Probing peptide libraries from Conus achatinus using mass spectrometry and cDNA sequencing: identification of delta and omega-conotoxins

Variable peptide processing of a Conus (Asprella) neocostatus α-conotoxin generates bioactive toxiforms that are potent against distinct nicotinic acetylcholine receptor subtypes

Conusvenoms are composed of peptides that are commonly post-translationally modified, increasing their chemical diversity beyond what is encoded in the genome and enhancing their potency and selectivity. This study describes how PTMs alter an α-conotoxin's selectivity for specific nAChR subtypes. Venom from the cone snailConus(Asprella)neocostatuswas fractionated using high-performance liquid chromatography and tested using a behavioral intracranial mouse bioassay and a cholinergic calcium imaging assay using SH-SY5Y neuroblastoma cells. Four peptides were isolated from three HPLC fractions and found to have similar amino acid sequences using tandem mass spectrometry; they all containC-terminal amidation. The four peptides appear to be encoded by a single gene as indicated by transcriptomic analysis. One of these, NcIA, contains no additional PTM. NcIB lacked the two glycine residues found in the N-terminus of NcIA and contained two hydroxylated prolines. Analogs of both peptides containing a ɣ-carboxylated glutamic residue (NcIA[E15γ] and NcIB[E13γ]) were also isolated. Functional assays revealed distinct receptor selectivity: NcIA inhibited nicotine-evoked responses by over 70 %, while NcIA[E15γ] did not. Conversely, NcIB[E13γ] was inhibitory (∼60 %), but NcIB was not. Against choline-evoked responses, NcIA was weakly inhibitory (∼40 %), whereas the other three were nearly fully inhibitory. The IC50values for NcIB and NcIB[E13γ] were 91.0 nM and 64.7 nM, respectively. These findings indicate that PTMs andN-terminal modifications influence peptide potency and receptor specificity, suggesting that cone snails use variable peptide processing not only to generate chemical diversity in their venom but also to fine-tune the pharmacology of its components.

Conotoxins: Classification, Prediction, and Future Directions in Bioinformatics

Conotoxins, a diverse family of disulfide-rich peptides derived from the venom of Conus species, have gained prominence in biomedical research due to their highly specific interactions with ion channels, receptors, and neurotransmitter systems. Their pharmacological properties make them valuable molecular tools and promising candidates for therapeutic development. However, traditional conotoxin classification and functional characterization remain labor-intensive, necessitating the increasing adoption of computational approaches. In particular, machine learning (ML) techniques have facilitated advancements in sequence-based classification, functional prediction, and de novo peptide design. This review explores recent progress in applying ML and deep learning (DL) to conotoxin research, comparing key databases, feature extraction techniques, and classification models. Additionally, we discuss future research directions, emphasizing the integration of multimodal data and the refinement of predictive frameworks to enhance therapeutic discovery.

Structural and Functional Characterization of Conotoxins from Conus achatinus Targeting NMDAR

Conotoxin-Ac1 and its variant conotoxin-Ac1-O6P, were isolated from the venom duct of Conus achatinus, a fish-hunting cone snail species collected in the Sea of Hainan, China. Conotoxin-Ac1 is linear peptide that contain 15 amino acids. In the present study, we synthesized and structurally and functionally characterized conotoxin-Ac1 as well as 19 variants. Electrophysiological results showed that conotoxin-Ac1 inhibited N-methyl-D-aspartate receptor subunit 2B (NR2B) with an IC₅₀ of 8.22 ± 0.022 μM. Further structure-activity studies of conotoxin-Ac demonstrated that polar amino acid residues were important for modulating its active, and the replacement of N1, O9, E10, and S12 by Ala resulted in a significant decrease in potency to NR2B. °Furthermore, conotoxin-Ac1 and conotoxin-Ac1-O6P were tested in hot-plate and tail-flick assays to measure the potential analgesic activity to an acute thermal stimulus in a dose-dependent manner. Subsequently, the analgesic activity of conotoxin-Ac1 mutants was analyzed by the hot-plate method. The results show that N1, Y2, Y3, E10, N11, S12, and T15 play an important role in the analgesic activity of conotoxin-Ac1. N1 and S12 have significant effects on conotoxin-Ac1 in inhibiting NR2B and analgesic activity. In conclusion, we have discovered that conotoxin-Ac1 is an inhibitor of NMDAR and displays antinociceptive activity.

Recent Advances in Conotoxin Classification by Using Machine Learning Methods

Conotoxins are disulfide-rich small peptides, which are invaluable peptides that target ion channel and neuronal receptors. Conotoxins have been demonstrated as potent pharmaceuticals in the treatment of a series of diseases, such as Alzheimer's disease, Parkinson's disease, and epilepsy. In addition, conotoxins are also ideal molecular templates for the development of new drug lead compounds and play important roles in neurobiological research as well. Thus, the accurate identification of conotoxin types will provide key clues for the biological research and clinical medicine. Generally, conotoxin types are confirmed when their sequence, structure, and function are experimentally validated. However, it is time-consuming and costly to acquire the structure and function information by using biochemical experiments. Therefore, it is important to develop computational tools for efficiently and effectively recognizing conotoxin types based on sequence information. In this work, we reviewed the current progress in computational identification of conotoxins in the following aspects: (i) construction of benchmark dataset; (ii) strategies for extracting sequence features; (iii) feature selection techniques; (iv) machine learning methods for classifying conotoxins; (v) the results obtained by these methods and the published tools; and (vi) future perspectives on conotoxin classification. The paper provides the basis for in-depth study of conotoxins and drug therapy research.

Identifying the Types of Ion Channel-Targeted Conotoxins by Incorporating New Properties of Residues into Pseudo Amino Acid Composition

Conotoxins are a kind of neurotoxin which can specifically interact with potassium, sodium type, and calcium channels. They have become potential drug candidates to treat diseases such as chronic pain, epilepsy, and cardiovascular diseases. Thus, correctly identifying the types of ion channel-targeted conotoxins will provide important clue to understand their function and find potential drugs. Based on this consideration, we developed a new computational method to rapidly and accurately predict the types of ion-targeted conotoxins. Three kinds of new properties of residues were proposed to use in pseudo amino acid composition to formulate conotoxins samples. The support vector machine was utilized as classifier. A feature selection technique based on F-score was used to optimize features. Jackknife cross-validated results showed that the overall accuracy of 94.6% was achieved, which is higher than other published results, demonstrating that the proposed method is superior to published methods. Hence the current method may play a complementary role to other existing methods for recognizing the types of ion-target conotoxins.

A perspective on toxicology of Conus venom peptides

The evolutionarily unique and ecologically diverse family Conidae presents fundamental opportunities for marine pharmacology research and drug discovery. The focus of this investigation is to summarize the worldwide distribution of Conus and their species diversity with special reference to the Indian coast. In addition, this study will contribute to understanding the structural properties of conotoxin and therapeutic application of Conus venom peptides. Cone snails can inject a mix of various conotoxins and these venoms are their major weapon for prey capture, and may also have other biological purposes, and some of these conotoxins fatal to humans. Conus venoms contain a remarkable diversity of pharmacologically active small peptides; their targets are an iron channel and receptors in the neuromuscular system. Interspecific divergence is pronounced in venom peptide genes, which is generally attributed to their species specific biotic interactions. There is a notable interspecific divergence observed in venom peptide genes, which can be justified as of biotic interactions that stipulate species peculiar habitat and ecology of cone snails. There are several conopeptides used in clinical trials and one peptide (Ziconotide) has received FDA approval for treatment of pain. This perspective provides a comprehensive overview of the distribution of cone shells and focus on the molecular approach in documenting their taxonomy and diversity with special reference to geographic distribution of Indian cone snails, structure and properties of conopeptide and their pharmacological targets and future directions.

Novel M-Superfamily and T-Superfamily conotoxins and contryphans from the vermivorous snail Conus figulinus

The venom of Conus figulinus, a vermivorous cone snail, found in the south east coast of India, has been studied in an effort to identify novel peptide toxins. The amino acid sequences of seven peptides have been established using de novo mass spectrometric based sequencing methods. Among these, three peptides belong to the M-Superfamily conotoxins, namely, Fi3a, Fi3b, and Fi3c, and one that belongs to the T-Superfamily, namely, Fi5a. The other three peptides are contryphans, namely, contryphans fib, fic, and fid. Of these Fi3b, Fi3c, Fi5a, and contryphan fib are novel and are reported for the first time from venom of C. figulinus. The details of the sequencing methods and the relationship of these peptides with other 'M'-Superfamily conotoxins from the fish hunting and mollusk hunting clades are discussed. These novel peptides could serve as a lead compounds for the development of neuropharmacologically important drugs.

iCTX-type: a sequence-based predictor for identifying the types of conotoxins in targeting ion channels

Conotoxins are small disulfide-rich neurotoxic peptides, which can bind to ion channels with very high specificity and modulate their activities. Over the last few decades, conotoxins have been the drug candidates for treating chronic pain, epilepsy, spasticity, and cardiovascular diseases. According to their functions and targets, conotoxins are generally categorized into three types: potassium-channel type, sodium-channel type, and calcium-channel types. With the avalanche of peptide sequences generated in the postgenomic age, it is urgent and challenging to develop an automated method for rapidly and accurately identifying the types of conotoxins based on their sequence information alone. To address this challenge, a new predictor, called iCTX-Type, was developed by incorporating the dipeptide occurrence frequencies of a conotoxin sequence into a 400-D (dimensional) general pseudoamino acid composition, followed by the feature optimization procedure to reduce the sample representation from 400-D to 50-D vector. The overall success rate achieved by iCTX-Type via a rigorous cross-validation was over 91%, outperforming its counterpart (RBF network). Besides, iCTX-Type is so far the only predictor in this area with its web-server available, and hence is particularly useful for most experimental scientists to get their desired results without the need to follow the complicated mathematics involved.

The UniProtKB/Swiss-Prot Tox-Prot program: A central hub of integrated venom protein data

Animal toxins are of interest to a wide range of scientists, due to their numerous applications in pharmacology, neurology, hematology, medicine, and drug research. This, and to a lesser extent the development of new performing tools in transcriptomics and proteomics, has led to an increase in toxin discovery. In this context, providing publicly available data on animal toxins has become essential. The UniProtKB/Swiss-Prot Tox-Prot program (http://www.uniprot.org/program/Toxins) plays a crucial role by providing such an access to venom protein sequences and functions from all venomous species. This program has up to now curated more than 5000 venom proteins to the high-quality standards of UniProtKB/Swiss-Prot (release 2012_02). Proteins targeted by these toxins are also available in the knowledgebase. This paper describes in details the type of information provided by UniProtKB/Swiss-Prot for toxins, as well as the structured format of the knowledgebase.

Mass spectrometry in India

This review emphasizes the mass spectrometry research being performed at academic and established research institutions in India. It consists of three main parts covering the work done in organic, atomic and biological mass spectrometry. The review reveals that the use of mass spectrometry techniques started in the middle of the 20th century and was applied to research in the fields of organic, nuclear, geographical and atomic chemistry. Later, with the advent of soft and atmospheric ionization techniques it has been applied to pharmaceutical and biological research. In due course, several research centers with advanced mass spectrometry facilities have been established for specific areas of research such as gas-phase ion chemistry, ion-molecule reactions, proscribed chemicals, pesticide residues, pharmacokinetics, protein/peptide chemistry, nuclear chemistry, geochronological studies, archeology, petroleum industry, proteomics, lipidomics and metabolomics. Day-by-day the mass spectrometry centers/facilities in India have attracted young students for their doctoral research and other advanced research applications.

Disulfide-Depleted Selenoconopeptides: a Minimalist Strategy to Oxidative Folding of Cysteine-Rich Peptides

Despite the therapeutic promise of disulfide-rich, peptidic natural products, their discovery and structure/function studies have been hampered by inefficient oxidative folding methods for their synthesis. Here we report that converting the three disulfide-bridged mu-conopeptide KIIIA into a disulfide-depleted selenoconopeptide (by removal of a noncritical disulfide bridge and substitution of a disulfide- with a diselenide-bridge) dramatically simplified its oxidative folding while preserving the peptide's ability to block voltage-gated sodium channels. The simplicity of synthesizing disulfide-depleted selenopeptide analogs containing a single disulfide bridge allowed rapid positional scanning at Lys7 of mu-KIIIA, resulting in the identification of K7L as a mutation that improved the peptide's selectivity in blocking a neuronal (Na(v)1.2) over a muscle (Na(v)1.4) subtype of sodium channel. The disulfide-depleted selenopeptide strategy offers regioselective folding compatible with high throughput chemical synthesis and on-resin oxidation methods, and thus shows great promise to accelerate the use of disulfide-rich peptides as research tools and drugs.

Rapid sensitive analysis of cysteine rich peptide venom components

Disulfide-rich peptide venoms from animals such as snakes, spiders, scorpions, and certain marine snails represent one of nature's great diversity libraries of bioactive molecules. The various species of marine cone shells have alone been estimated to produce >50,000 distinct peptide venoms. These peptides have stimulated considerable interest because of their ability to potently alter the function of specific ion channels. To date, only a small fraction of this immense resource has been characterized because of the difficulty in elucidating their primary structures, which range in size between 10 and 80 aa, include up to 5 disulfide bonds, and can contain extensive posttranslational modifications. The extraordinary complexity of crude venoms and the lack of DNA databases for many of the organisms of interest present major analytical challenges. Here, we describe a strategy that uses mass spectrometry for the elucidation of the mature peptide toxin components of crude venom samples. Key to this strategy is our use of electron transfer dissociation (ETD), a mass spectrometric fragmentation technique that can produce sequence information across the entire peptide backbone. However, because ETD only yields comprehensive sequence coverage when the charge state of the precursor peptide ion is sufficiently high and the m/z ratio is low, we combined ETD with a targeted chemical derivatization strategy to increase the charge state of cysteine-containing peptide toxins. Using this strategy, we obtained full sequences for 31 peptide toxins, using just 7% of the crude venom from the venom gland of a single cone snail (Conus textile).

Structural studies of conotoxins

Conotoxins are small disulfide-rich peptides from the venoms of marine cone snails. They target a variety of ion channels, transporters, and receptors besides the interest in their natural functions in venoms and they are of much interest as drug leads. This short article gives an overview of the structural diversity of conotoxins, and illustrates this diversity with recent selected examples of conotoxin structures.

Integrating the discovery pipeline for novel compounds targeting ion channels

Many ion channels are attractive therapeutic targets for the treatment of neurological or cardiovascular diseases; there is a continuous need for selective channel antagonists and/or agonists. Recently, several technologies have been developed that make exploration of the enormous diversity of venom-derived peptidic toxins more feasible. Integration of exogenomics with synthetic methods such as diselenide or fluorous bridges, backbone spacers, and N-to-C cyclization provides an emerging technology that promises to accelerate discovery and development of natural products based compounds. These drug-discovery efforts are complemented by novel approaches to modulate the activities of ion channels and receptors. Taken together, these technologies will advance our knowledge and understanding of ion channels and will accelerate their expansion as targets for first-in-class therapeutics.