Designing small-molecule modulators of protein function using computational and experimental techniques.
Our primary goal is to develop structure-based approaches for modulating protein function using small-molecules. We are exploring two parallel paths towards this overarching goal: the first is re-engineering proteins so that a small-molecule can be used to “turn on” function, and the second is identifying small-molecules that naturally complement and occlude a protein surface such that they can be used to “turn off” function.
In select cases, the ability to activate protein function with a pharmacological agent has already helped elucidate details of protein function in living cells. However, these cases have been limited either by the fact that the strategy must be catered to a particular protein system or by relatively slow kinetics of activation. Our goal is to develop a very general approach for engineering small-molecule dependent function into proteins in a way that circumvents these problems. Our novel strategy for activating protein function is predicated on adapting a well-known technique – chemical rescue – in an entirely new structure-based context. We start by identifying a “buttressing” tryptophan sidechain near the protein functional site; removal of this structural feature via mutation to glycine will lead to collapse of the nearby protein architecture, resulting in loss of function. We then restore the buttress via addition of exogenous indole, which restores the original protein conformation and thus rescues protein function. We have already demonstrated proof-of-concept for this approach by introducing indole-dependent function into an enzyme. Through enzymology and crystallographic studies, we then demonstrated that indeed this “activatable” protein works via exactly the anticipated mechanism.
Meanwhile, the ability to identify a small-molecule to inhibit a particular protein-protein interaction has long represented a promising avenue for therapeutic intervention in a variety of settings. The relative lack of success in this pursuit has led to a collective view that protein interactions represent a challenging therapeutic target. Our goal is to understand the root cause of these difficulties unlocking the vast potential associated with pharmacological inhibitors of protein interactions, and translate this understanding into new methods for identifying inhibitors with therapeutic potential. Our approach for understanding principles governing small-molecule binding at protein interaction sites began with a survey of known examples. We developed a computational structure-based approach for distinguishing between sites that are suitable for small-molecule binding and those that are not. We used this to study fluctuations at the protein surface, and found that we could distinguish known “druggable” sites from “undruggable” sites. We anticipate this methodology will prove useful not only in identifying druggable sites on the surface of a target protein, but also to assist in selecting the most druggable components within any protein interaction network. More recently we have used the shapes of these surface pockets to identify complementary small-molecules, and have begun testing candidate inhibitors in the wetlab.
In both cases our long-term goal is to apply these tools to understand how specific protein-protein interactions are responsible for normal and aberrant signal transduction in cells.
- Gowthaman R, Johnson D, Karanicolas J. "Small molecule docking and screening by a ray-casting approach" (manuscript in preparation).
- Johnson D, Karanicolas J. "Evaluating druggability of protein interaction sites" (submitted).
- Deckert K, Brunner LC, Budiardjo SJ, Lovell S, Karanicolas J. "Designing allosteric control into enzymes by chemical rescue of structure." J. Amer. Chem. Soc. 134, p. 10055-10060 (2012).
- Sievers SA, Karanicolas J, Chang HW, Zhao A, Jiang L, Zirafi O, Stevens JT, Munch J, Baker D, Eisenberg D. "Structure-based design of non-natural amino acid inhibitors of amyloid fibrillation." Nature 475, p. 96-100 (2011).
- Karanicolas J, Corn JE, Chen I, Joachimiak LA, Dym O, Peck SH, Albeck S, Unger T, Hu W, Liu G, Delbecq S, Montelione G, Spiegel C, Liu DR, Baker D. "A de novo protein binding pair by computational design and directed evolution." Mol. Cell. 42, p. 250-260 (2011).
- Karanicolas J, Kuhlman B. "Computational Design of Affinity and Specificity at Protein-Protein Interfaces." Curr. Opin. Struct. Biol., 19, p. 458-463 (2009).
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