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What is Physical Chemistry?01:23

What is Physical Chemistry?

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Physical chemistry is a branch of chemistry that studies the principles from physics underlying chemical reactions. It provides deep insights into the behaviors of molecules, the forces they experience, and their interactions and chemical reactions.The term "physical chemistry" was introduced by Mikhail Lomonosov in 1752. Since then, it has seen significant contributions from notable scientists such as Josiah Willard Gibbs, Wilhelm Ostwald, Jacobus Henricus van't Hoff, and Linus Pauling.Key...
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Organic chemistry is the study of compounds of carbon called organic compounds. Organic compounds either originate from living organisms or are synthesized by chemists. A defining trait of these compounds is the presence of carbon as the principal element, which is bonded to other carbon atoms and other elements such as hydrogen, oxygen, nitrogen, and sulfur. The existence of a wide array of organic molecules is a consequence of carbon atoms’ ability to form up to four strong bonds to...
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Chemoinformatics as a Theoretical Chemistry Discipline.

Alexandre Varnek1, Igor I Baskin2

  • 1Laboratoire d'Infochimie, UMR 7177 CNRS, Université de Strasbourg, 4, rue B. Pascal, Strasbourg 67000, France. varnek@unistra.fr.

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Chemoinformatics, a theoretical chemistry field, complements quantum chemistry and molecular modeling. This study explores their relationships, focusing on chemical space and structure-property modeling via Statistical Learning Theory.

Keywords:
Chemical spaceChemoinformaticsComputational learning theorySimilarity

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Area of Science:

  • Theoretical Chemistry
  • Computational Chemistry
  • Chemoinformatics

Background:

  • Chemoinformatics is a theoretical chemistry discipline.
  • It complements quantum chemistry and force-field molecular modeling.
  • Understanding these relationships is crucial for advancing chemical research.

Purpose of the Study:

  • To compare chemoinformatics with quantum chemistry and molecular modeling.
  • To explore the concept of chemical space in chemoinformatics.
  • To discuss the links between chemoinformatics and related fields.

Main Methods:

  • Comparative analysis of theoretical chemistry disciplines.
  • Review of Statistical Learning Theory for structure-property modeling.
  • Discussion of interdisciplinary connections.

Main Results:

  • Chemoinformatics, quantum chemistry, and molecular modeling differ in molecular representation, inference, concepts, and applications.
  • Chemical space, involving complex relations between chemical objects, is a key chemoinformatics concept.
  • Statistical Learning Theory is a primary mathematical approach for structure-property modeling.

Conclusions:

  • Chemoinformatics offers a unique perspective complementary to traditional computational chemistry methods.
  • The study highlights the importance of chemical space and advanced modeling techniques.
  • Established links between chemoinformatics, machine learning, chemometrics, and bioinformatics are reinforced.