Correlations between MO Eigenvectors and the Thermochemistry of Simple Organic Molecules, Related to Empirical Bond Additivity Schemes

A bondingness term is further developed to aid in heat of formation (ΔfHº) calculations for C, N, O and S containing molecules. Bondingness originated from qualitative investigations into the antibonding effect in the occupied MOs of ethane. Previous work used a single parameter for bondingness to calculate ΔfHº in an alkane homologous series using an additivity scheme. This work modifies the bondingness algorithm and uses the term to parameterise a test group of 345 molecules consisting of 17 subgroups that include alkanes, alkenes, alkynes, alcohols, ethers, aldehydes, ketones, carboxylic acids, esters, amines, amides, diazenes, nitriles, nitroalkanes, nitrates, thiols and benzenoids. Comparing experimental with calculated ΔfHº values, a standard deviation for the residuals of 6.3 kJ mol 1 can be achieved using bondingness with a simple steric repulsion term (SSR) in a bond additivity scheme, and a standard deviation of 5.2 kJ mol 1 can be achieved using a Lennard-Jones potential. The method is compared with the group method of Pedley, which for a slightly smaller set of 338 molecules, a subset of the test set of 345 molecules, gives a standard deviation of 7.0 kJ mol 1. Bondingness, along with SSR or a Lennard-Jones potential, is parameterised in the lowest level of ab initio (HF-SCF) or semiempirical quantum chemical calculations. It therefore may be useful in determining the ΔfHº values for the largest molecules that are amenable to quantum chemical calculation. As part of our analysis we calculated the difference between the lowest energy conformer and the average energy of a mixture populated with higher energy conformers. This is the difference between the experimental ΔfHº value and the ΔfHº calculated for a single conformer. Example calculations which we have followed are given by Dale and Eliel et al.. Dale calculates the energy difference for molecules as large as hexane using relative energies based on the number of 1,4 gauche interactions. We have updated these values with constant increments ascertained by Klauda et al. as well as ab initio MP2 cc-pVDZ relative energies and have included calculations for heptane and octane

Calculated conformer energies for organic molecules with multiple polar functionalities are method dependent: Taxol (case study)

BACKGROUND: Molecular mechanics (MM) and quantum chemical (QM) calculations are widely applied and powerful tools for the stereochemical and conformational investigations of molecules. The same methods have been extensively used to probe the conformational profile of Taxol (Figure 1) both in solution and at the β-tubulin protein binding site. RESULTS: In the present work, the relative energies of seven conformations of Taxol derived from NMR and X-ray analyses were compared with a set of widely used force fields and semiempirical MO methods coupled to a continuum solvent treatment. The procedures not only diverge significantly in their assessment of relative conformational energies, but none of them provide satisfactory agreement with experiment. CONCLUSIONS: For Taxol, molecular mechanics and semiempirical QM methods are unable to provide a consistent energetic ranking of side-chain conformations. For similar highly polar organic structures, "energy-free" conformational search methods are advised

Automated reaction mechanism generation : improving accuracy and broadening scope

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 169-186).Chemical kinetic modeling plays an important role in the study of reactive chemical systems. Thus, an automated means of constructing chemical kinetic models forms a useful tool in the engineering and science surrounding such systems. This document describes work to further develop one such tool, known as RMG (Reaction Mechanism Generator). Focus is placed on improving the accuracy of parameter estimation in the mechanism generation process and expanding the scope of applicability of the tool. In particular, effort has targeted the generation and use of explicit three-dimensional molecular structures for chemical species considered during reaction mechanism generation. This work has resulted in the generation of a software system integrated with RMG that can automatically generate and use such structures with quantum chemistry or force field codes to obtain more reliable thermochemistry estimates for cyclic structures without human intervention. Ultimately, the result of these updates is improved usefulness and reliability of the software system as a predictive tool. An application of the tool to the high temperature oxidation of JP-10, a jet fuel often used in military applications, is described. Using the newly refined RMG system, a detailed chemical kinetic model was constructed for this system. The resulting model represents a significant improvement upon existing work for JP- 10 oxidation by capturing detailed chemistry for this system. Simulations with this model have been found to produce results for ignition delay and product distribution that compare favorably with experimental results. The successful application of the refined RMG software system to this system demonstrates the practical utility of these updates.by Gregory Russell Magoon.Ph.D

On the inner workings of Monte Carlo codes

We review state-of-the-art Monte Carlo (MC) techniques for computing fluid coexistence properties (Gibbs simulations) and adsorption simulations in nanoporous materials such as zeolites and metal-organic frameworks. Conventional MC is discussed and compared to advanced techniques such as reactive MC, configurational-bias Monte Carlo and continuous fractional MC. The latter technique overcomes the problem of low insertion probabilities in open systems. Other modern methods are (hyper-)parallel tempering, Wang-Landau sampling and nested sampling. Details on the techniques and acceptance rules as well as to what systems these techniques can be applied are provided. We highlight consistency tests to help validate and debug MC codes

A new hydrocarbon empirical potential for molecular dynamics simulation

Molecular dynamics utilize energy model to solve the Newton’s equation of motion for a system of interacting particles. Ab-initio, semi-empirical and empirical approaches have been reported as main approaches to compute total energy of a system for describing its molecular structures and properties. In these approximation methods, the calculations achieved the level of accuracy in descending manner and in ascending order for computational time. Ab-initio approach also known as first principles method solved the complex energy evaluations in Schrödinger equation to account for electronic structures with limitation on the size of the system. Molecular mechanics (MM) is a conventional empirical approach that defined energy calculations in terms of functions with fitted parameters. The simple algorithm in MM allowed it to simulate larger system. Consequently, new potential function is always required either to produce higher accuracy result or to reduce the computational time. It is believed that there should be a compromise between the accuracy and the computational time depending on the simulation. The main contribution of this study is to propose a new hydrocarbon potential energy model which consist of bond stretching and angle bending function, where both functions are important components of short range potential for the force fields based on MM principle. The existing bond stretching and angle bending functions are found correlated to the piecewise polynomial concept. New models were then proposed based on piecewise polynomial concept and basic principles. Firstly, by neglecting the motion of electrons for fast computation purpose. Secondly, only the necessity independent variables are involved. Thirdly, structural properties such as symmetry and degeneracy are considered. In this regard, the interatomic distance was determined as the independent variable in bond stretching model since single independent variable is assumed sufficient in reproducing the chemical reaction for one motion involvement. Angle was selected as independent variable when the interactions were treated as a plane with triangle shape. However, there is more than one motion involvement in angle bending model, thus, the deviation for angle is also considered as independent variable. The selection rules were developed and independent variables were coupled with the interatomic distance to account for structural properties. Hence, the angle bending model is developed based on the triangle and selection rules. The parameters were estimated by using least square method. The proposed model was then compared with data collected from two well-established methods and applied to the carbon nanotube application for validation. Most of the results obtained achieved a good agreement except for carbon nanotube application where the discussions were given. Good agreement with data collection indicates that proposed models can be alternative solution to the existing force fields. The results are significant for advancement of new knowledge

A THEORETICAL STUDY OF INTERACTION OF NANOPARTICLES WITH BIOMOLECULE

Many types of materials at nanoscale are currently being used in everyday life. The production and use of such products based on engineered nanomaterials have raised concerns of the possible risks and hazards associated with these nanomaterials. In order to evaluate and gain a better understanding of their effects on living organisms, we have performed first-principles quantum mechanical calculations and molecular dynamics simulations. Specifically, we will investigate the interaction of nanomaterials including semiconducting quantum dots and metallic nanoparticles with various biological molecules, such as dopamine, DNA nucleobases and lipid membranes. Firstly, interactions of semiconducting CdSe/CdS quantum dots (QDs) with the dopamine and the DNA nucleobase molecules are investigated using similar quantum mechanical approach to the one used for the metallic nanoparticles. A variety of interaction sites are explored. Our results show that small-sized Cd4Se4 and Cd4S4 QDs interact strongly with the DNA nucleobase if a DNA nucleobase has the amide or hydroxyl chemical group. These results indicate that these QDs are suitable for detecting subcellular structures, as also reported by experiments. The next two chapters describe a preparation required for the simulation of nanoparticles interacting with membranes leading to accurate structure models for the membranes. We develop a method for the molecular crystalline structure prediction of 1,2-Dimyristoyl-sn-glycero-3-phosphorylcholine (DMPC), 1,2-Dimyristoyl-sn-glycero-3-phosphorylethanolamine (DMPE) and cyclic di-amino acid peptide using first-principles methods. Since an accurate determination of the structure of an organic crystal is usually an extremely difficult task due to availability of the large number of its conformers, we propose a new computational scheme by applying knowledge of symmetry, structural chemistry and chemical bonding to reduce the sampling size of the conformation space. The interaction of metal nanoparticles with cell membranes is finally carried out by molecular dynamics simulations, and the results are reported in the last chapter. A new force field is developed which accurately describes the interaction forces between the clusters representing small-sized metal nanoparticles and the lipid bilayer molecules. The permeation of nanoparticles into the cell membrane is analyzed together with the RMSD values of the membrane modeled by a lipid bilayer. The simulation results suggest that the AgNPs could cause the same amount of deformation as the AuNPs for the dysfunction of the membrane

Potential energy functions: From consistent force fields to spectroscopically determined polarizable force fields

We review our methodology for producing physically accurate potential energy functions, particularly relevant in the context of Lifson's goal of including frequency agreement as one of the criteria of a self-consistent force field. Our spectroscopically determined force field (SDFF) procedure guarantees such agreement by imposing it as an initial constraint on parameter optimization, and accomplishes this by an analytical transformation of ab initio “data” into the energy function format. After describing the elements of the SDFF protocol, we indicate its implementation to date and then discuss recent advances in our representation of the force field, in particular those required to produce an SDFF for the peptide group. © 2003 Wiley Periodicals, Inc. Biopolymers: 383–394, 2003Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34327/1/10254_ftp.pd

Developing and validating Fuzzy-Border continuum solvation model with POlarizable Simulations Second order Interaction Model (POSSIM) force field for proteins

The accurate, fast and low cost computational tools are indispensable for studying the structure and dynamics of biological macromolecules in aqueous solution. The goal of this thesis is development and validation of continuum Fuzzy-Border (FB) solvation model to work with the Polarizable Simulations Second-order Interaction Model (POSSIM) force field for proteins developed by Professor G A Kaminski. The implicit FB model has advantages over the popularly used Poisson Boltzmann (PB) solvation model. The FB continuum model attenuates the noise and convergence issues commonly present in numerical treatments of the PB model by employing fixed position cubic grid to compute interactions. It also uses either second or first-order approximation for the solvent polarization which is similar to the second-order explicit polarization applied in POSSIM force field. The FB model was first developed and parameterized with nonpolarizable OPLS-AA force field for small molecules which are not only important in themselves but also building blocks of proteins and peptide side chains. The hydration parameters are fitted to reproduce the experimental or quantum mechanical hydration energies of the molecules with the overall average unsigned error of ca. 0.076kcal/mol. It was further validated by computing the absolute pKa values of 11 substituted phenols with the average unsigned error of 0.41pH units in comparison with the quantum mechanical error of 0.38pH units for this set of molecules. There was a good transferability of hydration parameters and the results were produced only with fitting of the specific atoms to the hydration energy and pKa targets. This clearly demonstrates the numerical and physical basis of the model is good enough and with proper fitting can reproduce the acidity constants for other systems as well. After the successful development of FB model with the fixed charges OPLS-AA force field, it was expanded to permit simulations with Polarizable Simulations Second-order Interaction Model (POSSIM) force field. The hydration parameters of the small molecules representing analogues of protein side chains were fitted to their solvation energies at 298.15K with an average error of ca.0.136kcal/mol. Second, the resulting parameters were used to reproduce the pKa values of the reference systems and the carboxylic (Asp7, Glu10, Glu19, Asp27 and Glu43) and basic residues (Lys13, Lys29, Lys34, His52 and Lys55) of the turkey ovomucoid third domain (OMTKY3) protein. The overall average unsigned error in the pKa values of the acid residues was found to be 0.37pH units and the basic residues was 0.38 pH units compared to 0.58pH units and 0.72 pH units calculated previously using polarizable force field (PFF) and Poisson Boltzmann formalism (PBF) continuum solvation model. These results are produced with fitting of specific atoms of the reference systems and carboxylic and basic residues of the OMTKY3 protein. Since FB model has produced improved pKa shifts of carboxylic residues and basic protein residues in OMTKY3 protein compared to PBF/PFF, it suggests the methodology of first-order FB continuum solvation model works well in such calculations. In this study the importance of explicit treatment of the electrostatic polarization in calculating pKa of both acid and basic protein residues is also emphasized. Moreover, the presented results demonstrate not only the consistently good degree of accuracy of protein pKa calculations with the second-degree POSSIM approximation of the polarizable calculations and the first-order approximation used in the Fuzzy-Border model for the continuum solvation energy, but also a high degree of transferability of both the POSSIM and continuum solvent Fuzzy Border parameters. Therefore, the FB model of solvation combined with the POSSIM force field can be successfully applied to study the protein and protein-ligand systems in water