Handbook of Computational Chemistry

Quantum chemical calculations rely on a few fortunate circumstances, like usually small relativistic and negligible electrodynamic (QED) corrections, and large nuclei-to-electrons mass ratio. Unprecedented progress in computer technology has revolutionized quantum chemistry, making it a valuable tool for experimenters. It is important for computational chemistry to elaborate methods that look at molecules in a multiscale way, provide its global and synthetic description, and compare this description with those for other molecules. Only such a picture can free researchers from seeing molecules as a series of case-by-case studies. Chemistry is a science of analogies and similarities, and computational chemistry should provide the tools for seeing this.

Arguments are advanced to support the view that at present it is not possible to derive molecular structure from the full quantum mechanical Coulomb Hamiltonian associated with a given molecular formula that is customarily regarded as representing the molecule in terms of its constituent electrons and nuclei. However molecular structure may be identified provided that some additional chemically motivated assumptions that lead to the clamped nuclei Hamiltonian are added to the quantum mechanical account.

Methods of computational chemistry seem to often be simply a melange of undecipherable acronyms. Frequently, the ability to characterize methods with respect to their quality and applied approximations or to ascribe the proper methodology to the physicochemical property of interest is sufficient to perform research. However, it is worth knowing the fundamental ideas underlying the computational techniques so that one may exploit the approximations intentionally and efficiently. This chapter is an introduction to quantum chemistry methods based on the wave function search in one-electron approximation.

Two aspects are quintessential if one seeks to successfully perform DFT calculations: A basic understanding of how the concepts and models underlying the various manifestations of DFT are built, and an essential knowledge of what can be expected from DFT calculations and how to achieve the most appropriate results. This chapter expands on the development and philosophy of DFT, and aims to illustrate the essentials of DFT in a manner that is intuitively accessible. An analysis of the performance and applicability of DFT focuses on a representative selection of chemical properties, including bond lengths, bond angles, vibrational frequencies, electron affinities and ionization potentials, atomization energies, heats of formation, energy barriers, bond energies hydrogen bonding, weak interactions, spin states, and excited states.

This chapter provides a concise introduction to quantum chemical response theory as implemented in a number of widely used electronic structure software packages. While avoiding technical derivations of response functions, the fundamental idea of response theory, namely, the calculation of field-induced molecular properties through changes in expectation values, is explained in a manner equally valid for approximate wave function and density functional theories. Contrasting response theory to textbook treatments of perturbation theory, key computational concepts such as iterative solution of response equations, and the identification and calculation of electronic excitation energies are elucidated. The wealth of information that can be extracted from approximate linear, quadratic, and higher-order response functions is discussed on the basis of the corresponding exact response functions. Static response functions and their identification and numerical calculation as energy derivatives are discussed separately. Practical issues related to the lack of gauge and origin invariance in approximate calculations are discussed without going into too much theoretical detail regarding the sources of these problems. Finally, the effects of nuclear motion (molecular vibrations, in particular) and how to include them in computational studies are treated in some detail.

Van der Waals interactions determine a number of phenomena in the fields of physics, chemistry and biology. As we seek to increase our understanding of physical systems and develop detailed and more predictive theoretical models, it becomes even more important to provide an accurate description of the underlying molecular interactions. The goal of this chapter is to describe recent developments in the theory of intermolecular interactions that have revolutionised the field due to their comparatively low computational costs and high accuracies. These are the symmetry-adapted perturbation theory based on density functional theory (SAPT(DFT)) for interaction energies and the Williams–Stone–Misquitta (WSM) method for molecular properties in distributed form. These theories are applicable to systems of small organic molecules containing as many as 30 atoms each and have demonstrated accuracies comparable to the best electronic structure methods. We also discuss the numerical aspects of these theories and recent applications which demonstrate the range of problems that can now be approached with these accurate ab initio methods.

This chapter provides an overview of different hierarchical levels of molecular dynamics (MD) simulations spanning a wide range of time and length scales – from first principles approaches via classical atomistic methods to coarse graining techniques. The theoretical background of the most widely used methods and algorithms is briefly reviewed and practical instructions are given on the choice of input parameters for an actual computer simulation. In addition, important postprocessing procedures such as data analysis and visualization are discussed.

Single molecule force spectroscopy constitutes a robust method for probing the unfolding of biomolecules. Knowledge gained from statistical mechanics is helping to build our understanding about more complex structure and function of biopolymers. Here, we have review some of the models and techniques that have been employed to study force-induced transitions in biopolymers. We briefly describe the merit and limitation of these models and techniques. In this context, we discuss statistical models of polymer along with numerical techniques, which may provide enhanced insight in understanding the unfolding of biomolecules.

The ultimate justification for the many severe approximations and assumptions made in the present work comes from the fact that the agreement between the simple calculations and the available experimental data is as good as it is.N. L. Allinger, J. Am. Chem. Soc., 81, 5727, 1959A short survey of the general principles and various applications of molecular mechanics (MM) is presented. The origin of molecular mechanics and its evolution is followed starting from “pre-computer” and the first computer-aided estimations of the structure and potential energy of simple molecular systems to the modern force fields and the large system computations. The problem of “classic mechanics” description of essentially quantum properties and processes is considered. Various approaches to a selection of force field mathematical expressions and parameters are reviewed. The relation between MM simplicity and “physical nature” of the properties and events is examined. The possibility of a priori predictions of the properties of large systems is discussed in view of modern improvements of MM scheme. Quantum chemistry contributions to MM description of complex molecular and biomolecular systems are considered.

This chapter deals with two very important aspects of modern ab initio computational chemistry: the determination of molecular structure and the calculation, and visualization, of vibrational spectra. It deals primarily with the practical aspects of determining molecular structure and vibrational spectra computationally. Both minima (i.e., stable molecules) and transition states are discussed, as well as infrared (IR), Raman, and vibrational circular dichroism (VCD) spectra, all of which can now be computed theoretically.

The theory and applications of ab initio methods for the calculation of molecular properties are reviewed. A wide range of properties characterizing the interactions of molecules with external or internal sources of static or dynamic electromagnetic fields (including nonlinear properties and those related to nuclear and electron spins) is considered. Emphasis is put on the properties closely connected to the parameters used to describe experimentally observed spectra. We discuss the definitions of these properties, their relation to experiment, and give some remarks regarding various computational aspects. Theory provides a unified approach to the analysis of molecular properties in terms of average values, transition moments, and linear and nonlinear responses to the perturbing fields. Several literature examples are given, demonstrating that theoretical calculations are becoming easier, and showing that computed ab initio molecular properties are in many cases more accurate than those extracted from experimentally observed data.

Weak intermolecular interactions, which are ubiquitous in biological and materials chemistry, are fast becoming more routinely and accurately investigated owing to the increased performance of computational methods being actively developed. A vast array of pragmatic methods have been proposed using empirical, semi-empirical, density functional theory, and ab initio approaches, which all serve to widen the scope of feasible problems. Especially for the calculation of the important London dispersion interactions, significant progress has been achieved. Herein, we present a general overview on a number of illustrative strategies used to routinely investigate structures and energies of such systems. The composition and advantages/disadvantages of different benchmark sets, which have been found to be of crucial importance in assessing such a wide range of methods is discussed. Finally, a number of experience-based perspectives are provided in relation to the scaling and accuracy of the “more popular” methods used when investigating non-covalent interactions.

This chapter provides an introduction to the calculation of thermochemical data for chemical reactions using quantum chemical methods. The basic procedure is first described, namely, obtaining molecular structures and electronic energies of reactants and products, followed by vibrational frequency calculations and evaluation of thermal corrections. Since it is harder to obtain a given accuracy for some types of reactions than others, some discussion is provided on classes of reactions (e.g., isodesmic reactions) for which a given accuracy is easier to achieve than for a general reaction. Three examples illustrate different aspects of thermochemical calculations. The first example, the formation of ammonia from its elements, illustrates a variety of basis set and correlation effects on calculated data. The second example is concerned with calculations on small fluorine-oxygen species and a systematic side-by-side comparison of coupled-cluster and density-functional methods, including the use of isodesmic reactions. The third example describes the use of high-level coupled-cluster calculations to predict the standard enthalpy of formation of S(OH)₂.

​Excited states participate in photoinduced events as well as in thermally activated reactions, even in many cases in which only the ground state is believed to be involved. Life on Earth also depends, both directly and indirectly, on the influence that light has on chemistry. The energy of the Sun’s visible and ultraviolet radiation promotes processes that not only permit the continued existence of life on the planet, but which are keys for evolution by means of mutations. To study a system in an excited state, far away from its optimum situation, is a challenge for chemists, both experimentalists and theoreticians. This chapter is focused on the practical aspects related to the calculation of excited states in molecular systems by using quantum-chemical methods, a type of study that escapes in many cases from the well-established computational strategies used for the molecular ground states, both because of the complexity of the problem itself and for the methodological requirements. A short review of the spectroscopic and photochemical panorama will be provided first in order to explain which are the main parameters and processes to be determined, followed by a compact description of the most relevant and employed quantum-chemical methods and computational strategies for excited states. A number of applied examples of actual calculations on paradigmatic excited state problems will be provided in the different subchapters, followed in each case by comments on practical issues occurring in the calculations. With these cases we will try to demonstrate that in the last years the quantum-chemical studies on excited states have reached the required maturity to interpret and predict, at a molecular level, different types of chemical situations.

The properties of a molecule may change quite substantially when passing from the isolated state to a solution, and computational chemistry requires the possibility of taking into account the effects of a solvent on molecular properties. These changes are mainly due to long range interactions, and electrostatics involving a large number of solvent molecules play the major role in the phenomenon and free energy changes have to be evaluated. Statistical calculations by means of usual Monte Carlo or molecular dynamics coupled with a full quantum chemical description of a sample representative of the solution is still out of reach for standard molecular modeling computations nowadays. Nevertheless, several simplified approaches are available to evaluate the free energy changes which appear when an isolated molecule, as described by standard quantum computations, undergoes the influence of a solvent and to predict the changes in the molecular properties which are the consequences of solvation. In this chapter, we develop the principles of the most usual methods that a computational chemist can find in standard codes or can implement more or less easily to approach the solvent effects in quantum chemistry investigations.

The working equations of auxiliary density functional theory (ADFT) and auxiliary density perturbation theory (ADPT) are derived in the framework of the linear combination of Gaussian type orbital expansion. The ADFT and ADPT implementations in the density functional theory program deMon2k are discussed. The use of ADFT and ADPT in first-principle Born–Oppenheimer molecular dynamics at the pico- to nanosecond time scale is reviewed. In particular, the long-standing mystery of the discrepancy between experiment and computations for the polarizability of small sodium clusters is resolved. Applications of the parallel deMon2k ADFT implementation to systems on the nanometer scale are reviewed. This includes Al-zeolites and giant fullerenes. It is shown that structures as large as C₅₄₀m can be fully optimized without any symmetry constrains in the ADFT framework employing all-electron basis sets within a few days.

This chapter reviews most of the widely used non-relativistic quantum chemistry program packages. Considering that information about availability and capabilities of the free quantum chemistry programs is more limited than that of the commercial ones, the authors concentrated on the free programs. More specifically, the reviewed programs are free for the academic community. Features of these programs are described in detail. The capabilities of each free program can generally be categorized into five fields: independent electron model; electron correlation treatment; excited state calculation; nuclear dynamics including gradient and hessian; and parallel computation. Examples of input files for the Møller–Plesset calculation of formaldehyde are presented for most of the free programs to illustrate how to create the input files. The main contributors of each free program and their institutions are also introduced, with a brief history of program development if available. All the key references of the cited algorithms and the hyperlinks of the home page of each program (both free and commercial) are given in this review for the interested readers. As the most important information of every cited free program’s documentation has been extracted here, it is appropriate to consider this chapter to be the manual of manuals.

This chapter reports numerical models devoted to predict the optical and vibrational properties of nanoparticles treated as isolated objects or confined in host matrixes. The theoretical data obtained by the numerical simulations were confronted with the experimental investigations carried out by several spectroscopic methods such as Raman, IR, and UV-Vis absorption as well as photoluminescence. As model cluster systems, the physical properties of nanosized silicon carbide (SiC) particles in vacuum were numerically modeled. The computer simulations were also performed for SiC confined in polymeric matrix, namely, poly(methyl methacrylate), poly-N-vinylcarbazole, and polycarbonate. The obtained host–guest nanocomposites exhibit original optical and electro-optical features.The considered systems were built using molecular dynamic simulations method and the full atomistic modeling of the composite materials was performed using CVFF method. The equilibrated geometries of nanocomposites were used to evaluate their key physical features. Particularly, the electronic and vibrational properties of SiC were calculated in the cluster approach model. The suitable cluster size and the nature of terminating bonds used to saturate the outermost nanograin surface were judiciously evaluated with the criterion to achieve consistent agreement with experimental results such as IR absorption, Raman, vibrational density of states and photoluminescence responses. The role of SiC clusters and its interaction with the surrounding polymer were investigated for the hybrid host–guest nanocomposites and their electro-optical functionalities were evaluated. The polarizability and first-order hyperpolarizabilities responsible for second harmonic generation and Pockels effect were calculated using DFT method. Then, taking into account the environmental interaction between host and guest molecules the optical susceptibilities were predicted. The effect of the local electric fields involved at the organic–inorganic interfaces on the NLO parameters was taken into account for each system. Additionally it was found that polymer environment reconstructs the surface of the SiC nanograin, which contributes critically to the NLO properties of hybrid materials. Finally, the chapter shows in exhaustive way that the developed methodologies associating key experimental works and relevant numerical methods allows to tailor the suitable nanostructured materials with the optimal physical responses.

This chapter describes general principles in the stability and bonding of empty fullerenes, endohedral fullerenes, and exohedral derivatives of empty fullerenes. First, an overview of the structural properties of empty fullerenes is given. The problem of isomers’ enumeration is described and the origin of the intrinsic steric strain of the fullerenes is discussed in terms of POAV (π-orbital vector analysis) leading to the isolated pentagon rule (IPR). Finally, theoretical studies of the isomers of fullerenes are discussed. In the second part of the chapter, bonding phenomena and molecular structures of endohedral metallofullerenes (EMFs) are reviewed. First, the bonding situation in EMFs is discussed in terms of ionic/covalent dichotomy. Then, the factors determining isomers of EMFs, including those favoring formation of non-IPR cage isomers, are reviewed. In the third part, general principles governing addition of atomic addends and trifluoromethyl radicals to fullerenes are analyzed.

Materials that exhibit an electrical resistivity between that of conductor and insulator are called semiconductors. Devices based on semiconductor materials, such as transistors, solar cells, light-emitting diodes, digital integrated circuits, solar photovoltaics, and much more, are the base of modern electronics. Silicon is used in most of the semiconductor devices while other materials such as germanium, gallium arsenide, and silicon carbide are used for specialized applications. The obvious theoretical and technological importance of semiconductor materials has led to phenomenal success in making semiconductors with near-atomic precision such as quantum wells, wires, and dots. As a result, there is a lot of undergoing research in semiconductor clusters of small and medium sizes both experimentally and by means of computational chemistry since the miniaturization of devices still continues. In the next pages, we are going to learn which the most studied semiconductor clusters are, we will explore their basic structural features and visit some of the most representative ab initio studies that are considered as works of reference in this research realm. Also, we are going to be introduced to the theory of the electric properties applied in the case of clusters by visiting some of the most illustrative studies into this research area. It is one of the purposes of this presentation to underscore the strong connection between the electric properties of clusters and their structure.

This chapter discusses the structures, energetics, and vibrational spectra of the first few (n ≤ 24) water clusters obtained from high-level electronic structure calculations. The results are discussed in the perspective of being used to parameterize/assess the accuracy of classical and quantum force fields for water. To this end, a general introduction with the classification of those force fields is presented. Several low-lying families of minima for the medium cluster sizes are considered. The transition from the “all surface” to the “fully coordinated” cluster structures occurring at n = 17 and its spectroscopic signature is presented. The various families of minima for n = 20 are discussed together with the low-energy networks of the pentagonal dodecahedron (H₂O)₂₀ water cage. Finally, the low-energy networks of the tetrakaidecahedron (T-cage) (H₂O)₂₄ cluster are shown and their significance in the construction of periodic lattices of structure I (sI) of the hydrate lattices is discussed.

This chapter provides information on various carbon allotropes, and in-depth details of structures, electronic and chemical properties of graphene, fullerenes, and single-walled carbon nanotubes (SWCNTs). We have given an overview of different computational methods that were employed to understand various properties of carbon nanostructures. Importance of application of computational methods in exploring different sizes of fullerenes and their isomers is given. The concept of isolated pentagon rule (IRP) in fullerene chemistry has been revealed. The computational and experimental studies involving Stone–Wales (SW) and vacancy defects in fullerene structures are discussed in this chapter. The relationship between the local curvature and the reactivity of the defect-free and defective fullerene and single-walled carbon nanotubes has been revealed. We reviewed the influence of different defects in graphene on hydrogen addition. The viability of hydrogen and fluorine atom additions on the external surface of the SWCNTs is revealed using computational techniques. We have briefly pointed out the current utilization of carbon nanostructures and their potential applications.

This chapter reviews the fundamental concepts of excitons and excitonic polaritons and their extraordinary optical properties in quantum dot nano-composite materials. By starting with the optical excitation of an exciton in the nanostructure we show that the effective dielectric constant of the nanostructure becomes significantly modified due to the exciton generation and recombination, resulting in high positive and negative dielectric constants. We also discuss single exciton generation by multiple photons and multiple exciton generation by single photon. All these nonlinear optical properties of quantum dot nano-composite materials offer novel possibilities and are expected to have deep impact in nanophotonics.

The purpose of this chapter is to describe and review examples of how theoretical investigations can be applied to elucidate the behavior of carbon nanostructures and to understand the physical mechanisms taking place at the molecular level. We will place a special emphasis in theoretical works utilizing density functional theory. We assume that the reader is familiar with the basics of density functional theory as well as the electronic properties of single-walled carbon nanotubes and graphene nanoribbons (GNRs). We do not intend to present an extensive review; instead, we focus on several examples to illustrate the powerful predictive capabilities of current computational approaches.

Recent computer simulations have indicated that there is a linear relationship between the melting and the Curie temperatures for Ni _n (n ≤ 201) clusters. In this chapter, it is argued that this result is a consequence of the fact that the surface and the core (bulk) contributions to the cluster properties vary with the cluster size in an analogous way. The universal aspect of this result is also discussed. Among the many interesting consequences resulting from this relationship is the intriguing possibility of the coexistence of melting and magnetization. As demonstrated, these conclusions have as their origin the major contribution coming from the melting/magnetization ratio arising from surface effects and appear to overshadow all other contributions. As a result, this can be quantified with approximate methods which are suitable for describing any major surface contribution to a cluster property.

Clusters contain more than just some few atoms but not so many that theycan be considered as being infinite. By varying their size, their properties canoften be varied in a more or less controllable way. Often, however, the precise relation between size and property is largely unknown: The sizes of the systems are below the thermodynamic limit so that simple scaling laws do not apply. Theoretical studies of such systems can provide relevant information, although in many cases idealized systems have to be treated. The challenge of such calculations is the combination of the relatively large size of the systems together with an often unknown structure.In this presentation, different theoretical methods for circumventing these problems shall be discussed. They shall be illustrated through applications on various types of clusters. These include isolated metal clusters with one or two types of atoms, metal clusters deposited on a surface, nanostructured HAlO, semiconductor nanoparticles, and metallocarbohedrenes. Special emphasis is put on the construction of descriptors that can be used in identifying general trends.

Materials properties show a dependence on the dimensionality of the systems studied. Due to the increased importance of surfaces and edges, lower-dimensional systems display behavior that may be widely different from their bulk counterparts. As a means to complement the newly developed experimental methods to study these reduced dimensional systems, a large fraction of the theoretical effort in the field continues to be channeled towards computer simulations. This chapter reviews briefly the computational methods used for the low dimensional materials and presents how the materials properties change with dimensionality. Low dimensional systems investigated are classified into a few broad classes: 0D nanoparticles, 1D nanotubes, nanowires, nanorods, and 2D graphene and derivatives. A comprehensive literature will guide the readers’ interest in computational materials sciences.

Recent extensions of the coupled-cluster (CC) theory to molecular solutes described with the Polarizable Continuum Model (PCM) are summarized. The recent advances covered in this review regard: (1) the analytical gradients for the PCM-CC theory at the single and double excitation level and (2) the analytical gradients for the PCM-EOM-CC theory at the single and double excitation level for the descriptions of the excited state properties of molecular solutes. As coupled-cluster is the top level that quantum mechanical (QM) calculations on molecules can presently be performed, and the PCM model gives an effective description of the solute-solvent interaction, these computational advances can be profitably used to study molecular processes in condensed phase, where both the accuracy of the QM descriptions and the influence of the environment play a critical role.

We review the general concept of nonadiabatic quantum spin transitions in biochemistry. A few important examples are highlighted to illustrate the concept: the role of spin effects in oxidases, cytochromes, in dioxygen binding to heme, in photosynthesis, and in tentative models of consciousness. The most thoroughly studied of these effects are connected with dioxygen activation by enzymes. Discussion on the mechanisms of overcoming spin prohibitions in dioxygen reactions with flavin-dependent oxygenases and with hemoglobin and myoglobin is presented in some detail. We consider spin-orbit coupling (SOC) between the starting triplet state from the entrance channel of the O₂ binding to glucose oxidase, to ferrous heme, and the final singlet open-shell state in these intermediates. Both triplet (T) and singlet (S) states in these examples are dominated by the radical-pair structures $${\mathrm{D}}^{+}\mbox{ -}{\mathrm{O}}_{2}^{-}$$ induced by charge transfer; the peculiarities of their orbital configurations are essential for the SOC analysis. An account of specific SOC in the open π_g-shell of dioxygen helps to explain the probability of T-S transitions in the active site near the transition state. Simulated potential energy surface cross-sections along the reaction coordinates for these multiplets, calculated by density functional theory, agree with the notion of a relatively strong SOC induced inside the oxygen moiety by an orbital angular momentum change in the π_g-shell during the T-S transition. The SOC model explains well the efficient spin inversion during the O₂ binding with heme and glucose oxidase, which constitutes a key mechanism for understanding metabolism. Other examples of nontrivial roles of spin effects in biochemistry are briefly discussed.

Proteins play a crucial role in biological processes, therefore, understanding their structure and function is very important. In this chapter we give an overview on computer models of proteins. First we treat both major experimental structure determination methods, X-ray diffraction and NMR spectroscopy. In subsequent sections computer modeling techniques as well as their application to the construction of explicit models are discussed. An overview on molecular mechanics and structure prediction is followed by an overview of molecular graphics methods of structure representation. Protein electrostatics and the concept of the solvent-accessible surface are treated in detail. We devote a special section to dynamics, where time scales, structures, and interactions are discussed. Protein interactions are especially important, so protein hydration, ligand binding, and protein–protein interactions receive special attention. Finally, computer modeling of enzyme mechanisms is discussed. We try to demonstrate that protein representation by computers arrived to a very high degree of sophistication and reliability; therefore, even lots of experimental studies make use of such models. A list with 80 up-to-date bibliographic references helps the reader to get informed on further details.

Advances in computer technology offer great opportunities for new explorations of protein structure and dynamics. Sound and well-established theoretical models may be successfully used for searching new biochemical phenomena, correlations, and protein properties. In this review the fast-growing field of computer simulations of protein dynamics is presented. The principles of currently used computational methods are outlined and representative examples of their recent advanced applications are given. In particular, protein folding studies, protein-drug interactions, transport phenomena, ion channels activity, molecular machines mechanics, origins of molecular diseases, and simulations of single molecule AFM experiments are addressed.Experimentalists and management will not only become used to accepting the use of molecular modeling, but they will expect it. (Phillip R. Westmoreland)WTEC Panel Report on Applications of Molecular and Materials Modeling,NIST 2002 (USA)

Molecular dynamics (MD) simulations based on a classical force field are increasingly being used to study the structure and dynamics of nucleic acids. Simulation studies are limited by the accuracy of the force field description and by the time scale accessible by current MD approaches. In the case of specific conformational transitions it is often possible to improve the sampling of possible states by adding a biasing or umbrella potential along some coordinate describing the conformational transition. It is also possible to extract the associated free energy change along the reaction coordinate. The development of advanced sampling methods such as the replica-exchange MD (REMD) approach allows significant enhancement of conformational sampling of nucleic acids. Recent applications of umbrella sampling and REMD simulation as well as combinations of both methodologies on nucleic acids will be presented. These approaches have the potential to tackle many open questions in structural biology such as the role of nucleic acid structure during recognition and packing and the function of nucleic acid fine structure and dynamics.

Mixed-quantum classical dynamics simulations have recently become an important tool for investigations of time-dependent properties of electronically excited molecules, including non-adiabatic effects occurring during internal conversion processes. The high computational costs involved in such simulations have often led to simulation of model compounds instead of the full biochemical system. This chapter reviews recent dynamics results obtained for models of three classes of biologically relevant systems: protonated Schiff base chains as models for the chromophore of rhodopsin proteins; nucleobases and heteroaromatic rings as models for UV-excited nucleic acids; and formamide as a model for photoexcited peptide bonds.

Low-energy electrons (LEE) have been experimentally found to result in DNA damage such as base damage, base release, and strand breaks. This has engendered a considerable number of theoretical studies of the mechanisms involved in the DNA damage. In this chapter, we discuss the various pathways for LEE interaction with DNA and the theoretical treatments most suited to unravel these pathways. For example, inelastic electron scattering produces excitation, ionization, and transient negative ions (TNI) via shape, core-excited, and vibrational Feshbach resonances, which can all lead to DNA damage. Each of these pathways is distinguished and pertinent to the experimental results and theoretical approaches used to explain the results described. Shape resonances can be understood as interactions with the electron with unoccupied molecular orbitals of neutral molecule, while core-excited states involve excitation of inner shell electrons and can be treated with theoretical methods such as time-dependent density functional theory (TD-DFT) or CASSCF. In treating the electron–molecule interaction, special care is needed to distinguish between diffuse and valence states of the TNI. The role of the vertical and adiabatic states of the radical anion is important as the electron adds to the neutral molecular framework, and reactions induced likely occur before equilibration to the adiabatic state. The effect of solvation is critical to both energetics of the interaction and the nature of the TNI formed. For example, gas-phase calculations show diffuse dipole-bound character for adenine, guanine, and cytosine anion radicals, but each of these is found to be in a valence state in aqueous solution by experiment. DNA base anion radicals often show ground states that are diffuse in character and that collapse to valence states on solvation. Such processes are shown to be accounted for inclusion of the polarized continuum model (PCM) for solvation. TD-DFT excited-state calculations including solvation show that the diffuse states rise in energy on solvation as expected. For LEE in the aqueous phase, new energy states become available such as conduction band or presolvated electrons, which may have sufficient energy to cause DNA damage.

A comprehensive analysis of the benefits and pitfalls of quantum chemical methods used to determine the structures, properties, and functions of DNA and RNA fragments is presented. Main emphasis is given to the application of different ab initio quantum chemical methods. An overview of computations reveals that quantum chemical methods provide an important means to investigate structures and interactions in nucleic acids. However, judicious selection of computational approach is necessary, depending upon the nature of the problem under investigation.

This review summarizes computational studies devoted to interactions of metal cations with nucleobases, nucleotides, and short oligonucleotides considered as DNA/RNA models. Since this topic is complex, basically only the results obtained using ab initio and DFT methods are discussed. Part I focuses mainly on the interactions of the isolated bases with metal cations in bare, hydrated, and ligated forms. First, interactions of bare cations with nucleobases in gas phase approach are mentioned. Later, solvation effects using polarizable continuum models are analyzed and a comparison with explicitly hydrated ions is presented. In Part II, adducts of alkali metal, metal of alkaline earth, and zinc group metal cations with canonical base pairs are discussed. A separate section is devoted to platinum complexes related to anticancer treatment. Stacked bases and larger systems are discussed in last section. Here, semiempirical methods and molecular modeling are also discussed due to extensive size of studied complexes.

Quantitative structure–activity relationship (QSAR) modeling is the major chemin- formatics approach to exploring and exploiting the dependency of chemical, biological, toxicological, or other types of activities or properties on their molecular features. QSAR modeling has been traditionally used as a lead optimization approach in drug discovery research. However, in recent years QSAR modeling found broader applications in hit and lead discovery by the means of virtual screening as well as in the area of drug-like property prediction, and chemical risk assessment. These developments have been enabled by the improved protocols for model development and most importantly, model validation that focus on developing models with independently validated external prediction power. This chapter reviews the predictive QSAR modeling workflow developed in this laboratory that incorporates rigorous procedures for QSAR model development, validation, and application to virtual screening. It also provides several examples of the workflow application to the identification of experimentally confirmed hit compounds as well as to chemical toxicity modeling. We believe that methods and applications considered in this chapter will be of interest and value to researchers working in the field of computational drug discovery and environmental chemical risk assessment.

A thorough antimicrobial review of an increasing number of reports reveals a broad spectrum of research activity in the development practices that are used to treat a variety of diseases. The quantitative relationship between chemical structure and biological activity has received considerable attention in recent years because it allows one to predict theoretically bioactivity without an inordinate amount of experimental time and effort. In this chapter we collect and discuss critically published results concerning the QSAR research on antimicrobial compounds. Finally, we present an updated perspective about the future trends in this area.

This chapter focuses on the computational investigations of light-induced chemical reactions in different systems ranging from organic molecules in vacuo to chromophores in complex protein environments. The aim is to show how the methods of computational photochemistry can be used to attain a molecular-level understanding of the mechanisms of photochemical and photophysical transformations. Following a brief introduction to the field, the most frequently used quantum chemical methods for mapping excited state potential energy surfaces and for studying the mechanism of photochemical reactions in isolated molecules are outlined. In the following sections, such methods and concepts are further developed to allow the investigation of photo-induced reactions in solution and in the protein environment.