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Computational design of fusion proteins against ErbB2-amplified tumors inspired by ricin toxin.

ABSTRACT: Although the anti-cancer activity of ricin is well-known, its non-specific targeting challenges the development of ricin-derived medicines. In the present study, novel potential ribosome-inactivating fusion proteins (RIPs) were computationally engineered by incorporation of an ErbB2-dependant penetrating peptide (KCCYSL, MARAKE, WYSWLL, MARSGL, MSRTMS, and WYAWML), a linker (either EAAAK or GGGGS) and chain A of ricin which is responsible for the ribosome inactivation. Molecular dynamics simulations assisted in making sure that the least change is made in conformation and dynamic behavior of ricin chain A in selected chimeric protein (CP). Moreover, the potential affinity of the selected CPs against the ligand-uptaking ErbB2 domain was explored by molecular docking. The results showed that two CPs (CP2 and 10) could bind the receptor with the greatest affinity.

SUBMITTER: Ahmadi Moghaddam Y

PROVIDER: S-EPMC10018397 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Computational design of fusion proteins against ErbB2-amplified tumors inspired by ricin toxin.

Ahmadi Moghaddam Yasser Y Maroufi Asad A Zareei Sara S Irani Mehdi M

Frontiers in molecular biosciences 20230302

Although the anti-cancer activity of ricin is well-known, its non-specific targeting challenges the development of ricin-derived medicines. In the present study, novel potential ribosome-inactivating fusion proteins (RIPs) were computationally engineered by incorporation of an ErbB2-dependant penetrating peptide (KCCYSL, MARAKE, WYSWLL, MARSGL, MSRTMS, and WYAWML), a linker (either EAAAK or GGGGS) and chain A of ricin which is responsible for the ribosome inactivation. Molecular dynamics simulat ...[more]

PMID: 36936983

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Project description:Many pathogenic viruses, including influenza virus, Ebola virus, coronaviruses, and Pneumoviruses, rely on class I fusion proteins to fuse viral and cellular membranes. To drive the fusion process, class I fusion proteins undergo an irreversible conformational change from a metastable prefusion state to an energetically more favorable and stable postfusion state. An increasing amount of evidence exists highlighting that antibodies targeting the prefusion conformation are the most potent. However, many mutations have to be evaluated before identifying prefusion-stabilizing substitutions. We therefore established a computational design protocol that stabilizes the prefusion state while destabilizing the postfusion conformation. As a proof of concept, we applied this principle to the fusion protein of the RSV, hMPV, and SARS-CoV-2 viruses. For each protein, we tested less than a handful of designs to identify stable versions. Solved structures of designed proteins from the three different viruses evidenced the atomic accuracy of our approach. Furthermore, the immunological response of the RSV F design compared to a current clinical candidate in a mouse model. While the parallel design of two conformations allows identifying and selectively modifying energetically less optimized positions for one conformation, our protocol also reveals diverse molecular strategies for stabilization. We recaptured many approaches previously introduced manually for the stabilization of viral surface proteins, such as cavity-filling, optimization of polar interactions, as well as postfusion-disruptive strategies. Using our approach, it is possible to focus on the most impacting mutations and potentially preserve the immunogen as closely as possible to its native version. The latter is important as sequence re-design can cause perturbations to B and T cell epitopes. Given the clinical significance of viruses using class I fusion proteins, our algorithm can substantially contribute to vaccine development by reducing the time and resources needed to optimize these immunogens.

Project description:BACKGROUND: Around 20% of breast cancers (BC) show ERBB2 gene amplification and overexpression of the ERBB2 tyrosine kinase receptor. They are associated with a poor prognosis but can benefit from targeted therapy. A better knowledge of these BCs, genomically and biologically heterogeneous, may help understand their behavior and design new therapeutic strategies. METHODS: We defined the high resolution genome and gene expression profiles of 54 ERBB2-amplified BCs using 244K oligonucleotide array-comparative genomic hybridization and whole-genome DNA microarrays. Expression of ERBB2, phosphorylated ERBB2, EGFR, IGF1R and FOXA1 proteins was assessed by immunohistochemistry to evaluate the functional ERBB2 status and identify co-expressions. RESULTS: First, we identified the ERBB2-C17orf37-GRB7 genomic segment as the minimal common 17q12-q21 amplicon, and CRKRS and IKZF3 as the most frequent centromeric and telomeric amplicon borders, respectively. Second, GISTIC analysis identified 17 other genome regions affected by copy number aberration (CNA) (amplifications, gains, losses). The expression of 37 genes of these regions was deregulated. Third, two types of heterogeneity were observed in ERBB2-amplified BCs. The genomic profiles of estrogen receptor-positive (ER+) and negative (ER-) ERBB2-amplified BCs were different. The WNT/?-catenin signaling pathway was involved in ER- ERBB2-amplified BCs, and PVT1 and TRPS1 were candidate oncogenes associated with ER+ ERBB2-amplified BCs. The size of the ERBB2 amplicon was different in inflammatory (IBC) and non-inflammatory BCs. ERBB2-amplified IBCs were characterized by the downregulated and upregulated mRNA expression of ten and two genes in proportion to CNA, respectively. IHC results showed (i) a linear relationship between ERBB2 gene amplification and its gene and protein expressions with a good correlation between ERBB2 expression and phosphorylation status; (ii) a potential signaling cross-talk between EGFR or IGF1R and ERBB2, which could influence response of ERBB2-positive BCs to inhibitors. FOXA1 was frequently coexpressed with ERBB2 but its expression did not impact on the outcome of patients with ERBB2-amplified tumors. CONCLUSION: We have shown that ER+ and ER- ERBB2-amplified BCs are different, distinguished ERBB2 amplicons in IBC and non-IBC, and identified genomic features that may be useful in the design of alternative therapeutical strategies.

Dataset Information

Computational design of fusion proteins against ErbB2-amplified tumors inspired by ricin toxin.

Publications

Computational design of fusion proteins against ErbB2-amplified tumors inspired by ricin toxin.

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