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A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction
Protein-protein interactions regulate almost all cellular functions and rely on a fine tune of surface amino acids properties involved on both molecular partners. The disruption of a molecular association can be caused even by a single residue mutation, often leading to a pathological modification o...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548301/ https://www.ncbi.nlm.nih.gov/pubmed/33101606 http://dx.doi.org/10.1016/j.csbj.2020.09.020 |
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author | Di Rienzo, Lorenzo Milanetti, Edoardo Testi, Claudia Montemiglio, Linda Celeste Baiocco, Paola Boffi, Alberto Ruocco, Giancarlo |
author_facet | Di Rienzo, Lorenzo Milanetti, Edoardo Testi, Claudia Montemiglio, Linda Celeste Baiocco, Paola Boffi, Alberto Ruocco, Giancarlo |
author_sort | Di Rienzo, Lorenzo |
collection | PubMed |
description | Protein-protein interactions regulate almost all cellular functions and rely on a fine tune of surface amino acids properties involved on both molecular partners. The disruption of a molecular association can be caused even by a single residue mutation, often leading to a pathological modification of a biochemical pathway. Therefore the evaluation of the effects of amino acid substitutions on binding, and the ad hoc design of protein-protein interfaces, is one of the biggest challenges in computational biology. Here, we present a novel strategy for computational mutation and optimization of protein-protein interfaces. Modeling the interaction surface properties using the Zernike polynomials, we describe the shape and electrostatics of binding sites with an ordered set of descriptors, making possible the evaluation of complementarity between interacting surfaces. With a Monte Carlo approach, we obtain protein mutants with controlled molecular complementarities. Applying this strategy to the relevant case of the interaction between Ferritin and Transferrin Receptor, we obtain a set of Ferritin mutants with increased or decreased complementarity. The extensive molecular dynamics validation of the method results confirms its efficacy, showing that this strategy represents a very promising approach in designing correct molecular interfaces. |
format | Online Article Text |
id | pubmed-7548301 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-75483012020-10-22 A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction Di Rienzo, Lorenzo Milanetti, Edoardo Testi, Claudia Montemiglio, Linda Celeste Baiocco, Paola Boffi, Alberto Ruocco, Giancarlo Comput Struct Biotechnol J Research Article Protein-protein interactions regulate almost all cellular functions and rely on a fine tune of surface amino acids properties involved on both molecular partners. The disruption of a molecular association can be caused even by a single residue mutation, often leading to a pathological modification of a biochemical pathway. Therefore the evaluation of the effects of amino acid substitutions on binding, and the ad hoc design of protein-protein interfaces, is one of the biggest challenges in computational biology. Here, we present a novel strategy for computational mutation and optimization of protein-protein interfaces. Modeling the interaction surface properties using the Zernike polynomials, we describe the shape and electrostatics of binding sites with an ordered set of descriptors, making possible the evaluation of complementarity between interacting surfaces. With a Monte Carlo approach, we obtain protein mutants with controlled molecular complementarities. Applying this strategy to the relevant case of the interaction between Ferritin and Transferrin Receptor, we obtain a set of Ferritin mutants with increased or decreased complementarity. The extensive molecular dynamics validation of the method results confirms its efficacy, showing that this strategy represents a very promising approach in designing correct molecular interfaces. Research Network of Computational and Structural Biotechnology 2020-09-24 /pmc/articles/PMC7548301/ /pubmed/33101606 http://dx.doi.org/10.1016/j.csbj.2020.09.020 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Di Rienzo, Lorenzo Milanetti, Edoardo Testi, Claudia Montemiglio, Linda Celeste Baiocco, Paola Boffi, Alberto Ruocco, Giancarlo A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction |
title | A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction |
title_full | A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction |
title_fullStr | A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction |
title_full_unstemmed | A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction |
title_short | A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction |
title_sort | novel strategy for molecular interfaces optimization: the case of ferritin-transferrin receptor interaction |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7548301/ https://www.ncbi.nlm.nih.gov/pubmed/33101606 http://dx.doi.org/10.1016/j.csbj.2020.09.020 |
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