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====== Typical use cases of Mcule ====== | ====== Typical use cases of Mcule ====== | ||
- | **__[[ordsingle|Ordering a single compounds | + | - **[[usecasehitident|IDENTIFY NEW HITS FOR YOUR TARGET |
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- | **__[[ordmculelist|Ordering a list of compounds from mcule ID list >>]]__** | + | - **[[ordsingle|ORDER A SINGLE COMPOUND |
- | + | - **[[ordmculelist|ORDER A LIST OF COMPOUNDS FROM MCULE ID LIST >> | |
- | **__[[ordlist|Ordering a list of compounds >> | + | - **[[ordlist|ORDER A LIST OF COMPOUNDS |
- | + | - **[[ordancat|ORDER ANALOGS FROM CATALOGS | |
- | **__[[ordancat|Order analogs from catalogs (hit expansion) >> | + | - **[[usecasedownload|DOWNLOAD THE MCULE DATABASE AND COME BACK FOR ORDERING |
- | + | - **[[usecaseprefilter|PREFILTER THE MCULE DATABASE | |
- | **__[[usecasedownload|Download the Mcule database and come back for ordering >> | + | |
- | + | - **[[inhouseext|EXTEND YOUR IN-HOUSE COMPOUND DECK >> | |
- | **__[[usecaseprefilter|Prefilter the Mcule database (design a screening library) >> | + | |
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- | **__[[usecasedownloadsubset|Download the Mcule database and come back for ordering >> | + | |
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- | ==== Extend your in-house compound deck ==== | + | |
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- | The Mcule database contains millions of **[[purchasable|Purchasable compounds]]** providing a great pool of compounds to extend your existing in-house library. You can prefilter the Mcule database based on your own criteria, export it, select the interesting compounds in-house and **[[http:// | + | |
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- | **__[[usecases|Go back to use cases >>]]__** | + | |
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- | ==== Optimize hits and leads ==== | + | |
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- | [[http:// | + | |
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- | Mcule offers a continuously growing set of intuitive, easy-to-use modeling applications specifically designed to evaluate and generate ideas in the hit/lead optimization process. | + | |
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- | **__[[usecases|Go back to use cases >>]]__** | + | |
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- | == A) Optimize binding affinity and selectivity with 1-Click Docking == | + | |
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- | Molecular docking simulations predict the binding orientation and affinity of a ligand to a target. | + | |
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- | 1. Go to **[[http:// | + | |
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- | 2. Specify your existing hit/lead (either by drawing or by providing a chemical identifier such as mcule ID, SMILES, InChI or InChIKey) | + | |
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- | 3. Select or upload a target | + | |
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- | 4. Click on **" | + | |
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- | 5. After the docking calculation finishes you can check the estimated binding affinity (docking score - more negative means higher affinity) and visualize the critical interactions that have been formed between your ligand and the target by clicking on **" | + | |
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- | 6. Go back and draw a slightly modified version of your hit/lead | + | |
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- | 7. Click on **" | + | |
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- | 8. After the docking calculation finishes you can compare the docking scores and the formed interactions of the modified molecule and those of the original hit/lead. | + | |
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- | 9. To get an idea where the compound can be further adjusted, take a closer look at the binding mode (**" | + | |
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- | 10. Continue testing new ideas and improve the docking scores. You can also run other Lead Optimization tools, such as **[[http:// | + | |
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- | 11. You can check your previous 1-Click Docking results and queries **[[http:// | + | |
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- | 12. Additionally, | + | |
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- | **__[[usecases|Go back to use cases >>]]__** | + | |
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- | == B) Generate new ideas and eliminate problematic parts by 1-Click Scaffold Hop == | + | |
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- | Scaffold hopping is about finding novel active ligands structurally different from a reference ligand (query). Scaffold hopping can be particularly useful during lead optimization to generate new ideas or to eliminate particular parts of your hit/lead to fix IP, toxicity, selectivity or pharmacokinetic issues. 1-Click Scaffold Hop is searching different subsets of **[[purchasable|Purchasable compounds]]** | + | |
- | that might be structurally different but share pharmacophore properties with those of the query. | + | |
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- | 1. Go to **[[http:// | + | |
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- | 2. Depending on your **[[http:// | + | |
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- | 3. Specify your existing hit / lead / reference ligand | + | |
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- | 4. Click on **" | + | |
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- | 5. After the calculation finishes you can find a number of diverse scaffolds that have similar pharmacophore properties as your query | + | |
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- | 6. Click on **" | + | |
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- | 7. Remember that all displayed hits are purchasable. To order any of them, click on the orange **" | + | |
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- | 8. You can check your previous 1-Click Scaffold Hop results and queries **[[http:// | + | |
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- | 9. You can use the other Lead Optimization tools, such as **[[http:// | + | |
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- | **__[[usecases|Go back to use cases >>]]__** | + | |
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- | == C) Property calculator == | + | |
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- | ADMET properties heavily depend on physicochemical properties. For example, high logP (> 5) and molecular weight (> 500 g/mol) are typically associated with unsuitable ADMET profile. Property calculator creates a physicochemical property profile for your compound in seconds. You can reject compounds with unsuitable logP, insufficient number of H-bond acceptors/ | + | |
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- | 1. Go to **[[http:// | + | |
- | + | ||
- | 2. Specify your existing hit/lead (either by drawing or by providing a chemical identifier such as mcule ID, SMILES, InChI or InChIKey) | + | |
- | + | ||
- | 3. Click on **" | + | |
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- | 4. Check the calculated properties of your original hit/lead. Depending on your **[[http:// | + | |
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- | 5. Go back and draw a slightly modified version of your hit/lead | + | |
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- | 6. Click on **" | + | |
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- | 7. After the calculation finishes you can check the individual properties and see if problematic properties got improved due to your modification in the hit/lead structure | + | |
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- | 8. You can use the other Lead Optimization tools, such as **[[http:// | + | |
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- | **__[[usecases|Go back to use cases >>]]__** | + | |
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- | == D) Toxicity checker == | + | |
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- | Certain structural elements of a molecule can be responsible for toxicity. In fact, some substructural motifs occur more frequently in toxic compounds than in non-toxic ones. It therefore makes sense to eliminate such structural motifs from hits/leads as early as possible. Toxicity Checker is based on more than 100 toxic and promiscuous scaffolds. It displays an alert, when such a motif is found, and it displays the incriminated part of the molecule. | + | |
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- | 1. Go to **[[http:// | + | |
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- | 2. Specify your existing hit/ | + | |
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- | 3. Click on **" | + | |
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- | 4. If the compound contains any potential toxic substructure, | + | |
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- | 5. Go back and try to modify the problematic motif of your hit/lead | + | |
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- | 6. Click on **" | + | |
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- | 7. Continue the modifications, | + | |
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- | 8. You can use the other Lead Optimization tools, such as **[[http:// | + | |
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- | **__[[usecases|Go back to use cases >>]]__** | + | |
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- | ==== Hit identification ==== | + | |
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- | [[http:// | + | |
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- | You can identify new inhibitors/ | + | |
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- | == A) Structure-based virtual screen == | + | |
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- | Structure-based virtual screening utilizes the 3D structure of the target when searching for new hits. During the screening, predicted 3D structures of small molecules are fitted into the binding site of the experimentally determined or modeled 3D structure of the target (docking calculation). The 3D structures of thousands of large macromolecules have been already determined by X-ray crystallography or NMR spectroscopy and can be easily selected or uploaded in Mcule. Small molecules predicted to form critical interactions with the target get better (more negative) docking scores and are ranked higher. | + | |
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- | 1. Go to **[[https:// | + | |
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- | 2. Select the input collection if other than all **[[purchasable|Purchasable compounds]]** of the Mcule database | + | |
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- | 3. The loaded template workflow includes a number of individual workflow steps that will be executed sequentially on the input collection. Detailed description of the available workflow steps can be found **[[tools|HERE]]**. | + | |
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- | 4. RUN | + | |
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- | go back and change pm-s and see the results | + | |
- | output collection size | + | |
- | sampler | + | |
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- | **__[[usecases|Go back to use cases >> | + | |
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- | == B) Ligand-based virtual screen == | + | |
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- | Ligand-based virtual screening does not utilize the 3D structure of the target when searching for new hits. Instead, it is based on the structure of a reference ligand (endogenous ligand, known inhibitor, etc.) that binds to a target and/or exhibits some beneficial effect. In ligand-based virtual screening, compounds are typically ranked based on the similarity to the reference ligand (query). | + | |
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- | **__[[usecases|Go back to use cases >>]]__** | + |
usecases.txt · Last modified: 2014/01/01 15:23 by flack