Computational and Functional Characterization of Terebrid Venom Peptides

Author

Favour T. Achimba, CUNY Graduate CenterFollow

Date of Degree

2-2026

Document Type

Doctoral Dissertation

Degree Name

Doctor of Philosophy

Program

Biochemistry

Advisor

Mandë Holford

Committee Members

Anjana Saxena

Roland Dunbrack

Joan Font-Burgada

Olorunseun Ogunwobi

Subject Categories

Biochemistry | Biodiversity | Bioinformatics | Marine Biology | Molecular Biology | Other Biochemistry, Biophysics, and Structural Biology | Structural Biology

Keywords

venom peptides, teretoxins, conotoxins, protein structure prediction, artificial intelligence and machine learning, AlphaFold2-based modeling, molecular docking and molecular dynamics simulations, ion channels, TRP channels, hepatocellular carcinoma

Abstract

Venom peptides represent a natural repertoire of bioactive compounds that are potent modulators of ion channels. Teretoxins, venom peptides from terebrid snails, remain underexplored despite their structural and functional diversity. This thesis is the first to comprehensively explore the structure and function of teretoxins using a comparative computational sequence and structure model followed by experimental assays. The majority of the functional focus has been on identifying the ion channel molecular targets of uncharacterized teretoxins. Teretoxins, like other venom peptides, are hypothesized to manipulate the cellular function of a diversity of ion channels. Dysregulation of ion channels leads to several human diseases and disorders, including pain and cancer. In this work I introduce how venom peptides from marine snails have a demonstrated potential for drug discovery and development, and how uncharacterized venom peptides, like teretoxins, can be used to target dysregulated ion channels in the most common form of liver cancer, hepatocellular carcinoma (Chapter 1).

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths and disproportionately affects Black and Asian populations. HCC is often diagnosed at advanced stages where treatment options are limited, and sorafenib offers only modest benefits. As a channelopathy, HCC is characterized by the overexpression of transient receptor potential (TRP) ion channels. Teretoxins that target dysregulated ion channels represent a promising source of anti-HCC therapies. One of the focus areas of this dissertation investigates the structural, and functional characteristics of teretoxins with the goal of identifying candidates with antitumor and ion-channel-modulatory potential (Chapter 2). This chapter examines the feasibility of that effort by reviewing the current literature and practices and outlining the inherent advantages of venom peptides in the HCC use case scenario.

The central hypothesis guiding this dissertation research is that teretoxins sharing structural features with functionally characterized venom peptides would exhibit similar functional activity. To test this, I performed a large-scale computational screening of approximately 4,000 venom peptides (1,558 teretoxins and 2,322 conotoxins) using AlphaFold2 for structure prediction—the first application of this tool to a comprehensive terebrid peptide dataset (Chapter 3). Structural clustering with TM-align identified seven peptide co-clusters with various predicted activities including neurotoxin, ion-channel targeting and Kunitz-type protease inhibitors with potential ion-channel-modulatory functions. Predicted function activity of the Kunitz-type peptide cluster was orthogonally validated through molecular docking and molecular-dynamics simulations, further strengthening analysis to deorphanize teretoxin Tar2.9 and cone snail venom peptide, conotoxin P07849. In an effort to apply sequence and structural predictions to large datasets of uncharacterized venom peptides, I co-developed MARC (Molecular Arms Race Classifier), a machine-learning model that classifies venom peptides by their ion-channel molecular targets –potassium (K⁺), sodium (Na⁺), calcium (Ca²⁺), or non-ion channel acting (Chapter 4). MARC predicted that 28 unique teretoxin peptides were primarily K⁺ channel modulators. This prediction was validated by the overall stability of a docked complex of the highest rated teretoxin Cje1.9, with the K⁺ channel, MthK (pdb_00004hyo).

To bridge the computational predictions with experimental efforts, I optimized peptide synthesis and oxidative folding workflows for cysteine-rich teretoxins and characterized the bioactivity of the teretoxin Tv1 in human HCC cell lines (Chapter 5). Tv1 demonstrated selective antiproliferative effects in SNU475 and HUH7 cells compared to normal liver cells, suggesting anti-cancer specificity. Although the precise mechanism of Tv1’s anti-cancer activity remains unresolved, experimental evidence indicates that Tv1’s activity is not mediated by manipulation of TRPC3 channels but may involve other calcium-channel interactions.

Overall, this work integrates computational modeling, machine learning, and molecular experimentation to establish a framework for studying teretoxins as potential ion-channel modulators and anticancer agents. It expands the structural and functional understanding of terebrid venom peptides and lays the foundation for future mechanistic and therapeutic development.

Recommended Citation

Achimba, Favour T., "Computational and Functional Characterization of Terebrid Venom Peptides" (2026). CUNY Academic Works.
https://academicworks.cuny.edu/gc_etds/6537