Inverse design of large molecules using linear diophantine equations

Shawn Martin, W. M. Brown, J. Faulon, Derick C. Weis, D. Visco
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引用次数: 1

Abstract

We have previously developed a method for the inverse design of small ligands. This method can be used to design novel compounds with optimized properties (such as drugs) and has been applied successfully to the design of small peptide antagonists to leukocyte functional antigen-1 (LFA-1) and its intercellular adhesion molecule (ICAM-1). A key step in our method involves computing the Hilbert basis of a system of linear Diophantine equations. In our previous application, the ligands considered were small peptide rings, so that the resulting system of Diophantine equations was relatively small and easy to solve. When considering larger molecules, however, the Diophantine system is larger and more difficult to solve. In this work we present a method for reducing the system of Diophantine equations before they are solved, allowing the inverse design of larger compounds. We present this reduction on our original LFA-1/ICAM-1 dataset, where we were able to reduce a system with 24 equations and 49 variables to an equivalent system with 11 equations and 34 variables, giving a 10 times speedup in performance. We also present the results of our reduction on two new datasets, neither of which we could solve previously: a set of 27 conazole fungicides and a set of 61 /spl gamma/-secrerase inhibitors.
利用线性丢番图方程的大分子反设计
我们以前已经开发了一种小配体逆设计的方法。该方法可用于设计具有优化性能的新化合物(如药物),并已成功应用于设计白细胞功能抗原-1 (LFA-1)及其细胞间粘附分子(ICAM-1)的小肽拮抗剂。我们方法的一个关键步骤是计算线性丢芬图方程系统的希尔伯特基。在我们之前的应用中,考虑的配体是小的肽环,因此得到的丢芬图方程体系相对较小,易于求解。然而,当考虑更大的分子时,丢番图体系更大,更难以求解。在这项工作中,我们提出了一种方法来减少丢番图方程的系统之前,他们被解决,允许反设计较大的化合物。我们在原始的LFA-1/ICAM-1数据集上展示了这种缩减,在那里我们能够将具有24个方程和49个变量的系统减少到具有11个方程和34个变量的等效系统,从而使性能加速10倍。我们还展示了我们在两个新数据集上的还原结果,这两个数据集以前都无法解决:一组27个康唑杀菌剂和一组61 /spl γ /-分泌酶抑制剂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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