The Biocrystal Facility, a large multidisciplinary laboratory established at the Institute of Molecular Biology and Pathology (IBPM) of CNR, in collaboration with the Biochemistry Department of Sapienza University aims at supporting the italian scientists and the pharmaceutical companies in the research to find new drug and vaccine against the endemic and epidemic diseases through structure-based drug design.
Technologies
In this section it is possible to view, also through targeted research, the technologies inserted in the PROMO-TT Database. For further information on the technologies and to contact the CNR Research Teams who developed them, it is necessary to contact the Project Manager (see the references at the bottom of each record card).
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The final technology will add polarimetric capability to imaging cameras in the NUV/optical, providing simultaneous measurements of the different polarization states of the light. This will be obtained by the development of an innovative coating based on nanostructured emissive materials sensitive to the polarization of the incident light. A double layer film of two organic systems will be coupled to image detectors so that the two polarization components of the incoming light are converted into two different colors.
The assessment of bio-humoral markers beyond clinical evaluation would allow a more comprehensive pheno/endotyping of patients affected by chronic inflammatory diseases. Therapy personalization would require a profile of the mediators that are relevant in the disease pathogenesis and that well correlate with prognosis. Currently, the measurement of multiple biomarkers is not included in patient evaluation because it has high costs, requires centralized laboratories, experienced personnel and bulky equipment and is time-consuming.
The virtual dynamic docking, carried out in the MOLBD3 lab of the Institute of Biophysics, allows the identification of new drugs through the structural information deriving from the study of target proteins, responsible for some human pathologies. In particular, we screen drugs or small molecules (commercial/own libraries) against known protein sites, surface cavities, surfaces of protein-protein interactions (fixed/rigid hotspots) or structural transition states (dynamic hotspots).
Inert biomedical devices with modular load-bearing function designed with peculiar multi-domain composite microstructures. The reference compositional system is Zirconia-Alumina with a prevailing overall composition of customizable zirconia or alumina. Examples of devices are 3D structures consisting of parts with differentiated functional properties, due to different composition/microstructure/architecture, and further functionalizable ex-post to favor and improve the stabilization of the implantation by newly formed bone in superior quantity and quality.
In the last years, genetics played a strategic role in the identification of therapeutic targets for complex diseases. Genetic studies identified thousands of variants contributing to disease onset and/or to the influence of measurable features (phenotypes) impacting health. The mechanism of action by which they modulate diseases and phenotypes is still unknown for the vast majority.
Integrative omics has posed new challenges in modern precision medicine, particularly in oncology, including i) the identification of new tumor markers for early, precise, and non-invasive diagnostics, and ii) the discovery of innovative molecular targets for therapeutic applications. Our studies on medulloblastoma, a highly malignant childhood tumor, have contributed to identifying RNA molecules that meet these criteria.
The aim of the research group is the creation of 3D models (microorgan/ organoids) constructed using samples obtained from patients, both biopsy samples and samples collected with non-invasive techniques (exhaled breath condensate, induced sputum, blood samples).
We have identified the presence of the poorly characterized precursor proNGF-A in human tissues, deposited its coding nucleotide sequence (GenBank MH358394) and demonstrated its neuroprotective and neurotrophic activity in vitro and in vivo. We inserted mutations into the native molecule, identified through computational analysis, which allow proNGF-A production by eukaryotic expression systems, through a method currently validated on a laboratory scale.
We have identified compounds that show a neuroprotective action in vivo, in models of neurodegenerative diseases (e.g. SMA, Parkinson, Alzheimer, Huntington) in the model organism C. elegans. These compounds consist of: mixtures of 22 natural extracts, 15 natural molecules and 11 synthetic molecules.
Solid State Nuclear Magnetic Resonance spectroscopy (SSNMR) is today one of the most powerful techniques for characterizing solid and soft materials and systems. This spectroscopy allows the detailed characterization of structural and dynamic properties over large spatial (0.1-100 nm) and time (102-10-11 s) scales. Accessing these properties allows a deep knowledge of a material to be obtained and its design and optimization to be oriented.
Plants can compete favorably with traditional expression systems (mammalian cells, yeasts or bacteria) to produce recombinant proteins/peptides of pharmaceutical/industrial/agrifood interest. This technology names “Plant Molecular Farming”. The CNR-IBBA research team offers the study of new strategies for the expression and optimization of recombinant proteins/peptides in plant-based systems (plant tissues, transgenic plants, plant cell culture). Our pipeline is based on the following modules:
SITODIET is an innovative software that supports a translational approach to health’s state. It integrates various sources of physiological, behavioral, and psychological data to reduce the risks associated with the onset of lifestyle-related diseases (primary prevention), to support health professionals in early diagnosis (secondary prevention) or to manage the personalized therapy’s patient (tertiary prevention). SITODIETcollects data automatically, through actigraphy tools, as wristband or smartwatch, or manually