Computational methods of studying the binding of toxins from venomous animals to biological ion channels: theory and applications

Effect of animal venom toxins on the main links of the homeostasis of mammals (Review)

The human body is affected by environmental factors. The dynamic balance between the organism and its environment results from the influence of natural, anthropogenic and social aspects. The factors of exogenous origin determine development of adaptive changes. The present article summarises the mechanisms of animal venom toxins and homeostasis disruption in the body of mammals. The mechanisms underlying pathological changes are associated with shifts in biochemical reactions. Components of the immune, nervous and endocrine systems are key in the host defense and adaptation processes in response to venom by triggering signalling pathways (PI3kinase pathway, arachidonic acid cascade). Animal venom toxins initiate the development of inflammatory processes, the synthesis of pro-inflammatory mediators (cytokines), ROS, proteolytic enzymes, activate the migration of leukocytes and macrophages. Keratinocytes and endothelial cells act as protective barriers under the action of animal venom toxins on the body of mammals. In addition, the formation of pores in cell membranes, structural changes in cell ion channels are characteristic of the action of animal venom toxins.

Modern venomics-Current insights, novel methods, and future perspectives in biological and applied animal venom research

Venoms have evolved >100 times in all major animal groups, and their components, known as toxins, have been fine-tuned over millions of years into highly effective biochemical weapons. There are many outstanding questions on the evolution of toxin arsenals, such as how venom genes originate, how venom contributes to the fitness of venomous species, and which modifications at the genomic, transcriptomic, and protein level drive their evolution. These questions have received particularly little attention outside of snakes, cone snails, spiders, and scorpions. Venom compounds have further become a source of inspiration for translational research using their diverse bioactivities for various applications. We highlight here recent advances and new strategies in modern venomics and discuss how recent technological innovations and multi-omic methods dramatically improve research on venomous animals. The study of genomes and their modifications through CRISPR and knockdown technologies will increase our understanding of how toxins evolve and which functions they have in the different ontogenetic stages during the development of venomous animals. Mass spectrometry imaging combined with spatial transcriptomics, in situ hybridization techniques, and modern computer tomography gives us further insights into the spatial distribution of toxins in the venom system and the function of the venom apparatus. All these evolutionary and biological insights contribute to more efficiently identify venom compounds, which can then be synthesized or produced in adapted expression systems to test their bioactivity. Finally, we critically discuss recent agrochemical, pharmaceutical, therapeutic, and diagnostic (so-called translational) aspects of venoms from which humans benefit.

The Kv1.3 K+ channel in the immune system and its "precision pharmacology" using peptide toxins

Since the discovery of the Kv1.3 voltage-gated K⁺ channel in human T cells in 1984, ion channels are considered crucial elements of the signal transduction machinery in the immune system. Our knowledge about Kv1.3 and its inhibitors is outstanding, motivated by their potential application in autoimmune diseases mediated by Kv1.3 overexpressing effector memory T cells (e.g., Multiple Sclerosis). High affinity Kv1.3 inhibitors are either small organic molecules (e.g., Pap-1) or peptides isolated from venomous animals. To date, the highest affinity Kv1.3 inhibitors with the best Kv1.3 selectivity are the engineered analogues of the sea anemone peptide ShK (e.g., ShK-186), the engineered scorpion toxin HsTx1[R14A] and the natural scorpion toxin Vm24. These peptides inhibit Kv1.3 in picomolar concentrations and are several thousand-fold selective for Kv1.3 over other biologically critical ion channels. Despite the significant progress in the field of Kv1.3 molecular pharmacology several progressive questions remain to be elucidated and discussed here. These include the conjugation of the peptides to carriers to increase the residency time of the peptides in the circulation (e.g., PEGylation and engineering the peptides into antibodies), use of rational drug design to create novel peptide inhibitors and understanding the potential off-target effects of Kv1.3 inhibition.

Expression and purification of recombinant alpha-toxin AnCra1 from the scorpion Androctonus crassicauda and its functional characterization on mammalian sodium channels

BACKGROUND

Alpha-scorpion toxins with long-chain peptide and four disulfide bonds represent diverse pharmacological profiles for various subtypes of voltage-gated sodium channels. Obtaining the natural toxins are difficult and time-consuming process, which represents the major difficulty to interpreting analysis of their structural and functional properties.

METHODS AND RESULTS

This study describes the toxin peptide and plasmid construct containing the gene coding for mammalian toxin AnCra1 from the scorpion Androctonus crassicauda venom. We have established genetic construction of fusion protein in pET32a + vector containing thioredoxin (Trx-tag), enterokinase cleavage site and 6xhistidine-tag for efficient expression in Escherichia coli strain RG2 (DE3). The soluble expressed peptide, then purified by Ni-NTA resin affinity chromatography and its purity was confirmed by reverse-phase HPLC and mass spectrometry (7433.54 Da.). The electrophysiological data showed that recombinant AnCra1 selectively inhibits the fast inactivation of hNav1.7 channel (EC₅₀ = 136.7 ± 6.6 nM).

CONCLUSIONS

Our findings demonstrate that the AnCra1 is structurally and functionally analogous to alpha excitatory toxins; furthermore, expression and purification of bioactive scorpion toxins in bacterial cells can be a practicable and efficient way to obtain a novel source of toxin peptides as tools to study the function and physiological responses of ion channels.

A Molecular Lid Mechanism of K+ Channel Blocker Action Revealed by a Cone Peptide

Many venomous organisms carry in their arsenal short polypeptides that block K⁺ channels in a highly selective manner. These toxins may compete with the permeating ions directly via a "plug" mechanism or indirectly via a "pore-collapse" mechanism. An alternative "lid" mechanism was proposed but remained poorly defined. Here we study the Drosophila Shaker channel block by Conkunitzin-S1 and Conkunitzin-C3, two highly similar toxins derived from cone venom. Despite their similarity, the two peptides exhibited differences in their binding poses and biophysical assays, implying discrete action modes. We show that while Conkunitzin-S1 binds tightly to the channel turret and acts via a "pore-collapse" mechanism, Conkunitzin-C3 does not contact this region. Instead, Conk-C3 uses a non-conserved Arg to divert the permeant ions and trap them in off-axis cryptic sites above the SF, a mechanism we term a "molecular-lid". Our study provides an atomic description of the "lid" K⁺ blocking mode and offers valuable insights for the design of therapeutics based on venom peptides.

Slow-, Tight-Binding Inhibition of CYP17A1 by Abiraterone Redefines Its Kinetic Selectivity and Dosing Regimen

Substantial evidence underscores the clinical efficacy of inhibiting CYP17A1-mediated androgen biosynthesis by abiraterone for treatment of prostate oncology. Previous structural analysis and in vitro assays revealed inconsistencies surrounding the nature and potency of CYP17A1 inhibition by abiraterone. Here, we establish that abiraterone is a slow-, tight-binding inhibitor of CYP17A1, with initial weak binding preceding the subsequent slow isomerization to a high-affinity CYP17A1-abiraterone complex. The in vitro inhibition constant of the final high-affinity CYP17A1-abiraterone complex ( ( K _i * = 0.39 nM )yielded a binding free energy of -12.8 kcal/mol that was quantitatively consistent with the in silico prediction of -14.5 kcal/mol. Prolonged suppression of dehydroepiandrosterone (DHEA) concentrations observed in VCaP cells after abiraterone washout corroborated its protracted CYP17A1 engagement. Molecular dynamics simulations illuminated potential structural determinants underlying the rapid reversible binding characterizing the two-step induced-fit model. Given the extended residence time (42 hours) of abiraterone within the CYP17A1 active site, in silico simulations demonstrated sustained target engagement even when most abiraterone has been eliminated systemically. Subsequent pharmacokinetic-pharmacodynamic (PK-PD) modeling linking time-dependent CYP17A1 occupancy to in vitro steroidogenic dynamics predicted comparable suppression of downstream DHEA-sulfate at both 1000- and 500-mg doses of abiraterone acetate. This enabled mechanistic rationalization of a clinically reported PK-PD disconnect, in which equipotent reduction of downstream plasma DHEA-sulfate levels was achieved despite a lower systemic exposure of abiraterone. Our novel findings provide the impetus for re-evaluating the current dosing paradigm of abiraterone with the aim of preserving PD efficacy while mitigating its dose-dependent adverse effects and financial burden. SIGNIFICANCE STATEMENT: With the advent of novel molecularly targeted anticancer modalities, it is becoming increasingly evident that optimal dose selection must necessarily be predicated on mechanistic characterization of the relationships between target exposure, drug-target interactions, and pharmacodynamic endpoints. Nevertheless, efficacy has always been perceived as being exclusively synonymous with affinity-based measurements of drug-target binding. This work demonstrates how elucidating the slow-, tight-binding inhibition of CYP17A1 by abiraterone via in vitro and in silico analyses was pivotal in establishing the role of kinetic selectivity in mediating time-dependent CYP17A1 engagement and eventually downstream efficacy outcomes.

Identification of Aethina tumida Kir Channels as Putative Targets of the Bee Venom Peptide Tertiapin Using Structure-Based Virtual Screening Methods

Venoms are comprised of diverse mixtures of proteins, peptides, and small molecules. Identifying individual venom components and their target(s) with mechanism of action is now attainable to understand comprehensively the effectiveness of venom cocktails and how they collectively function in the defense and predation of an organism. Here, structure-based computational methods were used with bioinformatics tools to screen and identify potential biological targets of tertiapin (TPN), a venom peptide from Apis mellifera (European honey bee). The small hive beetle (Aethina tumida (A. tumida)) is a natural predator of the honey bee colony and was found to possess multiple inwardly rectifying K⁺ (Kir) channel subunit genes from a genomic BLAST search analysis. Structure-based virtual screening of homology modelled A. tumida Kir (atKir) channels found TPN to interact with a docking profile and interface “footprint” equivalent to known TPN-sensitive mammalian Kir channels. The results support the hypothesis that atKir channels, and perhaps other insect Kir channels, are natural biological targets of TPN that help defend the bee colony from infestations by blocking K⁺ transport via atKir channels. From these in silico findings, this hypothesis can now be subsequently tested in vitro by validating atKir channel block as well as in vivo TPN toxicity towards A. tumida. This study highlights the utility and potential benefits of screening in virtual space for venom peptide interactions and their biological targets, which otherwise would not be feasible.

Diverse Structural Features of Potassium Channels Characterized by Scorpion Toxins as Molecular Probes

Scorpion toxins are well-known as the largest potassium channel peptide blocker family. They have been successfully proven to be valuable molecular probes for structural research on diverse potassium channels. The potassium channel pore region, including the turret and filter regions, is the binding interface for scorpion toxins, and structural features from different potassium channels have been identified using different scorpion toxins. According to the spatial orientation of channel turrets with differential sequence lengths and identities, conformational changes and molecular surface properties, the potassium channel turrets can be divided into the following three states: open state with less hindering effects on toxin binding, half-open state or half-closed state with certain effects on toxin binding, and closed state with remarkable effects on toxin binding. In this review, we summarized the diverse structural features of potassium channels explored using scorpion toxin tools and discuss future work in the field of scorpion toxin-potassium channel interactions.

Computational Study of the Loss-of-Function Mutations in the Kv1.5 Channel Associated with Atrial Fibrillation

Atrial fibrillation (AF) is a heart disease caused by defective ion channels in the atria, which affect the action potential (AP) duration and disturb normal heart rhythm. Rapid firing of APs in neighboring atrial cells is a common mechanism of AF, and therefore, therapeutic approaches have focused on extending the AP duration by inhibiting the K⁺ channels involved in repolarization. Of these, Kv1.5 that carries the I _Kur current is a promising target because it is expressed mainly in atria and not in ventricles. In genetic studies of AF patients, both loss-of-function and gain-of-function mutations in Kv1.5 have been identified, indicating that either decreased or increased I _Kur currents could trigger AF. Blocking of already downregulated Kv1.5 channels could cause AF to become chronic. Thus, a molecular-level understanding of how the loss-of-function mutations in Kv1.5 affect I _Kur would be useful for developing new therapeutics. Here, we perform molecular dynamics simulations to study the effect of three loss-of-function mutations in the pore domain of Kv1.5 on ion permeation. Comparison of the pore structures and ion free energies in the wild-type and mutant Kv1.5 channels indicates that conformational changes in the selectivity filter could hinder ion permeation in the mutant channels.

Inhibition of Voltage-Gated K+ Channel Kv1.5 by Antiarrhythmic Drugs

Molecular dynamics simulations are employed to determine the inhibitory mechanisms of three drugs, 5-(4-phenoxybutoxy)psoralen (PAP-1), vernakalant, and flecainide, on the voltage-gated K⁺ channel Kv1.5, a target for the treatment of cardiac arrhythmia. At neutral pH, PAP-1 is neutral, whereas the other two molecules carry one positive charge. We show that PAP-1 forms stable dimers in water, primarily through hydrophobic interactions between aromatic rings. All three molecules bind to the cavity between the Ile508 and Val512 residues from the four subunits of the channel. Once bound, the drug molecules are flexible, with the average root-mean-square fluctuation being between 2 and 3 Å, which is larger than the radius of gyration of a bulky amino acid. The presence of a monomeric PAP-1 causes the permeating K⁺ ion to dehydrate, thereby creating a significant energy barrier. In contrast, vernakalant blocks the ion permeation primarily via an electrostatic mechanism and, therefore, must be in the protonated and charged form to be effective.

Guanidinium Toxins and Their Interactions with Voltage-Gated Sodium Ion Channels

Guanidinium toxins, such as saxitoxin (STX), tetrodotoxin (TTX) and their analogs, are naturally occurring alkaloids with divergent evolutionary origins and biogeographical distribution, but which share the common chemical feature of guanidinium moieties. These guanidinium groups confer high biological activity with high affinity and ion flux blockage capacity for voltage-gated sodium channels (NaV). Members of the STX group, known collectively as paralytic shellfish toxins (PSTs), are produced among three genera of marine dinoflagellates and about a dozen genera of primarily freshwater or brackish water cyanobacteria. In contrast, toxins of the TTX group occur mainly in macrozoa, particularly among puffer fish, several species of marine invertebrates and a few terrestrial amphibians. In the case of TTX and analogs, most evidence suggests that symbiotic bacteria are the origin of the toxins, although endogenous biosynthesis independent from bacteria has not been excluded. The evolutionary origin of the biosynthetic genes for STX and analogs in dinoflagellates and cyanobacteria remains elusive. These highly potent molecules have been the subject of intensive research since the latter half of the past century; first to study the mode of action of their toxigenicity, and later as tools to characterize the role and structure of NaV channels, and finally as therapeutics. Their pharmacological activities have provided encouragement for their use as therapeutants for ion channel-related pathologies, such as pain control. The functional role in aquatic and terrestrial ecosystems for both groups of toxins is unproven, although plausible mechanisms of ion channel regulation and chemical defense are often invoked. Molecular approaches and the development of improved detection methods will yield deeper understanding of their physiological and ecological roles. This knowledge will facilitate their further biotechnological exploitation and point the way towards development of pharmaceuticals and therapeutic applications.

Functionalized Fullerene Targeting Human Voltage-Gated Sodium Channel, hNav1.7

Mutations of hNa_v1.7 that cause its activities to be enhanced contribute to severe neuropathic pain. Only a small number of hNa_v1.7 specific inhibitors have been identified, most of which interact with the voltage-sensing domain of the voltage-activated sodium ion channel. In our previous computational study, we demonstrated that a [Lys₆]-C₈₄ fullerene binds tightly (affinity of 46 nM) to Na_vAb, the voltage-gated sodium channel from the bacterium Arcobacter butzleri. Here, we extend this work and, using molecular dynamics simulations, demonstrate that the same [Lys₆]-C₈₄ fullerene binds strongly (2.7 nM) to the pore of a modeled human sodium ion channel hNa_v1.7. In contrast, the fullerene binds only weakly to a mutated model of hNa_v1.7 (I1399D) (14.5 mM) and a model of the skeletal muscle hNa_v1.4 (3.7 mM). Comparison of one representative sequence from each of the nine human sodium channel isoforms shows that only hNa_v1.7 possesses residues that are critical for binding the fullerene derivative and blocking the channel pore.

Modelling the interactions between animal venom peptides and membrane proteins

The active components of animal venoms are mostly peptide toxins, which typically target ion channels and receptors of both the central and peripheral nervous system, interfering with action potential conduction and/or synaptic transmission. The high degree of sequence conservation of their molecular targets makes a range of these toxins active at human receptors. The high selectivity and potency displayed by some of these toxins have prompted their use as pharmacological tools as well as drugs or drug leads. Molecular modelling has played an essential role in increasing our molecular-level understanding of the activity and specificity of animal toxins, as well as engineering them for biotechnological and pharmaceutical applications. This review focuses on the biological insights gained from computational and experimental studies of animal venom toxins interacting with membranes and ion channels. A host of recent X-ray crystallography and electron-microscopy structures of the toxin targets has contributed to a dramatic increase in the accuracy of the molecular models of toxin binding modes greatly advancing this exciting field of study. This article is part of the Special Issue entitled 'Venom-derived Peptides as Pharmacological Tools.'

Spatiotemporal multistage consensus clustering in molecular dynamics studies of large proteins

The aim of this work is to find semi-rigid domains within large proteins as reference structures for fitting molecular dynamics trajectories. We propose an algorithm, multistage consensus clustering, MCC, based on minimum variation of distances between pairs of Cα-atoms as target function. The whole dataset (trajectory) is split into sub-segments. For a given sub-segment, spatial clustering is repeatedly started from different random seeds, and we adopt the specific spatial clustering with minimum target function: the process described so far is stage 1 of MCC. Then, in stage 2, the results of spatial clustering are consolidated, to arrive at domains stable over the whole dataset. We found that MCC is robust regarding the choice of parameters and yields relevant information on functional domains of the major histocompatibility complex (MHC) studied in this paper: the α-helices and β-floor of the protein (MHC) proved to be most flexible and did not contribute to clusters of significant size. Three alleles of the MHC, each in complex with ABCD3 peptide and LC13 T-cell receptor (TCR), yielded different patterns of motion. Those alleles causing immunological allo-reactions showed distinct correlations of motion between parts of the peptide, the binding cleft and the complementary determining regions (CDR)-loops of the TCR. Multistage consensus clustering reflected functional differences between MHC alleles and yields a methodological basis to increase sensitivity of functional analyses of bio-molecules. Due to the generality of approach, MCC is prone to lend itself as a potent tool also for the analysis of other kinds of big data.

Molecular Simulations of Disulfide-Rich Venom Peptides with Ion Channels and Membranes

Disulfide-rich peptides isolated from the venom of arthropods and marine animals are a rich source of potent and selective modulators of ion channels. This makes these peptides valuable lead molecules for the development of new drugs to treat neurological disorders. Consequently, much effort goes into understanding their mechanism of action. This paper presents an overview of how molecular simulations have been used to study the interactions of disulfide-rich venom peptides with ion channels and membranes. The review is focused on the use of docking, molecular dynamics simulations, and free energy calculations to (i) predict the structure of peptide-channel complexes; (ii) calculate binding free energies including the effect of peptide modifications; and (iii) study the membrane-binding properties of disulfide-rich venom peptides. The review concludes with a summary and outlook.

Biobetters From an Integrated Computational/Experimental Approach

Biobetters are new drugs designed from existing peptide or protein-based therapeutics by improving their properties such as affinity and selectivity for the target epitope, and stability against degradation. Computational methods can play a key role in such design problems—by predicting the changes that are most likely to succeed, they can drastically reduce the number of experiments to be performed. Here we discuss the computational and experimental methods commonly used in drug design problems, focusing on the inverse relationship between the two, namely, the more accurate the computational predictions means the less experimental effort is needed for testing. Examples discussed include efforts to design selective analogs from toxin peptides targeting ion channels for treatment of autoimmune diseases and monoclonal antibodies which are the fastest growing class of therapeutic agents particularly for cancers and autoimmune diseases.

The Origin of Coupled Chloride and Proton Transport in a Cl-/H+ Antiporter

The ClC family of transmembrane proteins functions throughout nature to control the transport of Cl^– ions across biological membranes. ClC-ec1 from Escherichia coli is an antiporter, coupling the transport of Cl^– and H⁺ ions in opposite directions and driven by the concentration gradients of the ions. Despite keen interest in this protein, the molecular mechanism of the Cl^–/H⁺ coupling has not been fully elucidated. Here, we have used multiscale simulation to help identify the essential mechanism of the Cl^–/H⁺ coupling. We find that the highest barrier for proton transport (PT) from the intra- to extracellular solution is attributable to a chemical reaction, the deprotonation of glutamic acid 148 (E148). This barrier is significantly reduced by the binding of Cl^– in the “central” site (Cl^–_cen), which displaces E148 and thereby facilitates its deprotonation. Conversely, in the absence of Cl^–_cen E148 favors the “down” conformation, which results in a much higher cumulative rotation and deprotonation barrier that effectively blocks PT to the extracellular solution. Thus, the rotation of E148 plays a critical role in defining the Cl^–/H⁺ coupling. As a control, we have also simulated PT in the ClC-ec1 E148A mutant to further understand the role of this residue. Replacement with a non-protonatable residue greatly increases the free energy barrier for PT from E203 to the extracellular solution, explaining the experimental result that PT in E148A is blocked whether or not Cl^–_cen is present. The results presented here suggest both how a chemical reaction can control the rate of PT and also how it can provide a mechanism for a coupling of the two ion transport processes.

Molecular dynamics of the honey bee toxin tertiapin binding to Kir3.2

Tertiapin (TPN), a short peptide isolated from the venom of the honey bee, is a potent and selective blocker of the inward rectifier K⁺ (Kir) channel Kir3.2. Here we examine in atomic detail the binding mode of TPN to Kir3.2 using molecular dynamics, and deduce the key residue in Kir3.2 responsible for TPN selectivity. The binding of TPN to Kir3.2 is stable when the side chain of either Lys16 (TPN^K16-Kir3.2) or Lys17 (TPN^K17-Kir3.2) of the toxin protrudes into the channel pore. However, the binding affinity calculated from only TPN^K17-Kir3.2 and not TPN^K16-Kir3.2 is consistent with experiment, suggesting that Lys17 is the most plausible pore-blocking residue. The alanine mutation of Kir3.2-Glu127, which is not present in TPN-resistant channels, reduces the inhibitory ability of TPN by over 50 fold in TPN^K17-Kir3.2, indicating that Kir3.2-Glu127 is important for the selectivity of TPN.

Complexes of Peptide Blockers with Kv1.6 Pore Domain: Molecular Modeling and Studies with KcsA-Kv1.6 Channel

Potassium voltage-gated Kv1.6 channel, which is distributed primarily in neurons of central and peripheral nervous systems, is of significant physiological importance. To date, several high-affinity Kv1.6-channel blockers are known, but the lack of selective ones among them hampers the studies of tissue localization and functioning of Kv1.6 channels. Here we present an approach to advanced understanding of interactions of peptide toxin blockers with a Kv1.6 pore. It combines molecular modeling studies and an application of a new bioengineering system based on a KcsA-Kv1.6 hybrid channel for the quantitative fluorescent analysis of blocker-channel interactions. Using this system we demonstrate that peptide toxins agitoxin 2, kaliotoxin1 and OSK1 have similar high affinity to the extracellular vestibule of the K⁺-conducting pore of Kv1.6, hetlaxin is a low-affinity ligand, whereas margatoxin and scyllatoxin do not bind to Kv1.6 pore. Binding of toxins to Kv1.6 pore has considerable inverse dependence on the ionic strength. Model structures of KcsA-Kv1.6 and Kv1.6 complexes with agitoxin 2, kaliotoxin 1 and OSK1 were obtained using homology modeling and molecular dynamics simulation. Interaction interfaces, which are formed by 15-19 toxin residues and 10 channel residues, are described and compared. Specific sites of Kv1.6 pore recognition are identified for targeting of peptide blockers. Analysis of interactions between agitoxin 2 derivatives with point mutations (S7K, S11G, L19S, R31G) and KcsA-Kv1.6 confirms reliability of the calculated complex structure.

Docking Simulation of the Binding Interactions of Saxitoxin Analogs Produced by the Marine Dinoflagellate Gymnodinium catenatum to the Voltage-Gated Sodium Channel Nav1.4

Saxitoxin (STX) and its analogs are paralytic alkaloid neurotoxins that block the voltage-gated sodium channel pore (Na_v), impeding passage of Na⁺ ions into the intracellular space, and thereby preventing the action potential in the peripheral nervous system and skeletal muscle. The marine dinoflagellate Gymnodinium catenatum produces an array of such toxins, including the recently discovered benzoyl analogs, for which the mammalian toxicities are essentially unknown. We subjected STX and its analogs to a theoretical docking simulation based upon two alternative tri-dimensional models of the Na_v1.4 to find a relationship between the binding properties and the known mammalian toxicity of selected STX analogs. We inferred hypothetical toxicities for the benzoyl analogs from the modeled values. We demonstrate that these toxins exhibit different binding modes with similar free binding energies and that these alternative binding modes are equally probable. We propose that the principal binding that governs ligand recognition is mediated by electrostatic interactions. Our simulation constitutes the first in silico modeling study on benzoyl-type paralytic toxins and provides an approach towards a better understanding of the mode of action of STX and its analogs.

Modeling of the Binding of Peptide Blockers to Voltage-Gated Potassium Channels: Approaches and Evidence

Modeling of the structure of voltage-gated potassium (KV) channels bound to peptide blockers aims to identify the key amino acid residues dictating affinity and provide insights into the toxin-channel interface. Computational approaches open up possibilities for in silico rational design of selective blockers, new molecular tools to study the cellular distribution and functional roles of potassium channels. It is anticipated that optimized blockers will advance the development of drugs that reduce over activation of potassium channels and attenuate the associated malfunction. Starting with an overview of the recent advances in computational simulation strategies to predict the bound state orientations of peptide pore blockers relative to KV-channels, we go on to review algorithms for the analysis of intermolecular interactions, and then take a look at the results of their application.

Peptidomimetic Star Polymers for Targeting Biological Ion Channels

Four end-functionalized star polymers that could attenuate the flow of ionic currents across biological ion channels were first de novo designed computationally, then synthesized and tested experimentally on mammalian K+ channels. The 4-arm ethylene glycol conjugate star polymers with lysine or a tripeptide attached to the end of each arm were specifically designed to mimic the action of scorpion toxins on K+ channels. Molecular dynamics simulations showed that the lysine side chain of the polymers physically occludes the pore of Kv1.3, a target for immuno-suppression therapy. Two of the compounds tested were potent inhibitors of Kv1.3. The dissociation constants of these two compounds were computed to be 0.1 μM and 0.7 μM, respectively, within 3-fold to the values derived from subsequent experiments. These results demonstrate the power of computational methods in molecular design and the potential of star polymers as a new infinitely modifiable platform for ion channel drug discovery.

Computational Studies of Venom Peptides Targeting Potassium Channels

Small peptides isolated from the venom of animals are potential scaffolds for ion channel drug discovery. This review article mainly focuses on the computational studies that have advanced our understanding of how various toxins interfere with the function of K⁺ channels. We introduce the computational tools available for the study of toxin-channel interactions. We then discuss how these computational tools have been fruitfully applied to elucidate the mechanisms of action of a wide range of venom peptides from scorpions, spiders, and sea anemone.

Computational approaches for designing potent and selective analogs of peptide toxins as novel therapeutics

Peptide toxins provide valuable therapeutic leads for many diseases. As they bind to their targets with high affinity, potency is usually ensured. However, toxins also bind to off-target receptors, causing potential side effects. Thus, a major challenge in generating drugs from peptide toxins is ensuring their specificity for their intended targets. Computational methods can play an important role in solving such design problems through construction of accurate models of receptor-toxin complexes and calculation of binding free energies. Here we review the computational methods used for this purpose and their application to toxins targeting ion channels. We describe ShK and HsTX1 toxins, high-affinity blockers of the voltage-gated potassium channel Kv1.3, which could be developed as therapeutic agents for autoimmune diseases.

Bioinformatics-Aided Venomics

Venomics is a modern approach that combines transcriptomics and proteomics to explore the toxin content of venoms. This review will give an overview of computational approaches that have been created to classify and consolidate venomics data, as well as algorithms that have helped discovery and analysis of toxin nucleic acid and protein sequences, toxin three-dimensional structures and toxin functions. Bioinformatics is used to tackle specific challenges associated with the identification and annotations of toxins. Recognizing toxin transcript sequences among second generation sequencing data cannot rely only on basic sequence similarity because toxins are highly divergent. Mass spectrometry sequencing of mature toxins is challenging because toxins can display a large number of post-translational modifications. Identifying the mature toxin region in toxin precursor sequences requires the prediction of the cleavage sites of proprotein convertases, most of which are unknown or not well characterized. Tracing the evolutionary relationships between toxins should consider specific mechanisms of rapid evolution as well as interactions between predatory animals and prey. Rapidly determining the activity of toxins is the main bottleneck in venomics discovery, but some recent bioinformatics and molecular modeling approaches give hope that accurate predictions of toxin specificity could be made in the near future.

Theoretical and simulation studies on voltage-gated sodium channels

Voltage-gated sodium (Na_v) channels are indispensable membrane elements for the generation and propagation of electric signals in excitable cells. The successes in the crystallographic studies on prokaryotic Na_v channels in recent years greatly promote the mechanistic investigation of these proteins and their eukaryotic counterparts. In this paper, we mainly review the progress in computational studies, especially the simulation studies, on these proteins in the past years.

A computational design approach for virtual screening of peptide interactions across K(+) channel families

Ion channels represent a large family of membrane proteins with many being well established targets in pharmacotherapy. The ‘druggability’ of heteromeric channels comprised of different subunits remains obscure, due largely to a lack of channel-specific probes necessary to delineate their therapeutic potential in vivo. Our initial studies reported here, investigated the family of inwardly rectifying potassium (Kir) channels given the availability of high resolution crystal structures for the eukaryotic constitutively active Kir2.2 channel. We describe a ‘limited’ homology modeling approach that can yield chimeric Kir channels having an outer vestibule structure representing nearly any known vertebrate or invertebrate channel. These computationally-derived channel structures were tested ""in silico for ‘docking’ to NMR structures of tertiapin (TPN), a 21 amino acid peptide found in bee venom. TPN is a highly selective and potent blocker for the epithelial rat Kir1.1 channel, but does not block human or zebrafish Kir1.1 channel isoforms. Our Kir1.1 channel-TPN docking experiments recapitulated published in vitro ""findings for TPN-sensitive and TPN-insensitive channels. Additionally, in silico site-directed mutagenesis identified ‘hot spots’ within the channel outer vestibule that mediate energetically favorable docking scores and correlate with sites previously identified with in vitro thermodynamic mutant-cycle analysis. These ‘proof-of-principle’ results establish a framework for virtual screening of re-engineered peptide toxins for interactions with computationally derived Kir channels that currently lack channel-specific blockers. When coupled with electrophysiological validation, this virtual screening approach may accelerate the drug discovery process, and can be readily applied to other ion channels families where high resolution structures are available.

Binding modes of two scorpion toxins to the voltage-gated potassium channel kv1.3 revealed from molecular dynamics

Molecular dynamics (MD) simulations are used to examine the binding modes of two scorpion toxins, margatoxin (MgTx) and hongotoxin (HgTx), to the voltage gated K+ channel, Kv1.3. Using steered MD simulations, we insert either Lys28 or Lys35 of the toxins into the selectivity filter of the channel. The MgTx-Kv1.3 complex is stable when the side chain of Lys35 from the toxin occludes the channel filter, suggesting that Lys35 is the pore-blocking residue for Kv1.3. In this complex, Lys28 of the toxin forms one additional salt bridge with Asp449 just outside the filter of the channel. On the other hand, HgTx forms a stable complex with Kv1.3 when the side chain of Lys28 but not Lys35 protrudes into the filter of the channel. A survey of all the possible favorable binding modes of HgTx-Kv1.3 is carried out by rotating the toxin at 3° intervals around the channel axis while the position of HgTx-Lys28 relative to the filter is maintained. We identify two possible favorable binding modes: HgTx-Arg24 can interact with either Asp433 or Glu420 on the vestibular wall of the channel. The dissociation constants calculated from the two binding modes of HgTx-Kv1.3 differ by approximately 20 fold, suggesting that the two modes are of similar energetics.

Geometric analysis of alloreactive HLA α-helices

Molecular dynamics (MD) is a valuable tool for the investigation of functional elements in biomolecules, providing information on dynamic properties and processes. Previous work by our group has characterized static geometric properties of the two MHC α-helices comprising the peptide binding region recognized by T cells. We build upon this work and used several spline models to approximate the overall shape of MHC α-helices. We applied this technique to a series of MD simulations of alloreactive MHC molecules that allowed us to capture the dynamics of MHC α-helices' steric configurations. Here, we discuss the variability of spline models underlying the geometric analysis with varying polynomial degrees of the splines.

Finding semirigid domains in biomolecules by clustering pair-distance variations

Dynamic variations in the distances between pairs of atoms are used for clustering subdomains of biomolecules. We draw on a well-known target function for clustering and first show mathematically that the assignment of atoms to clusters has to be crisp, not fuzzy, as hitherto assumed. This reduces the computational load of clustering drastically, and we demonstrate results for several biomolecules relevant in immunoinformatics. Results are evaluated regarding the number of clusters, cluster size, cluster stability, and the evolution of clusters over time. Crisp clustering lends itself as an efficient tool to locate semirigid domains in the simulation of biomolecules. Such domains seem crucial for an optimum performance of subsequent statistical analyses, aiming at detecting minute motional patterns related to antigen recognition and signal transduction.

Molecular dynamics simulations of scorpion toxin recognition by the Ca(2+)-activated potassium channel KCa3.1

The Ca(2+)-activated channel of intermediate-conductance (KCa3.1) is a target for antisickling and immunosuppressant agents. Many small peptides isolated from animal venoms inhibit KCa3.1 with nanomolar affinities and are promising drug scaffolds. Although the inhibitory effect of peptide toxins on KCa3.1 has been examined extensively, the structural basis of toxin-channel recognition has not been understood in detail. Here, the binding modes of two selected scorpion toxins, charybdotoxin (ChTx) and OSK1, to human KCa3.1 are examined in atomic detail using molecular dynamics (MD) simulations. Employing a homology model of KCa3.1, we first determine conduction properties of the channel using Brownian dynamics and ascertain that the simulated results are in accord with experiment. The model structures of ChTx-KCa3.1 and OSK1-KCa3.1 complexes are then constructed using MD simulations biased with distance restraints. The ChTx-KCa3.1 complex predicted from biased MD is consistent with the crystal structure of ChTx bound to a voltage-gated K(+) channel. The dissociation constants (Kd) for the binding of both ChTx and OSK1 to KCa3.1 determined experimentally are reproduced within fivefold using potential of mean force calculations. Making use of the knowledge we gained by studying the ChTx-KCa3.1 complex, we attempt to enhance the binding affinity of the toxin by carrying out a theoretical mutagenesis. A mutant toxin, in which the positions of two amino acid residues are interchanged, exhibits a 35-fold lower Kd value for KCa3.1 than that of the wild-type. This study provides insight into the key molecular determinants for the high-affinity binding of peptide toxins to KCa3.1, and demonstrates the power of computational methods in the design of novel toxins.

Mechanism of μ-conotoxin PIIIA binding to the voltage-gated Na+ channel NaV1.4

Several subtypes of voltage-gated Na+ (NaV) channels are important targets for pain management. μ-Conotoxins isolated from venoms of cone snails are potent and specific blockers of different NaV channel isoforms. The inhibitory effect of μ-conotoxins on NaV channels has been examined extensively, but the mechanism of toxin specificity has not been understood in detail. Here the known structure of μ-conotoxin PIIIA and a model of the skeletal muscle channel NaV1.4 are used to elucidate elements that contribute to the structural basis of μ-conotoxin binding and specificity. The model of NaV1.4 is constructed based on the crystal structure of the bacterial NaV channel, NaVAb. Six different binding modes, in which the side chain of each of the basic residues carried by the toxin protrudes into the selectivity filter of NaV1.4, are examined in atomic detail using molecular dynamics simulations with explicit solvent. The dissociation constants (Kd) computed for two selected binding modes in which Lys9 or Arg14 from the toxin protrudes into the filter of the channel are within 2 fold; both values in close proximity to those determined from dose response data for the block of NaV currents. To explore the mechanism of PIIIA specificity, a double mutant of NaV1.4 mimicking NaV channels resistant to μ-conotoxins and tetrodotoxin is constructed and the binding of PIIIA to this mutant channel examined. The double mutation causes the affinity of PIIIA to reduce by two orders of magnitude.

Designing a C84 fullerene as a specific voltage-gated sodium channel blocker

Fullerene derivatives demonstrate considerable potential for numerous biological applications, such as the effective inhibition of HIV protease. Recently, they were identified for their ability to indiscriminately block biological ion channels. A fullerene derivative which specifically blocks a particular ion channel could lead to a new set of drug leads for the treatment of various ion channel-related diseases. Here, we demonstrate their extraordinary potential by designing a fullerene which mimics some of the functions of μ-conotoxin, a peptide derived from cone snail venom which potently binds to the bacterial voltage-gated sodium channel (NavAb). We show, using molecular dynamics simulations, that the C84 fullerene with six lysine derivatives uniformly attached to its surface is selective to NavAb over a voltage-gated potassium channel (Kv1.3). The side chain of one of the lysine residues protrudes into the selectivity filter of the channel, while the methionine residues located just outside of the channel form hydrophobic contacts with the carbon atoms of the fullerene. The modified C84 fullerene strongly binds to the NavAb channel with an affinity of 46 nM but binds weakly to Kv1.3 with an affinity of 3 mM. This potent blocker of NavAb may serve as a structural template from which potent compounds can be designed for the targeting of mammalian Nav channels. There is a genuine need to target mammalian Nav channels as a form of treatment of various diseases which have been linked to their malfunction, such as epilepsy and chronic pain.

Complex structures between the N-type calcium channel (CaV2.2) and ω-conotoxin GVIA predicted via molecular dynamics

The N-type voltage-gated Ca(2+) channel CaV2.2 is one of the important targets for pain management. ω-Conotoxins isolated from venoms of cone snails, which specifically inhibit CaV2.2, are promising scaffolds for novel analgesics. The inhibitory action of ω-conotoxins on CaV2.2 has been examined experimentally, but the modes of binding of the toxins to this and other related subfamilies of Ca(2+) channels are not understood in detail. Here molecular dynamics simulations are used to construct models of ω-conotoxin GVIA in complex with a homology model of the pore domain of CaV2.2. Three different binding modes in which the side chain of Lys2, Arg17, or Lys24 from the toxin protrudes into the selectivity filter of CaV2.2 are considered. In all the modes, the toxin forms a salt bridge with an aspartate residue of subunit II just above the EEEE ring of the selectivity filter. Using the umbrella sampling technique and potential of mean force calculations, the half-maximal inhibitory concentration (IC50) values are calculated to be 1.5 and 0.7 nM for the modes in which Lys2 and Arg17 occlude the ion conduction pathway, respectively. Both IC50 values compare favorably with the values of 0.04-1.0 nM determined experimentally. The similar IC50 values calculated for the different binding modes demonstrate that GVIA can inhibit CaV2.2 with alternative binding modes. Such a multiple-binding mode mechanism may be common for ω-conotoxins.