Chemoinformatics as a Theoretical Chemistry Discipline

  title={Chemoinformatics as a Theoretical Chemistry Discipline},
  author={Alexandre Varnek and Igor I. Baskin},
  journal={Molecular Informatics},
Here, chemoinformatics is considered as a theoretical chemistry discipline complementary to quantum chemistry and force‐field molecular modeling. These three fields are compared with respect to molecular representation, inference mechanisms, basic concepts and application areas. A chemical space, a fundamental concept of chemoinformatics, is considered with respect to complex relations between chemical objects (graphs or descriptor vectors). Statistical Learning Theory, one of the main… 
Chemoinformatics Analysis and Structural Similarity Studies of Food-Related Databases
Structural/activity relationships studies commonly conducted in medicinal chemistry for the purpose of drug discovery can be generalized to the study of structure–property relationships (SPR) for virtually any chemistry-related project.
Progress on open chemoinformatic tools for expanding and exploring the chemical space
This work discusses the recent progress on chemoinformatic tools developed to expand and characterize the chemical space of compound data sets using different types of molecular representations, generate visual representations of such spaces, and explore structure–property relationships in the context of chemical spaces.
Machine Learning Methods for Property Prediction in Chemoinformatics: Quo Vadis?
New approaches and concepts are focused on that may provide efficient solutions of common problems in chemoinformatics: improvement of predictive performance of structure-property (activity) models, generation of structures possessing desirable properties, model applicability domain, modeling of properties with functional endpoints, and accounting for multiple molecular species.
Continuous Molecular Fields Approach Applied to Structure-Activity Modeling
The Method of Continuous Molecular Fields is a universal approach to predict various properties of chemical compounds, in which molecules are represented by means of continuous fields (such as
Cheminformatics Explorations of Natural Products.
This work focuses on three major aspects: exploration of the chemical space of natural products to identify bioactive compounds, with emphasis on drug discovery; assessment of the toxicity profile of natural Products; and diversity analysis of natural product collections and the design of chemical collections inspired by natural sources.
Approaches for enhancing the analysis of chemical space for drug discovery.
INTRODUCTION Chemical space is a powerful, general, and practical conceptual framework in drug discovery and other areas in chemistry that addresses the diversity of molecules and it has various
Molpher: a software framework for systematic chemical space exploration
Molpher is an open-source software framework for the design of virtual chemical libraries focused on a particular mechanistic class of compounds that produces a path of structurally-related compounds through a process the authors term ‘molecular morphing’.
The Evolution of Data-Driven Modeling in Organic Chemistry
A synopsis of the history of data-driven modeling in organic chemistry and the terms used to describe these endeavors is provided and a timeline of the steps that led to its current state is included.
Diversity-Oriented Synthesis as a Tool for Chemical Genetics
In this review, the combination of chemical genetics and diversity-oriented synthesis to identify new chemotypes as hit compounds in chemical biology and drug discovery is reported, giving an overview of basic concepts and selected case studies.


Chemoinformatics: a new field with a long tradition
  • J. Gasteiger
  • Chemistry
    Analytical and bioanalytical chemistry
  • 2006
All areas of chemistry from analytical chemistry to drug design can benefit from chemoinformatics methods, and there are still many challenging chemical problems waiting for solutions through the further development of chemoin formatics.
Chemoinformatics—an introduction for computer scientists
The emphasis is placed on describing the general methods that are routinely applied in molecular discovery and in a context that provides for an easily accessible article for computer scientists as well as scientists from other numerate disciplines.
Chemoinformatics: Past, Present, and Future†
  • W. L. Chen
  • Computer Science
    J. Chem. Inf. Model.
  • 2006
The history of chemoinformatics is reviewed in a decade-by-decade manner from the 1940s to the present. The focus is placed on four traditional research areas: chemical database systems,
Basic Overview of Chemoinformatics
This review provides a general overview of basic methods in the specific fields of chemoinformatics, from encoding chemical compounds, storing and searching data in databases, to generating and analyzing these data.
Chemoinformatics: A Textbook
The "Textbook" provides an introduction to the representation of molecular structures and reactions, data types and databases/data sources, search methods, methods for data analysis as well as such applications as structure elucidation, reaction simulation, synthesis planning and drug design.
Molecular Field Topology Analysis Method in QSAR Studies of Organic Compounds
A new method of QSAR analysis for organic compounds, molecular field topology analysis (MFTA), is considered that involves the topological superposition of the training set structures and the
Quantifying the Relationships among Drug Classes
This work calculated the similarities between hundreds of drug targets and their ligands and mapped the relationship between them in a formal network, finding the chemoinformatics networks were more natural and more organized, by network theory, than their bioinformatics counterparts: ligand-based networks were found to be small-world and broad-scale.
Using molecular quantum similarity measures as descriptors in quantitative structure-toxicity relationships.
M molecular quantum similarity measures (MQSM) are used to describe molecular toxicity and to construct Quantitative Structure-Toxicity Relationships (QSTR) models and a new type of MQSM is presented: it is based on the expectation value of electron-electron repulsion energy.
Graph Kernels for Molecular Similarity
This work reviews the major types of kernels between graphs (based on random walks, subgraphs, and optimal assignments, respectively), and discusses their advantages, limitations, and successful applications in cheminformatics.
Chemometric Analysis of Ligand Receptor Complementarity: Identifying Complementary Ligands Based on Receptor Information (CoLiBRI)
It is shown that knowledge of the receptor active site structure affords identification of its complimentary ligand among the top 1% of a large chemical database in over 90% of all test active sites when a binding site of the same protein family was present in the training set.