arXiv subjects

Pablo M. Blanco

Publications and source records attributed to Pablo M. Blanco.

6 recordsLinked to original sources

arXiv2026

Short Peptide Tails Modulate DNA Association and Condensation by PAMAM Dendrimers

Poly(amidoamine) (PAMAM) dendrimers are promising candidates for nucleic acid delivery; however, biocompatibility and transfection efficiency remain a challenge. Here, we investigated how the composition of short peptide tails conjugated to generation 2 PAMAM (G2) dendrimers influence DNA association and condensation across a range of pH values. Using a combination of potentiometric titrations, DNA precipitation assays, and coarse-grained molecular simulations with charge regulation, we show that the ionization of G2 dendrimers is strongly affected by both pH and proximity to DNA. Although charge regulation enhances dendrimer protonation and strengthens DNA association at low pH, DNA condensation by unmodified G2 remains largely insensitive to pH within the studied range. In contrast, conjugation of a single peptide tail introduces a pronounced pH dependence to DNA condensation. Histidine-containing conjugates exhibit the strongest response, with condensation efficiency decreasing markedly as the pH increases. Simulations reveal that the interaction strength between conjugates and DNA depends on both peptide composition and pH and that histidine-containing peptide tails become nearly neutral at physiological pH, contributing little to DNA binding. While single-conjugate simulations explain the trends in DNA association, they do not fully account for the observed condensation behavior, highlighting the importance of collective effects involving multiple conjugates. Overall, peptide conjugation transforms G2 PAMAM dendrimers from relatively pH-insensitive DNA condensing agents into pH-responsive DNA-binding systems. These findings provide molecular-level insight into the interplay between charge regulation, peptide composition, and DNA condensation.

cond-mat.soft↗

arXiv2026

Cooperative Conformational Transitions in Macromolecules under Mechanical Stretching. An Exactly Solved Model for Single Molecule Experiments

The stretching behavior of linear macromolecules undergoing conformational transitions is investigated. An exact solution is provided for a two-state system within the elastic freely jointed chain model. This minimal framework contains the smallest set of parameters required to describe such transitions: two Kuhn lengths, two elastic force constants, a free energy difference between both states and a nearest-neighbor interaction energy accounting for cooperativity. Explicit analytical expressions are derived for the chain extension and the probabilities of each state as functions of the applied force.The approach accurately reproduces the experimental force-extension curves of poly(ethylene-glycol) (PEG) and hyaluronic acid (HA), revealing no cooperativity for PEG and negative cooperativity for HA. It also describes the B-DNA to S-DNA conformational transition, a process that exhibits positive cooperativity.We analyze the mathematical conditions required for a transition and identify two fundamental driving mechanisms: differences in Kuhn lengths and differences in force constants.Extensions of the model to systems with more than two conformational states per Kuhn segment are also discussed. The results presented here apply equally to transitions that are intrinsic to the macromolecular structure or induced by ligand-receptor interactions, unifying both cases within a single thermodynamically consistent framework.

cond-mat.soft↗

arXiv2025

When and How Ultrasound Enhances Nanoparticle Diffusion in Hydrogels: A Stick-and-Release Mechanism

Nanoparticles (NPs) are widely used as drug carriers in cancer therapy due to their ability to accumulate in tumor tissue via the enhanced permeability and retention effect. However, their transport within tumors is often hindered by the dense extracellular matrix, where diffusion dominates. Several studies suggest that ultrasound (US) irradiation can enhance NP diffusion in ECM-mimicking hydrogels, yet the underlying molecular mechanisms remain unclear, and experimental findings are often contradictory. Here, we use coarse-grained Langevin Dynamics simulations to investigate the conditions under which US can enhance NP diffusion in hydrogels. After validating our simulation framework against an exact analytical solution for NP motion under US in dilute buffer, we systematically explore NP diffusion in hydrogels with varying degrees of NP-network attraction. Our results reveal that acoustic enhancement arises from reduced contact time between NPs and the hydrogel matrix. This effect becomes significant only when NP-hydrogel interactions are sufficiently strong and US pulses are long enough to disrupt these interactions, following a "stick-and-release" mechanism. These findings reconcile previously conflicting experimental observations and explain why acoustic enhancement is observed in some studies but not others. Overall, our study provides a molecular-level explanation for US-enhanced NP diffusion in hydrogels and establishes design principles for optimizing therapeutic US protocols in drug delivery applications.

cond-mat.soft↗

arXiv2024

The explicit bonding Reaction ensemble Monte Carlo method

We present the explicit bonding Reaction ensemble Monte Carlo (eb-RxMC) method, designed to sample reversible bonding reactions in macromolecular systems in thermodynamic equilibrium. Our eb-RxMC method is based on the Reaction ensemble method, however, its implementation differs from the latter by the representation of the reaction. In the eb-RxMC implementation, we are adding or deleting bonds between existing particles, instead of inserting or deleting particles with different chemical identities. This new implementation makes the eb-RxMC method suitable for simulating the formation of reversible linkages between macromolecules, which would not be feasible with the original implementation. To enable coupling of our eb-RxMC algorithm with Molecular Dynamics algorithm for sampling of the configuration space, we biased the sampling of reactions only within a certain inclusion radius. We validated our algorithm using a set of ideally behaving systems undergoing dimerization and polycondensation reactions, for which analytical results are available. For dimerization reactions with various equilibrium constants and initial compositions, the degree of conversion measured in our simulations perfectly matched the reference values given by the analytical equations. We also showed that this agreement is not affected by the arbitrary choice of the inclusion radius or the stiffness of the harmonic bond potential. Next, we showed that our simulations can correctly match the analytical results for the distribution of the degree of polymerization and end-to-end distance of ideal chains in polycondensation reactions. Altogether, we demonstrated that our eb-RxMC simulations correctly sample both reaction and configuration space of these reference systems, opening the door to future simulations of more complex interacting macromolecular systems.

cond-mat.soft↗

arXiv2024

pyMBE: the Python-based Molecule Builder for ESPResSo

We present the Python-based Molecule Builder for ESPResSo (pyMBE), an open source software to design custom Coarse-Grained (CG) models, as well as pre-defined models of polyelectrolytes, peptides and globular proteins in the Extensible Simulation Package for Research on Soft Matter (ESPResSo). The Python interface of \espresso offers a flexible framework, capable of building custom CG models from scratch. As a downside, building CG models from scratch is error-prone, especially for newcomers in the field of CG modeling, or for molecules with complex architectures. The pyMBE module builds CG models in \espresso using a hierarchical bottom-up approach, providing a robust tool to automate the setup of CG models and helping new users prevent common mistakes. ESPResSo features the constant pH (cpH) and grand-reaction (G-RxMC) methods, which have been designed to study chemical reaction equilibria in macromolecular systems with many reactive species. However, setting up these methods for systems which contain several types of reactive groups is an error-prone task, especially for beginners. The pyMBE module enables the automatic setup of cpH and G-RxMC simulations in \espresso, lowering the barrier for newcomers and opening the door to investigate complex systems not studied with these methods yet. To demonstrate some of the applications of pyMBE, we showcase several case studies where we successfully reproduce previously published simulations of charge-regulating peptides and globular proteins in bulk solution and weak polyelectrolytes in dialysis. The pyMBE module is publicly available as a GitHub repository (https://github.com/pyMBE-dev/pyMBE) which includes its source code and various sample and test scripts, including the ones that we used to generate the data presented in this article.

cond-mat.soft↗

arXiv2024

Exact solution for a general FJC polyelectrolyte model with up to Next Nearest Neighbour Interactions

This work presents a polyelectrolyte (PE) model based on a freely jointed chain (FJC) in which the beads are ionizable and the bonds are rigid. Electrostatic interactions considered are of the short range type up to next-nearest neighbours using a Debye-Hückel (DH) potential. Exact expressions for the conformational and protonation properties are obtained as a function of the pH using the transfer matrix method and the integration of the angular variables. For the finite cases with low N values, relevant differences arise on both the protonation curve and the end to end distance due to the end effects. However, when increasing N a rather rapid convergence is observed to the infinite chain limiting case.

cond-mat.soft↗