Bringing the idea of integrating manmade oxidoreductases and allied proteins into cell and organelle to replace or augment component parts of metabolic and bioenergetic machinery, has some way to go to before benefit to mankind can be expected. Nevertheless, once realized, the impact on solar energy conversion into chemical fuels, on remediating hemorrhagic traumas, or on correcting respiratory dysfunction of genetic or aging origins will be considerable. We combine first-principles light- and oxidant/reductant substrate-driven electron transfer engineering common to natural oxidoreductase proteins with first-principles α-helical protein design to reproduce oxidoreductase and related functions in structurally transparent man-made proteins we call maquettes. Maquettes promote diverse natural functions including light-capture and multistep energy transfer and efficient charge-separation, diffusive inter-protein electron-transfer, and O2 ligation and transport. Maquettes prove to be biocompatible: bacterial expression is coupled with biogenesis and ligation of cofactors such as hemes B and C, bilins and indications of chlorophyll. Maquettes can be…

Protein-protein interactions are of fundamental importance in virtually all cellular processes. Our group has focused on the analysis and prediction of these interactions through the combined use of structural data and evolutionary information. In a study of over 1,000 couples of homologous interfaces, we uncovered astonishing plasticity in the way interface structure evolves. We also identified some rather invariant features which provide tracks for extracting meaningful information from multiple sequence alignments of binding partners. On these bases, we developed a protein docking method which improves the prediction of protein interfaces and was used in a number of protein docking cases related to the maintenance of genome stability. Understanding how interfaces co-evolve opens new perspectives for the design of novel protein binders which we shall also discussed.

In living related kidney transplant recipients, current strategies to improve graft outcome consider information at the HLA locus. Given that more than 50 % of fully HLA matched kidneys fail at 10 years post-transplant, we investigated whether information outside of the HLA locus can also impact long-term graft function (LTGF). We used a new method using DNA exome sequencing from kidney graft recipients (R) and their living donors (D) to determine R/D mismatches at the amino acid level over entire exomes. We estimated the number of amino acid mismatches in transmembrane proteins, more likely to be recognized as foreign by the recipient's immune system, and designated this tally as the allogenomics mismatch score (AMS). The AMS can be measured prior to transplantation for potential donor and recipient pairs and could be used in graft attribution algorithms. We examined the degree of relationship between the AMS and post-transplantation kidney allograft function using mixed…

Cancer cells are highly proliferative. Drugs that impair cell proliferation – antimitotic drugs – are indeed quite effective in treating cancer. Their mechanism of action is quite well understood. Several antimitotic drugs impair microtubule polymerization and thus do not allow cells to segregate their chromosomes. Cells arrested in their division cycle, however, will not remain arrested forever. Some will die and some will adapt resuming proliferation. The choice between these two fates is stochastic, with virtually identical cells going different paths. With a combination of mathematical models and live-cell imaging, we have analyzed the phenomenon of adaptation, and we have identified a possible source of variability that contributes to determine cell fate under constant drug treatment.

DNA damage and ensuing DNA damage response activation are key players in tumor suppression and ageing. I will discuss how DDR impacts on them and on the biology of stem cells. Finally, I will propose a novel and unprecedented role of non-coding RNAs in the modulation of the DNA damage response.

Predictive understanding of signaling network kinetics is essential for design of rational intervention strategies in diseases. However, inference of network parameters, such as reaction rates and species abundances, that govern intracellular signaling network dynamics is challenging due to parameter non-identifiability and cell-to-cell variability. We present a maximum entropy (ME) inference of the joint probability distribution over network parameters that reproduces snapshots of cell to cell variability in species abundances measured at multiple time points. We studied a network implicated in many diseases; phosphorylation of protein kinase B (Akt, pAkt) via the EGF/EGFR pathway. Our framework combined with experimental data on cell-to-cell variability in pAkt abundances allowed us to computationally reconstruct the experimentally inaccessible ensemble of trajectories of intracellular pAkt dynamics. Using the ensemble of trajectories, we could predict the fraction of cells that entered the cell cycle after prolonged exposure to EGF. The analysis allowed us explore sub-populations of cells that failed…

Membrane proteins (MPs) are abundant important functional proteins and as such they represent more than 60% of drug targets. However, experimentally, the fine characterisation of their structure and function is made difficult by the environment in which they are embedded. Dedicated bioinformatics methods and specific molecular simulations approaches are thus required to gain relevant information. I will discuss recent progresses made in our team in the development of structural bioinformatics methods for MPs. I will also illustrate the power and limits of molecular dynamics simulations to explore transport properties and conformational changes of MPs