Drugging the cell's best friend

The tumor suppressor p53 is one of the cell’s very best friends. Just how good a friend it is becomes apparent when, just like in other relationships, this particular relationship turns sour. p53 is the “master guardian angel” of the genome and constitutes the most frequent genetic alteration in cancer. More than 50% of human tumors contain a mutation in the p53 gene. With this kind of glowing track record, p53 would be a prime target for drugs.

It turns out that discovering drugs for p53 is trickier than you think. The protein displays complex structural biology, and the mechanism of inhibitor action is not clear. But p53 malfunction is also characterized by one of the most distinctive physical mechanisms to ever emerge in an oncoprotein- about 30% of mutations in p53 simply lower the melting temperature (Tm) so that the protein becomes unstable and disordered. Thus, potential inhibitors of mutated p53 have been often termed ‘rescuers’ since ideally they would ‘rescue’ the protein from its unstable state.

In a recent paper, a team led by Alan Fersht of Cambridge- one of the world’s foremost protein chemists and p53 experts- explores one frequent mutation in p53 and how its consequences could be suitably exploited for rational drug discovery. The study is a nice example of the value of interdisciplinary research in tackling a complex problem. The rogue mutation is quite simple; it turns a tyrosine on the protein surface to a cysteine. The change to a smaller amino acid opens up a cavity on the protein surface. Is this cavity druggable’, that is, can a small molecule be found that selectively and potently binds to this cavity? This is what the researchers seek to do in this study (The presence of the cysteine makes me wonder if someone has tried a covalent tethering strategy for targeting this site).

The targeted site is an interesting one. It’s not exactly an allosteric site, since it is far away from the functional site but does not seem to affect the functional site. But Fersht and his colleagues have previously found a small molecule that binds to this site and raises the melting temperature. In this report, the authors extent p53 inhibitor discovery for the Y220C mutation further by using a combination of experimental and computational techniques.

They start by screening a fragment library; fragment-based drug discovery is now a stable of rational drug design. To minimize false positives and negatives, they use two complementary techniques: a 1D NMR method and a technique called thermal denaturation scanning fluorimetry, which detects the effect of a ligand using an exogenous dye. The two methods interestingly gave quite diverse hits, indicating the wisdom of combining them. To further confirm the binding of the fragments to the protein, they then use N15/H1 HSQC, an NMR method that detects changes in the proton and N15 chemical shifts when a ligand binds to the protein. By comparing unbound protein shifts to bound ones, one can locate only the amino acids that interact with the ligand. This is a really nice method since one can make out the concerned amino acids just by inspection; in the figure below, the multi-colored areas indicate significantly perturbed amino acids, and it’s very useful to locate the exact binding sites since amino acids outside the site don’t seem to be affected. In this particular case the key residues turned out to be a valine, an aspartate and a few others.




The study proceeded by employing the one method which can confirm ligand binding better than any other- x-ray crystallography. Crystal structures revealed binding modes for a few of the hits. One molecule turned out to bind to the binding cavity in two copies.

What exactly are the hits doing to the protein? To investigate this, the authors used molecular dynamics (MD) simulations in isopropanol. In this case isopropanol is not a solvent mimic but it’s actually a drug mimic. It has a polar and non-polar part and it can approximate a typical protein-binding molecule well. Binding cavities can be detected by looking at the density of isopropanol in the pockets. In this particular example, the highest density is actually found in other sites, but those sites are not relevant for this study.

The most intriguing observation from the MD simulations was that the size of the cavity fluctuates wildly when the ligand is not present. This dynamic flexibility of residues can be characteristic of an unstable region (this was also observed in some computational enzyme designs that I described earlier). To validate this flexibility, the simulations were run with the ligand present; not surprisingly, the size fluctuation in the cavity reduces. Intriguingly, the ligand seems to play the role of the previous tyrosine in packing against the other residues and keeping the site stable.

There is some way to go before we have a bonafide drug that ‘rescues’ p53 from its ignominious fate. But this study is a nice illustration of how only interdisciplinary computational and experimental work can really help us to unravel the mysteries of this ubiquitous and enigmatic Jekyll and Hyde.

Basse, N., Kaar, J., Settanni, G., Joerger, A., Rutherford, T., & Fersht, A. (2010). Toward the Rational Design of p53-Stabilizing Drugs: Probing the Surface of the Oncogenic Y220C Mutant Chemistry & Biology, 17 (1), 46-56 DOI: 10.1016/j.chembiol.2009.12.011