Molecular basis for the interplay of apoptosis and proliferation mediated by Bcl-xL:Bim interactions in pancreatic cancer cells
ABSTRACT A major mechanism through which cancer cells avoid apoptosis is by promoting the association of anti-apoptotic members of the pro-survival Bcl-2 protein family (like Bcl-2 and Bcl-xL) with BH(3) domain-only proteins (like Bim and Bid). Apoptosis and cell proliferation have been shown to be linked for many cancers but the molecular basis for this link is far from understood. We have identified the Bcl-xL:Bim protein-protein interface as a direct regulator of proliferation and apoptosis in pancreatic cancer cells. We were able to predict and subsequently verify experimentally the effect of various Bcl-xL single-point mutants (at the position A142) on binding to Bim by structural analysis and computational modeling of the inter-residue interactions at the Bcl-xL:Bim protein-protein interface. The mutants A142N, A142Q, and A142Y decreased binding of Bim to Bcl-xL and A142S increased this binding. The Bcl-xL mutants, with decreased affinity for Bim, caused an increase in apoptosis and a corresponding decrease in cell proliferation. However, we could prevent these effects by introducing a small interfering RNA (siRNA) targeted at Bim. These results show a novel role played by the Bcl-xL:Bim interaction in regulating proliferation of pancreatic cancer cells at the expense of apoptosis. This study presents a physiologically relevant model of the Bcl-xL:Bim interface that can be used for rational therapeutic design for the inhibition of proliferation and cancer cell resistance to apoptosis.
SourceAvailable from: R. John MacleodLaboratory Investigation 12/2012; 92(12):1670-3. DOI:10.1038/labinvest.2012.151 · 3.83 Impact Factor
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ABSTRACT: A long-term aim of computational design is to generate specific protein–protein interactions at desired affinity, specificity, and kinetics. The past three years have seen the first reports on atomically accurate de novo interactions. These were based on advances in design algorithms and the ability to harness high-throughput experimental characterization of design variants to optimize binding. Current state-of-the-art in computational design lacks precision, and therefore requires intensive experimental optimization to achieve parity with natural binders. Recent successes (and failures) point the way to future progress in design methodology that would enable routine and robust design of binders and inhibitors, while also shedding light on the essential features of biomolecular recognition.Current Opinion in Structural Biology 12/2013; 23(6). DOI:10.1016/j.sbi.2013.08.003 · 8.75 Impact Factor