The Kryptonite, based on PPIs, of drug discovery

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It is not far away the time when diseases such as Smallpox or Diphteria were very common among people. Or when the word “cancer” was a clear synonym of death. Scientific research has not only brought understanding of diseases, but has also contributed to the generation of drugs and vaccines. In the field of drugs, small molecules represented the great hope. Millions and billions of combinations could be obtained, generating a vast collection of magical keys that could open the ensemble of protein targets.Later on, with the advent of the new technologies on drug discovery we though that we were almost invincible and there was hope for finding the cure against many diseases. High-throughput screening, fragment screening, combinatorial chemistry and the improvement of computational tools represented a set of weapons to fight against known and new diseases.

However (because there is always a “however”) the happily ever after was not fulfilled. Nowadays, despite the research intensity in some areas, there are unmet clinical needs. What happened? In these lines we will focus on a certain type of Kryptonite: “Protein-protein interactions” (PPI). The model of lock and key was suitable for targets such as kinases, phosphatases and some receptors. Nevertheless, small molecule keys are, generally, not effective for PPI. Filling an enzyme active site with small molecules is feasible, while targeting flat and vast PPI interfaces is not an easy endeavour.

Figure 1. Left: active site of HMG-CoA reductase with simvastatin (1hw9.pdb); Right: Peptide bound to estrogen receptor alpha (2yjA.pdb). The enzyme active site is effectively targeted by a small molecule, while the protein surface of estrogen receptor alpha, which interacts with a high variety of proteins, is targeted with a peptide instead.

 

PPIs participate in many pathways, and therefore, are involved in a considerable number of diseases. The number of PPI in humans is estimated to be 650,000 (1) and around 14,000 of high-quality human binary PPI have been mapped. (2) The potential beneath PPI is huge, and thus, PPI are relevant targets that deserve a specific perspective to be targeted.

 

Figure 2. Interaction of GTPase Ras (orange) and SOS1 (green) (4uru.pdb). Many interaction points participate in the large PPI interface.

 

We already mentioned the limitations that small molecules have in order to confront PPIs. Scientists from all over the world have struggled in order to target them with other strategies. In this line, biologics and peptides emerged as the solution.

Biologics (proteins and antibodies), can cover the vast protein surface. Furthermore, they can be very specific, more than small molecules. Trastuzumab is just an example of monoclonal antibodies used for cancer treatment. It binds to HER2, a membrane protein with tyrosine kinase activity. HER2 intracellular domain is autophosphorylated after dimerization, activating the Ras/MAP kinase pathway which results in the promotion of tumorigenesis. (3) Trastuzumab binds to the HER2 extracellular domain IV avoiding the ligand-independent HER2 dimerization and thus avoiding the Ras/MAP kinase pathway activation.

But not everything in the garden of biologics is rosy. While being large is a positive aspect for PPI, it is the main drawback for cell-membrane or blood-brain barrier permeability and oral bioavailability. Their inability to cross biological membranes hampers their application for intracellular targets, or proteins from the Central Nervous System.

Then, what happens with intracellular PPIs? Small molecules can reach intracellular targets but are not effective against PPI and biologics can modulate PPIs but are not cell-permeable. Is there anything that can control PPIs? Luckily for us, there is a third option.

Peptidomimetics offer the advantages of small molecules (bioavailability and permeability) while can target PPIs, as biologics. On the contrary of peptides, peptidomimetics have higher proteolytic stability and can be fine-tuned for better permeability. While there are several approaches for stability increasing,(4) the permeability improvement is far more intricate. A strategy that has been widely applied is the use of shuttles. However, it’s not the panacea. Some peptide shuttles cross membranes through receptor-mediated endocytosis. This implies a competition with the endogenous ligand that can cause secondary effects. Besides, after being internalized, the peptide might be trapped in vesicles, and thus it would be inactive. Other shuttles create pores in the membrane that can ultimately provoke cell death. Therefore, the implementation of features on peptide-like molecules that can increase permeability is the perfect option for the generation of bioavailable peptidomimetic molecules. These “features” are special moieties and modifications that change the nature of the molecule, making it more likely to cross biological barriers. Though it may seem simple, the pro-permeability adjustment can be a crusade.

A crusade, yes, but not impossible. Only if the permeability rules for peptidomimetics are understood, one may predict which molecules will be permeable.

At Iproteos we have developed a technology that effectively designs potent and bioavailable peptidomimetics. IPROTech is a combination of computational and in vitro techniques that are based on the vast experience of the team in the field of peptidomimetics.

IPROTech has been effectively applied at Iproteos projects and external ones. It is perfect for the generation of novel and customized peptidomimetics for PPIs, and the best part, it actually works! If you have an interesting PPI or “undruggable” target, just contact us. We will analyze your project to show you the potential of IPROTech and how can it help to boost your R&D.

Bibliography

  • Estimating the size of the human interactome (2008); PNAS, 105(19), 6959-6964
  • A proteome-scale map of the human interactome network (2014); Cell,159, 1212-1226
  • Neoadjuvant therapy for early-stage breast cancer: the clinical utility of pertuzumab (2016); Cancer Management and Research, 8, 21-31
  • Peptide-based inhibitors of protein-protein interactions (2016); Bioorg Med Chem Lett., 26(3), 707-713