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By Kenny B. Lipkowitz, Donald B. Boyd
Computational chemistry is more and more utilized in so much parts of molecular technology together with natural, inorganic, medicinal, organic, actual, and analytical chemistry. Researchers in those fields who do molecular modelling have to comprehend and remain present with fresh advancements. This quantity, like these sooner than it, positive factors chapters by way of specialists in numerous fields of computational chemistry. chapters specialize in molecular docking, certainly one of which pertains to drug discovery and cheminformatics and the opposite to proteomics. furthermore, this quantity includes tutorials on spin-orbit coupling and mobile automata modeling, in addition to an in depth bibliography of computational chemistry books.FROM reports OF THE sequence "Reviews in Computational Chemistry is still the main useful connection with tools and strategies in computational chemistry."—JOURNAL OF MOLECULAR photographs AND MODELLING"One can't typically do larger than to aim to discover a suitable article within the hugely winning experiences in Computational Chemistry. the fundamental philosophy of the editors appears to be like to aid the authors produce chapters which are entire, exact, transparent, and available to experimentalists (in specific) and different nonspecialists (in general)."—JOURNAL OF the yank CHEMICAL SOCIETY
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Additional resources for Reviews in Computational Chemistry, Volume 17
Example text
Handling Protein Flexibility Most approaches for protein–ligand docking treat the protein as a rigid structure. Although this is an oversimplification in the general case, for many proteins this is a reasonable assumption, but for other proteins the assumption fails. Protein flexibility plays an important role in protein–ligand binding, and algorithms considering these additional degrees of freedom should work better. In principle, protein flexibility can directly be handled by MD- or MCbased algorithms as described above.
During the MD simulation, only the protein’s receptor site atoms and the ligand atoms are allowed to move and are considered explicitly in the energy calculation. The method can be combined with an implicit model of solvation. Although such approaches lead to a significant speedup over methods that treat the protein as fully flexible, they are still too time consuming for screening purposes. Therefore, one is interested in introducing protein flexibility into the much faster, fragmentation-based approaches.
Currently, the best performing docking algorithms take about 1–3 min of CPU time for a ligand–protein docking experiment. The use of docking as a virtual screening tool is more challenging than using it as a ligand design tool. If many structurally diverse compounds are docked, they need to be ranked according to their predicted binding affinity to the protein. In practice, it is rather unlikely to find a strongly binding ligand in a screening database of compounds. Hence, the docking–scoring approach has to be able to identify weak binders in a pool of nonbinders.