Simulated Epidemics in 3D Protein Structures to Detect Functional Properties

Miotto, Mattia; Rienzo, Lorenzo Di; Corsi, Pietro; Ruocco, G.; Raimondo, Domenico; Milanetti, Edoardo

doi:10.1021/acs.jcim.9b01027

Cited by 15 publications

(18 citation statements)

References 50 publications

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“…Moreover, given the great interest in the structural characterization of interacting regions of proteins ( Chen et al, 2003 ; De Vries et al, 2010 ; Obarska-Kosinska et al, 2016 ; Miotto et al, 2020 ), a wide number of parameter-free methods have been developed. Some of these methods are based on atom densities ( Mitchell et al, 2001 ) or tessellation ( Walls and Sternberg, 1992 ; Li et al, 2007 ), while others are based on the series exploration of a set of function, such as spherical harmonics ( Leicester et al, 1988 ; Max and Getzoff, 1988 ), Fourier-correlation theory ( Gabb et al, 1997 ), Wigner D-functions ( Saberi Fathi et al, 2014 ) or 3D Zernike polynomials ( Venkatraman et al, 2009 ; Kihara et al, 2011 ; Di Rienzo et al, 2017 ; Daberdaku and Ferrari, 2019 ; Di Rienzo et al, 2020 ; Guzenko et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

In-Silico Evidence for a Two Receptor Based Strategy of SARS-CoV-2

Milanetti

Miotto

Rienzo

et al. 2021

Front. Mol. Biosci.

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We propose a computational investigation on the interaction mechanisms between SARS-CoV-2 spike protein and possible human cell receptors. In particular, we make use of our newly developed 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 isoelectronic density surface in terms of 2D Zernike polynomials, allows the rapid and quantitative assessment of the geometrical shape complementarity between interacting proteins, which was unfeasible with previous methods. Our results indicate that SARS-CoV-2 uses a dual strategy: in addition to the known interaction with angiotensin-converting enzyme 2, the viral spike protein can also interact with sialic-acid receptors of the cells in the upper airways.

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Section: Introductionmentioning

confidence: 99%

In-Silico Evidence for a Two Receptor Based Strategy of SARS-CoV-2

Milanetti

Miotto

Rienzo

et al. 2021

Front. Mol. Biosci.

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“…Indeed, we calculated for each frame the non-covalent energies (Coulomb and Van der Walls terms) exchanged through the molecular interface between any atoms of the 2 molecules. We adopted the same formalism as we did in [58] , [59] .…”

Section: Resultsmentioning

confidence: 99%

A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction

Rienzo

Milanetti

Testi

et al. 2020

Computational and Structural Biotechnology Journal

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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.

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“…In order to explain the mechanism by which these perturbations are transmitted across the structure of the main protease, Abadias et al. [112] developed a fractional Susceptible–Infected (SI) model based on the assumption that there are similarities between epidemic spreading and a diffusive process on a protein residue network to prove the capability of propagating information in complex 3D protein structures [113] . The new fractional SI model on a network was defined as:

with initial condition

, and where

is the infection rate,

is the adjacency matrix,

is an all-ones column vector, and

is the Caputo fractional derivative defined as

where

, and where

is the smallest integer greater than or equal to

.…”

Section: Modeling For Drug Repurposingmentioning

confidence: 99%

COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

2020

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Since December 2019 the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has produced an outbreak of pulmonary disease which has soon become a global pandemic, known as COronaVIrus Disease-19 (COVID-19). The new coronavirus shares about 82% of its genome with the one which produced the 2003 outbreak (SARS CoV-1). Both coronaviruses also share the same cellular receptor, which is the angiotensin-converting enzyme 2 (ACE2) one. In spite of these similarities, the new coronavirus has expanded more widely, more faster and more lethally than the previous one. Many researchers across the disciplines have used diverse modeling tools to analyze the impact of this pandemic at global and local scales. This includes a wide range of approaches – deterministic, data-driven, stochastic, agent-based, and their combinations – to forecast the progression of the epidemic as well as the effects of non-pharmaceutical interventions to stop or mitigate its impact on the world population. The physical complexities of modern society need to be captured by these models. This includes the many ways of social contacts – (multiplex) social contact networks, (multilayers) transport systems, metapopulations, etc. – that may act as a framework for the virus propagation. But modeling not only plays a fundamental role in analyzing and forecasting epidemiological variables, but it also plays an important role in helping to find cures for the disease and in preventing contagion by means of new vaccines. The necessity for answering swiftly and effectively the questions: could existing drugs work against SARS CoV-2? and can new vaccines be developed in time? demands the use of physical modeling of proteins, protein-inhibitors interactions, virtual screening of drugs against virus targets, predicting immunogenicity of small peptides, modeling vaccinomics and vaccine design, to mention just a few. Here, we review these three main areas of modeling research against SARS CoV-2 and COVID-19: (1) epidemiology; (2) drug repurposing; and (3) vaccine design. Therefore, we compile the most relevant existing literature about modeling strategies against the virus to help modelers to navigate this fast-growing literature. We also keep an eye on future outbreaks, where the modelers can find the most relevant strategies used in an emergency situation as the current one to help in fighting future pandemics.

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Simulated Epidemics in 3D Protein Structures to Detect Functional Properties

Cited by 15 publications

References 50 publications

In-Silico Evidence for a Two Receptor Based Strategy of SARS-CoV-2

In-Silico Evidence for a Two Receptor Based Strategy of SARS-CoV-2

A novel strategy for molecular interfaces optimization: The case of Ferritin-Transferrin receptor interaction

COVID-19 and SARS-CoV-2. Modeling the present, looking at the future

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