Omar Valsson

• PhD
• Professor (Assistant) at University of North Texas

In computational physics, chemistry, and biology, the implementation of new techniques in shared and open-source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several challenges. Common methods like direct knowledge transfer and in-person workshops are limited in...

Targeted protein degradation has emerged as a promising strategy for developing novel therapeutics, particularly for "undruggable" disease-related proteins. One approach is the use of PROteolysis TArgeting Chimeras (PROTACs) degraders, which induce the formation of ternary complexes between the target protein and E3 ligase, leading to ubiquitinatio...

In computational physics, chemistry, and biology, the implementation of new techniques in a shared and open source software lowers barriers to entry and promotes rapid scientific progress. However, effectively training new software users presents several challenges. Common methods like direct knowledge transfer and in-person workshops are limited i...

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, th...

Analyzing large volumes of high-dimensional data requires dimensionality reduction: finding meaningful low-dimensional structures hidden in their high-dimensional observations. Such practice is needed in atomistic simulations of complex systems where even thousands of degrees of freedom are sampled. An abundance of such data makes gaining insight i...

Acrylic polymers, commonly used in paints, can degrade over time by several different chemical and physical mechanisms, depending on structure and exposure conditions. While exposure to UV light and temperature results in irreversible chemical damage, acrylic paint surfaces in museums can also accumulate pollutants, such as volatile organic compoun...

Analyzing large volumes of high-dimensional data requires dimensionality reduction: finding meaningful low-dimensional structures hidden in their high-dimensional observations. Such practice is needed in atomistic simulations of dynamical systems where even thousands of degrees of freedom are sampled. An abundance of such data makes it strenuous to...

A common problem that affects simulations of complex systems within the computational physics and chemistry communities is the so-called sampling problem or rare event problem where proper sampling of energy landscapes is impeded by the presences of high kinetic barriers that hinder transitions between metastable states on typical simulation time s...

The steric stability of inorganic colloidal particles in an apolar solvent is usually described in terms of the balance between three contributions: the van der Waals attraction, the free energy of mixing, and the ligand compression. However, in the case of nanoparticles, the discrete nature of the ligand shell and the solvent has to be taken into...

Enhanced sampling methods are indispensable in computational chemistry and physics, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space of dynamical systems due to the sampling problem. A class of such enhanced sampling methods works by identifying a few slow degrees of freedom, termed collective variable...

The steric stability of inorganic colloidal particles in an apolar solvent is usually described in terms of the balance between three contributions: the van der Waals attraction, the free energy of mixing, and the ligand compression. However, in the case of nanoparticles, the discrete nature of the ligand shell and the solvent has to be taken into...

A common problem that affects simulations of complex systems within the computational physics and chemistry communities is the so-called sampling problem or rare event problem where proper sampling of energy landscapes is impeded by the presences of high kinetic barriers that hinder transitions between metastable states on typical simulation time s...

The steric stability of inorganic colloidal particles in an apolar solvent is usually described in terms of the balance between three contributions: the van der Waals attraction, the free energy of mixing, and the ligand compression. However, in the case of nanoparticles, the discrete nature of the ligand shell and the solvent has to be taken into...

Enhanced sampling algorithms have emerged as powerful methods to extend the utility of molecular dynamics simulations and allow the sampling of larger portions of the configuration space of complex systems in a given amount of simulation time. This review aims to present the unifying principles of and differences between many of the computational m...

Enhanced sampling methods are indispensable in computational physics and chemistry, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space of dynamical systems due to the sampling problem. A class of such enhanced sampling methods works by identifying a few slow degrees of freedom, termed collective variable...

Collective variable-based enhanced sampling methods are routinely used on systems with metastable states, where high free energy barriers impede the proper sampling of the free energy landscapes when using conventional molecular dynamics simulations. One such method is variationally enhanced sampling (VES), which is based on a variational principle...

The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data principles (Findable, Accessible, Interoperable, and Reusable) must not be too narrow. Besides, th...

Collective variable-based enhanced sampling methods are routinely used on systems with metastable states, where high free energy barriers impede proper sampling of the free energy landscapes when using conventional molecular dynamics simulations. One such method is variationally enhanced sampling (VES), which is based on a variational principle whe...

Enhanced sampling algorithms have emerged as powerful methods to extend the potential of molecular dynamics simulations and allow the sampling of larger portions of the configuration space of complex systems. This review aims to present the unifying principles and differences of several computational methods for enhanced sampling in molecular simul...

Most of the artwork and cultural heritage objects are stored in museums under conditions that are difficult to monitor. While advanced technologies aim to control and prevent the degradation of cultural heritage objects in line with preventive conservation measures, there is much to be learned in terms of the physical processes that lead to the deg...

Machine learning methods provide a general framework for automatically finding and representing the essential characteristics of simulation data. This task is particularly crucial in enhanced sampling simulations. There we seek a few generalized degrees of freedom, referred to as collective variables (CVs), to represent and drive the sampling of th...

Polymorphism rationalizes how processing can control the final structure of a material. The rugged free-energy landscape and exceedingly slow kinetics in the solid state have so far hampered computational investigations. We report for the first time the free-energy landscape of a polymorphic crystalline polymer, syndiotactic polystyrene. Coarse-gra...

DOI:https://doi.org/10.1103/PhysRevLett.125.159902

RNA molecules selectively bind to specific metal ions to populate their functional active states making it important to understand their source of ion selectivity. In large RNA systems, metal ions interact with the RNA at multiple locations making it difficult to decipher the precise role of ions in folding. To overcome this complexity, we studied...

Polymorphism rationalizes how processing can control the final structure of a material. The rugged free-energy landscape and exceedingly slow kinetics in the solid state have so far hampered computational investigations. We report for the first time the free-energy landscape of a polymorphic crystalline polymer, syndiotactic polystyrene. Coarse-gra...

Machine learning methods provide a general framework for automatically finding and representing the essential characteristics of simulation data. This task is particularly crucial in enhanced sampling simulations, where we seek a few generalized degrees of freedom, referred to as collective variables (CVs), to represent and drive the sampling of th...

RNA molecules selectively bind to specific metal ions to populate their functional active states making it important to understand their source of ion selectivity. In large RNA systems, metal ions interact with the RNA at multiple locations making it difficult to decipher the precise role of ions in folding. To overcome this complexity, we studied...

Searching for reaction pathways describing rare events in large systems presents a long-standing challenge in chemistry and physics. Incorrectly computed reaction pathways result in the degeneracy of microscopic configurations and inability to sample hidden energy barriers. To this aim, we present a general enhanced sampling method to find multiple...

Searching for reaction pathways of large systems presents a long-standing challenge in physics. We present a general molecular dynamics method to find multiple diverse reaction pathways of ligand unbinding through minimization of a loss function describing ligand--protein interactions. The method successfully overcomes large energy barriers using a...

We study by computer simulation the nucleation of a supersaturated Lennard-Jones vapor into the liquid phase. The large free energy barriers to transition make the time scale of this process impossible to study by ordinary molecular dynamics simulations.Therefore we use a recently developed enhanced sampling method [Valsson and Parrinello, Phys. Re...

The numerical computation of chemical potential in dense, non-homogeneous fluids is a key problem in the study of confined fluids thermodynamics. To this day several methods have been proposed, however there is still need for a robust technique, capable of obtaining accurate estimates at large average densities. A widely established technique is th...

The numerical computation of chemical potential in dense, non-homogeneous fluids is a key problem in the study of confined fluids thermodynamics. To this day several methods have been proposed, however there is still need for a robust technique, capable of obtaining accurate estimates at large average densities. A widely established technique is th...

The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predictions of kinetics are particularly difficult because rates, in contrast to free energies, depend on the route taken and are thus not amenable to all enhanced sampling metho...

The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predictions of kinetics are particularly difficult because rates, in contrast to free energies, depend on the route taken and are thus not amenable to all enhanced sampling metho...

Many enhanced sampling methods, such as Umbrella Sampling, Metadynamics or Variationally Enhanced Sampling, rely on the identification of appropriate collective variables. For proteins, even small ones, finding appropriate collective variables has proven challenging. Here we suggest that the NMR $S^2$ order parameter can be used to this effect. We...

Many enhanced sampling methods, such as Umbrella Sampling, Metadynamics or Variationally Enhanced Sampling, rely on the identification of appropriate collective variables. For proteins, even small ones, finding appropriate collective variables has proven challenging. Here we suggest that the NMR $S^2$ order parameter can be used to this effect. We...

Significance A multiscale description is believed to be the only feasible route toward the simulation of complex systems. Yet moving from one scale to another is not a trivial task, and many different approaches can be taken. We propose here a systematic approach to go from a fine scale to a coarser one, based on the recently introduced variational...

We have studied the reaction dynamics of a prototypical organic reaction using a variationally optimized truncated bias to accelerate transitions between educts and products reactant states. The asymmetric SN2nucleophilic substitution reaction of fluoromethane and chloromethane CH3F + Cl- <=> CH3Cl + F- is considered and many independent biased mol...

Crystallization is a process of great practical relevance in which rare but crucial fluctuations lead to the formation of a solid phase starting from the liquid. Like in all first order first transitions there is an interplay between enthalpy and entropy. Based on this idea, we introduce two collective variables, one enthalpic and the other entropi...

Crystallization is a process of great practical relevance in which rare but crucial fluctuations lead to the formation of a solid phase starting from the liquid. Like in all first order first transitions there is an interplay between enthalpy and entropy. Based on this idea, to drive crystallization in molecular simulations, we introduce two collec...

In recent work, we demonstrated that it is possible to obtain approximate representations of high-dimensional free energy surfaces with variationally enhanced sampling (Shaffer, P.; Valsson, O.; Parrinello, M. Proc. Natl. Acad. Sci.,2016, 113, 17). The high-dimensional spaces considered in that work were the set of backbone dihedral angles of a sma...

Light-sensing in photoreceptor proteins is subtly modulated by the multiple interactions between the chromophoric unit and its binding pocket. Many theoretical and experimental studies have tried to uncover the fundamental origin of these interactions but reached contradictory conclusions as to whether electrostatics, polarization, or intrinsically...

We study by computer simulation the nucleation of a supersaturated Lennard-Jones vapor into the liquid phase. The large free energy barriers to transition make the time scale of this process impossible to study by ordinary molecular dynamics simulations. Therefore we use a recently developed enhanced sampling method [Valsson and Parrinello, Phys. R...

Atomistic simulations play a central role in many fields of science. However, their usefulness is often limited by the fact that many systems are characterized by several metastable states separated by high barriers, leading to kinetic bottlenecks. Transitions between metastable states are thus rare events that occur on significantly longer timesca...

Obtaining efficient sampling of multiple metastable states through molecular dynamics and hence determining free energy differences is central for understanding many important phenomena. Here we present a new biasing strategy, which employs the recent variationally enhanced sampling approach (Valsson and Parrinello, Phys. Rev. Lett. 2014, 113, 0906...

Significance The problem of sampling complex systems characterized by metastable states separated by kinetic bottlenecks is a universal one that has received much attention. Popular strategies involve applying a bias to a small number of collective variables. This strategy fails when the choice of collective variable is not clear or when the system...

We propose a new method to obtain kinetic properties of infrequent events from molecular dynamics simulation. The procedure employs a recently introduced variational approach [Valsson and Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] to construct a bias potential which acts in the space spanned by a small number of collective variables and is de...

We propose a simple yet effective iterative scheme that allows us to employ the well-tempered distribution as a target distribution for the collective variables in our recently introduced variational approach to enhanced sampling and free energy calculations [Valsson and Parrinello, Phys. Rev. Lett. 2014, 113, 090601]. The performance of the scheme...

The excited-state relaxation of retinal protonated Schiff bases (PSBs) is an important test case for biological applications of time-dependent (TD) density-functional theory (DFT). While well-known shortcomings of approximate TD-DFT might seem discouraging for application to PSB relaxation, progress continues to be made in the development of new fu...

The ability of widely used sampling methods, such as molecular dynamics or Monte Carlo, to explore complex free energy landscapes is severely hampered by the presence of kinetic bottlenecks. A large number of solutions have been proposed to alleviate this problem. Many are based on the introduction of a bias potential which is a function of a small...

We explore the performance of the well-tempered ensemble combined with parallel tempering (PT-WTE) in obtaining a thermodynamical description of a given molecular system. We carefully explain the theoretical procedure employed to extract all the relevant thermodynamical quantities from a PT-WTE simulation. As a specific molecular system, we conside...

Embedding potentials are frequently used to describe the effect of an environment on the electronic structure of molecules in larger systems, including their excited states. If such excitations are accompanied by significant rearrangements in the electron density of the embedded molecule, large differential polarization effects may take place, whic...

Bovine rhodopsin is the most extensively studied retinal protein and is considered the prototype of this important class of photosensitive biosystems involved in the process of vision. Many theoretical investigations have attempted to elucidate the role of the protein matrix in modulating the absorption of retinal chromophore in rhodopsin, but, whi...

We employ a variety of highly-correlated approaches including quantum Monte Carlo (QMC) and the n-electron valence state perturbation theory (NEVPT2) to compute the vertical excitation energies of retinal protonated Schiff base (RPSB) models in the gas phase. We find that the NEVPT2 excitation energies are in good agreement with the QMC values and...

We employ state-of-the-art first-principle approaches to investigate whether temperature effects are responsible for the unusually broad and flat spectrum of protonated Schiff base retinal observed in photodissociation spectroscopy, as has recently been proposed. We first carefully calibrate how to construct a realistic geometrical model of retinal...

The simplest cyanine dye series [H2N(CH)nNH2]+ with n = 1, 3, 5, 7, and 9 appears to be a challenge for all theoretical excited-state methods since the experimental spectra are difficult to predict and the observed deviations cannot be easily explained with standard arguments. We compute here the lowest vertical excitation energies of these dyes us...

We present a systematic investigation of the structural relaxation in the excited state of model retinal chromophores in the gas phase using the complete-active-space self-consistent theory (CASSCF), multiconfigurational second-order perturbation theory (CASPT2), quantum Monte Carlo (QMC), and coupled cluster (CC) methods. In contrast to the CASSCF...

We investigate phase coherent electronic transport in an open quantum system, which consists of quantum dots side-coupled to a nanowire. It is demonstrated that coherent switching can be characterized by adjusting the electronic energy. A comparative analysis of quantum coherence effects in side-coupled quantum-dot systems is presented. Our results...