The field of structure-based drug design is a rapidly growing area in which many successes have occurred in recent years. The explosion of genomic, proteomic, and structural information has provided hundreds of new targets and opportunities for future drug lead discovery. This review summarizes the process of structure-based drug design and includes, primarily, the choice of a target, the evaluation of a structure of that target, the pivotal questions to consider in choosing a method for drug lead discovery, and evaluation of the drug leads. Key principles in the field of structure-based drug design will be illustrated through a case study that explores drug design for AmpC beta-lactamase.

This article applies an individual-level routine activities perspective to explaining rates of delinquency. The theoretical analysis also links the opportunity processes of that perspective to key themes of social disorganization theory. Multilevel analyses of 4,358 eighth-grade students from thirty-six schools in ten cities support the central hypothesis: Time spent in unstructured socializing with peers has both individual and contextual effects that explain a large share of the variation in rates of delinquency across groups of adolescents who attend different schools. In addition, parental monitoring has a very strong contextual effect on unstructured socializing, which supports the proposed integration of routine activity and social disorganization perspectives.Although it is individual adolescents who engage in delinquent behavior, delinquency is not strictly an individual-level phenomenon. Rates of delinquency also vary across groups, such as networks of friends (Esbensen and Huizinga, 1993;Haynie, 2001), youth attending the same The authors are especially grateful to Finn Esbensen for access to these data and for his longstanding support for their work. Thanks also to Rich Felson, Phil Schwadel, Jennifer Schwartz, Brian Goesling and Eric Silver for helpful comments on earlier drafts.

We report a computational, structure-based redesign of the phenylalanine adenylation domain of the nonribosomal peptide synthetase enzyme gramicidin S synthetase A (GrsA-PheA) for a set of noncognate substrates for which the wild-type enzyme has little or virtually no specificity. Experimental validation of a set of top-ranked computationally predicted enzyme mutants shows significant improvement in the specificity for the target substrates. We further present enhancements to the methodology for computational enzyme redesign that are experimentally shown to result in significant additional improvements in the target substrate specificity. The mutant with the highest activity for a noncognate substrate exhibits 1/6 of the wild-type enzyme/wild-type substrate activity, further confirming the feasibility of our computational approach. Our results suggest that structure-based protein design can identify active mutants different from those selected by evolution.

Realization of novel molecular function requires the ability to alter molecular complex formation. Enzymatic function can be altered by changing enzyme-substrate interactions via modification of an enzyme's active site. A redesigned enzyme may either perform a novel reaction on its native substrates or its native reaction on novel substrates. A number of computational approaches have been developed to address the combinatorial nature of the protein redesign problem. These approaches typically search for the global minimum energy conformation among an exponential number of protein conformations. We present a novel algorithm for protein redesign, which combines a statistical mechanics-derived ensemble-based approach to computing the binding constant with the speed and completeness of a branch-and-bound pruning algorithm. In addition, we developed an efficient deterministic approximation algorithm, capable of approximating our scoring function to arbitrary precision. In practice, the approximation algorithm decreases the execution time of the mutation search by a factor of ten. To test our method, we examined the Phe-specific adenylation domain of the nonribosomal peptide synthetase gramicidin synthetase A (GrsA-PheA). Ensemble scoring, using a rotameric approximation to the partition functions of the bound and unbound states for GrsA-PheA, is first used to predict binding of the wildtype protein and a previously described mutant (selective for leucine), and second, to switch the enzyme specificity toward leucine, using two novel active site sequences computationally predicted by searching through the space of possible active site mutations. The top scoring in silico mutants were created in the wetlab and dissociation/binding constants were determined by fluorescence quenching. These tested mutations exhibit the desired change in specificity from Phe to Leu. Our ensemble-based algorithm, which flexibly models both protein and ligand using rotamer-based partition functions, has application in enzyme redesign, the prediction of protein-ligand binding, and computer-aided drug design.

Few studies have examined the degree to which citizens access registry information or take preventative action in response. Survey responses from a representative sample of Nebraska residents were used to examine the degree to which people access registration information, the feelings this information invokes, and if preventative measures are subsequently taken by citizens. The results suggest that the majority of citizens had not accessed registry information, although the majority of people knew the registry existed, and few respondents took any preventative measures as a result of learning sex offender information. The implications of the results on notification laws are discussed.