| Abstract
| - Methods that rapidly evaluate molecular complexity and synthetic feasibility are becoming increasinglyimportant for in silico chemistry. We propose a new metric based on relative atomic electronegativities andbond parameters that evaluate both synthetic and molecular complexity (SMCM) starting from chemicalstructures. Against molecular weight, SMCM has the lowest fraction of adjusted variance (R2=0.535) on aseries 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 whenthe 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 ofsubstructure patterns can be directly incorporated into this scheme, SMCM is relatively straightforward andcan be easily tailored to rapidly evaluate virtual (combinatorial) libraries and high throughput screeninghits.
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