Publications by authors named "Luis Borges-Araujo"

Coarse-grained molecular dynamics simulations enable the modeling of increasingly complex systems at millisecond timescales. The transferable coarse-grained force field Martini 3 has shown great promise in modeling a wide range of biochemical processes, yet folded proteins in Martini 3 are not stable without the application of external bias potentials, such as elastic networks or Go̅-like models. We herein develop an algorithm, called OLIVES, which identifies native contacts with hydrogen bond capabilities in coarse-grained proteins and use it to implement a novel Go̅-like model for Martini 3.

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Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of the Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein-ligand binding. However, the current ligand parametrization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking.

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Article Synopsis
  • Coarse-grained (CG) protein models, like the Martini force field, help scientists study how proteins behave and interact in living things.*
  • The new version, Martini 3, fixes some problems found in the older version (Martini 2) and enhances the protein model.*
  • The review talks about the updates from Martini 3, its current issues, and ideas for making it even better in the future.*
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Cholesterol plays a crucial role in biomembranes by regulating various properties, such as fluidity, rigidity, permeability, and organization of lipid bilayers. The latest version of the Martini model, Martini 3, offers significant improvements in interaction balance, molecular packing, and inclusion of new bead types and sizes. However, the release of the new model resulted in the need to reparameterize many core molecules, including cholesterol.

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The molecular details involved in the folding, dynamics, organization, and interaction of proteins with other molecules are often difficult to assess by experimental techniques. Consequently, computational models play an ever-increasing role in the field. However, biological processes involving large-scale protein assemblies or long time scale dynamics are still computationally expensive to study in atomistic detail.

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Energy-coupling factor (ECF)-type transporters mediate the uptake of micronutrients in many bacteria. They consist of a substrate-translocating subunit (S-component) and an ATP-hydrolysing motor (ECF module) Previous data indicate that the S-component topples within the membrane to alternately expose the binding site to either side of the membrane. In many ECF transporters, the substrate-free S-component can be expelled from the ECF module.

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Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has killed over 6 million people and is having a devastating social and economic impact around the world. The rise of new variants of concern (VOCs) represents a difficult challenge due to the loss of vaccine and natural immunity, as well as increased transmissibility. All VOCs contain mutations in the spike glycoprotein, which mediates fusion between the viral and host cell membranes.

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Despite its low abundance, phosphatidylinositol 4,5-bisphosphate (PI(4,5)P) is a key modulator of membrane-associated signaling events in eukaryotic cells. Temporal and spatial regulation of PI(4,5)P concentration can achieve localized increases in the levels of this lipid, which are crucial for the activation or recruitment of peripheral proteins to the plasma membrane. The recent observation of the dramatic impact of physiological divalent cation concentrations on PI(4,5)P clustering, suggests that protein anchoring to the plasma membrane through PI(4,5)P is likely not defined solely by a simple (monomeric PI(4,5)P)/(protein bound PI(4,5)P) equilibrium, but instead depends on complex protein interactions with PI(4,5)P clusters.

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Phosphoinositides are a family of membrane phospholipids that play crucial roles in membrane regulatory events. As such, these lipids are often a key part of molecular dynamics simulation studies of biological membranes, in particular of those employing coarse-grain models because of the potential long times and sizes of the involved membrane processes. Version 3 of the widely used Martini coarse-grain force field has been recently published, greatly refining many aspects of biomolecular interactions.

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Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P) plays a critical role in the regulation of various plasma membrane processes and signaling pathways in eukaryotes. A significant amount of cellular resources are spent on maintaining the dominant 1-stearoyl-2-arachidonyl PI(4,5)P acyl-chain composition, while less abundant and more saturated species become more prevalent in response to specific stimuli, stress or aging. Here, we report the impact of acyl-chain structure on the biophysical properties of cation-induced PI(4,5)P nanodomains.

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Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P) is an essential plasma membrane component involved in several cellular functions, including membrane trafficking and cytoskeleton organization. This function multiplicity is partially achieved through a dynamic spatiotemporal organization of PI(4,5)P within the membrane. Here, we use a Förster resonance energy transfer (FRET) approach to quantitatively assess the extent of PI(4,5)P confinement within the plasma membrane.

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Phosphatidylinositol 4,5-bisphosphate (PI(4,5)P) is a minor but ubiquitous component of the inner leaflet of the plasma membrane of eukaryotic cells. However, due to its particular complex biophysical properties, it stands out from its neighboring lipids as one of the most important regulators of membrane-associated signaling events. Despite its very low steady-state concentration, PI(4,5)P is able to engage in a multitude of simultaneous cellular functions that are temporally and spatially regulated through the presence of localized transient pools of PI(4,5)P in the membrane.

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