Structural determinants of peptide-dependent TAP1-TAP2 transit passage targeted by viral proteins and altered by cancer-associated mutations

The TAP1-TAP2 complex transports antigenic peptide substrates into the endoplasmic reticulum (ER). In ER, the peptides are further processed and loaded on the major histocompatibility class (MHC) I molecules by the peptide loading complex (PLC). The TAP transporters are linked with the PLC; a target for cancers and viral immune evasion. But the mechanisms whereby the cancer-derived mutations in TAP1-TAP2 or viral factors targeting the PLC, interfere peptide transport are only emerging. This study describes that transit of peptides through TAP can take place via two different channels (4 or 8 helices) depending on peptide length and sequence. Molecular dynamics and binding affinity predictions of peptide-transporters demonstrated that smaller peptides (8–10 mers; e.g. AAGIGILTV, SIINFEKL) can transport quickly through the transport tunnel compared to longer peptides (15-mer; e.g. ENPVVHFFKNIVTPR). In line with a regulated and selective peptide transport by TAPs, the immunopeptidome upon IFN-γ treatment in melanoma cells induced the shorter length (9-mer) peptide presentation over MHC-I that exhibit a relatively weak binding affinity with TAP. A conserved distance between N and C terminus residues of the studied peptides in the transport tunnel were reported. Furthermore, by adversely interacting with the TAP transport passage or affecting TAPNBD domains tilt movement, the viral proteins and cancer-derived mutations in TAP1-TAP2 may induce allosteric effects in TAP that block conformation of the tunnel (closed towards ER lumen). Interestingly, some cancer-associated mutations (e.g. TAP1R372Q and TAP2R373H) can specifically interfere with selective transport channels (i.e. for longer-peptides). These results provide a model for how viruses and cancer-associated mutations targeting TAP interfaces can affect MHC-I antigen presentation, and how the IFN-γ pathway alters MHC-I antigen presentation via the kinetics of peptide transport

In silico-in vitro screening of protein-protein interactions: towards the next generation of therapeutics.

International audienceProtein-protein interactions (PPIs) have a pivotal role in many biological processes suggesting that targeting macromolecular complexes will open new avenues for the design of the next generation of therapeutics. A wide range of "in silico methods" can be used to facilitate the design of protein-protein modulators. Among these methods, virtual ligand screening, protein-protein docking, structural predictions and druggable pocket predictions have become established techniques for hit discovery and optimization. In this review, we first summarize some key data about protein-protein interfaces and introduce some recently reported computer methods pertaining to the field. URLs for several recent free packages or servers are also provided. Then, we discuss four studies aiming at developing PPI modulators through the combination of in silico and in vitro screening experiments

Highly Conserved Homotrimer Cavity Formed by the SARS-CoV-2 Spike Glycoprotein: A Novel Binding Site

An important stage in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) life cycle is the binding of the spike (S) protein to the angiotensin converting enzyme-2 (ACE2) host cell receptor. Therefore, to explore conserved features in spike protein dynamics and to identify potentially novel regions for drugging, we measured spike protein variability derived from 791 viral genomes and studied its properties by molecular dynamics (MD) simulation. The findings indicated that S2 subunit (heptad-repeat 1 (HR1), central helix (CH), and connector domain (CD) domains) showed low variability, low fluctuations in MD, and displayed a trimer cavity. By contrast, the receptor binding domain (RBD) domain, which is typically targeted in drug discovery programs, exhibits more sequence variability and flexibility. Interpretations from MD simulations suggest that the monomer form of spike protein is in constant motion showing transitions between an “up” and “down” state. In addition, the trimer cavity may function as a “bouncing spring” that may facilitate the homotrimer spike protein interactions with the ACE2 receptor. The feasibility of the trimer cavity as a potential drug target was examined by structure based virtual screening. Several hits were identified that have already been validated or suggested to inhibit the SARS-CoV-2 virus in published cell models. In particular, the data suggest an action mechanism for molecules including Chitosan and macrolides such as the mTOR (mammalian target of Rapamycin) pathway inhibitor Rapamycin. These findings identify a novel small molecule binding-site formed by the spike protein oligomer, that might assist in future drug discovery programs aimed at targeting the coronavirus (CoV) family of viruses

The immunopeptidome from a genomic perspective:Establishing the noncanonical landscape of MHC class I–associated peptides

G.B., D.B., K.W., A.P., R.F., T.R.H., S.K., and J.A.A. received support from Fundacja na rzecz Nauki Polskiej (FNP) (grant ID: MAB/3/2017). D.R.G. received support from Genome Canada & Genome BC (grant ID: 264PRO). D.J.H. received support from NuCana plc (grant ID: SMD0-ZIUN05). H.A. received support from Swedish Cancer Foundation (grant ID: 211709). H.G. received support from United Kingdom Research and Innovation (UKRI) (grant ID: EP/S02431X/1). C.P. received support from Fundação para a Ciência e a Tecnologia (FCT) through LASIGE Research Unit (grant ID: UIDB/00408/2020 and UIDP/00408/2020). A.L. F.M.Z., C.P., A.R., A.P., and J.A.A. received support from European Union’s Horizon 2020 research and innovation programme (grant ID: 101017453). C.B. received support from Agence Nationale de la Recherche (ANR) through GRAL LabEX (grant ID: ANR-10-LABX-49-01) and CBH-EUR-GS 32 (grant ID: ANR-17-EURE0003). S.N.S. received support from Cancer Research UK (CRUK) and the Chief Scientist's Office of Scotland (CSO): Experimental Cancer Medicine Centre (ECMC) (grant ID: ECMCQQR-2022/100017). A.L. received support from Chief Scientist's Office of Scotland (CSO) NRS Career Researcher Fellowship. R.O.N. received support from CRUK Cambridge Centre Thoracic Cancer Programme (grant ID: CTRQQR-2021\100012).Tumor antigens can emerge through multiple mechanisms, including translation of non-coding genomic regions. This non-canonical category of antigens has recently gained attention; however, our understanding of how they recur within and between cancer types is still in its infancy. Therefore, we developed a proteogenomic pipeline based on deep learning de novo mass spectrometry to enable the discovery of non-canonical MHC-associated peptides (ncMAPs) from non-coding regions. Considering that the emergence of tumor antigens can also involve post-translational modifications, we included an open search component in our pipeline. Leveraging the wealth of mass spectrometry-based immunopeptidomics, we analyzed 26 MHC class I immunopeptidomic studies of 9 different cancer types. We validated the de novo identified ncMAPs, along with the most abundant post-translational modifications, using spectral matching and controlled their false discovery rate (FDR) to 1%. Interestingly, the non-canonical presentation appeared to be 5 times enriched for the A03 HLA supertype, with a projected population coverage of 54.85%. Here, we reveal an atlas of 8,601 ncMAPs with varying levels of cancer selectivity and suggest 17 cancer-selective ncMAPs as attractive targets according to a stringent cutoff. In summary, the combination of the open-source pipeline and the atlas of ncMAPs reported herein could facilitate the identification and screening of ncMAPs as targeting agents for T-cell therapies or vaccine development.Publisher PDFPeer reviewe

Epstein Barr Virus-Encoded EBNA1 Interference with MHC Class I Antigen Presentation Reveals a Close Correlation between mRNA Translation Initiation and Antigen Presentation

Viruses are known to employ different strategies to manipulate the major histocompatibility (MHC) class I antigen presentation pathway to avoid recognition of the infected host cell by the immune system. However, viral control of antigen presentation via the processes that supply and select antigenic peptide precursors is yet relatively unknown. The Epstein-Barr virus (EBV)-encoded EBNA1 is expressed in all EBV-infected cells, but the immune system fails to detect and destroy EBV-carrying host cells. This immune evasion has been attributed to the capacity of a Gly-Ala repeat (GAr) within EBNA1 to inhibit MHC class I restricted antigen presentation. Here we demonstrate that suppression of mRNA translation initiation by the GAr in cis is sufficient and necessary to prevent presentation of antigenic peptides from mRNAs to which it is fused. Furthermore, we demonstrate a direct correlation between the rate of translation initiation and MHC class I antigen presentation from a certain mRNA. These results support the idea that mRNAs, and not the encoded full length proteins, are used for MHC class I restricted immune surveillance. This offers an additional view on the role of virus-mediated control of mRNA translation initiation and of the mechanisms that control MHC class I restricted antigen presentation in general

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com

Etude des mécanismes moléculaires permettant à la protéine EBNA1 du virus Epstein-Barr d'échapper au système immunitaire

PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF

L' inter-régulation des protéines p53, Mdm2 et Mdmx

PARIS7-Bibliothèque centrale (751132105) / SudocPARIS-BIUP (751062107) / SudocSudocFranceF