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Most proteins perform their biological function by interacting with one or more molecular partners. In this respect, characterizing local features of the molecular surface, that can potentially be involved in the interaction with other molecules, represents a step forward in the investigation of the mechanisms of recognition and binding between molecules. Predictive methods often rely on extensive samplings of molecular patches with the aim to identify hot spots on the surface. In this framework, analysis of large proteins and/or many molecular dynamics frames is often unfeasible due to the high computational cost. Thus, finding optimal ways to reduce the number of points to be sampled maintaining the biological information (including the surface shape) carried by the molecular surface is pivotal. In this perspective, we here present a new theoretical and computational algorithm with the aim of defining a set of molecular surfaces composed of points not uniformly distributed in space, in such a way as to maximize the information of the overall shape of the molecule by minimizing the number of total points. We test our procedure's ability in recognizing hot-spots by describing the local shape properties of portions of molecular surfaces through a recently developed method based on the formalism of 2D Zernike polynomials. The results of this work show the ability of the proposed algorithm to preserve the key information of the molecular surface using a reduced number of points compared to the complete surface, where all points of the surface are used for the description. In fact, the methodology shows a significant gain of the information stored in the sampling procedure compared to uniform random sampling. [ABSTRACT FROM AUTHOR]

As the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic continues to spread, several variants of the virus, with mutations distributed all over the viral genome, are emerging. While most of the variants present mutations having little to no effects at the phenotypic level, some of these variants are spreading at a rate that suggests they may present a selective advantage. In particular, these rapidly spreading variants present specific mutations on the spike protein. These observations call for an urgent need to characterize the effects of these variants' mutations on phenotype features like contagiousness and antigenicity. With this aim, we performed molecular dynamics simulations on a selected set of possible spike variants in order to assess the stabilizing effect of particular amino acid substitutions on the molecular complex. We specifically focused on the mutations that are both characteristic of the top three most worrying variants at the moment, i.e the English, South African, and Amazonian ones, and that occur at the molecular interface between SARS-CoV-2 spike protein and its human ACE2 receptor. We characterize these variants' effect in terms of (i) residue mobility, (ii) compactness, studying the network of interactions at the interface, and (iii) variation of shape complementarity via expanding the molecular surfaces in the Zernike basis. Overall, our analyses highlighted greater stability of the three variant complexes with respect to both the wild type and two negative control systems, especially for the English and Amazonian variants. In addition, in the three variants, we investigate the effects a not-yet observed mutation in position 501 could provoke on complex stability. We found that a phenylalanine mutation behaves similarly to the English variant and may cooperate in further increasing the stability of the South African one, hinting at the need for careful surveillance for the emergence of these mutations in the population. Ultimately, we show that the proposed observables describe key features for the stability of the ACE2-spike complex and can help to monitor further possible spike variants. Miotto et al. perform molecular dynamics simulations on a selected set of possible SARS-CoV-2 spike variants in order to assess the stabilizing effect of particular amino acid substitutions on the molecular complex. Their analysis can help to monitor further possible spike variants. [ABSTRACT FROM AUTHOR]

We discuss the role of non-hydrodynamic processes in viscoelastic transition in pure liquids. In particular, using both analytical results and molecular dynamics simulations, we clarify the effect of the shear stress relaxation on the transverse dynamics. We use as an example the Lennard-Jones fluids. We analyse the frequency dependence of the shear modulus and its connection to the non-hydrodynamic shear relaxation mode. The analysis of the relaxation times of the non-hydrodynamic modes in longitudinal and transverse dynamics makes evidence that the emergence of the non-hydrodynamic transverse excitations outside the propagation gap is not directly connected to the onset of the positive sound dispersion. [ABSTRACT FROM AUTHOR]

Molecular dynamics (MD) simulations of the glass-former 2Ca(NO3)2·3KNO3, CKN, were performed as a function of temperature at pressures 0.1 MPa, 0.5 GPa, 1.0 GPa, and 2.0 GPa. Diffusion coefficient, relaxation time of the intermediate scattering function, and anion reorientational time were obtained as a function of temperature and densitiy ρ. These dynamical properties of CKN scale as ργ/T with a common value γ = 1.8 ± 0.1. The scaling parameter γ is consistent with the exponent of the repulsive part of an effective intermolecular potential for the repulsion between the atoms at shortest distance in the equilibrium structure of liquid CKN, Ca2+, and oxygen atoms of NO3-. Correlation between potential energy and virial is obeyed for the short-range terms of the potential function, but not for the whole potential including coulombic interactions. Decoupling of diffusion coefficient and reorientational relaxation time from relaxation time take place at a given ργ/T value, i.e., breakdown of Stokes-Einstein and Debye-Stokes-Einstein equations result from combined thermal and volume effects. The MD results agree with correlations proposed between long-time relaxation and short-time dynamics, lnτ ∝ 1/, where the mean square displacement concerns a time window of 10.0 ps. It has been found that scales as ργ/T above and below the glass transition temperature, so that thermodynamic scaling of liquid dynamics can be thought as a consequence of theories relating short- and long-time dynamics, and the more fundamental scaling concerns short-time dynamical properties. [ABSTRACT FROM AUTHOR]

Molecular dynamics simulations of the glass-forming liquid 2Ca(NO3)2·3KNO3 (CKN) were performed from high temperature liquid states down to low temperature glassy states at six different pressures from 10-4 to 5.0 GPa. The temperature dependence of the structural relaxation time indicates that the fragility of liquid CKN changes with pressure. In line with recent proposal [Scopigno et al., Science 302, 849 (2003)], the change on liquid fragility is followed by a proportional change of the nonergodicity factor of the corresponding glass at low temperature. [ABSTRACT FROM AUTHOR]

A new methodology of calculation of dispersion and damping of collective excitations fromab initiomolecular dynamics (AIMD) of liquid metals is proposed. It is suggested to use for the analysis of AIMD-derived time correlation functions a thermo-viscoelastic dynamic model within an approach of the generalised collective modes. The proposed scheme, in which the viscoelastic matrix elements of the generalised hydrodynamic matrix are directly calculated from AIMD and the matrix elements requiring knowledge of energy density fluctuations in the system are treated as fitting parameters, allows to recover AIMD time correlation functions in a wide range of wave numbers. The dispersion and damping of collective excitations are obtained as a complex-conjugated pair of the generalised hydrodynamic matrix. An issue of sum rules in the proposed scheme is discussed. The methodology is applied for calculations of dispersion and damping of generalised acoustic modes in molten lithium. [ABSTRACT FROM AUTHOR]

Abstract: We report scaling results on the world’s largest supercomputer of our recently developed Billions-Body Molecular Dynamics (BBMD) package, which was especially designed for massively parallel simulations of the short-range atomic dynamics in structural glasses and amorphous materials. The code was able to scale up to 72 racks of an IBM BlueGene/P, with a measured 89% efficiency for a system with 100 billion particles. The code speed, with 0.13s per iteration in the case of 1 billion particles, paves the way to the study of billion-body structural glasses with a resolution increase of two orders of magnitude with respect to the largest simulation ever reported. We demonstrate the effectiveness of our code by studying the liquid–glass transition of an exceptionally large system made by a binary mixture of 1 billion particles. [Copyright &y& Elsevier]

Dispersion and damping of collective excitations in supercritical argon along the isothermal line of 280 K are studied by a combination of molecular dynamics simulations and Generalized Collective Mode (GCM) analysis. ‘Positive dispersion’ of collective excitations and its dependence on density is discussed on the basis of GCM theory of ‘positive dispersion’. [ABSTRACT FROM AUTHOR]

Many of the molecular mechanisms underlying the pathological aggregation of proteins observed in neurodegenerative diseases are still not fully understood. Among the aggregate-associated diseases, Amyotrophic Lateral Sclerosis (ALS) is of relevant importance. In fact, although understanding the processes that cause the disease is still an open challenge, its relationship with protein aggregation is widely known. In particular, human TDP-43, an RNA/DNA binding protein, is a major component of the pathological cytoplasmic inclusions observed in ALS patients. Indeed, the deposition of the phosphorylated full-length TDP-43 in spinal cord cells has been widely studied. Moreover, it has also been shown that the brain cortex presents an accumulation of phosphorylated C-terminal fragments (CTFs). Even if it is debated whether the aggregation of CTFs represents a primary cause of ALS, it is a hallmark of TDP-43 related neurodegeneration in the brain. Here, we investigate the CTFs aggregation process, providing a computational model of interaction based on the evaluation of shape complementarity at the molecular interfaces. To this end, extensive Molecular Dynamics (MD) simulations were conducted for different types of protein fragments, with the aim of exploring the equilibrium conformations. Adopting a newly developed approach based on Zernike polynomials, able to find complementary regions in the molecular surface, we sampled a large set of solvent-exposed portions of CTFs structures as obtained from MD simulations. Our analysis proposes and assesses a set of possible association mechanisms between the CTFs, which could drive the aggregation process of the CTFs. To further evaluate the structural details of such associations, we perform molecular docking and additional MD simulations to propose possible complexes and assess their stability, focusing on complexes whose interacting regions are both characterized by a high shape complementarity and involve β 3 and β 5 strands at their interfaces. [ABSTRACT FROM AUTHOR]

Exact relation for contributions to heat capacity of liquids is obtained from hydrodynamic theory. It is shown from analysis of the long-wavelength limit of heat density autocorrelation functions that the heat capacity of simple liquids is represented as a sum of two contributions due to 'phonon-like' collective excitations and heat relaxation. The ratio of both contributions being the analogy of Landau-Placzek ratio for heat processes depends on the specific heats ratio. The theory of heat density autocorrelation functions in liquids is verified by computer simulations. Molecular dynamics simulations for six liquids having the ratio of specific heats γ in the range 1.1-2.3, were used for evaluation of the heat density autocorrelation functions and predicted Landau-Placzek ratio for heat processes. The dependence of contributions from collective excitations and heat relaxation process to specific heat on γ is shown to be in excellent agreement with the theory. [ABSTRACT FROM AUTHOR]

Static and dynamic autocorrelations of charge density, composed of positive point ions and instantaneous distribution of electron density, are studied in liquid Li in a pressure range from ambient to 186 GPa using ab initio molecular dynamics simulations. It is shown analytically that the long-wavelength limit of the charge-charge static structure factor SQQ (k) of liquid metals is proportional to k4. Time-dependent charge-charge correlations in liquid Li at low pressures show identical relaxation as the density-density time correlation functions, in complete agreement with the linear response theory, whereas at extreme pressures we observed different relaxation of the charge and density autocorrelations. The static and dynamic properties of a part of electron density, that corresponds to the nonspherical distribution around ions, are discussed. [ABSTRACT FROM AUTHOR]

The SARS-CoV-2 pandemic still poses a threat to the global health as the virus continues spreading in most countries. Therefore, the identification of molecules capable of inhibiting the binding between the ACE2 receptor and the SARS-CoV-2 spike protein is of paramount importance. Recently, two DNA aptamers were designed with the aim to inhibit the interaction between the ACE2 receptor and the spike protein of SARS-CoV-2. Indeed, the two molecules interact with the ACE2 receptor in the region around the K353 residue, preventing its binding of the spike protein. If on the one hand this inhibition process hinders the entry of the virus into the host cell, it could lead to a series of side effects, both in physiological and pathological conditions, preventing the correct functioning of the ACE2 receptor. Here, we discuss through a computational study the possible effect of these two very promising DNA aptamers, investigating all possible interactions between ACE2 and its experimentally known molecular partners. Our in silico predictions show that some of the 10 known molecular partners of ACE2 could interact, physiologically or pathologically, in a region adjacent to the K353 residue. Thus, the curative action of the proposed DNA aptamers could recruit ACE2 from its biological functions. • The DNA aptamers could prevent the binding between ACE2 and its molecular partners. • The action of the two DNA aptamers could recruit ACE2 from its biological functions. • The MP-ACE2 predicted complexes were studied with molecular dynamics simulations. • The stability of the interaction between ACE2 and its MPs was analyzed in MD. [ABSTRACT FROM AUTHOR]