arXiv subjects

Uriel N. Morzan

Publications and source records attributed to Uriel N. Morzan.

6 recordsLinked to original sources

arXiv2024

Exploring the Mechanisms Behind Non Aromatic Fluorescence with Density Functional Tight Binding Method

Recent experimental findings reveal non-conventional fluorescence emission in biological systems devoid of conjugated bonds or aromatic compounds, termed \textit{Non-Aromatic Fluorescence} (NAF). This phenomenon is exclusive to aggregated or solid states, remaining absent in monomeric solutions. Previous studies focused on small model systems in vacuum show that the carbonyl stretching mode along with strong interaction of short hydrogen bonds (SHBs) remain the primary vibrational mode explaining NAF in these systems. In order to simulate larger model systems taking into account the effects of the surrounding environment, in this work we propose using the density functional tight-binding (DFTB) method in combination with non-adiabatic molecular dynamics (NAMD) and the mixed quantum/molecular mechanics (QM/MM) approach. We investigate the mechanism behind NAF in the crystal structure of L-pyroglutamine-ammonium, comparing it with the related non-fluorescent amino acid L-glutamine. Our results extend our previous findings to more realistic systems, demonstrating the efficiency and robustness of the proposed DFTB method in the context of NAMD in biological systems. Furthemore, due to its inherent low computational cost, this method allows for a better sampling on the non-radiative events at the conical intersection which is crucial for a complete understanding of this phenomenon. Beyond contributing to the ongoing exploration of NAF, this work paves the way for future application of this method in more complex biological systems such as amyloid aggregates, biomaterials and non-aromatic proteins.

physics.chem-ph↗

arXiv2024

Aqueous Solution Chemistry In Silico and the Role of Data Driven Approaches

The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has been a tremendous growth in the use of data-driven approaches to develop more accurate potentials for water as well as to characterize its complexity in chemical and biological contexts. We highlight the progress, giving a historical context, on the path to the development of many-body and reactive potentials to model aqueous chemistry, including the role of machine learning strategies. We focus specifically on conceptual and methodological challenges along the way in performing simulations that seek to tackle problems in modeling the chemistry of aqueous solutions. In conclusion, we summarize our perspectives on the use and integration of advanced data-science techniques to provide chemical insights in physical chemistry and how this will influence computer simulations of aqueous systems in the future.

physics.chem-ph↗

arXiv2023

Water Self-Dissociation is Insensitive to Nanoscale Environments

Nanoconfinement effects on water dissociation and reactivity remain controversial, despite their importance to understand the aqueous chemistry at interfaces, pores, or aerosols. The pKw in confined environments has been assessed from experiments and simulations in a few specific cases, leading to dissimilar conclusions. Here, with the use of carefully designed \textit{ab-initio} simulations, we demonstrate that the energetics of bulk water dissociation is conserved intact to unexpectedly small length-scales, down to aggregates of only a dozen molecules or pores of widths below 2 nm. The reason is that most of the free-energy involved in water autoionization comes from breaking the O-H covalent bond, which has a comparable barrier in the bulk liquid, in a small droplet of nanometer size, or in a nanopore in the absence of strong interfacial interactions. Thus, dissociation free-energy profiles in nanoscopic aggregates or in 2D slabs of 1 nm width reproduce the behavior corresponding to the bulk liquid, regardless of whether the corresponding nanophase is delimited by a solid or a gas interface. The present work provides a definite and fundamental description of the mechanism and thermodynamics of water dissociation at different scales with broader implications on reactivity and self-ionization at the air-liquid interface.

cond-mat.soft↗

arXiv2022

The Collective Burst Mechanism of Angular Jumps in Liquid Water

Understanding the microscopic origins of collective reorientational motions in aqueous systems requires techniques that allow us to reach beyond our chemical imagination. Herein, we elucidate a mechanism using unsupervised learning, showing that large angular jumps in liquid water involve highly cooperative orchestrated motions. Our automatized detection of angular fluctuations, unravels a heterogeneity in the type of angular jumps occurring concertedly in the system. We show that large orientational motions require a highly collective dynamic process involving correlated motion of up to 10% of water molecules in the hydrogen-bond network that form spatially connected clusters. This phenomenon is rooted in the collective fluctuations of the network topology which results in the creation of defects in waves on the ThZ timescale. The mechanism we propose involves a cascade of hydrogen-bond fluctuations underlying angular jumps and provides new insights into the current localized picture of angular jumps, and in its wide use in the interpretations of numerous spectroscopies as well in reorientational dynamics of water near biological and inorganic systems.

cond-mat.soft↗

arXiv2018

Eigenvector Centrality Distribution for Characterization of Protein Allosteric Pathways

Determining the principal energy pathways for allosteric communication in biomolecules, that occur as a result of thermal motion, remains challenging due to the intrinsic complexity of the systems involved. Graph theory provides an approach for making sense of such complexity, where allosteric proteins can be represented as networks of amino acids. In this work, we establish the eigenvector centrality metric in terms of the mutual information, as a mean of elucidating the allosteric mechanism that regulates the enzymatic activity of proteins. Moreover, we propose a strategy to characterize the range of the physical interactions that underlie the allosteric process. In particular, the well known enzyme, imidazol glycerol phosphate synthase (IGPS), is utilized to test the proposed methodology. The eigenvector centrality measurement successfully describes the allosteric pathways of IGPS, and allows to pinpoint key amino acids in terms of their relevance in the momentum transfer process. The resulting insight can be utilized for refining the control of IGPS activity, widening the scope for its engineering. Furthermore, we propose a new centrality metric quantifying the relevance of the surroundings of each residue. In addition, the proposed technique is validated against experimental solution NMR measurements yielding fully consistent results. Overall, the methodologies proposed in the present work constitute a powerful and cost effective strategy to gain insight on the allosteric mechanism of proteins.

q-bio.BM↗

arXiv2016

Electron transport in real time from first-principles

While the vast majority of calculations reported on molecular conductance have been based on the static non-equilibrium Green's function formalism combined with density functional theory, in recent years a few time-depedent approaches to transport have started to emerge. Among these, the driven Liouville-von Neumann equation (J. Chem. Phys. 124, 214708 (2006)) is a simple and appealing route relying on a tunable rate parameter, which has been explored in the context of semi-empirical methods. In the present study, we adapt this formulation to a density functional theory framework and analyze its performance. In particular, it is implemented in an efficient all-electron DFT code with Gaussian basis functions, suitable for quantum-dynamics simulations of large molecular systems. At variance with the case of the tight-binding calculations reported in the literature, we find that now the initial perturbation to drive the system out of equilibrium plays a fundamental role in the stability of the electron dynamics, and that the equation of motion used in previous tight-binding implementations has to be modified to conserve the total number of particles during time propagation. Moreover, we propose a procedure to get rid of the dependence of the current-voltage curves on the rate parameter. This method is employed to obtain the current-voltage characteristic of saturated and unsaturated hydrocarbons of different lenghts, with very promising prospects.

cond-mat.mtrl-sci↗