Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery: Bridging Experiments and Computations - September 10-14, 2014, Istanbul, Turkey

Modeling of Biomolecular Systems Interactions, Dynamics, and Allostery Session VI Abstracts

Computational Design of Drugs for Autoimmune Diseases from Peptide Toxins Serdar Kuyucak . University of Sydney, Sydney, NSW, Northwest Territorie, Australia. Developing drugs from natural products such as toxins has a great potential but progress has been slow due to complexity of the problem. Combination of experimental methods with accurate simulations of protein-peptide complexes could help to improve this situation. Two main computational challenges are construction of accurate models of complexes and prediction of reliable binding free energies. The former can be achieved using docking programs, followed by refinement via molecular dynamics (MD) simulations. Binding free energies can be obtained from the potential of mean force (PMF) calculations. We showed the feasibility of this approach in a potassium channel-charybdotoxin complex, where the complex structure is known from NMR [1]. As a real-life application, we considered ShK toxin, which binds to Kv1.3 channels with very high affinity, and therefore, it is developed as an immunosuppressant drug. However, it also binds to Kv1.1 with similar affinity, and it essential to find analogues of ShK with increased selectivity for Kv1.3. We have developed accurate models for Kv1.1-1.3 channels in complex with ShK, which are validated by comparing with available mutagenesis data and binding free energies [2]. The complex structures of ShK indicated several mutations on ShK (e.g. K18A, R29A) that could enhance its Kv1.3/Kv1.1 selectivity. Free energy perturbation and PMF calculations of the K18A mutation on ShK yielded about 2 kcal/mol improvement on its Kv1.3/Kv1.1 selectivity, which has been confirmed in subsequent experiments [3]. The computational methods considered here would be very useful in rational drug design, especially in solving selectivity problems for unintended targets. [1] P.C. Chen and S. Kuyucak. 2011. Biophys. J. 100:2466-2474. [2] M.H. Rashid and S. Kuyucak. 2012. J. Phys. Chem. B 116:4812-4822. [3] M.H. Rashid et al. 2013. PloS ONE 8:e78712.

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