Biology subjects

Orioli, S.

Publications and source records attributed to Orioli, S..

9 recordsLinked to original sources

bioRxiv2025

Production of high-affinity glycosylated anti-mouse conjugated nanobodies in Pichia pastoris

Nanobodies (NBs) are small antibody fragments derived from camelid heavy-chain antibodies which represent the minimal functional domain capable of antigen recognition and binding. NB are ten times smaller than conventional antibodies, exhibit a compact structure and high stability, making them ideal for recombinant production. The eukaryotic unicellular system Pichia pastoris provides multiple advantages for protein expression, including the ability to perform several eukaryotic posttranslational modifications. In this work, we engineered a modular plasmid sequence that, through specific restriction enzyme cuts and ligations, codes the expression of a secreted anti-mouse kappa chain NB fused with various accessory peptides in P. pastoris. This system enables the incorporation of a plastic binding sequence, a histidine tag (Hisx6) for purification, the horseradish peroxidase (HRP) enzyme for chemiluminescence detection, or the biotinylatable AviTag sequence, in multiple combinations. We successfully expressed and purified anti-kappa NBs fused to a Hisx6-tag ({kappa}NB) and to HRP -Hisx6-tag ({kappa}NB-HRP), with subsequent structural and functional characterization revealing high affinity for mouse immunoglobulins. The {kappa}NB-kappa light chain domain complex was modeled showing a fitted surface interaction of CDR3 domain. The position of a glycan in the complex was modeled predicting that glycan addition would not affect the interaction surface. Accordingly, no functional differences were observed in {kappa}NB after deglycosylation, indicating that high mannose glycan addition has not interfered with its binding capability. Moreover, glycosylated {kappa}NB fused to HRP was expressed with retained HRP activity, and proved to be functional as a secondary antibody, demonstrating the systems versatility in producing NBs and conjugated NBs with posttraslational modification that may be required for diverse biotechnological applications.

molecular biology↗

bioRxiv2025

A Bayesian approach to interpret time-resolved experiments using molecular simulations

Time-resolved experiments can provide unique insights into dynamical processes such as protein folding, ligand binding, and many other molecular processes. These experiments are, however, difficult to interpret at the molecular level because they generally report on signals that are averaged over multiple configurational states, and because they often report on processes that are well beyond what can be studied using most simulation methods. Here we describe an approach to use molecular simulations to model and interpret time-resolved experiments. The method, which we term trBME (time-resolved Bayesian/Maximum Entropy), is based on combining a model for the dynamics of the system, with 3D structural models of the protein that can be compared to the experiments. We illustrate the utility of the model using synthetic time-resolved small-angle X-ray scattering data and show how it can be used to extract detailed information from the experimental data on the process of protein unfolding.

biophysics↗

bioRxiv2023

Fitting Force Field parameters to NMR Relaxation Data

We present an approach to optimise force field parameters using time-dependent data from NMR relaxation experiments. To do so, we scan parameters in the dihedral angle potential energy terms describing the rotation of the methyl groups in proteins, and compare NMR relaxation rates calculated from molecular dynamics simulations with the modified force fields to deuterium relaxation measurements of T4 lysozyme. We find that a small modification of C{gamma} methyl groups improves the agreement with experiments both for the protein used to optimize the force field, and when validating using simulations of CI2 and ubiquitin. We also show that these improvements enable a more effective a posteriori reweighting of the MD trajectories. The resulting force field thus enables more direct comparison between simulations and side-chain NMR relaxation data, and makes it possible to construct ensembles that better represent the dynamics of proteins in solution.

biophysics↗

bioRxiv2021

Double mutant of chymotrypsin inhibitor 2 stabilized through increased conformational entropy

The conformational heterogeneity of a folded protein can affect both its function but also stability and folding. We recently discovered and characterized a stabilized double mutant (L49I/I57V) of the protein CI2 and showed that state-of-the-art prediction methods could not predict the increased stability relative to the wild-type protein. Here we have examined whether changed native state dynamics, and resulting entropy changes, can explain the stability changes in the double mutant protein, as well as the two single mutant forms. We have combined NMR relaxation measurements of the ps-ns dynamics of amide groups in the backbone and the methyl groups in the side-chains with molecular dynamics simulations to quantify the native state dynamics. The NMR experiments reveal that the mutations have different effects on the conformational flexibility of CI2: A reduction in conformational dynamics (and entropy) of the native state of L49I variant correlates with its decreased stability, while increased dynamics of the I57V and L49I/I57V variants correlates with their increased stability. These findings suggest that explicitly accounting for changes in native state entropy might be needed to improve the predictions of the effect of mutations on protein stability.

biophysics↗

bioRxiv2021

Transient exposure of a buried phosphorylation site in an autoinhibited protein

Autoinhibition is a mechanism used to regulate protein function, often by making functional sites inaccessible through the interaction with a cis-acting inhibitory domain. Such autoinhibitory domains often display a substantial degree of structural disorder when unbound, and only become structured in the inhibited state. This conformational dynamics makes it difficult to study the structural origin of regulation, including effects of regulatory post-translational modifications. Here, we study the autoinhibition of the Dbl Homology domain in the protein Vav1 by the so-called acidic inhibitory domain. We use molecular simulations to study the process by which a mostly unstructured inhibitory domain folds upon binding and how transient exposure of a key buried tyrosine residue makes it accessible for phosphorylation. We show that the inhibitory domain, which forms a helix in the bound and inhibited stated, samples helical structures already before binding and that binding occurs via a molten-globule-like intermediate state. Together, our results shed light on key interactions that enable the inhibitory domain to sample a finely-tuned equilibrium between an inhibited and a kinase-accessible state.

biophysics↗

bioRxiv2020

Ab-initio determination of the shape of membrane proteins in a nanodisc

We introduce a new software, called Marbles, that employs SAXS intensities to predict the shape of membrane proteins embedded into membrane nanodiscs. To gain computational speed and efficient convergence, the strategy is based on a hybrid approach that allows one to account for the nanodisc contribution to the SAXS intensity through a semi-analytical model, while the embedded membrane protein is treated as set of beads, similarly to well known ab-initio methods. The code, implemented in C++ with a Python user interface, provides a good performance and includes the possibility to systematically treat unstructured domains. We prove the reliability and flexibility of our approach by benchmarking the code on a toy model and two proteins of very different geometry and size.

biophysics↗

bioRxiv2020

Fitting side-chain NMR relaxation data using molecular simulations

Proteins display a wealth of dynamical motions that can be probed using both experiments and simulations. We present an approach to integrate side chain NMR relaxation measurements with molecular dynamics simulations to study the structure and dynamics of these motions. The approach, which we term ABSURDer (Average Block Selection Using Relaxation Data with Entropy Restraints) can be used to find a set of trajectories that are in agreement with relaxation measurements. We apply the method to deuterium relaxation measurements in T4 lysozyme, and show how it can be used to integrate the accuracy of the NMR measurements with the molecular models of protein dynamics afforded by the simulations. We show how fitting of dynamic quantities leads to improved agreement with static properties, and highlight areas needed for further improvements of the approach.

biophysics↗

bioRxiv2020

PHARMACOLOGICAL PROTEIN INACTIVATION BY TARGETING FOLDING INTERMEDIATES

Recent computational advancements in the simulation of biochemical processes allow investigating the mechanisms involved in protein regulation with realistic physics-based models, at an atomistic level of resolution. Using these techniques to study the negative regulation of the androgen receptor (AR), we discovered a key functional role played by non-native metastable states appearing along the folding pathway of this protein. This unexpected observation inspired us to design a completely novel drug discovery approach, named Pharmacological Protein Inactivation by Folding Intermediate Targeting (PPI-FIT), based on the rationale of negatively regulating protein expression by targeting folding intermediates. Here, PPI-FIT was tested for the first time on the cellular prion protein (PrP), a cell surface glycoprotein playing a key role in fatal and transmissible neurodegenerative pathologies known as prion diseases. We predicted the all-atom structure of an intermediate appearing along the folding pathway of PrP, and identified four different small molecule ligands for this conformer, all capable of selectively lowering the expression of the protein by promoting its degradation. Our data support the notion that the level of target proteins could be modulated by acting on their folding pathways, implying a previously unappreciated role for folding intermediates in the biological regulation of protein expression.

biochemistry↗

bioRxiv2018

Full Atomistic Model Of Prion Structure And Conversion

Prions are unusual protein assemblies that propagate their conformationally-encoded information in absence of nucleic acids. The first prion identified, the scrapie isoform (PrPSc) of the cellular prion protein (PrPC), is the only one known to cause epidemic and epizootic episodes(1). Most aggregates of other misfolding-prone proteins are amyloids, often arranged in a Parallel-In-Register-{beta}-Sheet (PIRIBS)(2) or {beta}-solenoid conformations(3). Similar folding models have also been proposed for PrPSc, although none of these have been confirmed experimentally. Recent cryo-electron microscopy (cryo-EM) and X-ray fiber-diffraction studies provided evidence that PrPSc is structured as a 4-rung {beta}-solenoid (4R{beta}S)(4, 5). Here, we combined different experimental data and computational techniques to build the first physically-plausible, atomic resolution model of mouse PrPSc, based on the 4R{beta}S architecture. The stability of this new PrPSc model, as assessed by Molecular Dynamics (MD) simulations, was found to be comparable to that of the prion forming domain of Het-s, a naturally-occurring {beta}-solenoid. Importantly, the 4R{beta}S arrangement allowed the first simulation of the sequence of events underlying PrPC conversion into PrPSc. Our results provide the most updated, experimentally-driven and physically-coherent model of PrPSc, together with an unprecedented reconstruction of the mechanism underlying the self-catalytic propagation of prions.\n\nSignificanceSince the original hypothesis by Stanley Prusiner, prions have represented enigmatic agents diverging from the classical concept of genetic inheritance. However, the structure of PrPSc, the infectious isoform of the cellular prion protein (PrPC), has so far remained elusive, mostly due to technical challenges posed by its aggregation propensity. Here, we present a new high resolution model of PrPSc derived from the integration of a wide array of recent experimental constraints. By coupling the information of such model with a newly developed computational method, we reconstructed for the first time the conformational transition of PrPC to PrPSc. This study offers a unique workbench for designing therapeutics against prion diseases, and a physically-plausible mechanism explaining how protein conformation could self-propagate.

biochemistry↗