Changes in serogroup and genotype prevalence among carried meningococci in the United Kingdom during vaccine implementation.

BACKGROUND: Herd immunity is important in the effectiveness of conjugate polysaccharide vaccines against encapsulated bacteria. A large multicenter study investigated the effect of meningococcal serogroup C conjugate vaccine introduction on the meningococcal population. METHODS: Carried meningococci in individuals aged 15-19 years attending education establishments were investigated before and for 2 years after vaccine introduction. Isolates were characterized by multilocus sequence typing, serogroup, and capsular region genotype and changes in phenotypes and genotypes assessed. RESULTS: A total of 8462 meningococci were isolated from 47 765 participants (17.7%). Serogroup prevalence was similar over the 3 years, except for decreases of 80% for serogroup C and 40% for serogroup 29E. Clonal complexes were associated with particular serogroups and their relative proportions fluctuated, with 12 statistically significant changes (6 up, 6 down). The reduction of ST-11 complex serogroup C meningococci was probably due to vaccine introduction. Reasons for a decrease in serogroup 29E ST-254 meningococci (from 1.8% to 0.7%) and an increase in serogroup B ST-213 complex meningococci (from 6.7% to 10.6%) were less clear. CONCLUSIONS: Natural fluctuations in carried meningococcal genotypes and phenotypes a can be affected by the use of conjugate vaccines, and not all of these changes are anticipatable in advance of vaccine introduction

Development of a novel descriptor targeted to high-throughput analysis in lead exploration and combinatorial library design

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Designing drugs on the internet? Free web tools and services supporting medicinal chemistry.

The drug discovery process is supported by a multitude of freely available tools on the Internet. This paper summarizes some of the databases and tools that are of particular interest to medicinal chemistry. These include numerous data collections that provide access to valuable chemical data resources, allowing complex queries of compound structures, associated physicochemical properties and biological activities to be performed and, in many cases, providing links to commercial chemical suppliers. Further applications are available for searching protein-ligand complexes and identifying important binding interactions that occur. This is particularly useful for understanding the molecular recognition of ligands in the lead optimization process. The Internet also provides access to databases detailing metabolic pathways and transformations which can provide insight into disease mechanism, identify new targets entities or the potential off-target effects of a drug candidate. Furthermore, sophisticated online cheminformatics tools are available for processing chemical structures, predicting properties, and generating 2D or 3D structure representations--often required prior to more advanced analyses. The Internet provides a wealth of valuable resources that, if fully exploited, can greatly benefit the drug discovery community. In this paper, we provide an overview of some of the more important of these and, in particular, the freely accessible resources that are currently available

Estimation of pKa for druglike compounds using semiempirical and information-based descriptors.

A pragmatic approach has been developed for the estimation of aqueous ionization constants (pKa) for druglike compounds. The method involves an algorithm that assigns ionization constants in a stepwise manner to the acidic and basic groups present in a compound. Predictions are made for each ionizable group using models derived from semiempirical quantum chemical properties and information-based descriptors. Semiempirical properties include the partial charge and electrophilic superdelocalizabilty of the atom(s) undergoing protonation or deprotonation. Importantly, the latter property has been extended to allow predictions to be made for multiprotic compounds, overcoming limitations of a previous approach described by Tehan et al. The information-based descriptions include molecular-tree structured fingerprints, based on the methodology outlined by Xing et al., with the addition of 2D substructure flags indicating the presence of other important structural features. These two classes of descriptor were found to complement one another particularly well, resulting in predictive models for a range of functional groups (including alcohols, amidines, amines, anilines, carboxylic acids, guanidines, imidazoles, imines, phenols, pyridines, and pyrimidines). A combined RMSE of 0.48 and 0.81 was obtained for the training set and an external test set compounds, respectively. The predictive models were based on compounds selected from the commercially available BioLoom database. The resultant speed and accuracy of the approach has also enabled the development of Web application on the Novartis intranet for pKa prediction

Quest for the rings. In silico exploration of ring universe to identify novel bioactive heteroaromatic scaffolds.

Bioactive molecules only contain a relatively limited number of unique ring types. To identify those ring properties and structural characteristics that are necessary for biological activity, a large virtual library of nearly 600 000 heteroaromatic scaffolds was created and characterized by calculated properties, including structural features, bioavailability descriptors, and quantum chemical parameters. A self-organizing neural network was used to cluster these scaffolds and to identify properties that best characterize bioactive ring systems. The analysis shows that bioactivity is very sparsely distributed within the scaffold property and structural space, forming only several relatively small, well-defined "bioactivity islands". Various possible applications of a large database of rings with calculated properties and bioactivity scores in the drug design and discovery process are discussed, including virtual screening, support for the design of combinatorial libraries, bioisosteric design, and scaffold hopping

<i>In silico</i> Design of Supramolecules from Their Precursors: Odd–Even Effects in Cage-Forming Reactions

We synthesize a series of imine cage molecules where increasing the chain length of the alkanediamine precursor results in an odd–even alternation between [2 + 3] and [4 + 6] cage macrocycles. A computational procedure is developed to predict the thermodynamically preferred product and the lowest energy conformer, hence rationalizing the observed alternation and the 3D cage structures, based on knowledge of the precursors alone

<i>In silico</i> Design of Supramolecules from Their Precursors: Odd–Even Effects in Cage-Forming Reactions

We synthesize a series of imine cage molecules where increasing the chain length of the alkanediamine precursor results in an odd–even alternation between [2 + 3] and [4 + 6] cage macrocycles. A computational procedure is developed to predict the thermodynamically preferred product and the lowest energy conformer, hence rationalizing the observed alternation and the 3D cage structures, based on knowledge of the precursors alone

A case-control study of the protective benefit of cervical screening against invasive cervical cancer in NSW women

Objective: To examine the effects of different Pap screening patterns in preventing invasive cervical cancer among women in New South Wales, Australia. Methods: A total of 877 women aged 20–69 years diagnosed with invasive cervical cancer during 2000–2003 were matched with 2,614 controls by month and year of birth. Screening behavior patterns in 4 years preceding the time of cancer diagnosis in the cases were classified into none (no Pap test in the 4 years), ‘irregular’ (1 of the 4 years with Pap test(s)), and ‘regular’ (2 or more of the 4 years with a Pap test), and compared with those in the matched non-cases over the same period. Conditional logistic regression modeling was used to estimate the relative risk, approximated by the odds ratio, of invasive cervical cancer for regular and irregular cervical screening compared with no screening in the previous 4 years, before and after controlling for potential confounders including the first recorded Pap test result in the preceding 6-year reference period. Results Compared with no screening, irregular Pap screening in the 4 years preceding the cancer diagnosis is estimated to reduce the risk of invasive cervical cancer by about 85% (RR = 0.15, 95% CI: 0.120–0.19); regular Pap screening reduces the risk by about 96% (RR = 0.04, 95% CI: 0.03–0.05). After adjusting for the index Pap test result, the relative risks for invasive cervical cancer were 0.19 (95% CI: 0.13–0.27) for irregular screening and 0.07 (95% CI: 0.04–0.10) for regular Pap screening. Conclusions Regular and irregular Pap tests among women aged 20–69 years were highly effective in preventing invasive cancer. At-risk women with no Pap test history should be encouraged to undergo a Pap test every 2 years, but any Pap screening over a 4-year period remains highly protective against future invasive cervical cancer.Baohui Yang, Stephen Morrell, Yeqin Zuo, David Roder, Elizabeth Tracey and Paul Jelf