No abstract

While small molecule internal strain is crucial to molecular docking, using it in evaluating ligand scores has remained elusive. Here, we investigate a technique that calculates strain using relative torsional populations in the Cambridge Structural Database, enabling fast precalculation of these energies. In retrospective studies of large docking screens of the dopamine D4 receptor and of AmpC β-lactamase, where close to 600 docking hits were tested experimentally, including such strain energies improved hit rates by preferentially reducing the ranks of strained high-scoring decoy molecules. In a 40-target subset of the DUD-E benchmark, we found two thresholds that usefully distinguished between ligands and decoys: one based on the total strain energy of the small molecules and another based on the maximum strain allowed for any given torsion within them. Using these criteria, about 75% of the benchmark targets had improved enrichment after strain filtering. Relying on precalculated population distributions, this approach is rapid, taking less than 0.04 s to evaluate a conformation on a standard core, making it pragmatic for precalculating strain in even ultralarge libraries. Since it is scoring function agnostic, it may be useful to multiple docking approaches; it is openly available at http://tldr.docking.org.

Social networks are typically constructed based on explicit and well-defined relationships among individuals. In this paper, we describe another class of social networks, known as implicit affinity networks, where links are implicit in the patterns of natural affinities among individuals. An effective mathematical formulation of social capital based on implicit and explicit connections is given. Results with two Web communities, one focused on people's interests and one focused on people's blogs, exhibit rich dynamics and show interesting patterns of community evolution.

Purpose It has been over 20 years since the landmark publication of Mizruchi (1996) and his examination of “what do interlocks do?”. Since then, the nature of interlocks and subsequent research on the subject has evolved. This paper aims to revisit the literature on interlocking directorates through a quantitative bibliometric analysis. Design/methodology/approach This study undertakes a bibliometric analysis of literature citing the Mizruchi (1996) to examine the state of research following up on “what do interlocks do”. This study examines 718 publications using keyword and co-word analysis, along with a thematic analysis to revisit the research that has followed Mizruchi’s topic of what do interlocks do. Findings This study finds that the topics of the corporate elite, capitalist economy and corporate governance have remained prominent themes in the field. Research areas that are emerging in the field of interlocking directorates include gender diversity, globalisation and advancing theoretical frameworks. Originality/value This paper provides a quantitative bibliometric analysis to revisit the extant literature on “what do interlocks do”, examining a high number of articles to identify areas which could be developed to advance research in the field.

While small molecule internal strain is crucial to molecular docking, using it in evaluating ligand scores has remained elusive. Here, we investigate a technique that calculates strain using relative torsional populations in the Cambridge Structural Database, enabling fast pre-calculation of these energies. In retrospective studies of large docking screens of the dopamine D4 receptor and of AmpC β-lactamase, where close to 600 docking hits were tested experimentally, including such strain energies improved hit rates by preferentially reducing high-scoring decoy molecules that were strained. In a 40 target subset of the DUD-E benchmark, we found two thresholds that usefully distinguished between ligands and decoys: one based on the total strain energy of the small molecules, and one based on the maximum strain allowed for any given torsion within them. Using these criteria, about 75% of the benchmark targets had improved enrichment after strain filtering. Relying on pre-calculated population distributions, this approach is rapid, taking less than 0.04 second to evaluate a conformation on a standard core, making it pragmatic for pre-calculating strain in even ultra-large libraries. Since it is scoring function agnostic, it may be useful to multiple docking approaches; it is openly available at http://tldr.docking.org