Biology subjects

Rapisarda, C.

Publications and source records attributed to Rapisarda, C..

4 recordsLinked to original sources

bioRxiv2026

pH-dependent anti-TfR1 NANOBODY(R) molecules deliver efficacious oligonucleotide payloads to muscle and CNS tissues

The blood-brain barrier (BBB) is a highly selective, semi-permeable border of endothelial cells that prevents solutes and therapeutic agents in systemic circulation from passively crossing into the central nervous system (CNS) parenchyma. The Transferrin receptor 1 (TfR1) endocytosis pathway for iron homeostasis is one of the most well-characterized strategies for therapeutic delivery across the BBB. The work presented here showcases the discovery of novel anti-TfR1 NANOBODY(R) shuttles. The identified anti-TfR1 NANOBODY(R) molecules display cross-reactivity and pH-dependent binding to human, cynomolgus (cyno), and mouse TfR1. Structural data further explain and support the underlying mechanism of this pH-dependent binding. These anti-TfR1 NANOBODY(R) molecules were successfully conjugated to both short-interfering RNA (siRNA) and antisense oligonucleotide (ASO) tool payloads. anti-TfR1 NANOBODY(R)-siRNA conjugates can induce up to 60% knockdown of the target mRNA transcript in skeletal muscle up to two weeks post a single IV dose in mice and up to 35-40% at four weeks post dose. Furthermore, extending the half-life of the anti-TfR1 NANOBODY(R)-ASO shuttles enhances heart, sciatic nerve, and brain exposure and enables up to 30-60% target knockdown in different CNS cell types. Altogether, these results highlight important features for the development of anti-TfR1 shuttles for the purpose of downregulating target mRNA transcripts in muscle and CNS for a variety of neurologic and neuromuscular indications.

neuroscience↗

bioRxiv2023

Finding Antibodies in Cryo-EM densities with CrAI

Therapeutic antibodies have emerged as a prominent class of new drugs due to their high specificity and their ability to bind to several protein targets. Once an initial antibody has been identified, an optimization of this hit compound follows based on the 3D structure, when available. Cryo-EM is currently the most efficient method to obtain such structures, supported by well-established methods that can transform raw data into a potentially noisy 3D map. These maps need to be further interpreted by inferring the number, position and structure of antibodies and other proteins that might be present. Unfortunately, existing automated methods addressing this last step have a limited accuracy and usually require additional inputs, high resolution maps, and exhibit long running times. We propose the first fully automatic and efficient method dedicated to finding antibodies in cryo-EM densities: CrAI. This machine learning approach leverages the conserved structure of antibodies and exploits a dedicated novel database that we built to solve this problem. Running a prediction takes only a few seconds, instead of hours, and requires nothing but the cryo-EM density, seamlessly integrating in automated analysis pipelines. Our method is able to find the location of both Fabs and VHHs, at resolutions up to 10[A] and is significantly more reliable than existing methods. It also provides an accurate estimation of the antibodies pose, even in challenging examples such as Fab binding to VHHs and vice-versa. We make our method available as a ChimeraX[44] bundle. 1

bioinformatics↗

bioRxiv2020

Automatic building of protein atomic models from cryo-EM density maps using residue co-evolution

Electron cryo-microscopy (cryo-EM) has emerged as a powerful method to obtain three-dimensional (3D) structures of macromolecular complexes at atomic or near-atomic resolution. However, de novo building of atomic models from near-atomic resolution (3-5 [A]) cryo-EM density maps is a challenging task, in particular since poorly resolved side-chain densities hamper sequence assignment by automatic procedures at a lower resolution. Furthermore, segmentation of EM density maps into individual subunits remains a difficult problem when no three-dimensional structures of these subunits exist, or when significant conformational changes occur between the isolated and complexed form of the subunits. To tackle these issues, we have developed a graph-based method to thread most of the C- trace of the protein backbone into the EM density map. The EM density is described as a weighted graph such that the resulting minimum spanning tree encompasses the high-density regions of the map. A pruning algorithm cleans the tree and finds the most probable positions of the C- atoms, using side-chain density when available, as a collection of C- trace fragments. By complementing experimental EM maps with contact predictions from sequence co-evolutionary information, we demonstrate that our approach can correctly segment EM maps into individual subunits and assign amino acids sequence to backbone traces to generate full-atom models.

bioinformatics↗

bioRxiv2018

In situ and high-resolution Cryo-EM structure of the Type VI secretion membrane complex

Bacteria have evolved macromolecular machineries that secrete effectors and toxins to survive and thrive in diverse environments. The type VI secretion system (T6SS) is a contractile machine that is related to Myoviridae phages. The T6SS is composed of a baseplate that contains a spike onto which an inner tube is built, surrounded by a contractile sheath. Unlike phages that are released to and act in the extracellular medium, the T6SS is an intracellular machine inserted in the bacterial membranes by a trans-envelope complex. This membrane complex (MC) comprises three proteins: TssJ, TssL and TssM. We previously reported the low-resolution negative stain electron microscopy structure of the enteroaggregative Escherichia coli MC and proposed a rotational 5-fold symmetry with a TssJ:TssL:TssM stoichiometry of 2:2:2. Here, cryo-electron tomography analysis of the T6SS MC confirmed the 5-fold symmetry in situ and identified the regions of the structure that insert into the bacterial membranes. A high resolution model obtained by single particle cryo-electron microscopy reveals its global architecture and highlights new features: five additional copies of TssJ, yielding a TssJ:TssL:TssM stoichiometry of 3:2:2, a 11-residue loop in TssM, protruding inside the lumen of the MC and constituting a functionally important periplasmic gate, and hinge regions. Based on these data, we revisit the model on the mechanism of action of the MC during T6SS assembly and function.

microbiology↗