By Ana Sofia Pina, Abid Hussain, Ana Cecília A. Roque (auth.), Ana Cecília A. Roque (eds.)
Drug study has been drastically reworked through the "omics revolution" and advances in computational instruments, combinatorial chemistry, and excessive throughput screening recommendations (HTS). those implements have complex the facility to spot goal molecules that function issues of assault for destiny medications, the layout and synthesis of power lead compounds, and additional characterization, screening, and assays for healing efficacy and toxicity. In Ligand-Macromolecular Interactions in Drug Discovery: tools and Protocols, specialists within the box spotlight the most ideas and methodologies at the moment used in the research of molecular interactions among compounds, both man-made or natural, and complementary organic ambitions, in the scope of drug discovery. starting with a ancient point of view of drug study concentrating on the contribution of genomics, proteomics, high-throughput equipment, and computational advancements in drug discovery, the e-book then delves into hugely exact tools on subject matters similar to NMR spectroscopy, compound library layout and synthesis, chemical and organic microarrays, etc. Written within the hugely winning Methods in Molecular Biology™ sequence structure, chapters contain introductions to their respective matters, lists of the required fabrics and reagents, step by step, easily reproducible protocols, and notes on troubleshooting and warding off recognized pitfalls.
Authoritative and state-of-the-art, Ligand-Macromolecular Interactions in Drug Discovery: tools and Protocols will function an amazing consultant to scientists in academia and in who're striving to extra our wisdom of medicines.
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Additional resources for Ligand-Macromolecular Interactions in Drug Discovery: Methods and Protocols
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Two approaches have been used in order to interpret the electron density of an unknown ligand, both relying on ligand databases. One method tries to fit a model into the unknown density. 46 Carvalho, Trincão, and Romão The second approach compares the unknown density with the calculated densities of ligands from the test set. Terwilliger and coworkers (41) have developed the ligand-fitting approach, applying it to many protein-ligand complexes found in the PDB using a large variety of ligands as diverse as the heme group, glycerol, ATP, cAMP, GTP, NAG.
Each possible ligand is fitted to the density and ranked based on the correlation between calculated and observed density. Ligands with unique shapes usually generate the best results. In these cases, the highest score corresponds to the correct ligand identification and fitting (and is usually easily distinguishable from the next best scores). Unfortunately, this is not always true for densities where many ligands can fit into. The resolution and the quality of the electron density maps are crucial for the discrimination between candidate ligands.