Symbolic Equation for the Instantaneous Amount of Substance in Linear Compartmental Systems

The symbolic time course equations corresponding to a general model of a linear compartmental system, closed or open, with or without traps and with zero input are presented in this chapter. From here, the steady state equations are obtained easily from the transient phase equations by setting the time towards infinite. Special attention is given to the open systems, for which an exhaustive kinetic analysis has been developed to obtain important properties. Besides, the results are particularized to open systems without traps. The software COEFICOM, easy to use and with a user-friendly format of the input of data and the output of results, allows the user to obtain the symbolic expressions of the coefficients involved in the general symbolic equation and all the information necessary to derive the symbolic time course equations for closed or open systems as well as for the derivation of the mean residence times.

Electrostatic Potential at Nuclei

Numerous applications showed that the EPN index, an accurate quantum mechanical quantity, predicts with remarkable accuracy the energy shifts accompanying hydrogen bonding. The theoretically evaluated EPN descriptor correlates also excellently with experimental and theoretically evaluated kinetic parameters for a number of important organic reactions. Based on these findings an efficient computational approach for the evaluation of substituent constants was developed.

Synthesis, Properties, and Applications of Special Substrates Coated by Titanium Dioxide Nanostructured Thin Films via Sol-Gel Process

In this chapter, the sol-gel made titanium dioxide nanostructured thin films deposited on special substrates such as glasses, mica, steels, textiles, fibers, and other organic/inorganic substrates were reviewed. Through this review, several distinctive properties such as optical, electrical, photocatalytic, morphological, and mechanical properties of TiO2 nanostructured thin films were described. Also, a wide range of practical application of TiO2 nanostructured thin films such as dye-sensitised solar cells, optical coatings, humidity and gas sensors, selfcleaning, dielectric, and antibacterial surfaces were discussed in details. Dip and spin coating techniques were demonstrated as suitable methods for deposition of thin films. It has been shown that properties of such films can be affected by type of coating technique, stabilizer, precursor material, solvents, pH and viscosity of precursor solution, aging, and etc. Finally, Successive Interference Fringes Method (SIFM) was presented as a simple method for the determination of optical constants and thickness of TiO2 thin films from single transmission measurements.

On Extended Topochemical Atom (ETA) Indices for QSPR Studies

Development of predictive models has been accepted as an important strategy to aid in toxicity screening of chemicals, determination of physicochemical as well as other biological activity of new molecules, and also in the generation and optimization of lead compounds in rational drug discovery process. The journey of quantitative structure-property relationship (QSPR) modeling started with the development of various property-based and two-dimensional descriptors to model various physicochemical and biological properties (including toxicity). Topological descriptors contain significant information encoded in the molecular structure. Extended topochemical atom (ETA) indices, a relatively new class of topological descriptors, are the focus point in this chapter. ETA indices contain important information regarding the nature of the atoms, bonds, atomic electronic environment and consider the contribution of different functional groups, molecular fragments, and branching to the response as evidenced by different reports showing their successful application in modeling different endpoints including toxicity, drug activity, and physicochemical properties. Extensive research is still going on for the refinement of the ETA indices by the incorporation of some novel parameters, and future reports on ETA indices will include these new indices.

Computational Techniques in Binding Affinity Prediction of Drugs

Computational techniques are widely used in the chemoinformatics and bioinformatics. Most of the drugs produce their effect by interacting with the target molecules via different interactions. However, these interactions are tough to be calculated without use of robotics techniques. The potentials of these drugs depend upon their binding affinity. Due to huge number of such drugs, the measurement of their relative potency is a hard task. In present chapter the authors have discussed about some most common techniques which are widely used in bioinformatics and chemoinformatics.

Virtual Screening

In this chapter, the authors analyze virtual screening advantages and the classification of virtual screening approaches. They also discuss the current and potential importance of virtual screening for drug development in Latin America. Finally, they present a brief overview on virtual screening perspectives.

Logistic vs. W-Lambert Information in Modeling Enzyme Kinetics at Quantum Level

The logistic temporal solution of the generalized Michaelis-Menten kinetics is employed to provide a quantum basis for the tunneling time and energy evaluations of Brownian enzymic reactions. The mono-substrate and mixed inhibition cases are treated and the associated quantum diagrams of the reaction mechanisms are depicted in terms of intermediate enzyme complexes. The methodology is suited for practically controlling of the enzymic activity throughout absorption spectroscopy.

Nanoparticles

Here, the authors show that an application of the QSAR methods for nanomaterials is nevertheless possible and can be useful in predicting their various properties and activities (toxicity). In the chapter briefly explained how the physico-chemical properties can be predicted for nanomaterials. Furthermore, it was also demonstrated how the biological activity, particularly toxicity, can be modeled and predicted for the series of nanoparticles, by applying the quantum-chemical methods in combination with the nano-QSAR.

An Epistemological Analysis of QSPR/QSAR Models

Computer sciences have deeply changed the way by which we make science or produce knowledge. With the era of computers and the development of computer science, quantum chemists were among the first scientists to explore the potentialities of the new tool, and even to collaborate in its development. In this way, they also became participants in what many dubbed as the Second Instrumental Revolution in chemistry. Deeply involved into this research field, QSAR methods are powerful tools to create knowledge on toxicology and drug design, among others. There are several epistemological questions to be analyzed in order to understand the truth and scientific value of their research results (from in silico to wet laboratories and vice versa).

Structural Classification of Complex Molecules by Artificial Intelligence Techniques

Algorithms for classification and taxonomy bases on criteria, e.g., information entropy. The feasibility of replacing a given molecule by similar ones in the composition of a complex drug is studied. Some local anaesthetics currently in use are classified using structural properties. In taxonomy the detailed comparison of the sequences of biomolecules, proteins or nucleic acids, allows the reconstruction of a molecular phylogenetic tree. The method is applied to the classifications of (1) indazolols (against Trichomonas vaginalis), (2) fullerenes and fullerite, (3) living and heat-inactivated lactic acid bacteria against cytokines, (4) phylogenesis of avian birds and 1918 influenza virus, (5) local anaesthetics, (6) transdermal-delivery percutaneous enhancers, (7) quantitative structure–activity relationship of anti-human immunodeficiency virus (HIV) compounds, (8) HIV inhibitors, e.g., thiocarbamates, N-aryloxazolidinone-5-carboxamides and styrylquinolines, (9) antimalarial aryltriazolylhydroxamates, (10) N-aryl-N-(3-aryl-1,2,4-oxadiazol-5-yl) amines against prostate cancer, antimitotic 2-phenylindole-3-carbaldehydes against breast cancer and anti-tubulin agents against gastric cancer with indole ring. The entropy contributions may be studied with the equipartition conjecture. It is not within the scope of our simulation method to replace biological tests of drugs or field data in palaeontology, but such simulation methods can be useful to assert priorities in detailed experimental research. Available experimental and field data should be examined by different classification algorithms to reveal possible features of real biological significance.