Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Fragmental approach in QSPR.

Nikolai S Zefirov1, Vladimir A Palyulin

  • 1Department of Chemistry, Moscow State University, Moscow 119992, Russia. zefirov@org.chem.msu.su

Journal of Chemical Information and Computer Sciences
|October 16, 2002
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Towards selecting the virtual series of molecules using the central fragment via R-FBDD at the early stages of drug discovery.

Molecular diversity·2026
Same author

Structural repair of mechanical defects in the Mycobacterium tuberculosis outer membrane. A molecular dynamics study.

Journal of molecular graphics & modelling·2026
Same author

Design of New Daunorubicin Derivatives with High Cytotoxic Potential.

International journal of molecular sciences·2025
Same author

Conjugates of amiridine and salicylic derivatives as promising multifunctional CNS agents for potential treatment of Alzheimer's disease.

Archiv der Pharmazie·2024
Same author

Ensemble docking based virtual screening of SARS-CoV-2 main protease inhibitors.

Molecular informatics·2024
Same author

Do electrostatic interactions make a difference in physics-based AutoDock4 scoring function?

Journal of computational chemistry·2024

Fragmental descriptors offer a transparent and interpretable alternative to topological indices for building quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) models when data is abundant.

Area of Science:

  • Computational chemistry
  • Cheminformatics

Background:

  • Quantitative structure-activity relationship (QSAR) and quantitative structure-property relationship (QSPR) models are crucial for predicting chemical compound properties.
  • Traditional methods often rely on topological indices, which can sometimes lack interpretability.

Purpose of the Study:

  • To address methodological challenges in using fragmental descriptors for QSAR/QSPR model construction.
  • To summarize and discuss key advancements in the application of fragmental descriptors.

Main Methods:

  • The study discusses the replacement of topological indices with sets of fragmental descriptors for model building.
  • Illustrative examples involve predicting retention indices and normal boiling points of organic compounds.

Main Results:

Related Experiment Videos

  • Fragmental descriptors can effectively substitute topological indices in statistically significant QSAR/QSPR models.
  • The fragmental approach demonstrates high predictive accuracy for various chemical properties.

Conclusions:

  • Fragmental descriptors provide a transparent and interpretable alternative for developing QSAR/QSPR models.
  • This approach enhances the understanding and application of structure-property relationships in chemistry.