The structure and rotational barrier for substituted diacylhydrazines are of significant interest given the role this functionality plays in peptidomimetics and ecdysone agonists, the latter of which have application as extremely selective insecticides. Ab initio calculations show that the lowest energy conformations are typically nonplanar with essentially perpendicular nitrogen lone pairs. Molecular mechanics calculations using the AMBER force field in MacroModel yield minima and rotational barriers that are both quantitatively and qualitatively inconsistent with the ab initio results. In this work the AMBER N-N rotational barriers for all configurations of the parent, methyl and di-methyl substituted diformylhydrazines have been fitted to MP2/6-31 + G relative energies. The resulting AMBER torsional parameters have been validated by calculating the rotational barriers for N-t-butyl substituted diformylhydrazine, dibenzoylhydrazine and an azadipeptide. In each case the new AMBER rotational barriers compare favorably with the corresponding MP2 calculated rotational barriers.

Ecdysone↗

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Diversity and coverage of structural sublibraries selected using the SAGE and SCA algorithms.

It is often impractical to synthesize and test all compounds in a large exhaustive chemical library. Herein, we discuss rational approaches to selecting representative subsets of virtual libraries that help direct experimental synthetic efforts for diverse library design. We compare the performance of two stochastic sampling algorithms, Simulating Annealing Guided Evaluation (SAGE; Zheng, W.; Cho, S. J.; Waller, C. L.; Tropsha, A. J. Chem. Inf. Comput. Sci. 1999, 39, 738-746.) and Stochastic Cluster Analysis (SCA; Reynolds, C. H.; Druker, R.; Pfahler, L. B. Lead Discovery Using Stochastic Cluster Analysis (SCA): A New Method for Clustering Structurally Similar Compounds J. Chem. Inf. Comput. Sci. 1998, 38, 305-312.) for their ability to select both diverse and representative subsets of the entire chemical library space. The SAGE and SCA algorithms were compared using u- and s-optimal metrics as an independent assessment of diversity and coverage. This comparison showed that both algorithms were capable of generating sublibraries in descriptor space that are diverse and give reasonable coverage (i.e. are representative) of the original full library. Tests were carried out using simulated two-dimensional data sets and a 27 000 compound proprietary structural library as represented by computed Molconn-Z descriptors. One of the key observations from this work is that the algorithmically simple SCA method is capable of selecting subsets that are comparable to the more computationally intensive SAGE method.

Journal Article↗