In silico toxicology investigation of μ-conotoxin KIIIA on human Na⁺ channel Na_v1.2

Conotoxins(CTXs) can specifically act on multiple ion channels, which are crucial for the development of neurobiology and novel targeted drug development. At present, >10,000 kinds of CTXs have been sequenced, it would be extremely laborious to conduct experiments for each. μ-CTX KIIIA is a type of substance that can selectively recognize voltage-gated sodium ion channels. This article constructs four derivatives of KIIIA and predicts their 3D structures; afterwards, their molecular orbital arrangements and physicochemical properties were calculated using DFT; then, predicted their toxicokinetic parameters such as absorption, distribution, metabolism, excretion (ADME) and toxicity (T) through Machine Learning (ML); finally, molecular docking and molecular dynamics are used to investigate the interaction modes and binding affinity. The results indicate that the toxicity of KIIIA and its derivatives (KIIIA-1 -KIIIA-4) to the human body is mainly concentrated in the liver and respiratory tract. Among four derivatives, KIIIA-2 (5 Ser → Arg) has better toxicokinetics properties and its binding energy to Na_v1.2 is -65.32 kcal/mol, which is higher than that of wild type(-32.13 kcal/mol). This study indicate that computational toxicology can facilitate the druggability research of CTXs, and KIIIA-2 can be developed as a potential antiepileptic drug.