Computational approaches for designing potent and selective analogs of peptide toxins as novel therapeutics.

Peptide toxins provide valuable therapeutic leads for many diseases. As they bind to their targets with high affinity, potency is usually ensured. However, toxins also bind to off-target receptors, causing potential side effects. Thus, a major challenge in generating drugs from peptide toxins is ensuring their specificity for their intended targets. Computational methods can play an important role in solving such design problems through construction of accurate models of receptor-toxin complexes and calculation of binding free energies. Here we review the computational methods used for this purpose and their application to toxins targeting ion channels. We describe ShK and HsTX1 toxins, high-affinity blockers of the voltage-gated potassium channel Kv1.3, which could be developed as therapeutic agents for autoimmune diseases.