Discovery of Entry Inhibitors for HIV-1

advertisement
Discovery of Entry Inhibitors for HIV-1: Predictions via a
Novel De Novo Protein Design Framework and
Experimental Validation
Meghan L. Bellows*, Hoki Fung, and Christodoulos A. Floudas
Department of Chemical Engineering, Princeton University
Lin Shen and Robert F. Siliciano
Department of Medicine, Johns Hopkins University
Martin S. Taylor and Phillip A. Cole
Department of Pharmacology, Johns Hopkins University
Session 3, Talk 2 (2:00 PM)
A new de novo design framework with a ranking metric based on approximate binding
affinity calculations is introduced. The framework consists of two stages: a sequence selection
stage and a validation stage. The sequence selection stage produces a rank-ordered list of amino
acid sequences with the lowest energies by solving an integer programming sequence selection
model [1]. The validation stage uses both fold specificity calculations and approximate binding
affinity calculations to re-rank the sequences from stage one, validating the sequence’s fold and
binding to a target protein [2].
We applied the framework to develop short peptide-based inhibitors of HIV-1 entry into
host cells. These peptidic inhibitors consist of 12 amino acids and target the core hydrophobic
pocket of gp41. The choice of the epitope is based on: (i) the success of enfuvirtide (Fuzeon),
(ii) the work on short constrained C-peptides that inhibit HIV-1 gp41, and (iii) the crystal
structure elucidated on the best inhibitor complexed with the gp41 hydrophobic core [3].
A number of the best-predicted sequences were synthesized and their inhibition of HIV-1
was tested in vitro. All of the peptides examined showed inhibitory activity when compared with
no drug present, and the novel peptide sequences outperformed the native template sequence
used for the design. The best sequence showed micromolar inhibition. In addition, all peptides
were shown to be non-toxic, maintaining their full viability at 500 μM.
[1]
[2]
[3]
H. K. Fung, M. S. Taylor, and C. A. Floudas, Optim. Methods & Software, 22 (2007).
M. L. Bellows, H. K. Fung, C. A. Floudas, A. Lopez de Victoria, and D. Morikis, Biophys.
J., submitted (2009).
S. K. Sia, P. A. Carr, A. G. Cochran, V. N. Malashkevich, and P. S. Kim, PNAS, 99 (2002).
Download