Web-based Fragment Library

A new polarized force field BioEFP for modeling process in biology is far superior in accuracy to the common classical force fields. One of the main shortcomings of BioEFP is that the parameters are not readily available, thus it will take a lot of time to be calculated. Developing an online repository of pre-computed fragment parameters and a similarity algorithm will allow ascribing each fragment of a biological macromolecule to a pre-defined fragment. This study incorporates three parts to create the online repository. First, the visual design for the website using the Hypertext Markup Language and the Cascading Style Sheets to create the format for each part on the web page. Secondly, the Hypertext Preprocessor is used for the server side to run certain functions and building dynamic websites. Lastly, an online database is created by MySQL to sort and organize all the data file. The results from the project is allowing us to upload our own file with xyz coordinates and get the result as the efp file

Water−Benzene Interactions: An Effective Fragment Potential and Correlated Quantum Chemistry Study

Structures and binding in small water−benzene complexes (1−8 water molecules and 1−2 benzene molecules) are studied using the general effective fragment potential (EFP) method. The lowest energy conformers of the clusters were found using a Monte Carlo technique. The binding energies in the smallest clusters (dimers, trimers, and tetramers) were also evaluated with second order perturbation theory (MP2) and coupled cluster theory (CCSD(T)). The EFP method accurately predicts structures and binding energies in the water−benzene complexes. Benzene is polarizable and consequently participates in hydrogen bond networking of water. Since the water−benzene interactions are only slightly weaker than water−water interactions, structures with different numbers of water−water, benzene−water, and benzene−benzene bonds often have very similar binding energies. This is a challenge for computational methods

Applying Machine Learning to Computational Chemistry: Can We Predict Molecular Properties Faster without Compromising Accuracy?

Non-covalent interactions are crucial in analyzing protein folding and structure, function of DNA and RNA, structures of molecular crystals and aggregates, and many other processes in the fields of biology and chemistry. However, it is time and resource consuming to calculate such interactions using quantum-mechanical formulations. Our group has proposed previously that the effective fragment potential (EFP) method could serve as an efficient alternative to solve this problem. However, one of the computational bottlenecks of the EFP method is obtaining parameters for each molecule/fragment in the system, before the actual EFP simulations can be carried out. Here we present a neural network model that is trained by pre-calculated EFP parameters for a set of fragment geometries, to predict the multipole moment parameters for the fragments with arbitrary geometries. We perform Monte Carlo simulation to assess accuracy of the model. The results demonstrate the ability to predict multipole moments within acceptable margin of error given that the training set is closely spaced. These results contribute towards extending the applicability of the EFP method to new types of chemistries and improving the accuracy and computational efficiency of describing non-covalent interactions

The Exciton Spectra Simulator of Photosynthetic Protein-pigment Complex

The solar energy is one of the most successful alternative energy sources because of its unlimited availability and environmental friendliness. However, the energy transfer rate in artificial solar devices is significantly lower than the energy transfer rate in plants and bacteria. The key factor that governs efficient energy transfer is the electronic couplings between photosynthetic pigments within living organisms. We are applying quantum mechanical / molecular mechanical (QM/MM), quantum mechanical / effective fragment potential (QM/EFP) and fragment molecular orbital (fmo) methods to elucidate the energy transfer pathway in Fenna-Matthews-Olson (FMO) complex through computing the site energies of bacteriochlorophylls and the electronic couplings between them. Based on the values of site energies and couplings computed with QM/MM, QM/EFP and fmo methods we generate the multiple electronic Hamiltonians describinga the energy transfer within the FMO complex. In this research, I am focusing on the improving the algorithm and developing the GUI for computing emission and absorption spectra for molecular systems with multiple chromophores. After taking the Hamiltonians matrixes as inputs, the researchers were able to predict the theoretical absorption and circular dichroism spectra. By comparing these spectra to experimental data, we managed to compare the efficiency and accuracy of the chosen methods and demonstrate the importance of accurate description of protein environment when studying the energy transfer within the pigment-protein complexes

Deconstructing Cation-pi Interactions: Understanding the Binding Energies Involved with Metal and Aromatic Amino Acid Residues

The Effective Fragment Potential (EFP) method is a computationally efficient technique for describing non-covalent interactions, such as hydrogen bonding and van der Waals forces. Cation-pi interactions are a type of non-covalent interactions and are thought to be important in biological processes, such as permittivity of ion channels. The goal of our work is to establish that the EFP method reliably describes the strength, directionality, and composition of cation-pi interactions. Optimal geometries were found for a series of biologically relevant cations (K+, Li+, Na+, Ca2+, and Mg2+) and aryl moieties appearing as residue groups in natural amino acids (3-methyl-1h-indole, p-cresol, phenylalanine, toluene, and tyrosine) using the MP2 level of theory and the cc-pVTZ basis set. The cation was then displaced along a line normal to the aromatic compound with EFP calculations performed for every 0.2 angstroms between 1 and 7 angstroms along the trajectory. The obtained binding energies and relative energy components were compared against Symmetry-Adapted Pertubation Theory (SAPT) calculations at 0.4 angstrom increments along the same trajectory. SAPT has been previously used to test the accuracy of EFP for a variety of systems. Preliminary results indicate that the EFP method accurately predicts equilibrium geometries in cation-pi complexes. The low computational cost of EFP against SAPT provides promise in expansion on the research of cation-pi interactions to larger systems using EFP

Fragmentation Methods: A Route to Accurate Calculations on Large Systems

Theoretical chemists have always strived to perform quantum mechanics (QM) calculations on larger and larger molecules and molecular systems, as well as condensed phase species, that are frequently much larger than the current state-of-the-art would suggest is possible. The desire to study species (with acceptable accuracy) that are larger than appears to be feasible has naturally led to the development of novel methods, including semiempirical approaches, reduced scaling methods, and fragmentation methods. The focus of the present review is on fragmentation methods, in which a large molecule or molecular system is made more computationally tractable by explicitly considering only one part (fragment) of the whole in any particular calculation. If one can divide a species of interest into fragments, employ some level of ab initio QM to calculate the wave function, energy, and properties of each fragment, and then combine the results from the fragment calculations to predict the same properties for the whole, the possibility exists that the accuracy of the outcome can approach that which would be obtained from a full (nonfragmented) calculation. It is this goal that drives the development of fragmentation methods

Effective Fragment Potentials for Flexible Molecules: Transferability of Parameters and Amino Acid Database

An accurate but efficient description of noncovalent interactions is a key to predictive modeling of biological and materials systems. The effective fragment potential (EFP) is an ab initio-based force field that provides a physically meaningful decomposition of noncovalent interactions of a molecular system into Coulomb, polarization, dispersion, and exchange-repulsion components. An EFP simulation protocol consists of two steps, preparing parameters for molecular fragments by a series of ab initio calculations on each individual fragment, and calculation of interaction energy and properties of a total molecular system based on the prepared parameters. As the fragment parameters (distributed multipoles, polarizabilities, localized wave function, etc.) depend on a fragment geometry, straightforward application of the EFP method requires recomputing parameters of each fragment if its geometry changes, for example, during thermal fluctuations of a molecular system. Thus, recomputing fragment parameters can easily become both computational and human bottlenecks and lead to a loss of efficiency of a simulation protocol. An alternative approach, in which fragment parameters are adjusted to different fragment geometries, referred to as “flexible EFP”, is explored here. The parameter adjustment is based on translations and rotations of local coordinate frames associated with fragment atoms. The protocol is validated on extensive benchmark of amino acid dimers extracted from molecular dynamics snapshots of a cryptochrome protein. A parameter database for standard amino acids is developed to automate flexible EFP simulations in proteins. To demonstrate applicability of flexible EFP in large-scale protein simulations, binding energies and vertical electron ionization and electron attachment energies of a lumiflavin chromophore of the cryptochrome protein are computed. The results obtained with flexible EFP are in a close agreement with the standard EFP procedure but provide a significant reduction in computational cost