Analysis of molecular structures and mechanisms for toxins derived from venomous animals

https://doi.org/10.1016/j.compbiolchem.2015.11.004Get rights and content

Highlights

  • We showed a linear behavior between availability and use of residues in non-toxins.

  • Five prediction rules were employed for 114 residue compositions in venom toxins.

  • A dual molecular mechanism by stereochemical interactions was revealed for toxins.

  • A new residue composition prediction method to analyze toxins was suggested.

Abstract

As predominant component in the venom of many dangerous animal species, toxins have been thoroughly investigated for drug design or as pharmacologic tools. The present study demonstrated the use of size and hydrophobicity of amino acid residues for the purposes of quantifying the valuable sequence–structure relationship and performing further analysis of interactional mechanisms in secondary structure elements (SSEs) for toxin native conformations. First, we showed that the presence of large and hydrophobic residues varying in availability in the primary sequences correspondingly affects the amount of these residues being used in the SSEs in accordance with linear behavioral patterns from empirical assessments of experimentally derived toxins and non-toxins. Subsequent derivation of prediction rules was established with the aim of analyzing molecular structures and mechanisms by means of 114 residue compositions for venom toxins. The obtained results concerning the linear behavioral patterns demonstrated the nature of the information transfer occurring from the primary to secondary structures. A dual action mechanism was established, taking into account steric and hydrophobic interactions. Finally, a new residue composition prediction method for SSEs of toxins was suggested.

Introduction

Toxins are proteins that predominantly constitute the venom of dangerous animals, such as snakes, scorpions, spiders, cone snails, sea anemones, insects and fish (Rash and Hodgson, 2002). Venom is strategically used when performing predation and defense, and often results in high morbidity and mortality rates, which have been reported as a serious hazard to public health in many countries (Ushanandini et al., 2006). Therefore, toxins have been actively investigated in basic research (Nagaraju et al., 2006, Whetstone and Hammock, 2007) as pharmacological and diagnostic tools (Harvey, 2002), templates for drug design, and therapeutic agent candidates, thereby transforming toxicity into profit. Animal toxins vary exceedingly in terms of their ability to endamage preys and threats due to diversified biological effects arising from the actions of venom (Cologna et al., 2009, Dokmetjian et al., 2009). These effects can include hemorrhagic, myotoxic, neurotoxic, hemolytic and proteolytic activities. For example, neurotoxic activity drastically influences neural transmission, and significantly alters muscular contraction and relaxation, respiration and cardiac function, which can have a potentially fatal effect on a prey or threat.

Multiple covalent disulfide bridges (Kong et al., 2004) formed by means of sequential distant cysteine residues (Matsunaga et al., 2009) strengthen native-state structures in toxins (or toxic proteins) (Redfern et al., 2008) as well as diminish macromolecule susceptibility to enzymatic digestion (Nayak et al., 1999), so that only a few toxic proteins without such bridges have been isolated and characterized in some breeds, e.g., scorpions (Zeng et al., 2005). In terms of function, toxins work as cell modulators through recognition and selective binding to ion channels (mainly calcium, chloride, potassium, and sodium) and membrane receptors (Restrepo-Angulo et al., 2010). In the case of ion channels (Gabashvili et al., 2007), toxins target these channels by blocking them, enhancing or decreasing their opening, preventing or slowing their inactivation, and modifying gating (electrophysiology). Thus, toxins affect various kinds of cells, alter fundamental physiological processes, and subsequently inflict severe biological effects (Cologna et al., 2009, Dokmetjian et al., 2009).

Functional native configurations of toxins and non-toxins (or other proteins that are not labeled as toxins) have secondary structure elements (SSEs) as underlying constituents, mainly α-helices and β-pleated sheets formed by strands. They are commonly divided into four classes: mostly α; mostly β; mixed α and β; and few secondary structures (Orengo et al., 1997). The process for predicting SSEs from the primary sequence isvery challenging. It has been thoroughly investigated using different approaches and specific details regarding the molecular forces stabilizing secondary structures and, significantly improving the process. However, the performance of prediction methods is still dependent on some peculiar features of the water-soluble and transmembrane proteins (Majorek et al., 2009). Another issue is related to secondary structural classes, where better predictive analyses usually occur for α classes (Gromiha and Selvaraj, 2004). Therefore, the greatest challenge should be to improve the prediction accuracy for β and mixed classes (Midic et al., 2007, Best and Mittal, 2010) of the interspersed α/β or segregated α + β forms (Lindström et al., 2009).

Size (steric hindrance) and hydrophobicity (hydrophobic clustering) are considered to be universal and common attributes of residues in toxins and non-toxins. These two attributes have long been recognized as the indispensable and primary determinants of the native folded state (Chothia, 1984, Ramachandran and Sasisekharan, 1968), and both were examined here. Excluded volume or steric interactions comprise the main factor involved in biomolecular structural organization (Richards, 1977), SSE packing (Jiang et al., 2003) and molecular interplays (Halperin et al., 2002). Computational simulations (Rocha et al., 2009), statistical analyses of known macromolecular conformations (Miyazawa and Jernigan, 1996) and structure prediction methods (Zhang et al., 1998) point to the fact that hydrophobic and hydrophilic interactions are very important and represent valuable driving forces required to maintain biological folding and stability.

In the present study, first we demonstrated five linear relations between the availabilities of large and hydrophobic residues by means of primary structures and how these residues can be employed by SSEs in the functional conformations of small toxins and non-toxins. Next, we performed an analysis of molecular structures and mechanisms in toxins through direct comparison of real and predicted residue compositions, which we surmised would reveal complementary (or predominant) contributions of residue size and hydrophobicity in 80% (or 20%) of SSEs. In order to carry out proper analysis a purely empirical approach was used, taking into account sequence and structure data extracted from experimentally determined macromolecules. A mathematical formulation utilizing representative measures of primary, secondary and tertiary structures, as well as computational algorithms allowing automatic processing of our sample choice, empirical approach and mathematical formulation, were employed during the investigation.

Section snippets

Macromolecules of the benchmark dataset

The native macromolecules in our dataset were obtained from a special set containing toxins and non-toxins. However, many elusive and redundant macromolecules are already deposited in the Protein Data Bank (PDB) (Berman et al., 2000). Thus, we defined the following criteria and restrictions: primary structure consisting solely of natural amino acids (among the 20 genetically encoded types); complete information provided regarding whole residue sequences and secondary structures; and use of

Global measures in 35-residue toxins and non-toxins

The proteins analyzed exhibited quite diversified primary (ni and disulfide bridges), secondary (Lj, ti,j, pi,j, Δti,j) and tertiary (RG) structures, diverse biological activities, and striking structural dissimilarities between toxins and non-toxins (Fig. 1).

Among 39 PDB proteins, 8 toxins had more limited amounts of large residues nL, ranging between 12 and 19. They represented cysteine-rich macromolecules with disulfide cross-linkages (Fig. 1a), which are typically required in secreted

Conclusions and future directions

The present article presents a thorough case (or non-statistical) study aiming to determine five straight line equations (from ni to pi,j, Fig. 2) for the purpose of identifying the nature of information transfers from primary to secondary structures in nativeconformations of (non-) toxins over 80 trials. The results also demonstrated the peculiarities of twofold and single mechanisms, thoroughly analyzed through 114 residue compositions (ti,j and Δti,j, Table 2, Table 3, Table 4), which are

Acknowledgements

The author would like to thank the anonymous reviewers for their comments and suggestions, which were very helpful in improving the article.

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