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Targeting ion channels with ultra-large library screening for hit discovery.
Melancon, Kortney; Pliushcheuskaya, Palina; Meiler, Jens; Künze, Georg.
Afiliación
  • Melancon K; Department of Chemistry, Vanderbilt University, Nashville, TN, United States.
  • Pliushcheuskaya P; Center for Structural Biology, Vanderbilt University, Nashville, TN, United States.
  • Meiler J; Medical Faculty, Institute for Drug Discovery, Leipzig University, Leipzig, Germany.
  • Künze G; Department of Chemistry, Vanderbilt University, Nashville, TN, United States.
Front Mol Neurosci ; 16: 1336004, 2023.
Article en En | MEDLINE | ID: mdl-38249296
ABSTRACT
Ion channels play a crucial role in a variety of physiological and pathological processes, making them attractive targets for drug development in diseases such as diabetes, epilepsy, hypertension, cancer, and chronic pain. Despite the importance of ion channels in drug discovery, the vastness of chemical space and the complexity of ion channels pose significant challenges for identifying drug candidates. The use of in silico methods in drug discovery has dramatically reduced the time and cost of drug development and has the potential to revolutionize the field of medicine. Recent advances in computer hardware and software have enabled the screening of ultra-large compound libraries. Integration of different methods at various scales and dimensions is becoming an inevitable trend in drug development. In this review, we provide an overview of current state-of-the-art computational chemistry methodologies for ultra-large compound library screening and their application to ion channel drug discovery research. We discuss the advantages and limitations of various in silico techniques, including virtual screening, molecular mechanics/dynamics simulations, and machine learning-based approaches. We also highlight several successful applications of computational chemistry methodologies in ion channel drug discovery and provide insights into future directions and challenges in this field.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Screening_studies Idioma: En Revista: Front Mol Neurosci Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Screening_studies Idioma: En Revista: Front Mol Neurosci Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza