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  2. Computational Resource for Drug Discovery - Wikipedia

    en.wikipedia.org/wiki/Computational_Resource_for...

    GDoQ: GDoQ (Prediction of GLMU inhibitors using QSAR and AutoDock) is an open source platform for predicting inhibitors against Mycobacterium tuberculosis (M.Tb) drug target N-acetylglucosamine-1-phosphate uridyltransferase (GLMU) protein. This is a potential drug target involved in bacterial cell wall synthesis.

  3. Chemoproteomics - Wikipedia

    en.wikipedia.org/wiki/Chemoproteomics

    An example drug affinity responsive target stability (DARTS) workflow. Binding of a drug to a protein often leads to ligand-induced stabilization of the protein. In DARTS, drug and control treated proteins are subjected to limited proteolysis and the extent of protein digestion can either be visualized on a gel or measured by mass spectrometry .

  4. Scoring functions for docking - Wikipedia

    en.wikipedia.org/wiki/Scoring_functions_for_docking

    Machine-learning scoring functions have consistently been found to outperform classical scoring functions at binding affinity prediction of diverse protein-ligand complexes. [17] [18] This has also been the case for target-specific complexes, [19] [20] although the advantage is target-dependent and mainly depends on the volume of relevant data ...

  5. Drug design - Wikipedia

    en.wikipedia.org/wiki/Drug_design

    The phrase "drug design" is similar to ligand design (i.e., design of a molecule that will bind tightly to its target). [6] Although design techniques for prediction of binding affinity are reasonably successful, there are many other properties, such as bioavailability, metabolic half-life, and side effects, that first must be optimized before a ligand can become a safe and effictive drug.

  6. Protein–ligand docking - Wikipedia

    en.wikipedia.org/wiki/Protein–ligand_docking

    Computer-aided drug design (CADD) was introduced in the 1980s in order to screen for novel drugs. [3] The underlying premise is that by parsing an extremely large data set for chemical compounds which may be viable to make a certain pharmaceutical, researchers were able to minimize the amount of novel without testing them all experimentally.

  7. Phenotypic screening - Wikipedia

    en.wikipedia.org/wiki/Phenotypic_screening

    This approach is known as "reverse pharmacology" or "target based drug discovery" (TDD). [5] However recent statistical analysis reveals that a disproportionate number of first-in-class drugs with novel mechanisms of action come from phenotypic screening [6] which has led to a resurgence of interest in this method. [1] [7] [8]

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  9. Therapeutic Targets Database - Wikipedia

    en.wikipedia.org/wiki/Therapeutic_Targets_Database

    Target validation normally requires the determination that the target is expressed in the disease-relevant cells/tissues, [6] it can be directly modulated by a drug or drug-like molecule with adequate potency in biochemical assay, [7] and that target modulation in cell and/or animal models ameliorates the relevant disease phenotype. [8]

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