Publications by authors named "Adolfo Poma"

Rational design of novel antibody therapeutics against viral infections such as coronavirus relies on surface complementarity and high affinity for their effectiveness. Here, we explore an additional property of protein complexes, the intrinsic mechanical stability, in SARS-CoV-2 variants when complexed with a potent antibody. In this study, we utilized a recent implementation of the GōMartini 3 approach to investigate large conformational changes in protein complexes with a focus on the mechanostability of the receptor-binding domain (RBD) from WT, Alpha, Delta, and XBB.

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The SARS-CoV-2 pandemic spurred numerous research endeavors to comprehend the virus and mitigate its global severity. Understanding the binding interface between the virus and human receptors is pivotal to these efforts and paramount to curbing infection and transmission. Here we employ atomic force microscopy and steered molecular dynamics simulation to explore SARS-CoV-2 receptor binding domain (RBD) variants and angiotensin-converting enzyme 2 (ACE2), examining the impact of mutations at key residues upon binding affinity.

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The self-assembly process of β-D-glucose oligomers on the surface of cellulose Iβ microfibril involves crystallization, and this process is analyzed herein, in terms of the length and flexibility of the oligomer chain, by means of molecular dynamics (MD) simulations. The characterization of this process involves the structural relaxation of the oligomer, the recognition of the cellulose I microfibril, and the formation of several hydrogen bonds (HBs). This process is monitored on the basis of the changes in non-bonded energies and the interaction with hydrophilic and hydrophobic crystal faces.

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The nanomechanical characterization of several biological fibrils that are the result of protein aggregation via molecular dynamics simulation is nowadays feasible, and together with atomic force microscopy experiments has widened our understanding of the forces in the regime of pN-nN and system sizes of about hundreds of nanometers. Several methodologies have been developed to achieve this target, and they range from the atomistic representation via molecular force fields to coarse-grained strategies that provide comparable results with experiments in a systematic way. In this chapter, we discuss several methodologies for the calculation of mechanical parameters, such as the elastic constants of relevant biological systems.

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High resolution data from all-atom molecular simulations is used to parameterize a Martini 3 coarse-grained (CG) model of cellulose I allomorphs and cellulose type-II fibrils. In this case, elementary molecules are represented by four effective beads centred in the positions of O2, O3, C6, and O6 atoms in the D-glucose cellulose subunit. Non-bonded interactions between CG beads are tuned according to a low statistical criterion of structural deviation using the Martini 3 type of interactions and are capable of being indistinguishable for all studied cases.

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We used single-molecule AFM force spectroscopy (AFM-SMFS) in combination with click chemistry to mechanically dissociate anticalin, a non-antibody protein binding scaffold, from its target (CTLA-4), by pulling from eight different anchor residues. We found that pulling on the anticalin from residue 60 or 87 resulted in significantly higher rupture forces and a decrease in by 2-3 orders of magnitude over a force range of 50-200 pN. Five of the six internal anchor points gave rise to complexes significantly more stable than N- or C-terminal anchor points, rupturing at up to 250 pN at loading rates of 0.

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Despite an unprecedented global gain in knowledge since the emergence of SARS-CoV-2, almost all mechanistic knowledge related to the molecular and cellular details of viral replication, pathology and virulence has been generated using early prototypic isolates of SARS-CoV-2. Here, using atomic force microscopy and molecular dynamics, we investigated how these mutations quantitatively affected the kinetic, thermodynamic and structural properties of RBD-ACE2 complex formation. We observed for several variants of concern a significant increase in the RBD-ACE2 complex stability.

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Amyloid beta (Aβ) oligomers are the most neurotoxic aggregates causing neuronal death and cognitive damage. A detailed elucidation of the aggregation pathways from oligomers to fibril formation is crucial to develop therapeutic strategies for Alzheimer's disease (AD). Although experimental techniques rely on the measure of time- and space-average properties, they face severe difficulties in the investigation of Aβ peptide aggregation due to their intrinsically disorder character.

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Alzheimer's disease (AD) is a neurodegenerative disorder and one of the main causes of dementia. The disease is associated with amyloid beta (Aβ) peptide aggregation forming initial clusters and then fibril structure and plaques. Other neurodegenerative diseases such as type 2 diabetes, amyotrophic lateral sclerosis, and Parkinson's disease follow a similar mechanism.

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Coarse-grained (CG) molecular dynamics (MD) simulations allow us to access much larger length and time scales than atomistic MD simulations, providing an attractive alternative to the conventional simulations. Based on the well-known MARTINI CG force field, the recently developed Gō-MARTINI model for proteins describes large-amplitude structural dynamics, which has not been possible with the commonly used elastic network model. Using the Gō-MARTINI model, we conduct MD simulations of the F-BAR Pacsin1 protein on lipid membrane.

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The novel coronavirus disease 2019 (COVID-19) pandemic has disrupted modern societies and their economies. The resurgence in COVID-19 cases as part of the second wave is observed across Europe and the Americas. The scientific response has enabled a complete structural characterization of the Severe Acute Respiratory Syndrome-novel Coronavirus 2 (SARS-CoV-2).

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We report on the novel observation about the gain in nanomechanical stability of the SARS-CoV-2 (CoV2) spike (S) protein in comparison with SARS-CoV from 2002 (CoV1). Our findings have several biological implications in the subfamily of coronaviruses, as they suggest that the receptor binding domain (RBD) (∼200 amino acids) plays a fundamental role as a damping element of the massive viral particle's motion prior to cell-recognition, while also facilitating viral attachment, fusion and entry. The mechanical stability via pulling of the RBD is 250 pN and 200 pN for CoV2 and CoV1 respectively, and the additional stability observed for CoV2 (∼50 pN) might play a role in the increasing spread of COVID-19.

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In the past two decades, the world has faced several infectious disease outbreaks. Ebola, Influenza A (H1N1), SARS, MERS, and Zika virus have had a massive global impact in terms of economic disruption, the strain on local and global public health. Most recently, the global outbreak of novel coronavirus 2019 (SARS-CoV-2) that causes COVID-19 is a newly discovered virus from the coronavirus family in Wuhan city, China, known to be a great threat to the public health systems.

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Molecular simulations of large biological systems, such as viral capsids, remains a challenging task in soft matter research. On one hand, coarse-grained (CG) models attempt to make the description of the entire viral capsid disassembly feasible. On the other hand, the permanent development of novel molecular dynamics (MD) simulation approaches, like enhanced sampling methods, attempt to overcome the large time scales required for such simulations.

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Membrane proteins, including G protein-coupled receptors (GPCRs), present a challenge in studying their structural properties under physiological conditions. Moreover, to better understand the activity of proteins requires examination of single molecule behaviors rather than ensemble averaged behaviors. Force-distance curve-based AFM (FD-AFM) was utilized to directly probe and localize the conformational states of a GPCR within the membrane at nanoscale resolution based on the mechanical properties of the receptor.

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We perform molecular dynamics simulation on several relevant biological fibrils associated with neurodegenerative diseases such as Aβ, Aβ, and α-synuclein systems to obtain a molecular understanding and interpretation of nanomechanical characterization experiments. The computational method is versatile and addresses a new subarea within the mechanical characterization of heterogeneous soft materials. We investigate both the elastic and thermodynamic properties of the biological fibrils in order to substantiate experimental nanomechanical characterization techniques that are quickly developing and reaching dynamic imaging with video rate capabilities.

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The elastic network (EN) is a prime model that describes the long-time dynamics of biomolecules. However, the use of harmonic potentials renders this model insufficient for studying large conformational changes of proteins (e.g.

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We study the mechanical response of cellulose and β-amyloid microfibrils to three types of deformation: tensile, indentational, and shear. The cellulose microfibrils correspond to the allomorphs Iα or Iβ whereas the β-amyloid microfibrils correspond to the polymorphs of either two- or three-fold symmetry. This response can be characterized by three elastic moduli, namely, Y, Y, and S.

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The application of coarse-grained (CG) models in biology is essential to access large length and time scales required for the description of many biological processes. The ELNEDIN protein model is based on the well-known MARTINI CG force-field and incorporates additionally harmonic bonds of a certain spring constant within a defined cutoff distance between pairs of residues, in order to preserve the native structure of the protein. In this case, the use of unbreakable harmonic bonds hinders the study of unfolding and folding processes.

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We construct two variants of coarse-grained models of three hexaoses: one based on the centers of mass of the monomers and the other associated with the C4 atoms. The latter is found to be better defined and more suitable for studying interactions with proteins described within α-C based models. We determine the corresponding effective stiffness constants through all-atom simulations and two statistical methods.

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The path integral single sweep method is used to assess quantum effects on the free energy barrier for hydrogen vacancy diffusion in a defective Na(3)AlH(6) crystal. This process has been investigated via experiments and simulations due to its potential relevance in the H release mechanism in sodium alanates, prototypical materials for solid state hydrogen storage. Previous computational studies, which used density functional methods for the electronic structure, were restricted to a classical treatment of the nuclear degrees of freedom.

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We propose a simple method to evaluate the approximation of separation of variables in molecular dynamics (MD) and related fields. It is based on a point-by-point evaluation of the difference between the true potential and the corresponding potential where the separation of variables is applied. The major advantage of such an approach is the fact that it requires only the analytical form of the potential as provided in most of the MD codes.

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