Protein structure prediction and refinement

Over the last few years it has been shown that protein modelling techniques, especially template based modelling, are now accurate enough for qualitative analysis and decision-making in support of a wide range of experimental work. Automatic protein modelling pipelines are becoming ever more accurate; however, this has come hand in hand with an increasingly complicated interplay between all components involved. Despite all progress, still important problems remain and so far computational methods cannot routinely meet the accuracy of experimentally determined protein structures. In protein modelling pipelines, several important steps dictate a model's quality. Selecting a good template and aligning the query sequence correctly, backbone completion, model refinement and final model selection are considered the main steps. As a first step to approach protein refinement, a genetic algorithm (GA) for protein model recombination and optimization is presented in this work. This algorithm has the potential, to drive models away from the template towards the native structure. Furthermore, a complete and novel modelling pipeline, incorporating this GA is presented. In this context, a new scoring scheme, backbone repair algorithm and several other findings are reported and presented: We introduce the novel concept of Alternating Evolutionary Pressure, i.e. intermediate rounds within the GA simulation, where unrestrained linear growth of the model population is allowed. This approach improves the structural sampling and thereby facilitates energy-based model selection. Finally, the GA in combination with molecular dynamics simulations is used in the context of protein engineering. Several mutants were identified to stabilise and increase the activity of the cancer drug L-Asparaginase, a complex enzyme. The successful prediction of these mutations stresses the importance of protein molecular modelling for cell biology and in a clinical context

Acute myeloid leukaemia niche regulates response to L-asparaginase

Eradicating the malignant stem cell is the ultimate challenge in the treatment of leukaemia. Leukaemic stem cells (LSC) hijack the normal haemopoietic niche, where they are mainly protected from cytotoxic drugs. The anti‐leukaemic effect of L‐asparaginase (ASNase) has been extensively investigated in acute lymphoblastic leukaemia, but only partially in acute myeloid leukaemia (AML). We explored the susceptibility of AML‐LSC to ASNase as well as the role of the two major cell types that constitute the bone marrow (BM) microenvironment, i.e., mesenchymal stromal cells (MSC) and monocytes/macrophages. Whilst ASNase was effective on both CD34+CD38+ and CD34+CD38− LSC fractions, MSC and monocytes/macrophages partially counteracted the effect of the drug. Indeed, the production of cathepsin B, a lysosomal cysteine protease, by BM monocytic cells and by AML cells classified as French‐American‐British M5 is related to the inactivation of ASNase. Our work demonstrates that, while MSC and monocytes/macrophages may provide a protective niche for AML cells, ASNase has a cytotoxic effect on AML blasts and, importantly, LSC subpopulations. Thus, these features should be considered in the design of future clinical studies aimed at testing ASNase efficacy in AML patients