8S2E

Fab4251-DS-SOSIP complex

This is a non-PDB format compatible entry.

Summary for 8S2E

• Entry DOI: 10.2210/pdb8s2e/pdb
• EMDB information: 19665
• Descriptor: variable heavy chain, variable light chain, Envelope glycoprotein gp120, ... (8 entities in total)
• Functional Keywords: hiv, viral protein
• Biological source: Homo sapiens; More
• Total number of polymer chains: 8
• Total formula weight: 256159.29

Authors

Nortier, P.,Perez, L. (deposition date: 2024-02-17, release date: 2024-07-03, Last modification date: 2024-11-06)

Primary citation

Perez, L.,Foglierini, M.
RAIN: a Machine Learning-based identification for HIV-1 bNAbs.
Res Sq, 2024

PubMed Abstract: Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infection. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoire is still lacking. Here, we developed a straightforward computational method for apid utomatic dentification of bAbs ) based on Machine Learning methods. In contrast to other approaches using one-hot encoding amino acid sequences or structural alignment for prediction, RAIN uses a combination of selected sequence-based features for accurate prediction of HIV-1 bNAbs. We demonstrate the performance of our approach on non-biased, experimentally obtained sequenced BCR repertoires from HIV-1 immune donors. RAIN processing leads to the successful identification of novel HIV-1 bNAbs targeting the CD4-binding site of the envelope glycoprotein. In addition, we validate the identified bNAbs using neutralization assay and we solve the structure of one of them in complex with the soluble native-like heterotrimeric envelope glycoprotein by single-particle cryo-electron microscopy (cryo-EM). Overall, we propose a method to facilitate and accelerate HIV-1 bNAbs discovery from non-selected immune repertoires.

PubMed: 38903123
DOI: 10.21203/rs.3.rs-4023897/v1

Experimental method

ELECTRON MICROSCOPY (3.8 Å)