Computational chemistry approaches to drug discovery in signal transduction (Record no. 45267)

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fixed length control field 02632nam a2200229Ia 4500
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control field MX-MdCICY
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control field 20250625140643.0
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Transcribing agency CICY
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Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) B-11040
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Title Computational chemistry approaches to drug discovery in signal transduction
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Volume/sequential designation Biotechnology Journal, 3(4), p.456-509, 2008
520 3# - SUMMARY, ETC.
Summary, etc. The advent of therapeutic strategies aimed at targeting specific macromolecular components of deregulated signaling pathways associated with particular disease states has given rise to the idea that it should be possible to design ligands as drug candidates to these targets from first principles. This concept has been beckoning for a long time but structure-based ligand design only became feasible once it was possible to determine the 3-D structures of molecular targets at atomic resolution. However, structure-based design turned out to be difficult, chiefly because under physiological conditions both receptors and ligands are not static but they behave dynamically. While it is possible to design ligands with high steric and electronic complementarity to a receptor site, it is always uncertain how biologically relevant the assumed conformations of both ligand and receptor actually are. The fact that it remains beyond our current abilities to predict with sufficient accuracy the affinity between hypothetical ligand and receptor poses is in part connected with this problem and continues to confound the reliable prediction of drug-like ligands for therapeutic targets. Nevertheless, significant progress has been made and so-called virtual screening methods that use computational methods to dock candidate ligands into receptor sites and to score the resulting complexes are now used routinely as one of the components in drug discovery screening campaigns. Here an overview is given of the underlying principles, implementations, and applications of structure-guided computational design technologies. Although the emphasis is on receptor-based strategies, mention will also be made of some of the more established ligand- based approaches, such as similarity analyses and quantitative structure-activity relationship methods.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTATIONAL CHEMISTRY
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MOLECULAR MODELING
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Topical term or geographic name entry element MOLECULAR RECOGNITION
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element STRUCTURE-BASED DRUG DESIGN
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element VIRTUAL SCREENING
700 12 - ADDED ENTRY--PERSONAL NAME
Personal name Fischer, P.M.
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Uniform Resource Identifier <a href="https://drive.google.com/file/d/11TWe7iCOCqwMnAo5hb3UwFG_7USVHvW3/view?usp=drivesdk">https://drive.google.com/file/d/11TWe7iCOCqwMnAo5hb3UwFG_7USVHvW3/view?usp=drivesdk</a>
Public note Para ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx
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Source of classification or shelving scheme Clasificación local
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  Clasificación local     Ref1 CICY CICY Documento préstamo interbibliotecario 25.06.2025   B-11040 25.06.2025 25.06.2025 Documentos solicitados