Computation Of Electrostatic Potential Research Articles

DAMQT 3: Advanced suite for the analysis of molecular density and related properties in large systems

A new version of the DAMQT package specially developed for large systems is reported. The graphical part has been entirely redesigned, using new OpenGL libraries (versions 3.3 or higher) for 3D display. Several 2D plotters and 3D viewers can be launched now in the same session and more than one molecule can be loaded in the same 3D window. Algorithms have been rescaled and modified to work with densities coming from ZDO computations in very big molecular systems (up to thousands of atoms) at a very moderate cost. New functionalities have been added including computation of molecular electrostatic potential over a molecular surface determined as a user-defined density isosurface. The method of Electrostatics for Intermolecular Complexation has been added to the package to serve as an auxiliary tool for cluster geometry optimization. Examples are provided which prove the good performance of the algorithms. Program summaryProgram Title: DAMQT_3CPC Library link to program files:https://doi.org/10.17632/2rxvgbsnhx.2Licensing provisions: GPLv3Programming language: Fortran90, C++ and PythonSupplementary material: Quick-start guide and User's manual in PDF format included in the package. User's manual is also accessible from the GUI.External routines/libraries: Qt (5.10 or higher), OpenGL (3.3 or higher), ffmpeg (3.4 or higher), OpenBabel (2.3 or higher, optional)Nature of problem: Analysis and visualization of the molecular electron density, electrostatic potential, critical points, gradient paths, atomic basins, electric field and Hellmann-Feynman forces on nuclei, clusters optimization with EPIC.Solution method: Molecular electron density is partitioned into (pseudo)atomic fragments by means of the method of Deformed Atoms in Molecules [1]. Electron densities of the fragments are expanded as a series of spherical harmonics times radial factors. The partition is used for defining molecular density deformations and for the fast calculation of several properties associated with density, including electrostatic potential, electric field and Hellmann-Feynman forces over nuclei. Exploration of density and potential topology is facilitated, and the computation of electrostatic potential over an isodensity surface is implemented. Cluster optimization facility with EPIC is also implemented.Additional comments including restrictions and unusual features: Density matrix must come from an LCAO calculation (any computational level) with spherical (not Cartesian) Slater or Gaussian functions.The program contains an OPEN statement to binary files (stream) in several files. This statement does not have a standard syntax in Fortran 90. Two possibilities are considered in conditional compilation: Intel's ifort and Fortran2003 standard. This latter is applied to compilers other than ifort (gfortran uses this one, for instance).

Efficient Evaluation of Molecular Electrostatic Potential in Large Systems

An algorithm for the efficient computation of molecular electrostatic potential is reported. It is based on the partition/expansion of density into (pseudo) atomic fragments with the method of Deformed Atoms in Molecules, which allows to compute the potential as a sum of atomic contributions. These contributions are expressed as a series of irregular spherical harmonics times effective multipole moments and inverse multipole moments, including short-range terms. The problem is split into two steps. The first one consists of the partition/expansion of density accompanied by the computation of multipole moments, and its cost depends on the size of the basis set used in the computation of electron density within the Linear Combination of Atomic Orbitals framework. The second one is the actual computation of the electrostatic potential from the quantities calculated in the first step, and its cost depends on the number of computation points. For a precision in the electrostatic potential of six decimal figures, the algorithm leads to a dramatic reduction of the computation time with respect to the calculation from electron density matrix and integrals involving basis set functions.

The Route to \u2018Chemobrain\u2019 - Computational probing of neuronal LTP pathway

Chemotherapy causes deleterious side effects during the course of cancer management. The toxic effects may be extended to CNS chronically resulting in altered cognitive function like learning and memory. The present study follows a computational assessment of 64 chemotherapeutic drugs for their off-target interactions against the major proteins involved in neuronal long term potentiation pathway. The cancer chemo-drugs were subjected to induced fit docking followed by scoring alignment and drug-targets interaction analysis. The results were further probed by electrostatic potential computation and ligand binding affinity prediction of the top complexes. The study identified novel off-target interactions by Dactinomycin, Temsirolimus, and Everolimus against NMDA, AMPA, PKA and ERK2, while Irinotecan, Bromocriptine and Dasatinib were top interacting drugs for CaMKII. This study presents with basic foundational knowledge regarding potential chemotherapeutic interference in LTP pathway which may modulate neurotransmission and synaptic plasticity in patient receiving these chemotherapies.

Comparative Analysis of Electrostatic Models for Ligand Docking.

The precise modeling of molecular interactions remains an important goal among molecular modeling techniques. Some of the challenges in the field include the precise definition of a Hamiltonian for biomolecular systems, together with precise parameters derived from Molecular Mechanics Force Fields, for example. The problem is even more challenging when interaction energies from different species are computed, such as the interaction energy involving a ligand and a protein, given that small differences must be computed from large energies. Here we evaluated the effects of the electrostatic model for ligand binding energy evaluation in the context of ligand docking. For this purpose, a classical Coulomb potential with distance-dependent dielectrics was compared with a Poisson-Boltzmann (PB) model for electrostatic potential computation, based on DelPhi calculations. We found that, although the electrostatic energies were highly correlated for the Coulomb and PB models, the ligand pose and the enrichment of actual ligands against decoy compounds, were improved when binding energies were computed using PB as compared to the Coulomb model. We observed that the electrostatic energies computed with the Coulomb model were, on average, ten times larger than the energies computed with the PB model, suggesting a strong overestimation of the polar interactions in the Coulomb model. We also found that a slightly smoothed Lennard-Jones potential combined with the PB model resulted in a good compromise between ligand sampling and energetic scoring.

The Impact of Iron Adsorption on the Electronic and Photocatalytic Properties of the Zinc Oxide (0001) Surface: A First-Principles Study.

The structural stability, electronic structure, and optical properties of an iron-adsorbed ZnO (0001) surface with three high-symmetry adsorption sites are investigated with first-principle calculations on the basis of density functional theory and the Hubbard-U method. It is found that the iron adatom in the H3 adsorption site of ZnO (0001) surface has the lowest adsorption energy of −5.665 eV compared with T4 and Top sites. For the Top site, compared with the pristine ZnO (0001) surface, the absorption peak located at 1.17 eV has a red shift, and the elevation of the absorption coefficient is more pronounced in the visible-light region, because the Fe-related levels are introduced in the forbidden band and near the Fermi level. The electrostatic potential computation reveals that the work function of the ZnO (0001) surface is significantly decreased from 2.340 to 1.768 eV when iron is adsorbed on the Top site. Furthermore, the degradation mechanism based on the band structure is analyzed. It can be concluded that the adsorption of iron will promote the separation of photoinduced carriers, thus improving the photocatalytic activity of ZnO (0001) surface. Our study benefits research on the photocatalytic activity of ZnO and the utilization rate of solar energy.

Electrostatic simulation using XFEM for conductor and dielectric interfaces

AbstractMany Micro‐Electro‐Mechanical Systems (e.g. RF‐switches, micro‐resonators and micro‐rotors) involve mechanical structures moving in an electrostatic field. For this type of problems, it is required to evaluate accurately the electrostatic forces acting on the devices. Extended Finite Element (X‐FEM) approaches can easily handle moving boundaries and interfaces in the electrostatic domain and seem therefore very suitable to model Micro‐Electro‐Mechanical Systems. In this study we investigate different X‐FEM techniques to solve the electrostatic problem when the electrostatic domain is bounded by a conducting material. Preliminary studies in one‐dimension have shown that one can obtain good results in the computation of electrostatic potential using X‐FEM. In this paper the extension of these preliminary studies to 2D problem is presented. In particular, a new type of enrichment functions is proposed in order to treat accurately Dirichlet boundary conditions on the interface. Copyright © 2010 John Wiley & Sons, Ltd.

Accelerating electrostatic surface potential calculation with multi-scale approximation on graphics processing units.

Tools that compute and visualize biomolecular electrostatic surface potential have been used extensively for studying biomolecular function. However, determining the surface potential for large biomolecules on a typical desktop computer can take days or longer using currently available tools and methods. Two commonly used techniques to speed-up these types of electrostatic computations are approximations based on multi-scale coarse-graining and parallelization across multiple processors. This paper demonstrates that for the computation of electrostatic surface potential, these two techniques can be combined to deliver significantly greater speed-up than either one separately, something that is in general not always possible. Specifically, the electrostatic potential computation, using an analytical linearized Poisson-Boltzmann (ALPB) method, is approximated using the hierarchical charge partitioning (HCP) multi-scale method, and parallelized on an ATI Radeon 4870 graphical processing unit (GPU). The implementation delivers a combined 934-fold speed-up for a 476,040 atom viral capsid, compared to an equivalent non-parallel implementation on an Intel E6550 CPU without the approximation. This speed-up is significantly greater than the 42-fold speed-up for the HCP approximation alone or the 182-fold speed-up for the GPU alone.

Two-scale finite element Green’s function approximations with applications to electrostatic potential computation

In this paper, a two-scale finite element approach is proposed and analyzed for approximations of Green’s function in three-dimensions. This approach is based on a two-scale finite element space defined, respectively, on the whole domain with size H and on some subdomain containing singular points with size h (h ≪ H). It is shown that this two-scale discretization approach is very efficient. In particular, the two-scale discretization approach is applied to solve Poisson-Boltzmann equations successfully.

Rpe65 Isomerase Associates with Membranes through an Electrostatic Interaction with Acidic Phospholipid Headgroups

Opsins are light-sensitive pigments in the vertebrate retina, comprising a G protein-coupled receptor and an 11-cis-retinaldehyde chromophore. Absorption of a photon by an opsin pigment induces isomerization of its chromophore to all-trans-retinaldehyde. After a brief period of activation, opsin releases all-trans-retinaldehyde and becomes insensitive to light. Restoration of light sensitivity to the apo-opsin involves the conversion of all-trans-retinaldehyde back to 11-cis-retinaldehyde via an enzyme pathway called the visual cycle. The critical isomerization step in this pathway is catalyzed by Rpe65. Rpe65 is strongly associated with membranes but contains no membrane-spanning segments. It was previously suggested that the affinity of Rpe65 for membranes is due to palmitoylation of one or more Cys residues. In this study, we re-examined this hypothesis. By two independent strategies involving mass spectrometry, we show that Rpe65 is not palmitoylated nor does it appear to undergo other post-translational modifications at significant stoichiometry. Instead, we show that Rpe65 binds the acidic phospholipids, phosphatidylserine, phosphatidylglycerol, and cardiolipin, but not phosphatidic acid. No binding of Rpe65 to basic phospholipids or neutral lipids was observed. The affinity of Rpe65 to acidic phospholipids was strongly pH-dependent, suggesting an electrostatic interaction of basic residues in Rpe65 with negatively charged phospholipid headgroups. Binding of Rpe65 to liposomes containing phosphatidylserine or phosphatidylglycerol, but not the basic or neutral phospholipids, allowed the enzyme to extract its insoluble substrate, all-trans-retinyl palmitate, from the lipid bilayer for synthesis of 11-cis-retinol. The interaction of Rpe65 with acidic phospholipids is therefore biologically relevant.

Influence of surface states on tunneling spectra ofn-type GaAs(110) surfaces

We show that surface states within the conduction band of $n$-type GaAs(110) surfaces play an important role in reducing the tunneling current out of an accumulation layer that forms due to an applied potential from a nearby probe tip. Numerical computation of the tunneling current combined with an electrostatic potential computation of the tip-induced band bending (TIBB) reveals that occupation of the surface states limits the TIBB, thus leading to the limitation of the accumulation. As a result, the tunneling current out of the accumulation layer is strongly suppressed, which is in quantitative agreement with the experiment.

A linear-scaling spectral-element method for computing electrostatic potentials

A new linear-scaling method is presented for the fast numerical evaluation of the electronic Coulomb potential. Our approach uses a simple real-space partitioning of the system into cubic cells and a spectral-element representation of the density in a tensorial basis of high-order Chebyshev polynomials. Electrostatic interactions between non-neighboring cells are described using the fast multipole method. The remaining near-field interactions are computed in the tensorial basis as a sum of differential contributions by exploiting the numerical low-rank separability of the Coulomb operator. The method is applicable to arbitrary charge densities, avoids the Poisson equation, and does not involve the solution of any systems of linear equations. Above all, an adaptive resolution of the Chebyshev basis in each cell facilitates the accurate and efficient treatment of molecular systems. We demonstrate the performance of our implementation for quantum chemistry with benchmark calculations on the noble gas atoms, long-chain alkanes, and diamond fragments. We conclude that the spectral-element method can be a competitive tool for the accurate computation of electrostatic potentials in large-scale molecular systems.

A finite element recovery approach to Green’s function approximations with applications to electrostatic potential computation

In this paper, a finite element recovery approach is proposed to improve the accuracy of finite element approximations for Green’s functions in three dimensions. This recovery approach is based on some simple postprocessing. It is proved by both theory and numerics that the recovery approach is very efficient. In particular, the approach is successfully applied to some electrostatic potential computations.

Accelerated Cartesian expansions – A fast method for computing of potentials of the form R− ν for all real ν

The need to compute potentials of the form R − ν for ν ⩾ 1 occur in a variety of areas ranging from electromagnetics to biophysics to molecular dynamics to astrophysics, etc. For instance, Coulomb, London, Lennard-Jones, H-bonds are of the form ν = 1 , 5, 6 (and 12), 10, respectively. For a systems with N source/observation points, the cost of computing these potentials scales proportional to O ( N 2 ) . Methods to overcome this computational bottleneck have been a popular research topic for quite some time. For instance, the fast multipole method (FMM) and their cousins—tree codes—have revolutionized the computation of electrostatic potentials ( ν = 1). These methods rely on a hierarchical decomposition of the computational domain, i.e, construction of a regular oct-tree decomposition, and exploits the principle of divide and conquer to compute potentials at each observation point. This paper presents two methods, in the vein of FMM, albeit based on Cartesian tensors. The salient features of the first are as follows: (i) it relies on totally symmetric tensors and (ii) the errors are independent of the height of the tree. The second method is presented specifically for ν = 1, and relies on traceless totally symmetric Cartesian tensors. Using the relationship between traceless Cartesian tensors and spherical harmonics, it will be shown that this technique has the same computational cost as the classical FMM. Generalization of the second method for ν ≠ 1 is trivial; however, one needs to use totally symmetric tensors instead. Finally, in the whole computation scheme, only the translation operator (that used to traverse across the tree) depends on ν. Convergence of the proposed method is proven for all ν ∈ R . Numerical results that validate the cost and accuracy are presented for several potential functions; these include those typically encountered in the analysis of physical systems (Coulombic, Lennard-Jones, Lattice gas).

Electrostatic potentials of proteins in water: a structured continuum approach

Electrostatic interactions play a crucial role in many biomolecular processes, including molecular recognition and binding. Biomolecular electrostatics is modulated to a large extent by the water surrounding the molecules. Here, we present a novel approach to the computation of electrostatic potentials which allows the inclusion of water structure into the classical theory of continuum electrostatics. Based on our recent purely differential formulation of nonlocal electrostatics [Hildebrandt, et al. (2004) Phys. Rev. Lett., 93, 108104] we have developed a new algorithm for its efficient numerical solution. The key component of this algorithm is a boundary element solver, having the same computational complexity as established boundary element methods for local continuum electrostatics. This allows, for the first time, the computation of electrostatic potentials and interactions of large biomolecular systems immersed in water including effects of the solvent's structure in a continuum description. We illustrate the applicability of our approach with two examples, the enzymes trypsin and acetylcholinesterase. The approach is applicable to all problems requiring precise prediction of electrostatic interactions in water, such as protein-ligand and protein-protein docking, folding and chromatin regulation. Initial results indicate that this approach may shed new light on biomolecular electrostatics and on aspects of molecular recognition that classical local electrostatics cannot reveal.

Universal method for computation of electrostatic potentials

A computational approach to determine electrostatic interaction and gravitational potentials by performing direct numerical integration is presented. The potential is expanded using finite-element functions of arbitrary order. The method does not involve any solutions of systems of linear equations. The potential is instead obtained as a sum of differential contributions. Thus, no boundary conditions for the potential are needed. It is computationally efficient and well suited for parallel computers, since the innermost loops constitute matrix multiplications and the outer ones can be used as parallel indices. Without using prescreening or other computational tricks to speed up the calculation, the algorithm scales as N4/3 where N denotes the grid size.

A DFT Study of Tin‐ and Crown‐Ether‐Based Host Molecules Capable of Binding Anions and Cations Simultaneously

AbstractDFT calculations are reported for a series of tin‐ and crown‐ether‐based host compounds {i.e., the trimethyl derivatives [18]‐crown‐6‐C6H3COOSn(CH3)3and [15]‐crown‐5‐C6H3COOSn(CH3)3} capable of binding cations and anions simultaneously. The B3LYP functional together with the 6‐31G* basis set was used for the atoms C, H, N, O, S, Na and K and the 3‐21G* basis set for Sn in order to obtain insights into the factors determining the nature of the interactions of these compounds with the neutral molecules acetone and H2O, the SCN−anion, and the Na+and K+cations. The interaction strength pattern with these molecules was explained by the use of a series of reactivity descriptors such as the Fukui function, hardness, local softness, and the MEP (molecular electrostatic potential). In all cases studied in this paper, the complexes with Na+were more stable than those with K+, correlating with the size of the cation and the volume available in the crown ether. Moreover, this finding is also in accordance with the greater hardness of Na+relative to K+, in combination with the hard environment of the crown ether moiety. This region was also analysed by computation of electrostatic potentials, which showed that highly negative values are associated with the inside region of the cavity of the crown, this region thus being amenable to electrophilic attack. The HSAB principle, characterising the reactive sites on the basis of local softness and the Fukui function, provided a firm explanation of the reactivity of the tin atom of the crown ether benzocarboxylate towards SCN−, acetone and water. The HSAB concept was also successfully used to explain the preference of the tin atoms in both crown ethers to bind with the nitrogen atom rather than the sulfur atom of SCN−. This result is a confirmation that the tin atoms in the compounds under consideration behave as hard atoms. Overall, these results fit remarkably well with previous experimentally measured NMR spectroscopy data and demonstrate that the interactions of this kind of molecules can be predicted and interpreted by the use of DFT calculations and DFT‐based reactivity descriptors, as well as MEP calculations. (© Wiley‐VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2003)

Evaluation of a finite multipole expansion technique for the computation of electrostatic potentials of dibenzo‐p‐dioxins and related systems

AbstractThe electrostatic potential V(r) that the nuclei and electrons of a molecule create in the surrounding space is well established as a guide in the study of molecular reactivity, and particularly, of biological recognition processes. Its rigorous computation is, however, very demanding of computer time for large molecules, such as those of interest in recognition interactions. We have accordingly investigated the use of an approximate finite multicenter multipole expansion technique to determine its applicability for producing reliable electrostatic potentials of dibenzo‐p‐dioxins and related molecules, with significantly reduced amounts of computer time, at distances of interest in recognition studies. A comparative analysis of the potentials of three dibenzo‐p‐dioxins and a substituted naphthalene molecule computed using both the multipole expansion technique and Gaussian 82 at the STO‐5G level has been carried out. Overall we find that regions of negative and positive V(r) at 1.75 Å above the molecular plane are very well reproduced by the multipole expansion technique, with up to a 20‐fold improvement in computer time.