AutoGrow: a novel algorithm for protein inhibitor design.

AutoGrow: a novel algorithm for protein inhibitor design.
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DOI:
10.1111/j.1747-0285.2008.00761.x
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发表时间:
2009-02
影响因子:
3
通讯作者:
McCammon JA
McCammon JA
中科院分区:
医学4区
文献类型:
--
作者:
Durrant JD;Amaro RE;McCammon JA

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在过去的几十年里,基于计算机的合理药物设计领域出现了爆炸式的发展,部分原因是晶体学蛋白质结构的可用性越来越高,以及计算能力的快速提高。通过优化配体-受体氢键、静电和疏水相互作用,已经开发了几种算法来识别或生成潜在的硅配体。我们在这里介绍AutoGrow,一种新型的计算机辅助药物设计算法,它结合了基于片段的生长和对接算法的优势。为了验证AutoGrow,我们从它们的组成片段重建了三个晶体学上分解的配体。
Due in part to the increasing availability of crystallographic protein structures as well as rapid improvements in computing power, the past few decades have seen an explosion in the field of computer-based rational drug design. Several algorithms have been developed to identify or generate potential ligands in silico by optimizing the ligand-receptor hydrogen bond, electrostatic, and hydrophobic interactions. We here present AutoGrow, a novel computer-aided drug design algorithm that combines the strengths of both fragment-based growing and docking algorithms. To validate AutoGrow, we recreate three crystallographically resolved ligands from their constituent fragments.
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