Delineation of the unbinding pathway of α-conotoxin ImI from the α7 nicotinic acetylcholine receptor

Synthesis and insecticidal activity of cysteine-free conopeptides from Conus betulinus

The cone snail Conus betulinus is a vermivorous species that is widely distributed in the South China Sea. Its crude venom contains various peptides used to prey on marine worms. In previous studies, a systematic analysis of the peptide toxin sequences from C. betulinus was carried out using a multiomics technique. In this study, 10 cysteine-free peptides that may possess insecticidal activity were selected from a previously constructed conopeptide library of C. betulinus using the CPY-Fe conopeptide as a template. These conopeptides were prepared by solid-phase peptide synthesis (SPPS), then characterized by the reverse-phase high performance liquid chromatography (HPLC) and mass spectrometry. Insect cytotoxicity and injection experiments revealed that these cysteine-free peptides exerted favorable insecticidal effects, and two of them (Bt010 and Bt016) exhibited high insecticidal efficacy with LD50 of 9.07 nM and 10.93 nM, respectively. In addition, the 3D structures of these peptides were predicted by homology modeling, and a phylogenetic tree was constructed based on the nucleotide data of conopeptides to analyze the relationships among structures, functions, and evolution. A preliminary mechanism for the insecticidal activity of the cysteine-free conopeptides was predicted by molecular docking. To the best of our knowledge, this is the first study to report the insecticidal activity of cysteine-free conopeptides derived from Conus betulinus, signaling that they could potentially be developed into bioinsecticides with desirable properties such as easy preparation, low cost, and high potency.

The first Conus genome assembly reveals a primary genetic central dogma of conopeptides in C. betulinus

Although there are various Conus species with publicly available transcriptome and proteome data, no genome assembly has been reported yet. Here, using Chinese tubular cone snail (C. betulinus) as a representative, we sequenced and assembled the first Conus genome with original identification of 133 genome-widely distributed conopeptide genes. After integration of our genomics, transcriptomics, and peptidomics data in the same species, we established a primary genetic central dogma of diverse conopeptides, assuming a rough number ratio of ~1:1:1:10s for the total genes: transcripts: proteins: post-translationally modified peptides. This ratio may be special for this worm-hunting Conus species, due to the high diversity of various Conus genomes and the big number ranges of conopeptide genes, transcripts, and peptides in previous reports of diverse Conus species. Only a fraction (45.9%) of the identified conotopeptide genes from our achieved genome assembly are transcribed with transcriptomic evidence, and few genes individually correspond to multiple transcripts possibly due to intraspecies or mutation-based variances. Variable peptide processing at the proteomic level, generating a big diversity of venom conopeptides with alternative cleavage sites, post-translational modifications, and N-/C-terminal truncations, may explain how the 133 genes and ~123 transcripts can generate thousands of conopeptides in the venom of individual C. betulinus. We also predicted many conopeptides with high stereostructural similarities to the putative analgesic ω-MVIIA, addiction therapy AuIB and insecticide ImI, suggesting that our current genome assembly for C. betulinus is a valuable genetic resource for high-throughput prediction and development of potential pharmaceuticals.

Nicotinic receptor pharmacology in silico: Insights and challenges

Nicotinic acetylcholine receptors (nAChR) are homo- or hetero-pentameric ligand-gated ion channels of the Cys-loop superfamily and play important roles in the nervous system and muscles. Studies on nAChR benefit from in silico modeling due to the lack of high-resolution structures for most receptor subtypes and challenges in experiments addressing the complex mechanism of activation involving allosteric sites. Although there is myriad of computational modeling studies on nAChR, the multitude of the methods and parameters used in these studies makes modeling nAChR a daunting task, particularly for the non-experts in the field. To address this problem, the modeling literature on Torpedo nAChR and α7 nAChR were focused on as examples of heteromeric and homomeric nAChR, and the key in silico modeling studies between the years 1995-2019 were concisely reviewed. This was followed by a critical analysis of these studies by comparing the findings with each other and with the emerging experimental and computational data on nAChR. Based on these critical analyses, suggestions were made to guide the future researchers in the field of in silico modeling of nAChR. This article is part of the special issue on 'Contemporary Advances in Nicotine Neuropharmacology'.

In Silico Modeling of the α7 Nicotinic Acetylcholine Receptor: New Pharmacological Challenges Associated with Multiple Modes of Signaling

The α7 nicotinic acetylcholine receptor is a homopentameric ion-channel of the Cys-loop superfamily characterized by its low probability of opening, high calcium permeability, and rapid desensitization. The α7 receptor has been targeted for the treatment of the cognitive symptoms of schizophrenia, depression, and Alzheimer's disease, but it is also involved in inflammatory modulation as a part of the cholinergic anti-inflammatory pathway. Despite its functional importance, in silico studies of the α7 receptor cannot produce a general model explaining the structural features of receptor activation, nor predict the mode of action for various ligand classes. Two particular problems in modeling the α7 nAChR are the absence of a high-resolution structure and the presence of five potentially nonequivalent orthosteric ligand binding sites. There is wide variability regarding the templates used for homology modeling, types of ligands investigated, simulation methods, and simulation times. However, a systematic survey focusing on the methodological similarities and differences in modeling α7 has not been done. In this work, we make a critical analysis of the modeling literature of α7 nAChR by comparing the findings of computational studies with each other and with experimental studies under the main topics of structural studies, ligand binding studies, and comparisons with other nAChR. In light of our findings, we also summarize current problems in the field and make suggestions for future studies concerning modeling of the α7 receptor.

Periplasmic Expression of 4/7 α-Conotoxin TxIA Analogs in E. coli Favors Ribbon Isomer Formation - Suggestion of a Binding Mode at the α7 nAChR

Peptides derived from animal venoms provide important research tools for biochemical and pharmacological characterization of receptors, ion channels, and transporters. Some venom peptides have been developed into drugs (such as the synthetic ω-conotoxin MVIIA, ziconotide) and several are currently undergoing clinical trials for various clinical indications. Challenges in the development of peptides include their usually limited supply from natural sources, cost-intensive chemical synthesis, and potentially complicated stereoselective disulfide-bond formation in the case of disulfide-rich peptides. In particular, if extended structure–function analysis is performed or incorporation of stable isotopes for NMR studies is required, the comparatively low yields and high costs of synthesized peptides might constitute a limiting factor. Here we investigated the expression of the 4/7 α-conotoxin TxIA, a potent blocker at α3β2 and α7 nicotinic acetylcholine receptors (nAChRs), and three analogs in the form of maltose binding protein fusion proteins in Escherichia coli. Upon purification via nickel affinity chromatography and release of the toxins by protease cleavage, HPLC analysis revealed one major peak with the correct mass for all peptides. The final yield was 1–2 mg of recombinant peptide per liter of bacterial culture. Two-electrode voltage clamp analysis on oocyte-expressed nAChR subtypes demonstrated the functionality of these peptides but also revealed a 30 to 100-fold potency decrease of expressed TxIA compared to chemically synthesized TxIA. NMR spectroscopy analysis of TxIA and two of its analogs confirmed that the decreased activity was due to an alternative disulfide linkage rather than the missing C-terminal amidation, a post-translational modification that is common in α-conotoxins. All peptides preferentially formed in the ribbon conformation rather than the native globular conformation. Interestingly, in the case of the α7 nAChR, but not the α3β2 subtype, the loss of potency could be rescued by an R5D substitution. In conclusion, we demonstrate efficient expression of functional but alternatively folded ribbon TxIA variants in E. coli and provide the first structure–function analysis for a ribbon 4/7-α-conotoxin at α7 and α3β2 nAChRs. Computational analysis based on these data provide evidence for a ribbon α-conotoxin binding mode that might be exploited to design ligands with optimized selectivity.

Snails In Silico: A Review of Computational Studies on the Conopeptides

Marine cone snails are carnivorous gastropods that use peptide toxins called conopeptides both as a defense mechanism and as a means to immobilize and kill their prey. These peptide toxins exhibit a large chemical diversity that enables exquisite specificity and potency for target receptor proteins. This diversity arises in terms of variations both in amino acid sequence and length, and in posttranslational modifications, particularly the formation of multiple disulfide linkages. Most of the functionally characterized conopeptides target ion channels of animal nervous systems, which has led to research on their therapeutic applications. Many facets of the underlying molecular mechanisms responsible for the specificity and virulence of conopeptides, however, remain poorly understood. In this review, we will explore the chemical diversity of conopeptides from a computational perspective. First, we discuss current approaches used for classifying conopeptides. Next, we review different computational strategies that have been applied to understanding and predicting their structure and function, from machine learning techniques for predictive classification to docking studies and molecular dynamics simulations for molecular-level understanding. We then review recent novel computational approaches for rapid high-throughput screening and chemical design of conopeptides for particular applications. We close with an assessment of the state of the field, emphasizing important questions for future lines of inquiry.

Role of the disulfide bond on the structure and activity of μ-conotoxin PIIIA in the inhibition of NaV1.4

μ-Conotoxin PIIIA, a peptide toxin isolated from Conus purpurascens, blocks the skeletal muscle voltage-gated sodium channel NaV1.4 with significant potency. PIIIA has three disulfide bonds, which contribute largely to its highly constrained and stable structure. In this study, a combination of experimental studies and computational modeling were performed to assess the effects of deletion of the disulfide bonds on the structure and activity of PIIIA. The final results indicate that the three disulfide bonds of PIIIA are required to produce the effective inhibition of NaV1.4, and the removal of any one of the disulfide bonds significantly reduces its binding affinity owing to secondary structure variation, among which the Cys11-Cys22 is the most important for sustaining the structure and activity of PIIIA.

α-Conotoxin ImI-modified polymeric micelles as potential nanocarriers for targeted docetaxel delivery to α7-nAChR overexpressed non-small cell lung cancer

A micelle system modified with α-Conotoxin ImI (ImI), a potently antagonist for alpha7 nicotinic acetylcholine receptor (α7-nAChR) previously utilized for targeting breast cancer, was constructed. Its targeting efficiency and cytotoxicity against non-small cell lung cancer (NSCLC) highly expressing α7-nAChR was investigated. A549, a non-small cell lung cancer cell line, was selected as the cell model. The cellular uptake study showed that the optimal modification ratio of ImI on micelle surface was 5% and ImI-modification increased intracellular delivery efficiency to A549 cells via receptor-mediated endocytosis. Intracellular Ca²⁺ transient assay demonstrated that ImI modification led to enhanced molecular interaction between nanocarriers and A549 cells. The in vivo near-infrared fluorescence imaging further revealed that ImI-modified micelles could facilitate the drug accumulation in tumor sites compared with non-modified micelles via α7-nAChR mediation. Moreover, docetaxel (DTX) was loaded in ImI-modified nanomedicines to evaluate its in vitro cytotoxicity. As a result, DTX-loaded ImI-PMs exhibited greater anti-proliferation effect on A549 cells compared with non-modified micelles. Generally, our study proved that ImI-modified micelles had targeting ability to NSCLC in addition to breast cancer and it may provide a promising strategy to deliver drugs to NSCLC overexpressing α7-nAChR.

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.'

Screening and Validation of Highly-Efficient Insecticidal Conotoxins from a Transcriptome-Based Dataset of Chinese Tubular Cone Snail

Most previous studies have focused on analgesic and anti-cancer activities for the conotoxins identified from piscivorous and molluscivorous cone snails, but little attention has been devoted to insecticidal activity of conotoxins from the dominant vermivorous species. As a representative vermivorous cone snail, the Chinese tubular cone snail (Conus betulinus) is the dominant Conus species inhabiting the South China Sea. We sequenced related venom transcriptomes from C. betulinus using both the next-generation sequencing and traditional Sanger sequencing technologies, and a comprehensive library of 215 conotoxin transcripts was constructed. In our current study, six conotoxins with potential insecticidal activity were screened out from our conotoxin library by homologous search with a reported positive control (alpha-conotoxin ImI from C. imperialis) as the query. Subsequently, these conotoxins were synthesized by chemical solid-phase and oxidative folding for further insecticidal activity validation, such as MTT assay, insect bioassay and homology modeling. The final results proved insecticidal activities of our achieved six conotoxins from the transcriptome-based dataset. Interestingly, two of them presented a lot of high insecticidal activity, which supports their usefulness for a trial as insecticides in field investigations. In summary, our present work provides a good example for high throughput development of biological insecticides on basis of the accumulated genomic resources.

α-Conotoxin [S9A]TxID Potently Discriminates between α3β4 and α6/α3β4 Nicotinic Acetylcholine Receptors

α3β4 nAChRs have been implicated in various pathophysiological conditions. However, the expression profile of α3β4 nAChRs and α6/α3β4 nAChRs overlap in a variety of tissues. To distinguish between these two subtypes, we redesigned peptide 1 (α-conotoxin TxID), which inhibits α3β4 and α6/α3β4 nAChR subtypes. We systematically mutated 1 to evaluate analogue selectivity for α3β4 vs α6/α3β4 nAChRs expressed in Xenopus laevis oocytes. One analogue, peptide 7 ([S9A]TxID), had 46-fold greater potency for α3β4 versus α6/α3β4 nAChRs. Peptide 7 had IC₅₀s > 10 μM for other nAChR subtypes. Molecular dynamics simulations suggested that Ser-9 of TxID was involved in a weak hydrogen bond with β4 Lys-81 in the α6β4 binding site but not in the α3β4 binding site. When Ser-9 was substituted by an Ala, this hydrogen bond interaction was disrupted. These results provide further molecular insights into the selectivity of 7 and provide a guide for designing ligands that block α3β4 nAChRs.

Molecular simulation study of the unbinding of α-conotoxin [ϒ4E]GID at the α7 and α4β2 neuronal nicotinic acetylcholine receptors

The α7 and α4β2 neuronal nicotinic receptors belonging to the family of ligand-gated ion channels are most prevalent in the brain, and are implicated in various neurodegenerative disorders. α-conotoxin GID (and its analogue [ϒ4E]GID) specifically inhibits these subtypes, with more affinity towards the human α7 (hα7) subtype, and is valuable in understanding the physiological roles of these receptors. In this study, we use umbrella-sampling molecular dynamics simulations to understand the mechanism of interaction between [ϒ4E]GID and the agonist binding pockets of the α4β2 and the hα7 receptors, and to estimate their relative binding affinities (ΔG_bind). The obtained ΔG_bind values indicate stronger interaction with the hα7 receptor, in agreement with previous experimental studies. Simulations also revealed different unbinding pathways between the two receptor subtypes, enabling identification of a number of interactions at locations far from the orthosteric binding site which may explain the difference in [ϒ4E]GID potency. The pathways identified will help in the design of novel conotoxins with increased potency at α4β2, for which there is currently no known highly potent conotoxin inhibitor. Computational mutational free energy analyses also revealed a number of possible single-site mutations to GID which might enhance its selective binding to α4β2 over α7.

Investigation of α-conotoxin unbinding using umbrella sampling

α-Conotoxins, a class of short and disulfide rich peptide toxins, specifically and potently block nicotinic acetylcholine receptors (nAChRs). In this study umbrella sampling was performed to study the unbinding pathways and potential of mean force (PMF) of α-conotoxin ImI and PNIA(A10L,D14K). Our results suggest that (i) the unbinding pathways of ImI and PNIA(A10L,D14K) are similar despite of their different disulfide framework and structure, and (ii) α-conotoxin unbinding requires large conformation perturbation of the C-loop and the backbone flexibility of the C-loop can affect the binding or unbinding kinetics of the α-conotoxins. In addition, (iii) umbrella sampling gave correct ranking of the binding affinities of ImI and PNIA(A10L,D14K) indicating its efficacy on prediction of the binding affinities of α-conotoxins and implicating its potential application in design of more potent α-conotoxin analogs.

Less is More: Design of a Highly Stable Disulfide-Deleted Mutant of Analgesic Cyclic α-Conotoxin Vc1.1

Cyclic α-conotoxin Vc1.1 (cVc1.1) is an orally active peptide with analgesic activity in rat models of neuropathic pain. It has two disulfide bonds, which can have three different connectivities, one of which is the native and active form. In this study we used computational modeling and nuclear magnetic resonance to design a disulfide-deleted mutant of cVc1.1, [C2H,C8F]cVc1.1, which has a larger hydrophobic core than cVc1.1 and, potentially, additional surface salt bridge interactions. The new variant, hcVc1.1, has similar structure and serum stability to cVc1.1 and is highly stable at a wide range of pH and temperatures. Remarkably, hcVc1.1 also has similar selectivity to cVc1.1, as it inhibited recombinant human α9α10 nicotinic acetylcholine receptor-mediated currents with an IC₅₀ of 13 μM and rat N-type (Ca_v2.2) and recombinant human Ca_v2.3 calcium channels via GABA_B receptor activation, with an IC₅₀ of ~900 pM. Compared to cVc1.1, the potency of hcVc1.1 is reduced three-fold at both analgesic targets, whereas previous attempts to replace Vc1.1 disulfide bonds by non-reducible dicarba linkages resulted in at least 30-fold decreased activity. Because it has only one disulfide bond, hcVc1.1 is not subject to disulfide bond shuffling and does not form multiple isomers during peptide synthesis.

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.

The impact of molecular dynamics on drug design: applications for the characterization of ligand-macromolecule complexes

Among all tools available to design new drugs, molecular dynamics (MD) simulations have become an essential technique. Initially developed to investigate molecular models with a limited number of atoms, computers now enable investigations of large macromolecular systems with a simulation time reaching the microsecond range. The reviewed articles cover four years of research to give an overview on the actual impact of MD on the current medicinal chemistry landscape with a particular emphasis on studies of ligand-protein interactions. With a special focus on studies combining computational approaches with data gained from other techniques, this review shows how deeply embedded MD simulations are in drug design strategies and articulates what the future of this technique could be.

Computational insights into inhibitory mechanism of azole compounds against human aromatase

We investigated the inhibitory mechanism of azole aromatase inhibitors. The results showed that letrozole and imazalil prefer different unbinding pathways.

GABA binding to an insect GABA receptor: a molecular dynamics and mutagenesis study

RDL receptors are GABA-activated inhibitory Cys-loop receptors found throughout the insect CNS. They are a key target for insecticides. Here, we characterize the GABA binding site in RDL receptors using computational and electrophysiological techniques. A homology model of the extracellular domain of RDL was generated and GABA docked into the binding site. Molecular dynamics simulations predicted critical GABA binding interactions with aromatic residues F206, Y254, and Y109 and hydrophilic residues E204, S176, R111, R166, S176, and T251. These residues were mutated, expressed in Xenopus oocytes, and their functions assessed using electrophysiology. The data support the binding mechanism provided by the simulations, which predict that GABA forms many interactions with binding site residues, the most significant of which are cation-π interactions with F206 and Y254, H-bonds with E204, S205, R111, S176, T251, and ionic interactions with R111 and E204. These findings clarify the roles of a range of residues in binding GABA in the RDL receptor, and also show that molecular dynamics simulations are a useful tool to identify specific interactions in Cys-loop receptors.

Unbinding pathways of GW4064 from human farnesoid X receptor as revealed by molecular dynamics simulations

Farnesoid X receptor (FXR, NR1H4) is a member of a nuclear receptor superfamily, which plays important roles in bile acid homeostasis, lipoprotein and glucose metabolism, and hepatic regeneration. GW4064 is a potent and selective FXR agonist and has become a tool compound to probe the physiological functions of FXR. Until now, the mechanism of GW4064 entering and leaving the FXR pocket is still poorly understood. Here, we report a computational study of GW4064 unbinding pathways from FXR by using several molecular dynamics (MD) simulation techniques. Based on the crystal structure of FXR in complex with GW4064, conventional MD was first used to refine the binding and check the stability of GW4064 in the FXR pocket. Random acceleration MD simulations were then performed to explore the possible unbinding pathways of GW4064 from FXR. Four main pathway clusters were found, among which three subpathways, namely Paths 2A, 2B, and 1B, were observed most frequently. Multiple steered MD simulations were further employed to estimate the maximum rupture force and the sum of the forces and to characterize the intermediate states of the ligand unbinding process. By comparing the average force profiles and structural changes, Paths 2A and 2B were identified to be the most favorable unbinding pathways. The former is located between the H1-H2 loop and the H5-H6 loop, and the latter is located in the cleft formed by the H5-H6 loop, H6, and H7. Moreover, the residues lining the pathways were analyzed for their roles in ligand unbinding. Based on our results, the possible structural modification strategies on GW4064 were also proposed.