Search Results (107)

The complexity of the biochemistry and the variety of possible environments make the subject of the no-growth limits of bacteria a very tough challenge. This present work addresses the problem of applying to the microbial cultures the polymer science approach, which is widespread in food technology. This requires the definition of a “dynamic state diagram” that reports the expected trends of the glass transition of two virtual polymers, which mimic the crowded cytoplasmic polymers and the polymeric meshwork of the cell envelope, respectively, versus the water content. At any given temperature, the water content at the glass transition represents the lowest limit for the relevant molecular mobility. This representation leads one to recognize that the lowest temperature to observe microbial growth coincides with that of the largest freeze-concentrated liquid phase, in line with the values predicted by the Ratkowsky empirical equation. In view of potential applications in predictive microbiology, this paper suggests an alternative interpretation for the highest tolerated temperature and the temperature of the largest specific growth rate. Full article

Background: Traditional molecular optimization methods struggle with high data dependency and significant computational demands. Additionally, conventional genetic algorithms often produce solutions with high similarity, leading to potential local optima and reduced molecular diversity, thereby limiting the exploration of chemical space. Methods: In order to address the above issues, this paper proposes an improved genetic algorithm for multi-objective drug molecular optimization (MoGA-TA). It uses the Tanimoto similarity-based crowding distance calculation and a dynamic acceptance probability population update strategy. The study employs a decoupled crossover and mutation strategy within chemical space for molecular optimization. The proposed crowding distance calculation method better captures molecular structural differences, enhancing search space exploration, maintaining population diversity, and preventing premature convergence. The dynamic acceptance probability strategy balances exploration and exploitation during evolution. Optimization continues until a predefined stopping condition is met. To assess MoGA-TA’s effectiveness, the algorithm is evaluated using metrics like success rate, dominating hypervolume, geometric mean, and internal similarity. Results: Experimental results show that compared to the comparative method, MoGA-TA performs better in drug molecule optimization and significantly improves the efficiency and success rate. Conclusions: The method described in this paper has been proven to be an effective and reliable method for multi-objective molecular optimization tasks. Full article

Arginine plays a critical role in biomolecular interactions due to its guanidinium side chain, which enables multivalent electrostatic and hydrogen bonding contacts. In this study, atomistic molecular dynamics simulations were conducted across a broad concentration range (26–605 mM) to investigate the thermodynamic and structural features of arginine self-assembly in aqueous solution. Key observables—including hydrogen bond count, radius of gyration, contact number, and isobaric heat capacity—were analyzed to characterize emergent behavior. A three-regime aggregation pattern (dilute, cooperative, and saturated) was identified and quantitatively modeled using the Hill equation, revealing a non-linear transition in clustering behavior. Spatial analyses were supplemented with trajectory-based clustering and radial distribution functions. The heat capacity peak observed near 360 mM was interpreted as a thermodynamic signature of hydration rearrangement. Trajectory analyses utilized both GROMACS tools and the MDAnalysis library. While force field limitations and single-replica sampling are acknowledged, the results offer mechanistic insight into how arginine concentration modulates molecular organization—informing the understanding of biomolecular condensates, protein–nucleic acid complexes, and the design of functional supramolecular systems. The findings are in strong agreement with experimental observations from small-angle X-ray scattering and differential scanning calorimetry. Overall, this work establishes a cohesive framework for understanding amino acid condensation and reveals arginine’s concentration-dependent behavior as a model for weak, reversible molecular association. Full article

Membrane tubes, a class of soft biological confinement for ubiquitous transport intermediates, are essential for cell trafficking and intercellular communication. However, the confinement interaction and directional migration of diffusive nanoparticles (NPs) are widely dismissed as improbable due to the surrounding environment compressive force. Here, combined with the mechanics analysis of nanoparticles (such as extracellular vesicles, EVs) to study their interaction in confinement, we perform dissipative particle dynamics (DPD) simulations to construct a model that is as large as possible to clarify the submissive behavior of NPs. Both molecular simulations and mechanical analysis revealed that the interactions between NPs are controlled by confinement deformation and the centroid distance of the NPs. When the centroid distance exceeds a threshold value, the degree of crowding variation becomes invalid for NPs motion. The above conclusions are further supported by the observed dynamics of multiple NPs under confinement. These findings provide new insights into the physical mechanism, revealing that the confinement squeeze generated by asymmetric deformation serves as the key factor governing the directional movement of the NPs. Therefore, the constraints acting on NPs differ between rigid confinement and soft confinement environments, with NPs maintaining relative stillness in rigid confinement. Full article

Recent advances in molecular dynamics (MD) simulations and the introduction of artificial intelligence (AI) have resulted in a significant increase in accuracy for structure prediction. However, the cell is a highly crowded environment consisting of various macromolecules, such as proteins and nucleic acids. The macromolecular crowding and solution conditions, such as temperature, ion concentration, and the presence of crowders, significantly influence the molecular interactions between and structural changes in proteins and nucleic acids. In this study, we investigate the presence of crowders and their effect on the melting of DNA molecules by analyzing melting profiles of short and long heterogeneous DNA duplexes. In particular, we examine how multiple inert crowders, randomly distributed along long DNA chains, influence DNA melting. We find that the presence of crowders stabilizes double-stranded DNA (dsDNA), with this effect being more pronounced in short DNA duplexes. These findings complement in vitro observations and improve our understanding of dsDNA in cell-like environments. Full article

Cytochrome c is one of the most prominent representatives of peripheral membrane proteins. Besides functioning as an electron transfer carrier in the mitochondrial respiratory chain, it can acquire peroxidase capability, promote the self-assembly of α-synuclein, and function as a scavenger of superoxide. An understanding of its function requires knowledge of how the protein interacts with the inner membrane of mitochondria. The first part of this article provides an overview of a variety of experiments that were aimed at exploring the details of cytochrome c binding to anionic lipid liposomes, which serve as a model system for the inner membrane. While cytochrome c binding involves a conformational change from a folded into a partially disordered state, α-synuclein is intrinsically disordered in solution and subjected to a partial coil -> helix transition on membranes. Depending on the solution conditions and the surface density of α-synuclein, the protein facilitates the self-assembly into oligomers and fibrils. As for cytochrome c, results of binding experiments are discussed. In addition, the article analyzes experiments that explored α-synuclein aggregation. Similarities and differences between cytochrome c and α-synuclein binding are highlighted. Finally, the article presents a brief account of the interplay between cytochrome c and α-synuclein and its biological relevance. Full article

The 1-anilino-8-naphthalenesulfonate (ANS) fluorescent dye is widely used in protein folding studies due to the significant increase in its fluorescence quantum yield upon binding to protein hydrophobic regions that become accessible during protein unfolding. However, when modeling cellular macromolecular crowding conditions in protein folding experiments in vitro using crowding agents with guanidine hydrochloride (GdnHCl) as the denaturant, the observed changes in ANS spectral characteristics require careful consideration. This study demonstrates that crowding agents can form clusters that interact differently with ANS. Furthermore, GdnHCl can disrupt these clusters and directly affect the ANS spectral characteristics. A model for the interaction between GdnHCl, crowders, and ANS is proposed. Using bovine serum albumin (BSA) as a model protein, the limitations of using ANS for studying conformational transitions induced by GdnHCl in the presence of crowding agents are demonstrated. Full article

Living systems cannot rely on random intermolecular approaches toward cell crowding, and hidden mechanisms must be present to favor only those molecular interactions required explicitly by the biological function. Electromagnetic messaging among proteins is proposed from the observation that charged amino acids located on the protein surface are mostly in adjacent sequence positions and/or in spatial proximity. Molecular dynamics (MD) simulations have been used to predict electric charge proximities arising from concerted motions of charged amino acid side chains in two protein model systems, human ubiquitin and the chitinolytic enzyme from Ostrinia furnacalis. This choice has been made for their large difference in size and sociality. Protein electrodynamics seems to emerge as the framework for a deeper understanding of the long-distance interactions of proteins with their molecular environment. Our findings will be valuable in orienting the design of proteins with specific recognition patterns. Full article

A coarse-grained model of a two-dimensional colloidal suspension was designed. The model was athermal and, in addition, a lattice approximation was introduced. It consisted of solvent (monomer) molecules, dimer molecules, and immobile impenetrable obstacles that introduced additional heterogeneity into the system. Dynamic properties were determined by a Monte Carlo simulation using the dynamic lattice liquid simulation algorithm. It is shown that there is a range of obstacle concentrations in which different diffusion characteristics were observed for dimers and solvents. In the system studied, it is possible to define the ranges of concentrations of individual components (solvent, dimers, and obstacles), in which the nature of the movement of dimers and solvents is different (normal diffusion vs. subdiffusion). The ratio of diffusion coefficients of solvent molecules and dimers for short times does not depend on the concentration of obstacles, while for long times, the ratio increases but remains independent of the concentration of the dimer. Full article

Water exists in the beginning and hydrates all matter. Life emerged in water, requiring three essential components in compartmentalized spaces: (1) universal energy sources driving biochemical reactions and processes, (2) molecules that store, encode, and transmit information, and (3) functional players carrying out biological activities and structural organization. Phosphorus has been selected to create adenosine triphosphate (ATP) as the universal energy currency, nucleic acids for genetic information storage and transmission, and phospholipids for cellular compartmentalization. Meanwhile, proteins composed of 20 α-amino acids have evolved into extremely diverse three-dimensional forms, including folded domains, intrinsically disordered regions (IDRs), and membrane-bound forms, to fulfill functional and structural roles. This review examines several unique findings: (1) insoluble proteins, including membrane proteins, can become solubilized in unsalted water, while folded cytosolic proteins can acquire membrane-inserting capacity; (2) Hofmeister salts affect protein stability by targeting hydration; (3) ATP biphasically modulates liquid–liquid phase separation (LLPS) of IDRs; (4) ATP antagonizes crowding-induced protein destabilization; and (5) ATP and triphosphates have the highest efficiency in inducing protein folding. These findings imply the following: (1) hydration might be encoded in protein sequences, central to manifestation and modulation of protein structures, dynamics, and functionalities; (2) phosphate anions have a unique capacity in enhancing μs-ms protein dynamics, likely through ionic state exchanges in the hydration shell, underpinning ATP, polyphosphate, and nucleic acids as molecular chaperones for protein folding; and (3) ATP, by linking triphosphate with adenosine, has acquired the capacity to spacetime-specifically release energy and modulate protein hydration, thus possessing myriad energy-dependent and -independent functions. In light of the success of AlphaFolds in accurately predicting protein structures by neural networks that store information as distributed patterns across nodes, a fundamental question arises: Could cellular networks also handle information similarly but with more intricate coding, diverse topological architectures, and spacetime-specific ATP energy supply in membrane-compartmentalized aqueous environments? Full article

Aspergillus fumigatus is intrinsically resistant to the widely used antifungal fluconazole, and therapeutic failure can result from acquired resistance to voriconazole, the primary treatment for invasive aspergillosis. The molecular basis of substrate specificity and innate and acquired resistance of A. fumigatus to azole drugs were addressed using crystal structures, molecular models, and expression in Saccharomyces cerevisiae of the sterol 14α-demethylase isoforms AfCYP51A and AfCYP51B targeted by azole drugs, together with their cognate reductase AfCPRA2 and AfERG6 (sterol 24-C-methyltransferase). As predicted by molecular modelling, functional expression of CYP51A and B required eburicol and not lanosterol. A crowded conformationally sensitive region involving the BC-loop, helix I, and the heme makes AfCYP51A T289 primarily responsible for resistance to fluconazole, VT-1161, and the agrochemical difenoconazole. The Y121F T289A combination was required for higher level acquired resistance to fluconazole, VT-1161, difenoconazole, and voriconazole, and confirms posaconazole, isavuconazole and possibly ravuconazole as preferred treatments for target-based azole-resistant aspergillosis due to such a combination of mutations. Full article

The pathological process of prion diseases implicates that the normal physiological cellular prion protein (PrP^C) converts into misfolded abnormal scrapie prion (PrP^Sc) through post-translational modifications that increase β-sheet conformation. We recently demonstrated that HuPrP(90–231) thermal unfolding is partially irreversible and characterized by an intermediate state (β-PrPI), which has been revealed to be involved in the initial stages of PrP^C fibrillation, with a seeding activity comparable to that of human infectious prions. In this study, we report the thermal unfolding characterization, in cell-mimicking conditions, of the truncated (HuPrP(90–231)) and full-length (HuPrP(23–231)) human prion protein by means of CD and NMR spectroscopy, revealing that HuPrP(90–231) thermal unfolding is characterized by two successive transitions, as in buffer solution. The amyloidogenic propensity of HuPrP(90–231) under crowded conditions has also been investigated. Our findings show that although the prion intermediate, structurally very similar to β-PrPI, forms at a lower temperature compared to when it is dissolved in buffer solution, in cell-mimicking conditions, the formation of prion fibrils requires a longer incubation time, outlining how molecular crowding influences both the equilibrium states of PrP and its kinetic pathways of folding and aggregation. Full article

The kinetics of amyloid aggregation was studied indirectly by monitoring the changes in the polydispersity of mixed dispersion of amyloid β peptide (1-40) and composite liposomes. The liposomes were prepared from the 1,2-dioleoyl-sn-glicero-3-phoshocholine (DOPC) phospholipid and stabilised by the electrostatic adsorption of κ-carrageenan. The produced homotaurine-loaded and unloaded liposomes had a highly negative electrokinetic potential and remarkable stability in phosphate buffer (pH 4 and 7.4). For the first time, the appearance and evolution of the aggregation of Aβ were presented through the variation in the standard percentile readings (D10, D50, and D90) obtained from the particle size distribution analysis. The kinetic experiments indicated the appearance of the first aggregates almost 30 min after mixing the liposomes and peptide solution. It was observed that by adding unloaded liposomes, the size of 90% of the particles in the dispersion (D90) increased. In contrast, the addition of homotaurine-loaded liposomes had almost minimal impact on the size of the fractions of larger particles during the kinetic experiments. Despite the specific bioactivity of homotaurine in the presence of natural cell membranes, this study reported an additional inhibitory effect of the compound on the amyloid peptide aggregation due to the charge effects and ‘molecular crowding’. Full article

The intracellular environment displays complex dynamics influenced by factors such as molecular crowding and the low Reynolds number of the cytoplasm. Enzymes exhibiting active matter properties further heighten this complexity which can lead to memory effects. Molecular simulations often neglect these factors, treating the environment as a “thermal bath” using the Langevin equation (LE) with white noise. One way to consider these factors is by using colored noise instead within the generalized Langevin equation (GLE) framework, which allows for the incorporation of memory effects that have been observed in experimental data. We investigated the structural and dynamic differences in Shikimate kinase (SK) using LE and GLE simulations. Our results suggest that GLE simulations, which reveal significant changes, could be utilized for assessing conformational motions’ impact on catalytic reactions. Full article

Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed. Full article