| QSAR services | |
| CDD offers computational services | |
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in the process of optimizing lead compounds |
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to rationalize results from screening programs |
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minimize adverse or toxic effects or to exclude compounds expected to show such effects |
| with the objective of saving experiments and increasing the chances for a successful drug discovery by supporting decision making in experimental work: | |
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Design of training series and chemical libraries to |
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obtain a maximum amount of information with a minimum of synthesis. |
| Set selection in combination with combinatorial chemistry to | |
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avoid redundancy. |
| Chemometric structure-activity analyses to | |
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optimize a desired effect |
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increase selectivity |
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decrease toxicity, side or adverse effects, respectively |
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filter out compounds with unfavorable properties |
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optimize pharmacokinetics |
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support "hit to lead" decisions. |
| Chemometric structure-property analysis to | |
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predict chemical properties |
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provide and select appropriate chemical parameters for structure-activity analysis. |
| Chemometric analyses of data from different tests or from screening systems to | |
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optimize biological test systems |
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check the relevance of in vitro tests |
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estimate biological potencies which may be difficult to measure from results in other tests |
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understand and predict pharmacological/biological profiles |
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separate pharmacodynamic and pharmacokinetic effects. |
| Analyses of large sets of structurally diverse compounds by topological methods to | |
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find topological pharmacophores |
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obtain more hits in screening programs |
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to arrive at new lead structures |
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extract knowledge from data bases. |
| A variety of chemometric methods supported by molecular modeling is available at CDD including 3D-QSAR and special techniques to deal with semiquantitative or qualitative biological data (e.g., scores). | |
| The service includes all necessary steps: | |
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Problem recognition and formulation |
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Data analysis |
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Feedback: detailed report and proposals for chemical synthesis and/or biological testing |
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Fine tuning to account for specific practical needs (e.g., synthetic feasibility). |