Evaluation of machine-learning methods for ligand-based virtual screening

Machine-learning methods can be used for virtual screening by analysing the structural characteristics of molecules of known (in)activity, and we here discuss the use of kernel discrimination and naive Bayesian classifier (NBC) methods for this purpose. We report a kernel method that allows the processing of molecules represented by binary, integer and real-valued descriptors, and show that it is little different in screening performance from a previously described kernel that had been developed specifically for the analysis of binary fingerprint representations of molecular structure. We then evaluate the performance of an NBC when the training-set contains only a very few active molecules. In such cases, a simpler approach based on group fusion would appear to provide superior screening performance, especially when structurally heterogeneous datasets are to be processed

CACHE (Critical Assessment of Computational Hit-finding Experiments): A public–private partnership benchmarking initiative to enable the development of computational methods for hit-finding

One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small-molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small-molecule binders for new and biologically relevant protein targets representing different prediction scenarios. Predicted compounds will be tested rigorously in an experimental hub, and all predicted binders as well as all experimental screening data, including the chemical structures of experimentally tested compounds, will be made publicly available and not subject to any intellectual property restrictions. The ability of a range of computational approaches to find novel binders will be evaluated, compared and openly published. CACHE will launch three new benchmarking exercises every year. The outcomes will be better prediction methods, new small-molecule binders for target proteins of importance for fundamental biology or drug discovery and a major technological step towards achieving the goal of Target 2035, a global initiative to identify pharmacological probes for all human proteins. [Figure not available: see fulltext.

Breast tumor characteristics of BRCA1 and BRCA2 gene mutation carriers on MRI

The appearance of malignant lesions in BRCA1 and BRCA2 mutation carriers (BRCA-MCs) on mammography and magnetic resonance imaging (MRI) was evaluated. Thus, 29 BRCA-MCs with breast cancer were retrospectively evaluated and the results compared with an age, tumor size and tumor type matched control group of 29 sporadic breast cancer cases. Detection rates on both modalities were evaluated. Tumors were analyzed on morphology, density (mammography), enhancement pattern and kinetics (MRI). Overall detection was significantly better with MRI than with mammography (55/58 vs 44/57, P = 0.021). On mammography, lesions in the BRCA-MC group were significantly more described as rounded (12//19 vs 3/13, P = 0.036) and with sharp margins (9/19 vs 1/13, P = 0.024). On MRI lesions in the BRCA-MC group were significantly more described as rounded (16/27 vs 7/28, P = 0.010), with sharp margins (20/27 vs 7/28, P < 0.001) and with rim enhancement (7/27 vs 1/28, P = 0.025). No significant difference was found for enhancement kinetics (P = 0.667). Malignant lesions in BRCA-MC frequently have morphological characteristics commonly seen in benign lesions, like a rounded shape or sharp margins. This applies for both mammography and MRI. However the possibility of MRI to evaluate the enhancement pattern and kinetics enables the detection of characteristics suggestive for a malignancy

Mechanisms of Action of Currently Prescribed and Newly Developed Antiepileptic Drugs

Clinically available antiepileptic drugs (AEDs) decrease membrane excitability by interacting with neurotransmitter receptors or ion channels. AEDs developed before 1980 appear to act on sodium (Na) channels, -y-aminobutyric acid A (GABA A ) receptors, or calcium (Ca) channels. Benzodiazepines and barbiturates enhance GABA A -receptor-mediated inhibition. Phenytoin, car-bamazepine and, possibly, valproate (VPA) decrease high-frequency repetitive firing of action potentials by enhancing Na channel inactivation. Ethosuximide and VPA reduce a low threshold (T-type) Ca-channel current. The mechanisms of action of recently developed AEDs are less clear. Lamotrigine may decrease sustained high-frequency repetitive firing of voltage-dependent Na action potentials, and gabapentin (GBP) appears to bind to a specific binding site in the CNS with a restricted regional distribution. However, the identity of the binding site and the mechanism of action of GBP remain uncertain. The antiepileptic effect of felbamate may involve interaction at the strychnine-insensitive glycine site of the Af-methyl-D-aspartate receptor, but the mechanism of action is not yet proven.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65554/1/j.1528-1157.1994.tb05955.x.pd

Insights into Long-Lasting Protection Induced by RTS,S/AS02A Malaria Vaccine: Further Results from a Phase IIb Trial in Mozambican Children

Background: The pre-erythrocytic malaria vaccine RTS,S/AS02A has shown to confer protection against clinical malaria for at least 21 months in a trial in Mozambican children. Efficacy varied between different endpoints, such as parasitaemia or clinical malaria; however the underlying mechanisms that determine efficacy and its duration remain unknown. We performed a new, exploratory analysis to explore differences in the duration of protection among participants to better understand the protection afforded by RTS,S. Methodology/Principal Findings: The study was a Phase IIb double-blind, randomized controlled trial in 2022 children aged 1 to 4 years. The trial was designed with two cohorts to estimate vaccine efficacy against two different endpoints: clinical malaria (cohort 1) and infection (cohort 2). Participants were randomly allocated to receive three doses of RTS,S/AS02A or control vaccines. We did a retrospective, unplanned sub-analysis of cohort 2 data using information collected for safety through the health facility-based passive case detection system. Vaccine efficacy against clinical malaria was estimated over the first six-month surveillance period (double-blind phase) and over the following 12 months (single-blind phase), and analysis was per-protocol. Adjusted vaccine efficacy against first clinical malaria episodes in cohort 2 was of 35.4% (95% CI 4.5-56.3; p = 0.029) over the double-blind phase and of 9.0% (230.6-36.6; p = 0.609) during the single-blind phase. Conclusions/Significance: Contrary to observations in cohort 1, where efficacy against clinical malaria did not wane over time, in cohort 2 the efficacy decreases with time. We hypothesize that this reduced duration of protection is a result of the early diagnosis and treatment of infections in cohort 2 participants, preventing sufficient exposure to asexual-stage antigens. On the other hand, the long-term protection against clinical disease observed in cohort 1 may be a consequence of a prolonged exposure to low-dose blood-stage asexual parasitaemia

Virtual Screening of Bioassay Data

Background: There are three main problems associated with the virtual screening of bioassay data. The first is access to freely-available curated data, the second is the number of false positives that occur in the physical primary screening process, and finally the data is highly-imbalanced with a low ratio of Active compounds to Inactive compounds. This paper first discusses these three problems and then a selection of Weka cost-sensitive classifiers (Naive Bayes, SVM, C4.5 and Random Forest) are applied to a variety of bioassay datasets. Results: Pharmaceutical bioassay data is not readily available to the academic community. The data held at PubChem is not curated and there is a lack of detailed cross-referencing between Primary and Confirmatory screening assays. With regard to the number of false positives that occur in the primary screening process, the analysis carried out has been shallow due to the lack of crossreferencing mentioned above. In six cases found, the average percentage of false positives from the High-Throughput Primary screen is quite high at 64%. For the cost-sensitive classification, Weka's implementations of the Support Vector Machine and C4.5 decision tree learner have performed relatively well. It was also found, that the setting of the Weka cost matrix is dependent on the base classifier used and not solely on the ratio of class imbalance. Conclusions: Understandably, pharmaceutical data is hard to obtain. However, it would be beneficial to both the pharmaceutical industry and to academics for curated primary screening and corresponding confirmatory data to be provided. Two benefits could be gained by employing virtual screening techniques to bioassay data. First, by reducing the search space of compounds to be screened and secondly, by analysing the false positives that occur in the primary screening process, the technology may be improved. The number of false positives arising from primary screening leads to the issue of whether this type of data should be used for virtual screening. Care when using Weka's cost-sensitive classifiers is needed - across the board misclassification costs based on class ratios should not be used when comparing differing classifiers for the same dataset

Breast cancer screening in women at increased risk according to different family histories: an update of the Modena Study Group experience

BACKGROUND: Breast cancer (BC) detection in women with a genetic susceptibility or strong family history is considered mandatory compared with BC screening in the general population. However, screening modalities depend on the level of risk. Here we present an update of our screening programs based on risk classification. METHODS: We defined different risk categories and surveillance strategies to identify early BC in 1325 healthy women recruited by the Modena Study Group for familial breast and ovarian cancer. Four BC risk categories included BRCA1/2 carriers, increased, intermediate, and slightly increased risk. Women who developed BC from January 1, 1994, through December 31, 2005 (N = 44) were compared with the number of expected cases matched for age and period. BRCA1/2 carriers were identified by mutational analysis. Other risk groups were defined by different levels of family history for breast or ovarian cancer (OC). The standardized incidence ratio (SIR) was used to evaluate the observed and expected ratio among groups. All statistical tests were two-sided. RESULTS: After a median follow-up of 55 months, there was a statistically significant difference between observed and expected incidence [SIR = 4.9; 95% confidence interval (CI) = 1.6 to 7.6; p < 0.001]. The incidence observed among BRCA carriers (SIR = 20.3; 95% CI = 3.1 to 83.9; P < 0.001), women at increased (SIR = 4.5; 95% CI = 1.5 to 8.3; P < 0.001) or intermediate risk (SIR = 7.0, 95% CI = 2.0 to 17.1; P = 0.0018) was higher than expected, while the difference between observed and expected among women at slightly increased risk was not statistically significant (SIR = 2.4, 95% CI = 0.9 to 8.3; P = .74). CONCLUSION: The rate of cancers detected in women at high risk according to BRCA status or strong family history, as defined according to our operational criteria, was significantly higher than expected in an age-matched general population. However, we failed to identify a greater incidence of BC in the slightly increased risk group. These results support the effectiveness of the proposed program to identify and monitor individuals at high risk, whereas prospective trials are needed for women belonging to families with sporadic BC or OC

Genetics of decayed sexual traits in a parasitoid wasp with endosymbiont-induced asexuality.

Trait decay may occur when selective pressures shift, owing to changes in environment or life style, rendering formerly adaptive traits non-functional or even maladaptive. It remains largely unknown if such decay would stem from multiple mutations with small effects or rather involve few loci with major phenotypic effects. Here, we investigate the decay of female sexual traits, and the genetic causes thereof, in a transition from haplodiploid sexual reproduction to endosymbiont-induced asexual reproduction in the parasitoid wasp Asobara japonica. We take advantage of the fact that asexual females cured of their endosymbionts produce sons instead of daughters, and that these sons can be crossed with sexual females. By combining behavioral experiments with crosses designed to introgress alleles from the asexual into the sexual genome, we found that sexual attractiveness, mating, egg fertilization and plastic adjustment of offspring sex ratio (in response to variation in local mate competition) are decayed in asexual A. japonica females. Furthermore, introgression experiments revealed that the propensity for cured asexual females to produce only sons (because of decayed sexual attractiveness, mating behavior and/or egg fertilization) is likely caused by recessive genetic effects at a single locus. Recessive effects were also found to cause decay of plastic sex-ratio adjustment under variable levels of local mate competition. Our results suggest that few recessive mutations drive decay of female sexual traits, at least in asexual species deriving from haplodiploid sexual ancestors