Geris, L. | Search bioRxiv

bioRxiv2021

An integrated in silico-in vitro approach for identification of therapeutic drug targets for osteoarthritis

Without the availability of disease-modifying drugs, there is an unmet therapeutic need for osteoarthritic patients. During osteoarthritis, the homeostasis of articular chondrocytes is dysregulated and a phenotypical transition called hypertrophy occurs, leading to cartilage degeneration. Targeting this phenotypic transition has emerged as a potential therapeutic strategy. Chondrocyte phenotype maintenance and switch are controlled by an intricate network of intracellular factors, each influenced by a myriad of feedback mechanisms, making it challenging to intuitively predict treatment outcomes. In this study, we developed a regulatory network model using knowledge-based and data-driven modelling technologies. The in silico high-throughput screening of (pairwise) perturbations operated with that network model highlighted conditions impacting the hypertrophic switch. Several combinations were tested in a murine cell line and primary chondrocytes to validate the predicted conditions potential. Our in silico-in vitro strategy opens a new route for developing osteoarthritis targeting therapies by refining the early stages of drug discovery.

systems biology↗

bioRxiv2020

Ribosome Exit Tunnel Electrostatics

The impact of the ribosome exit tunnel electrostatics on the protein elongation rate or on the forces acting upon the nascent polypeptide chain are currently not fully elucidated. In the past, researchers have measured the electrostatic potential inside the ribosome polypeptide exit tunnel at a limited number of spatial points, at least in prokaryotes. Here, we present a basic electrostatic model of the exit tunnel of the ribosome, providing a quantitative physical description of the tunnel interaction with the nascent proteins at all centro-axial points inside the tunnel. We show how the tunnel geometry causes a positive potential difference between the tunnel exit and entry points which impedes positively charged amino acid residues from progressing through the tunnel, affecting the elongation rate in a range of minus 40% to plus 85% when compared to the average elongation rate. The time spent by the ribosome to decode the genetic encrypted message is constrained accordingly. We quantitatively derived, at single residue resolution, the axial forces acting on the nascent peptide from its particular sequence embedded in the tunnel. The model sheds light on how the experimental data point measurements of the potential are linked to the local structural chemistry of the inner wall and the shape and size of the tunnel. The model consistently connects experimental observations coming from different fields in molecular biology, structural and physical chemistry, biomechanics, synthetic and multi-omics biology. Our model should be a valuable tool to gain insight into protein synthesis dynamics, translational control and into the role of the ribosomes mechanochemistry in the co-translational protein folding.

biophysics↗