Biophysica

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17 pages, 868 KiB

Open AccessArticle

Cellular Compartmentalization as a Physical Regulatory Mechanism of Signaling Pathways

by Ahmed N. Fayad, Diego Mazo-Durán and David G. Míguez

Biophysica 2024, 4(4), 634-650; https://doi.org/10.3390/biophysica4040042 - 10 Dec 2024

Viewed by 267

Abstract

Cells compartmentalize biochemical processes using physical barriers in the form of membranes. Eukaryotes have a wide diversity of membrane-based compartments that can be used in this context, with the main ones being the extracellular membrane, which separates the inside from the outside of [...] Read more.

Cells compartmentalize biochemical processes using physical barriers in the form of membranes. Eukaryotes have a wide diversity of membrane-based compartments that can be used in this context, with the main ones being the extracellular membrane, which separates the inside from the outside of the cell, and the nuclear membrane, which separates the nucleus from the cytoplasm. The nuclear membrane not only isolates and protects the DNA and the transcription and replication processes from the other processes that are occurring in the cytoplasm but also has an active role in the regulation of cellular signaling. The TGF-

β

pathway is one of the most important and conserved signaling cascades, and it achieves compartmentalization using a well-tuned balance between the import and export rates of the active and inactive forms of key proteins. Thus, compartmentalization serves as an additional regulatory mechanism, physically isolating transcription factors from their targets, influencing the dynamics and strength of signal transduction. This contribution focuses on this biophysical layer of regulation, using the TGF-

β

pathway to illustrate the molecular mechanisms underlying this process, as well as the biological consequences of this compartmentalization. We also introduce a simplified mathematical formulation for studying the dynamics of this process using a generalized approach. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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12 pages, 1619 KiB

Open AccessArticle

Gibbs Free Energy and Enthalpy–Entropy Compensation in Protein–Ligand Interactions

by Juan S. Jiménez and María J. Benítez

Biophysica 2024, 4(2), 298-309; https://doi.org/10.3390/biophysica4020021 - 14 Jun 2024

Cited by 1 | Viewed by 1495

Abstract

The thermodynamics of protein–ligand interactions seems to be associated with a narrow range of Gibbs free energy. As a consequence, a linear enthalpy–entropy relationship showing an apparent enthalpy–entropy compensation (EEC) is frequently associated with protein–ligand interactions. When looking for the most negative values [...] Read more.

The thermodynamics of protein–ligand interactions seems to be associated with a narrow range of Gibbs free energy. As a consequence, a linear enthalpy–entropy relationship showing an apparent enthalpy–entropy compensation (EEC) is frequently associated with protein–ligand interactions. When looking for the most negative values of ∆H to gain affinity, the entropy compensation gives rise to a barely noticeable increase in affinity, therefore negatively affecting the design and discovery of new and more efficient drugs capable of binding protein targets with a higher affinity. Originally attributed to experimental errors, compensation between ∆H and T∆S values is an observable fact, although its molecular origin has remained obscure and controversial. The thermodynamic parameters of a protein–ligand interaction can be interpreted in terms of the changes in molecular weak interactions as well as in vibrational, rotational, and translational energy levels. However, a molecular explanation to an EEC rendering a linear enthalpy–entropy relationship is still lacking. Herein, we show the results of a data search of ∆G values of 3025 protein–ligand interactions and 2558 “in vivo” ligand concentrations from the Protein Data Bank database and the Metabolome Database (2020). These results suggest that the EEC may be plausibly explained as a consequence of the narrow range of ∆G associated with protein–ligand interactions. The Gaussian distribution of the ∆G values matches very well with that of ligands. These results suggest the hypothesis that the set of ∆G values for the protein–ligand interactions is the result of the evolution of proteins. The conformation versatility of present proteins and the exchange of thousands (even millions) of minute amounts of energy with the environment may have functioned as a homeostatic mechanism to make the ∆G of proteins adaptive to changes in the availability of ligands and therefore achieve the maximum regulatory capacity of the protein function. Finally, plausible strategies to avoid the EEC consequences are suggested. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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9 pages, 1749 KiB

Open AccessArticle

Detecting Molecular Folding from Noise Measurements

by Marc Rico-Pasto and Felix Ritort

Biophysica 2023, 3(3), 539-547; https://doi.org/10.3390/biophysica3030036 - 5 Sep 2023

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Abstract

Detecting conformational transitions in molecular systems is key to understanding biological processes. Here, we investigate the force variance in single-molecule pulling experiments as an indicator of molecular folding transitions. We consider cases where Brownian force fluctuations are large, masking the force rips and [...] Read more.

Detecting conformational transitions in molecular systems is key to understanding biological processes. Here, we investigate the force variance in single-molecule pulling experiments as an indicator of molecular folding transitions. We consider cases where Brownian force fluctuations are large, masking the force rips and jumps characteristics of conformational transitions. We compare unfolding and folding data for DNA hairpin systems of loop sizes 4, 8, and 20 and the 110-amino acid protein barnase, finding conditions that facilitate the detection of folding events at low forces where the signal-to-noise ratio is low. In particular, we discuss the role of temperature as a useful parameter to improve the detection of folding transitions in entropically driven processes where folding forces are temperature independent. The force variance approach might be extended to detect the elusive intermediate states in RNA and protein folding. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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Review

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15 pages, 2533 KiB

Open AccessReview

Arrested Coalescence: A Tool to Explore Tissue Rheology

by Sotiris Samatas, Martí Planasdemunt-Hospital and David Oriola

Biophysica 2024, 4(4), 604-618; https://doi.org/10.3390/biophysica4040040 - 28 Nov 2024

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Abstract

Tissue spheroids are self-organised 3D cellular aggregates that serve as a versatile platform in tissue engineering. While numerous high-throughput methods exist to characterise the cellular function of tissue spheroids, equivalent techniques for the mechanical characterisation are still lacking. In this review, we focus [...] Read more.

Tissue spheroids are self-organised 3D cellular aggregates that serve as a versatile platform in tissue engineering. While numerous high-throughput methods exist to characterise the cellular function of tissue spheroids, equivalent techniques for the mechanical characterisation are still lacking. In this review, we focus on tissue fusion— a simple, fast, and inexpensive method to characterise the rheology of tissue spheroids. We begin by discussing the implications of tissue rheology in development and disease, followed by a detailed explanation of how the phenomenon of arrested coalescence can be used to explore the rheology of tissue spheroids. Finally, we present different theoretical models that, when combined with experimental data, allow us to extract rheological information. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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18 pages, 1259 KiB

Open AccessReview

No Country for Old Frameworks? Vertex Models and Their Ongoing Reinvention to Study Tissue Dynamics

by Natalia Briñas-Pascual, Jake Cornwall-Scoones, Daniel P. O’Hanlon, Pilar Guerrero and Ruben Perez-Carrasco

Biophysica 2024, 4(4), 586-603; https://doi.org/10.3390/biophysica4040039 - 27 Nov 2024

Viewed by 494

Abstract

Vertex models have become essential tools for understanding tissue morphogenesis by simulating the mechanical and geometric properties of cells in various biological systems. These models represent cells as polygons or polyhedra, capturing cellular interactions such as adhesion, tension, and force generation. This review [...] Read more.

Vertex models have become essential tools for understanding tissue morphogenesis by simulating the mechanical and geometric properties of cells in various biological systems. These models represent cells as polygons or polyhedra, capturing cellular interactions such as adhesion, tension, and force generation. This review explores the ongoing evolution of computational vertex models, highlighting their application to complex tissue dynamics, including organoid development, wound healing, and cancer metastasis. We examine different energy formulations used in vertex models, which account for mechanical forces such as surface tension, volume conservation, and intercellular adhesion. Additionally, this review discusses the challenges of expanding traditional 2D models to 3D structures, which require the inclusion of factors like mechanical polarisation and topological transitions. We also introduce recent advancements in modelling techniques that allow for more flexible and dynamic cell shapes, addressing limitations in earlier frameworks. Mechanochemical feedback and its role in tissue behaviour are explored, along with cutting-edge approaches like self-propelled Voronoi models. Finally, the review highlights the importance of parameter inference in these models, particularly through Bayesian methods, to improve accuracy and predictive power. By integrating these new insights, vertex models continue to provide powerful frameworks for exploring the complexities of tissue morphogenesis. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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16 pages, 1971 KiB

Open AccessReview

Mathematical Models of the Arabidopsis Circadian Oscillator

by Lucas Henao, Saúl Ares and Pablo Catalán

Biophysica 2024, 4(2), 267-282; https://doi.org/10.3390/biophysica4020019 - 28 May 2024

Viewed by 938

Abstract

We review the construction and evolution of mathematical models of the Arabidopsis circadian clock, structuring the discussion into two distinct historical phases of modeling strategies: extension and reduction. The extension phase explores the bottom-up assembly of regulatory networks, introducing as many components and [...] Read more.

We review the construction and evolution of mathematical models of the Arabidopsis circadian clock, structuring the discussion into two distinct historical phases of modeling strategies: extension and reduction. The extension phase explores the bottom-up assembly of regulatory networks, introducing as many components and interactions as possible to capture the oscillatory nature of the clock. The reduction phase deals with functional decomposition, distilling complex models to their essential dynamical repertoire. Current challenges in this field, including the integration of spatial considerations and environmental influences like light and temperature, are also discussed. The review emphasizes the ongoing need for models that balance molecular detail with practical simplicity. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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22 pages, 4283 KiB

Open AccessReview

Physical Virology in Spain

by David Reguera, Pedro J. de Pablo, Nicola G. A. Abrescia, Mauricio G. Mateu, Javier Hernández-Rojas, José R. Castón and Carmen San Martín

Biophysica 2023, 3(4), 598-619; https://doi.org/10.3390/biophysica3040041 - 31 Oct 2023

Viewed by 1774

Abstract

Virus particles consist of a protein coat that protects their genetic material and delivers it to the host cell for self-replication. Understanding the interplay between virus structure and function is a requirement for understanding critical processes in the infectious cycle such as entry, [...] Read more.

Virus particles consist of a protein coat that protects their genetic material and delivers it to the host cell for self-replication. Understanding the interplay between virus structure and function is a requirement for understanding critical processes in the infectious cycle such as entry, uncoating, genome metabolism, capsid assembly, maturation, and propagation. Together with well-established techniques in cell and molecular biology, physical virology has emerged as a rapidly developing field, providing detailed, novel information on the basic principles of virus assembly, disassembly, and dynamics. The Spanish research community contains a good number of groups that apply their knowledge on biology, physics, or chemistry to the study of viruses. Some of these groups got together in 2010 under the umbrella of the Spanish Interdisciplinary Network on Virus Biophysics (BioFiViNet). Thirteen years later, the network remains a fertile ground for interdisciplinary collaborations geared to reveal new aspects on the physical properties of virus particles, their role in regulating the infectious cycle, and their exploitation for the development of virus-based nanotechnology tools. Here, we highlight some achievements of Spanish groups in the field of physical virology. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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13 pages, 8969 KiB

Open AccessReview

Developmental Pattern Formation: Spanish Contributions from a Biophysical Perspective

by Javier Buceta and Léna Guitou

Biophysica 2023, 3(2), 335-347; https://doi.org/10.3390/biophysica3020022 - 6 May 2023

Viewed by 2500

Abstract

During the last few decades, developmental pattern formation has evolved from being a descriptive discipline to a quantitative one. That process has been possible due to the implementation of multidisciplinary approaches where biophysicists and mathematicians have played a key role. In this review, [...] Read more.

During the last few decades, developmental pattern formation has evolved from being a descriptive discipline to a quantitative one. That process has been possible due to the implementation of multidisciplinary approaches where biophysicists and mathematicians have played a key role. In this review, we highlight relevant Spanish contributions and stress their biophysical approaches, as well as provide some historical context. Finally, this work also aimed at bridging the concepts from biology to physics/math (and back) and at shedding light on some directions for future research. Full article

(This article belongs to the Special Issue State-of-the-Art Biophysics in Spain 2.0)

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