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

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

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

Structure- and Ligand-Based Design of Novel Antimicrobial Agents

The use of computer based techniques in the design of novel therapeutic agents is a rapidly emerging field. Although the drug-design techniques utilized by Computational Medicinal Chemists vary greatly, they can roughly be classified into structure-based and ligand-based approaches. Structure-based methods utilize a solved structure of the design target, protein or DNA, usually obtained by X-ray or NMR methods to design or improve compounds with activity against the target. Ligand-based methods use active compounds with known affinity for a target that may yet be unresolved. These methods include Pharmacophore-based searching for novel active compounds or Quantitative Structure-Activity Relationship (QSAR) studies. The research presented here utilized both structure and ligand-based methods against two bacterial targets: Bacillus anthracis and Mycobacterium tuberculosis. The first part of this thesis details our efforts to design novel inhibitors of the enzyme dihydropteroate synthase from B. anthracis using crystal structures with known inhibitors bound. The second part describes a QSAR study that was performed using a series of novel nitrofuranyl compounds with known, whole-cell, inhibitory activity against M. tuberculosis. Dihydropteroate synthase (DHPS) catalyzes the addition of p-amino benzoic acid (pABA) to dihydropterin pyrophosphate (DHPP) to form pteroic acid as a key step in bacterial folate biosynthesis. It is the traditional target of the sulfonamide class of antibiotics. Unfortunately, bacterial resistance and adverse effects have limited the clinical utility of the sulfonamide antibiotics. Although six bacterial crystal structures are available, the flexible loop regions that enclose pABA during binding and contain key sulfonamide resistance sites have yet to be visualized in their functional conformation. To gain a new understanding of the structural basis of sulfonamide resistance, the molecular mechanism of DHPS action, and to generate a screening structure for high-throughput virtual screening, molecular dynamics simulations were applied to model the conformations of the unresolved loops in the active site. Several series of molecular dynamics simulations were designed and performed utilizing enzyme substrates and inhibitors, a transition state analog, and a pterin-sulfamethoxazole adduct. The positions of key mutation sites conserved across several bacterial species were closely monitored during these analyses. These residues were shown to interact closely with the sulfonamide binding site. The simulations helped us gain new understanding of the positions of the flexible loops during inhibitor binding that has allowed the development of a DHPS structural model that could be used for high-through put virtual screening (HTVS). Additionally, insights gained on the location and possible function of key mutation sites on the flexible loops will facilitate the design of new, potent inhibitors of DHPS that can bypass resistance mutations that render sulfonamides inactive. Prior to performing high-throughput virtual screening, the docking and scoring functions to be used were validated using established techniques against the B. anthracis DHPS target. In this validation study, five commonly used docking programs, FlexX, Surflex, Glide, GOLD, and DOCK, as well as nine scoring functions, were evaluated for their utility in virtual screening against the novel pterin binding site. Their performance in ligand docking and virtual screening against this target was examined by their ability to reproduce a known inhibitor conformation and to correctly detect known active compounds seeded into three separate decoy sets. Enrichment was demonstrated by calculated enrichment factors at 1% and Receiver Operating Characteristic (ROC) curves. The effectiveness of post-docking relaxation prior to rescoring and consensus scoring were also evaluated. Of the docking and scoring functions evaluated, Surflex with SurflexScore and Glide with GlideScore performed best overall for virtual screening against the DHPS target. The next phase of the DHPS structure-based drug design project involved high-throughput virtual screening against the DHPS structural model previously developed and docking methodology validated against this target. Two general virtual screening methods were employed. First, large, virtual libraries were pre-filtered by 3D pharmacophore and modified Rule-of-Three fragment constraints. Nearly 5 million compounds from the ZINC databases were screened generating 3,104 unique, fragment-like hits that were subsequently docked and ranked by score. Second, fragment docking without pharmacophore filtering was performed on almost 285,000 fragment-like compounds obtained from databases of commercial vendors. Hits from both virtual screens with high predicted affinity for the pterin binding pocket, as determined by docking score, were selected for in vitro testing. Activity and structure-activity relationship of the active fragment compounds have been developed. Several compounds with micromolar activity were identified and taken to crystallographic trials. Finally, in our ligand-based research into M. tuberculosis active agents, a series of nitrofuranylamide and related aromatic compounds displaying potent activity was investigated utilizing 3-Dimensional Quantitative Structure-Activity Relationship (3D-QSAR) techniques. Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Indices Analysis (CoMSIA) methods were used to produce 3D-QSAR models that correlated the Minimum Inhibitory Concentration (MIC) values against M. tuberculosis with the molecular structures of the active compounds. A training set of 95 active compounds was used to develop the models, which were then evaluated by a series of internal and external cross-validation techniques. A test set of 15 compounds was used for the external validation. Different alignment and ionization rules were investigated as well as the effect of global molecular descriptors including lipophilicity (cLogP, LogD), Polar Surface Area (PSA), and steric bulk (CMR), on model predictivity. Models with greater than 70% predictive ability, as determined by external validation and high internal validity (cross validated r2 \u3e .5) were developed. Incorporation of lipophilicity descriptors into the models had negligible effects on model predictivity. The models developed will be used to predict the activity of proposed new structures and advance the development of next generation nitrofuranyl and related nitroaromatic anti-tuberculosis agents

Molecular modelling of meso- and nanoscale dynamics

Molecular modelling of meso- and nanoscale dynamics is concerned with length and time scales that are in the transition zone from molecular to continuum models. Molecular simulation methods, in particular molecular dynamics (MD), only allow the simulation of relatively small nanoscale systems. Continuum methods, such as computational fluid dynamics (CFD), are applicable at macroscopic scales but cease to be valid for nanoscales. This thesis is focused on hybrid MD-CFD methods with geometrical decomposition that seek to bridge the gap between molecular and continuum modelling. The hybrid solution interface (HSI) establishes the coupling between the molecular and the continuum domain. In this work, different realisation approaches for the HSI, flux and state coupling, are discussed and compared. A detailed investigation on MD flux boundary conditions, the most crucial part of a flux based HSI, is carried out. Different schemes for the imposition of mass, momentum and energy fluxes through convective and viscous transport are presented: direct and indirect flux imposition for convective fluxes; the imposition of momentum fluxes through reflective walls, external forces and the reverse velocity scheme; and imposition of energy fluxes through external forces and an energy transfer scheme. Different combinations of these schemes are compared for standard flow situations. The momentum and energy transfer by an external force creates a relaxation zone at the MD boundary. The characteristics of this zone is investigated in detail and a theoretical model for the density profile has been derived. The reverse velocity scheme has been created as part of this work to avoid the problems encountered when using the external force for the momentum transfer. It is shown that indirect convective flux imposition in conjunction with the reverse velocity scheme gives the best results for the standard flow situations. The scheme is also tested for liquid flow past Carbon nanotubes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Molecular modelling of meso- and nanoscale dynamics

Molecular modelling of meso- and nanoscale dynamics is concerned with length and time scales that are in the transition zone from molecular to continuum models. Molecular simulation methods, in particular molecular dynamics (MD), only allow the simulation of relatively small nanoscale systems. Continuum methods, such as computational fluid dynamics (CFD), are applicable at macroscopic scales but cease to be valid for nanoscales. This thesis is focused on hybrid MD-CFD methods with geometrical decomposition that seek to bridge the gap between molecular and continuum modelling. The hybrid solution interface (HSI) establishes the coupling between the molecular and the continuum domain. In this work, different realisation approaches for the HSI, flux and state coupling, are discussed and compared. A detailed investigation on MD flux boundary conditions, the most crucial part of a flux based HSI, is carried out. Different schemes for the imposition of mass, momentum and energy fluxes through convective and viscous transport are presented: direct and indirect flux imposition for convective fluxes; the imposition of momentum fluxes through reflective walls, external forces and the reverse velocity scheme; and imposition of energy fluxes through external forces and an energy transfer scheme. Different combinations of these schemes are compared for standard flow situations. The momentum and energy transfer by an external force creates a relaxation zone at the MD boundary. The characteristics of this zone is investigated in detail and a theoretical model for the density profile has been derived. The reverse velocity scheme has been created as part of this work to avoid the problems encountered when using the external force for the momentum transfer. It is shown that indirect convective flux imposition in conjunction with the reverse velocity scheme gives the best results for the standard flow situations. The scheme is also tested for liquid flow past Carbon nanotubes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Kinetic model construction using chemoinformatics

Kinetic models of chemical processes not only provide an alternative to costly experiments; they also have the potential to accelerate the pace of innovation in developing new chemical processes or in improving existing ones. Kinetic models are most powerful when they reflect the underlying chemistry by incorporating elementary pathways between individual molecules. The downside of this high level of detail is that the complexity and size of the models also steadily increase, such that the models eventually become too difficult to be manually constructed. Instead, computers are programmed to automate the construction of these models, and make use of graph theory to translate chemical entities such as molecules and reactions into computer-understandable representations. This work studies the use of automated methods to construct kinetic models. More particularly, the need to account for the three-dimensional arrangement of atoms in molecules and reactions of kinetic models is investigated and illustrated by two case studies. First of all, the thermal rearrangement of two monoterpenoids, cis- and trans-2-pinanol, is studied. A kinetic model that accounts for the differences in reactivity and selectivity of both pinanol diastereomers is proposed. Secondly, a kinetic model for the pyrolysis of the fuel “JP-10” is constructed and highlights the use of state-of-the-art techniques for the automated estimation of thermochemistry of polycyclic molecules. A new code is developed for the automated construction of kinetic models and takes advantage of the advances made in the field of chemo-informatics to tackle fundamental issues of previous approaches. Novel algorithms are developed for three important aspects of automated construction of kinetic models: the estimation of symmetry of molecules and reactions, the incorporation of stereochemistry in kinetic models, and the estimation of thermochemical and kinetic data using scalable structure-property methods. Finally, the application of the code is illustrated by the automated construction of a kinetic model for alkylsulfide pyrolysis

Modelling molecular flexibility for crystal structure prediction

In the crystal packing of molecules wherein a single bond links aromatic groups, a change in the torsion angle can optimise close packing of the molecule. The improved intermolecular interactions, Uinter, outweigh the conformational energy penalty, ΔEintra, to give a more stable lattice energy, Elatt = Uinter + ΔEintra. This thesis uses this lattice energy model hierarchically in a new Crystal Structure Prediction (CSP) algorithm, CrystalPredictor version 1.6, which varies the low-barrier torsion angles at the start of generating hypothetical crystal structures. The crystal structure of 1-benzyl-1H-tetrazole was successfully predicted in an informal ‘blind test’ when given the chemical diagram and the number of molecules in the asymmetric unit cell. Then, the concept of whether specific molecular fragments favour polymorphism (i.e. polymorphophore) was investigated by analysing the crystal energy landscapes of the monomorphic fenamic acid and the polymorphic derivative tolfenamic acid. The CSP results show that the polymorphophore promotes but does not guarantee polymorphism and that the substituents on the polymorphophore fragment decide the relative energies of the crystal structures. Molecular Dynamics (MD) cannot use this lattice energy model because many ab initio calculations of ΔEintra on a single molecule are expensive. However, the examination of the physical origin of the torsional barrier in fenamates aided the derivation of an analytical model fo ΔEintra. This thesis develops codes for fitting analytical intramolecular force fields to ab initio conformational profiles of fenamates. An intramolecular exp-6 atom-atom term (for the non-bonded repulsion-dispersion contributions) plus a cosine term (that represents the changes to the Molecular Orbitals) accurately model the ab initio conformational energy surfaces of fenamic and tolfenamic acids. This thesis provides a first step in extending ΔEintra data generated from CSP studies to help MD on condensed phases of pharmaceutical-like organic molecules