Filip Leonarski

New more accurate calculations of the ground state potential energy surface of H3

Explicitly correlated Gaussian functions with floating centers have been employed to recalculate the ground state potential energy surface (PES) of the H(3) (+) ion with much higher accuracy than it was done before. The nonlinear parameters of the Gaussians (i.e., the exponents and the centers) have been variationally optimized with a procedure employing the analytical gradient of the energy with respect to these parameters. The basis sets for calculating new PES points were guessed from the points already calculated. This allowed us to considerably speed up the calculations and achieve very high accuracy of the results.

Charge asymmetry in pure vibrational states of the HD molecule

Very accurate variational calculations of all rotationless states (also called pure vibrational states) of the HD molecule have been performed within the framework that does not assume the Born-Oppenheimer (BO) approximation. The non-BO wave functions of the states describing the internal motion of the proton, the deuteron, and the two electrons were expanded in terms of one-center explicitly correlated Gaussian functions multiplied by even powers of the internuclear distance. Up to 6000 functions were used for each state. Both linear and nonlinear parameters of the wave functions of all 18 states were optimized with a procedure that employs the analytical gradient of the energy with respect to the nonlinear parameters of the Gaussians. These wave functions were used to calculate expectation values of the interparticle distances and some other related quantities. The results allow elucidation of the charge asymmetry in HD as a function of the vibrational excitation.

Evolutionary Algorithm in the Optimization of a Coarse-Grained Force Field.

Simulations using residue-scale coarse-grained models of biomolecules are less computationally demanding than simulations employing full-atomistic force fields. However, the coarse-grained models are often difficult and tedious to parametrize for certain applications. Therefore, a systematic and objective method to help develop or adapt the coarse-grained models is needed. We present an automatic method that implements an evolutionary algorithm to find a set of optimal force field parameters for a one-bead coarse-grained model. In addition to an optimized force field, parameter correlations and significance of the potential energy terms can be determined. The method is applied to two classes of problems: the dynamics of an RNA helix and the RNA structure prediction.

Altering the Orientation of Proteins on Self-Assembled Monolayers: A Computational Study

A combined computational docking-molecular dynamics study has been performed on a system consisting of cytochrome c protein and alkanethiol self-assembled monolayers of various geometries. The results suggest that the orientation of the protein on the surface may be controlled or altered by means of designing specific structural motifs on the surface. The proposed computational approach may be used as a fast and reliable tool to complement other theoretical and experimental techniques of exploring other protein-surface interfaces.

Modeling Nucleic Acids at the Residue-Level Resolution

Coarse–grained models and force fields have become useful in the studies of the dynamics and physicochemical properties of nucleic acids. Reduced representations of DNA or RNA allow saving computational cost of a few orders of magnitude in comparison with full–atomistic simulations. In this chapter we describe a few selected coarse–grained models of nucleic acids in which one nucleotide is represented as either one, two or three beads. We present the examples of the models designed to investigate the internal dynamics and temperature-dependent denaturation of nucleic acids, as well as created to predict the tertiary structure of RNA or used for large ribonucleoprotein complexes. We describe how the purpose of the model affects the design of the potential energy function and the choice of the simulation method. We also address the limitations of these models.

Genetic algorithm optimization of force field parameters: application to a coarse-grained model of RNA

Determining force field parameters for molecular dynamics simulations of reduced models of biomolecules is a long, troublesome, and exhaustive process that is often performed manually. To improve this parametrization procedure we apply a continuous-space Genetic Algorithm (GA). GA is implemented to optimize parameters of a coarsegrained potential energy function of ribonucleic acid (RNA) molecules. The parameters obtained using GA are correctly reproducing the dynamical behavior of an RNA helix and other RNA tertiary motifs. Therefore, GA can be a useful tool for force field parametrization of the effective potentials in coarse-grained molecular models.

Asymmetric Behavior of Thymidylate Synthase Dimer Subunits in Denaturating Solvent Observed with Molecular Dynamics

A molecular dynamics simulations of the thymidylate synthase denaturation in chaotrope solvents (urea, guanidinium hydrochloride) were performed on 600 ns timescale. It appeared that this dimeric enzyme undergoes partial unfolding asymmetrically. It was shown also that urea is a better denaturant in the MD condition, as compared to guanidinium chloride. The unfolding occurs first at the external helices (AA 88-118) and follows by the AA 188-200 region. The present results correspond to the suggested in the literature activity of thymidylate synthase through a half-the-site mechanism.

RedMDStream: Parameterization and Simulation Toolbox for Coarse-Grained Molecular Dynamics Models

Coarse-grained (CG) models in molecular dynamics (MD) are powerful tools to simulate the dynamics of large biomolecular systems on micro- to millisecond timescales. However, the CG model, potential energy terms, and parameters are typically not transferable between different molecules and problems. So parameterizing CG force fields, which is both tedious and time-consuming, is often necessary. We present RedMDStream, a software for developing, testing, and simulating biomolecules with CG MD models. Development includes an automatic procedure for the optimization of potential energy parameters based on metaheuristic methods. As an example we describe the parameterization of a simple CG MD model of an RNA hairpin.