Superposition-free comparison and clustering of antibody binding sites: implications for the prediction of the nature of their antigen

Rienzo, Lorenzo Di; Milanetti, Edoardo; Lepore, Rosalba; Olimpieri, Pier Paolo; Tramontano, Anna

doi:10.1038/srep45053

Cited by 29 publications

(34 citation statements)

References 35 publications

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“…In the last decade the 3D Zernike formalism has been widely applied for the characterization of molecular interactions [29,[34][35][36]: in this work we adopted a new representation, based on the 2D Zernike polynomials, which allows the quantitative characterization of protein surface regions. As shown in Fig.1, our computational protocol associates to each molecular patch an ordered set of numbers (the expansion coefficients) that describes its shapes.…”

Section: Resultsmentioning

confidence: 99%

In-Silico evidence for two receptors based strategy of SARS-CoV-2

Milanetti

Miotto

Rienzo

et al. 2020

Preprint

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We propose a novel numerical method able to determine efficiently and effectively the relationship of complementarity between portions of protein surfaces. This innovative and general procedure, based on the representation of the molecular iso-electron density surface in terms of 2D Zernike polynomials, allows the rapid and quantitative assessment of the geometrical shape complementarity between interacting proteins, that was unfeasible with previous methods. We first tested the method with a large dataset of known protein complexes obtaining an overall area under the ROC curve of 0.76 in the blind recognition of binding sites and then applied it to investigate the features of the interaction between the Spike protein of SARS-CoV-2 and human cellular receptors. Our results indicate that SARS-CoV-2 uses a dual strategy: its spike protein could also interact with sialic acid receptors of the cells in the upper airways, in addition to the known interaction with Angiotensin-converting enzyme 2.

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Section: Resultsmentioning

confidence: 99%

In-Silico evidence for two receptors based strategy of SARS-CoV-2

Milanetti

Miotto

Rienzo

et al. 2020

Preprint

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“…We will refer to these descriptors as 3DZDs (3-Dimensional Zernike Descriptors) for consistency with prior work [ 27 ]. While this approach is straightforward and has proven to be widely applicable [ 26 , 37 ], the information loss is obvious: every (2 l + 1)-dimensional vector of parameters is reduced to a single invariant. These simpler 3DZD invariants are the base of 3D-surfer [ 26 ], the first widely available tool that made use of the Zernike moment decomposition for protein shape matching.…”

Section: Resultsmentioning

confidence: 99%

Real time structural search of the Protein Data Bank

2020

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Detection of protein structure similarity is a central challenge in structural bioinformatics. Comparisons are usually performed at the polypeptide chain level, however the functional form of a protein within the cell is often an oligomer. This fact, together with recent growth of oligomeric structures in the Protein Data Bank (PDB), demands more efficient approaches to oligomeric assembly alignment/retrieval. Traditional methods use atom level information, which can be complicated by the presence of topological permutations within a polypeptide chain and/or subunit rearrangements. These challenges can be overcome by comparing electron density volumes directly. But, brute force alignment of 3D data is a compute intensive search problem. We developed a 3D Zernike moment normalization procedure to orient electron density volumes and assess similarity with unprecedented speed. Similarity searching with this approach enables real-time retrieval of proteins/protein assemblies resembling a target, from PDB or user input, together with resulting alignments (http:// shape.rcsb.org).

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“…Then, we extracted by means of a voxelization procedure the three Zernike 3D functions (3DZD) [32,33], representing the shape, the positive electrostatics and the negative electrostatics of the selected region, i.e., the binding groove. Such a procedure was recently implemented and applied in our recent work on similar systems [34,35].…”

Section: Construction Of the Zernike Descriptormentioning

confidence: 99%

Molecular Dynamics Simulations Reveal Canonical Conformations in Different pMHC/TCR Interactions

Alba

Rienzo

Milanetti

et al. 2020

Cells

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The major defense system against microbial pathogens in vertebrates is the adaptive immune response and represents an effective mechanism in cancer surveillance. T cells represent an essential component of this complex system. They can recognize myriads of antigens as short peptides (p) originated from the intracellular degradation of foreign proteins presented by major histocompatibility complex (MHC) proteins. The clonotypic T-cell antigen receptor (TCR) is specialized in recognizing pMHC and triggering T cells immune response. It is still unclear how TCR engagement to pMHC is translated into the intracellular signal that initiates T-cell immune response. Some work has suggested the possibility that pMHC binding induces in the TCR conformational changes transmitted to its companion CD3 subunits that govern signaling. The conformational changes would promote phosphorylation of the CD3 complex ζ chain that initiates signal propagation intracellularly. Here, we used all-atom molecular dynamics simulations (MDs) of 500 ns to analyze the conformational behavior of three TCRs (1G4, ILA1 and ILA1α1β1) interacting with the same MHC class I (HLA-A*02:01) bound to different peptides, and modelled in the presence of a lipid bilayer. Our data suggest a correlation between the conformations explored by the β-chain constant regions and the T-cell response experimentally determined. In particular, independently by the TCR type involved in the interaction, the TCR activation seems to be linked to a specific zone of the conformational space explored by the β-chain constant region. Moreover, TCR ligation restricts the conformational space the MHC class I groove.

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Superposition-free comparison and clustering of antibody binding sites: implications for the prediction of the nature of their antigen

Cited by 29 publications

References 35 publications

In-Silico evidence for two receptors based strategy of SARS-CoV-2

In-Silico evidence for two receptors based strategy of SARS-CoV-2

Real time structural search of the Protein Data Bank

Molecular Dynamics Simulations Reveal Canonical Conformations in Different pMHC/TCR Interactions

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