A frequent problem in computational modeling is the interconversion of chemical structures between different formats. While standard interchange formats exist (for example, Chemical Markup Language) and de facto standards have arisen (for example, SMILES format), the need to interconvert formats is a continuing problem due to the multitude of different application areas for chemistry data, differences in the data stored by different formats (0D versus 3D, for example), and competition between software along with a lack of vendor-neutral formats. We discuss, for the first time, Open Babel, an open-source chemical toolbox that speaks the many languages of chemical data. Open Babel version 2.3 interconverts over 110 formats. The need to represent such a wide variety of chemical and molecular data requires a library that implements a wide range of cheminformatics algorithms, from partial charge assignment and aromaticity detection, to bond order perception and canonicalization. We detail the implementation of Open Babel, describe key advances in the 2.3 release, and outline a variety of uses both in terms of software products and scientific research, including applications far beyond simple format interconversion. Open Babel presents a solution to the proliferation of multiple chemical file formats. In addition, it provides a variety of useful utilities from conformer searching and 2D depiction, to filtering, batch conversion, and substructure and similarity searching. For developers, it can be used as a programming library to handle chemical data in areas such as organic chemistry, drug design, materials science, and computational chemistry. It is freely available under an open-source license from http://openbabel.org
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Open Babel: An open chemical toolbox

The halogen bond occurs when there is evidence of a net attractive interaction between an electrophilic region associated with a halogen atom in a molecular entity and a nucleophilic region in another, or the same, molecular entity. In this fairly extensive review, after a brief history of the interaction, we will provide the reader with a snapshot of where the research on the halogen bond is now, and, perhaps, where it is going. The specific advantages brought up by a design based on the use of the halogen bond will be demonstrated in quite different fields spanning from material sciences to biomolecular recognition and drug design.

The Halogen Bond

ZINC is a free public resource for ligand discovery. The database contains over twenty million commercially available molecules in biologically relevant representations that may be downloaded in popular ready-to-dock formats and subsets. The Web site also enables searches by structure, biological activity, physical property, vendor, catalog number, name, and CAS number. Small custom subsets may be created, edited, shared, docked, downloaded, and conveyed to a vendor for purchase. The database is maintained and curated for a high purchasing success rate and is freely available at zinc.docking.org.

ZINC: A Free Tool to Discover Chemistry for Biology

4.2.8. Reductive Coupling 3109 5. Reaction of Aromatic Compounds 3110 5.1. Electrophilic Substitutions 3110 5.2. Radical Substitution 3111 5.3. Oxidative Coupling 3111 5.4. Photochemical Reactions 3111 6. Reaction of Carbonyl Compounds 3111 6.1. Nucleophilic Additions 3111 6.1.1. Allylation 3111 6.1.2. Propargylation 3120 6.1.3. Benzylation 3121 6.1.4. Arylation/Vinylation 3121 6.1.5. Alkynylation 3121 6.1.6. Alkylation 3121 6.1.7. Reformatsky-Type Reaction 3122 6.1.8. Direct Aldol Reaction 3122 6.1.9. Mukaiyama Aldol Reaction 3124 6.1.10. Hydrogen Cyanide Addition 3125 6.2. Pinacol Coupling 3126 6.3. Wittig Reactions 3126 7. Reaction of R,â-Unsaturated Carbonyl Compounds 3127

Organic Reactions in Aqueous Media with a Focus on Carbon−Carbon Bond Formations: A Decade Update

This paper emphasizes the importance of rigorous validation as a crucial, integral component of Quantitative Structure Property Relationship (QSPR) model development. We consider some examples of published QSPR models, which in spite of their high fitted accuracy for the training sets and apparent mechanistic appeal, fail rigorous validation tests, and, thus, may lack practical utility as reliable screening tools. We present a set of simple guidelines for developing validated and predictive QSPR models. To this end, we discuss several validation strategies including (1) randomization of the modelled property, also called Y-scrambling, (2) multiple leave-many-out cross-validations, and (3) external validation using rational division of a dataset into training and test sets. We also highlight the need to establish the domain of model applicability in the chemical space to flag molecules for which predictions may be unreliable, and discuss some algorithms that can be used for this purpose. We advocate the broad use of these guidelines in the development of predictive QSPR models.

The Importance of Being Earnest: Validation is the Absolute Essential for Successful Application and Interpretation of QSPR Models

Internet technology offers an excellent opportunity for the development of tools by the cooperative effort of various groups and institutions. We have developed a multi-platform software system, Virtual Computational Chemistry Laboratory, http://www.vcclab.org, allowing the computational chemist to perform a comprehensive series of molecular indices/properties calculations and data analysis. The implemented software is based on a three-tier architecture that is one of the standard technologies to provide client-server services on the Internet. The developed software includes several popular programs, including the indices generation program, DRAGON, a 3D structure generator, CORINA, a program to predict lipophilicity and aqueous solubility of chemicals, ALOGPS and others. All these programs are running at the host institutes located in five countries over Europe. In this article we review the main features and statistics of the developed system that can be used as a prototype for academic and industry models.

Virtual computational chemistry laboratory - design and description

X-philic reactions

The numerical characteristics of molecular structures, called topological indices, which are used for the quantitative description of the structures of organic compounds, are examined. The method of topological indices is analysed as one of the procedures for determining the relation between the structure of chemical compounds and their properties. The bibliography includes 164 references.

http://iopscience.iop.org/article/10.1070/RC1988v057n03ABEH003344/pdf

Nikolai S. Zefirov

Papers

Virtual computational chemistry laboratory - design and description

X-philic reactions

Topological Indices in Organic Chemistry

A new general approach to bicyclopropylidenes

Inverse problem in QSAR/QSPR studies for the case of topological indexes characterizing molecular shape (Kier indices)