The authors introduce the concept of Molecular Quantum Similarity, developed in their laboratory, in a didactic form. The basis of the concept combines quantum theoretical calculations with molecular structure and properties even for large molecules. They give definitions and procedures to compute similarities molecules and provide graphical tools for visualization of sets of molecules as n-dimensional point charts.

In recent years the fundamental concepts and applied methodologies of molecular similarity analysis have experienced a revolutionary development. Motivated by the increased degree of understanding of elementary molecular properties on the levels ranging from fundamental quantum chemistry to the complex interactions of biomolecules, and aided by the spectacular progress in computer technology and access to computer power, the area has opened up to many new ideas and new approaches. This book covers topics in quantum similarity approaches, electron density shape analysis methods, and it provides better theoretical understanding of molecular similarity. Additionally, quantitative shape analysis, especially activity relations (QShAR) and the prediction of the pharmacological or toxicological effects of molecules in the related context of quantum QSAR (QQSAR). This volume written by the experts in the various subfields of molecular similarity, provides a collection of the most recent ideas, advances, and methodologies. It is the hope of the Editors that by representing these topics within a single volume, the readers will find a balanced overview of the status of the field. We also hope that the book will serve as a tool for selecting and assessing the best approach for various new types of problems of molecular similarity that may arise and it will provide a set of easy references for further studies and applications.

This volume highlights some of the advances in molecular similarity. Molecular similarity research is a dynamic field where the rapid transfer of ideas and methodologies from the theoretical, quantum chemical and mathematical chemistry disciplines to efficient algorithms and computer programs used in industrially important applications is especially evident. These applications often serve as motivating factors toward new advances in the fundamental and theoretical fields, and the combination of intellectual challenge and practical utility provides mutual advantages to theoreticians and experimentalists. The aim of this volume is to present an overview of the current methodologies of molecular similarity studies, and to point out new challenges, unsolved problems, and areas where important new advances can be expected.

Observing computational chemistry's proven value to the introduction of new medicines, Computational Medicinal Chemistry for Drug Discovery offers the techniques most frequently utilized by industry and academia for ligand design. Featuring contributions from more than 50 preeminent scientists, this book surveys molecular structure computation, intermolecular behavior, ligand-receptor interaction, and modeling. It also examines molecular mechanics, semi-empirical methods, wave function-based quantum chemistry, density functional theory, 3-D structure generation, and hybrid methods.

REVIEWS IN COMPUTATIONAL CHEMISTRY Kenny B. Lipkowitz, Raima Larter, and Thomas R. Cundari This volume, like those prior to it, features chapters by experts in various fields of computational chemistry. TOPICS COVERED IN Volume 21 iNCLUDE AB INITIO QUANTUM SIMULATION IN SOLID STATE CHEMISTRY; MOLECULAR QUANTUM SIMILARITY; ENUMERATING MOLECULES; VARIABLE SELECTION; BIOMOLECULAR APPLICATIONS OF POISSON-BOLTZMANN METHODS; AND DATA SOURCES AND COMPUTATIONAL APPROACHES FOR GENERATING MODELS OF GENE REGULATORY NETWORKS. FROM REVIEWS OF THE SERIES "Reviews in Computational Chemistry remains the most valuable reference to methods and techniques in computational chemistry." --JOURNAL OF MOLECULAR GRAPHICS AND MODELLING "One cannot generally do better than to try to find an appropriate article in the highly successful Reviews in Computational Chemistry. The basic philosophy of the editors seems to be to help the authors produce chapters that are complete, accurate, clear, and accessible to experimentalists (in particular) and other nonspecialists (in general)." --JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

Volumes 2 and 3 of the 3D QSAR in Drug Design series aim to review the progress being made in CoMFA and other 3D QSAR approaches since the publication of the highly successful first volume about four years ago. Volume 2 (Ligand-Protein Interactions and Molecular Similarity) divides into three sections dealing with Ligand-Protein Interactions, Quantum Chemical Models and Molecular Dynamics Simulations, and Pharmacophore Modelling and Molecular Similarity, respectively. Volume 3 (Recent Advances) is also divided into three sections, namely 3D QSAR Methodology: CoMFA and Related Approaches, Receptor Models and Other 3D QSAR Approaches, and 3D QSAR Applications. More than seventy distinguished scientists have contributed nearly forty reviews of their work and related research to these two volumes which are of outstanding quality and timeliness. These works present an up-to-date coverage of the latest developments in all fields of 3D QSAR.

As a result of new statistical and mathematical approaches, improved visualization tools, and recognition by international regulatory groups, quantitative structure-activity relationships (QSARs) now play important roles in pharmacology for the design of new drugs as well as in toxicology and ecotoxicology for hazard identification and risk assessm

The aim of this text is to provide reviews and monographs on topics involving molecular similarity, ranging from the fundamental physical properties underlying molecular behaviour to applications in industrially important fields such as pharmaceutical drug design and molecular engineering. The editors hope that this series will encourage new ideas and approaches, help to systematize the rapidly accumulating new chemical information, and make chemistry better understood and better applied.

Utilizing multiple theorems derived from Z = {∀Θ∈Z→∃s ∈ S ʌ ∃t ∈ T: Θ= 〈 (s,t)}., and formulating the equation: X=O+Σ H +( n (log)Φ/P d x , as well as some mathematical constraints and numerous implications in Quantum Physics, Classical Mechanics, and Algorithmic Quantization, we come up with a framework for mathematically representing our universe. These series of individualized papers make up a huge part of a dissertation on the subject matter of Quantum Similarity. Everything including how we view time itself and the origin point for our universe is explained in theoretical details throughout these papers.