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Rapid evaluation of synthetic and molecular complexity for in silico chemistry.

Abstract：

:Methods that rapidly evaluate molecular complexity and synthetic feasibility are becoming increasingly important for in silico chemistry. We propose a new metric based on relative atomic electronegativities and bond parameters that evaluate both synthetic and molecular complexity (SMCM) starting from chemical structures. Against molecular weight, SMCM has the lowest fraction of adjusted variance (R2=0.535) on a series of 261,048 diverse compounds, when compared to the complexity metric of Baron and Chanon (R2=0.777; J. Chem. Inf. Comput. Sci. 2001, 41, 269-272) and Rücker (R2=0.895 for log complexity values; J. Chem. Inf. Comput. Sci. 2004, 44, 378-386), respectively. These metrics are in general agreement when the metabolic synthesis of cholesterol from S-3-hydroxy-3-methyl-glutaryl coenzyme A is monitored, indicating that SMCM can be useful in discerning increases in complexity. Because the presence of substructure patterns can be directly incorporated into this scheme, SMCM is relatively straightforward and can be easily tailored to rapidly evaluate virtual (combinatorial) libraries and high throughput screening hits.

journal_name

J Chem Inf Model

journal_title

Journal of chemical information and modeling

authors

Allu TK,Oprea TI

doi

10.1021/ci0501387

keywords:

subject

Has Abstract

pub_date

2005-09-01 00:00:00

pages

1237-43

issue

5

eissn

1549-9596

issn

1549-960X

journal_volume

45

pub_type

杂志文章

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