Biological systems are characterized by complex processes which involves different lengths and time scales. It may start from the transcription of mRNA in order to make proteins, some of them going through a millisecond process denoted as folding into the native structure which is associated with a specific function at the cellular level. Malfunctioning at the molecular level of this process led to several so far irreversible (neurogenerative) diseases. Instead, the understanding of each processes in detail could enable the development of new medical therapies of great relevance in post-COVID-19 era.

My work focuses on the use of advanced molecular dynamics simulation which can bridge the gap between different scales. In order to achieve this goal my team has developed the GōMartini model which is coupled to Martini 3 force field and allows the exploration of large conformational changes in proteins. Our team is embracing new AI ideas, and the use “big data” computational approach to improve the modelling of more complex biomolecules of relevance for biomedical and biotechnological applications.

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In 2020 we uncovered the mechanical stability in the novel SARS-CoV-2 virus by comparing the SARS-CoV (CoV1) and the novel SARS-CoV-2 (CoV2) spike proteins which are part of the COVID-19 pandemic disease via pulling simulations. We learned about the typical forces neeeded for protein rupture in the recognition step. Our findings show an enhancing effect in VoCs[1,2]. This study paved the way for the integration of the mechanical stability into the virus spreading. This result can be employed to devise new strategies against the disease such as repurposing of the drugs [3, 4] to destabilize the spike protein (i.e. RBD) prior to binding to the human ACE2 receptor.

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Boosting plastic degradation via the novel design of an enzymatic complex

The discovery of bacterial and fungal organisms capable of degrading plastics [5] has increasingly attracted the attention of the scientific community, despite their actual low efficiency. The identification of “free enzymes” showing low activity on plastics and secreted extracellularly has established the current paradigm for plastic degradation. Our main task is to radically develop a novel approach to surpass the low degradability of PET plastics. Specifically, rather than persisting in the improvement of free enzyme systems by bioengineering techniques that resemble natural evolution and optimizing enzymes by mutagenesis, we were inspired by other complex nanomachines in nature to investigate a novel paradigm that cannot be obtained by direct evolutionary strategies. Our main focus is on data mining of novel enzyme sequences and plastic recognition via binding modules to enhance the plastic degradation process, which is currently hampered by the recalcitrancy of crystalline regions of the polymer.

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Nanomechanics of protein complexes

We have validated our pulling protocol through the GōMartini approach [6,7] against all-atom MD and experimental data. The results show the transferability of our methodology for different protein-protein complexes. For instance, we show the results for the cellulosome protein complex from the Clostridium thermocellum. This is represented in the panel on the right side where two major protein components: Cohesin (Coh in green) and Dockering (Doc in orange), and the full length complex is the so called, CohE:CttA-XDoc complex from Ruminococcus flavefaciens. It is formed by an Ig-like X-Module (Xmod) adjacent to the scaffold-borne Doc (CttA-XDoc), and the cell-wall anchored Cohesin E (CohE). This complex was shown to resist pulling forces of 500-800 pN at loading rates ranging from 2 to 300 nN/s both experimentally and through our approaches.