6) In disulphide-containing proteins, there exists structural hierarchy of S-S bridges in stabilizing the structural moieties and tertiary folding. 7) S-S bonds render not only structural stability but also functional features. 8) Structural features of disulphide-bridged moieties depend on the number of residues in the S-S-bridged loops and on the neighboring interactions surrounding the loop(s). Tertiary structure prediction methods, based on the primary structure data, can be applied to 'scorpion-toxin' type peptides and proteins, where the S-S bonds play a predominant role in the folding process. All scorpion venom toxins are neurotoxins, comprising "short" (~ 35 amino acid) polypeptides with three S-S bonds and "long" (~ 65 amino acid) polypeptides with four S-S bonds (vide literature). While amino acid sequence data (primary structure) data are available for many scorpion venom toxins, the three-dimensional structure data, either by X-ray diffraction methods[12],[13] or by solution NMR spectroscopic studies[14],[15],[16],[17], are meager. From the 'core' structural motif [Figure - 1] that exists in these polypeptides and emphasizing the empirical 'knowledge', and based on the structural motif that exists in the structure of scorpion venom toxin, CsEV3[12],[18] [Figure - 2], namely a dense core of secondary structural elements stabilized by two 'core' S-S bridges, it has been possible to classify all 'scorpion-toxin' type proteins under a few tertiary structural categories (canonical structures) from their amino acid sequence data[19], [20] [Figure - 3]. Bee venom toxin, apamin[21] and mast cell degranulating peptide, MCD-401[22] have two disulphide bonds with similar motif. Insect defensins - sapecin[23], phormacin[24] and royalsin[25] have the structural motif that is found in several scorpion venom (short) toxins with triple S-S bonds[17], the structural motif CnII-11[19],[20]. As these insect antibacterial peptides have sequence homology with the rabbit-lung macrophage bacterial peptides[24], the natural peptide antibodies of rabbit lung macrophages, MCP-1 and MCP-2[26], the tertiary structures of these peptides can be classified under the 'scorpion-toxin' type tertiary structures. (-conotoxins - GI, GII, MI and SI from fish-hunting snails, c. geographus[27], c. magus[28] and c. striatus[29] have 'apamin' structural motif. Structure prediction methods, incorporating the 'knowledge' about the structural and functional features of S-S bridged moieties/elements/motifs can be attempted to model 'putative' structures and refine them with geometrical and energy minimization constraints to arrive at plausible tertiary structures of these peptides from their amino acid sequence data. Snake venom neuro-, cardio- and cytotoxins are also disulphide-containing proteins, but they have different set of motifs/topologies of S-S moieties. All the same, structure prediction can be employed in modeling this class of disulphide-containing proteins and peptides also. The general strategy of resolving the protein-folding problem in the 'scorpion-toxin' type proteins is[1],[2],[3],[4],[5],[6],[7],[10],[11],[30],[31]: 1. Obtain amino acid sequence data from various protein data banks and find sequence homology of the protein under consideration with the amino acid sequences of other proteins by sequence alignment algorithms. 2. Cluster the protein sequence into families, which show a clear sequence relationship, followed, by clustering proteins into structural families. 3. Carry out protein modeling studies by 'knowledge-based' rational approaches. In modelling 'putative' proteins, alignment of sequences is followed by insertions, deletions and replacements in the three-dimensional structure(s) of the homologous protein(s). Amino acid replacements occur most often in surface positions so that main chain conformations are little affected. In most families, divergence is accompanied by changes in the hydrophobic core. Structural motifs ((((( (((, 8-fold ((barrel, Rossmann fold, immunoglobulin fold motifs etc.) can also be used in protein modeling. 4. Modelled proteins are refined using energy minimization and other methods to give final structures without appreciable steric hindrance. Alternatively, modeling can be carried out on the basis of each available known tertiary structure and test the resulting models for packing of side chains, solvent accessibility and other physico-chemical parameters. Simultaneously, but selectively, the information from the known tertiary structures of homologous family can be used. All scorpion toxins are disulphide-containing peptide neurotoxins, with three disulphide bonds in "short" and four in "long" neurotoxins. All scorpion venom toxins have a distinct structural motif, with a dense core of secondary structural elements comprising disulphide bonds stabilizing the structure[12],[18]. This structural motif can be used in the modeling of three-dimensional structures of scorpion venom toxins, from their amino acid sequence data, incorporating the natural structural constraints that the disulphide bonds would impose that would enable the protein-folding problem less complex. Based on the secondary structural elements, stabilized by two 'core' disulphide bonds (in the scorpion venom toxins), and incorporating the structural hierarchy of the S-S bridges in stabilizing the structural moieties and tertiary structure, 'scorpion-toxin' type peptides can be classified under few tertiary structural categories, from their amino acid sequence data[19]. Scorpion venom toxins, such as charybdotoxin and noxiustoxin and leiurotoxin and other peptides with similar core structural motif/topology, namely, bee venom toxin, apamin[21], mast cell degranulating peptide, MCD-401[22] and insect defensins (e.g., sapecin, phormacin and royalsin)[23],[24],[25],[26] can be classified under these canonical tertiary structures[20]. Energy minimization, distance geometry and other procedures[3],[4],[5] can be employed to refine individual 'putative' structures further; and their folding patterns can be evaluated by molecular dynamical programming simulations and other modeling procedures[11], [31],[32],[33],[34]. Similarly, structure prediction and modeling procedures can be undertaken, starting from their amino acid sequence data, on other disulphide-containing molecules, such as hormonal peptides, sea anemone and sea snail venom peptides[35].
[Figure - 1], [Figure - 2], [Figure - 3]
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