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Updated: Oct 4, 2026

Extraction of Venom and Venom Gland Microdissections from Spiders for Proteomic and Transcriptomic Analyses
Published on: November 3, 2014
Venom-derived and natural analgesic peptides: From venomics-based discovery to computational design and therapeutic
Fatemeh Aliakbari1, Masoumeh Sadat Mousavi Maleki2, Sajad Sadeghi3
1Research Center of Physiology, Neuroscience Research Institute, Semnan University of Medical Sciences, Semnan, Iran.
Abstract:
Pain is a complex physiological process and an important clinical issue due to thelimitations of the existing analgesics. Side effects, tolerance anddependence, and limited efficacy for the treatment of chronic pain are common complications of classic drugs, e.g., opioids and nonsteroidal anti-inflammatory drugs (NSAIDs). In the last decade, analgesic peptides have gained considerable attention as new drug candidates due to their high target specificity, structural complexity, and ability to interact with critical molecular players of nociceptive signaling such as ion channels, receptors and inflammatory pathways. Natural venoms as well as endogenous regulatory systems are an abundant sourceof bioactive peptide scaffolds with maximal analgesic potential. Also, the use of advanced computational methods such as molecular docking, molecular dynamics simulation and multi-omic data integration has accelerated the discovery and design of peptide-based drugs and has greatly reduced the need for costly and time-consuming experiments. In this review, the latest achievements related to analgesic peptides, including endogenous peptides, venom-derived and engineered peptides, are reviewed, along with their mechanisms of action and therapeutic potential. The role of omics technologies and in silico tools in peptide identification, design, and optimization is also highlighted, and a newly designed cyclic peptide is introduced as an example of rational and computationally driven development of analgesic drugs. Existing evidence suggests that peptide-based strategies could open new hopes for the development of safer, more specific, and more effective treatments for pain management, especially chronic pain.
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