title: Computational methods of studying the binding of toxins from venomous animals to biological ion channels: theory and applications.
abstract: The discovery of new drugs that selectively block or modulate ion channels has great potential to provide new treatments for a host of conditions. One promising avenue revolves around modifying or mimicking certain naturally occurring ion channel modulator toxins. This strategy appears to offer the prospect of designing drugs that are both potent and specific. The use of computational modeling is crucial to this endeavor, as it has the potential to provide lower cost alternatives for exploring the effects of new compounds on ion channels. In addition, computational modeling can provide structural information and theoretical understanding that is not easily derivable from experimental results. In this review, we look at the theory and computational methods that are applicable to the study of ion channel modulators. The first section provides an introduction to various theoretical concepts, including force-fields and the statistical mechanics of binding. We then look at various computational techniques available to the researcher, including molecular dynamics, brownian dynamics, and molecular docking systems. The latter section of the review explores applications of these techniques, concentrating on pore blocker and gating modifier toxins of potassium and sodium channels. After first discussing the structural features of these channels, and their modes of block, we provide an in-depth review of past computational work that has been carried out. Finally, we discuss prospects for future developments in the field.
authors.affiliation: Research School of Biology, The Australian National University, Acton, ACT 0200, Australia. dan.gordon@anu.edu.au
authors.forename: Dan
authors.initials: D
authors.lastname: Gordon
authors.forename: Rong
authors.initials: R
authors.lastname: Chen
authors.forename: Shin-Ho
authors.initials: SH
authors.lastname: Chung
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006801:Humans; D007473:Ion Channels / Q000737:chemistry* / Q000378:metabolism; D008958:Models, Molecular; D014118:Toxins, Biological / Q000737:chemistry* / Q000378:metabolism; D014688:Venoms / Q000737:chemistry* / Q000378:metabolism
chemical_list: D007473:Ion Channels; D014118:Toxins, Biological; D014688:Venoms