Use of structure-activity landscape index curves and curve integrals to evaluate the performance of multiple machine learning prediction models

<p>Abstract</p> <p>Background</p> <p>Standard approaches to address the performance of predictive models that used common statistical measurements for the entire data set provide an overview of the average performance of the models across the entire predictive space, but give little insight into applicability of the model across the prediction space. Guha and Van Drie recently proposed the use of structure-activity landscape index (SALI) curves via the SALI curve integral (SCI) as a means to map the predictive power of computational models within the predictive space. This approach evaluates model performance by assessing the accuracy of pairwise predictions, comparing compound pairs in a manner similar to that done by medicinal chemists.</p> <p>Results</p> <p>The SALI approach was used to evaluate the performance of continuous prediction models for MDR1-MDCK <it>in vitro </it>efflux potential. Efflux models were built with ADMET Predictor neural net, support vector machine, kernel partial least squares, and multiple linear regression engines, as well as SIMCA-P+ partial least squares, and random forest from Pipeline Pilot as implemented by AstraZeneca, using molecular descriptors from <it>SimulationsPlus </it>and AstraZeneca.</p> <p>Conclusion</p> <p>The results indicate that the choice of training sets used to build the prediction models is of great importance in the resulting model quality and that the SCI values calculated for these models were very similar to their Kendall τ values, leading to our suggestion of an approach to use this SALI/SCI paradigm to evaluate predictive model performance that will allow more informed decisions regarding model utility. The use of SALI graphs and curves provides an additional level of quality assessment for predictive models.</p

Idebenone and Resveratrol Extend Lifespan and Improve Motor Function of HtrA2 Knockout Mice

Heterozygous loss-of-function mutation of the human gene for the mitochondrial protease HtrA2 has been associated with increased risk to develop mitochondrial dysfunction, a process known to contribute to neurodegenerative disorders such as Huntington's disease (HD) and Parkinson's disease (PD). Knockout of HtrA2 in mice also leads to mitochondrial dysfunction and to phenotypes that resemble those found in neurodegenerative disorders and, ultimately, lead to death of animals around postnatal day 30. Here, we show that Idebenone, a synthetic antioxidant of the coenzyme Q family, and Resveratrol, a bioactive compound extracted from grapes, are both able to ameliorate this phenotype. Feeding HtrA2 knockout mice with either compound extends lifespan and delays worsening of the motor phenotype. Experiments conducted in cell culture and on brain tissue of mice revealed that each compound has a different mechanism of action. While Idebenone acts by downregulating the integrated stress response, Resveratrol acts by attenuating apoptosis at the level of Bax. These activities can account for the delay in neuronal degeneration in the striata of these mice and illustrate the potential of these compounds as effective therapeutic approaches against neurodegenerative disorders such as HD or PD

Resveratrol Acts Not through Anti-Aggregative Pathways but Mainly via Its Scavenging Properties against Aβ and Aβ-Metal Complexes Toxicity

It has been recently suggested that resveratrol can be effective in slowing down Alzheimer's disease (AD) development. As reported in many biochemical studies, resveratrol seems to exert its neuro-protective role through inhibition of β-amyloid aggregation (Aβ), by scavenging oxidants and exerting anti-inflammatory activities. In this paper, we demonstrate that resveratrol is cytoprotective in human neuroblastoma cells exposed to Aβ and or to Aβ-metal complex. Our findings suggest that resveratrol acts not through anti-aggregative pathways but mainly via its scavenging properties

Significant Effects of Antiretroviral Therapy on Global Gene Expression in Brain Tissues of Patients with HIV-1-Associated Neurocognitive Disorders

Antiretroviral therapy (ART) has reduced morbidity and mortality in HIV-1 infection; however HIV-1-associated neurocognitive disorders (HAND) persist despite treatment. The reasons for the limited efficacy of ART in the brain are unknown. Here we used functional genomics to determine ART effectiveness in the brain and to identify molecular signatures of HAND under ART. We performed genome-wide microarray analysis using Affymetrix U133 Plus 2.0 Arrays, real-time PCR, and immunohistochemistry in brain tissues from seven treated and eight untreated HAND patients and six uninfected controls. We also determined brain virus burdens by real-time PCR. Treated and untreated HAND brains had distinct gene expression profiles with ART transcriptomes clustering with HIV-1-negative controls. The molecular disease profile of untreated HAND showed dysregulated expression of 1470 genes at p<0.05, with activation of antiviral and immune responses and suppression of synaptic transmission and neurogenesis. The overall brain transcriptome changes in these patients were independent of histological manifestation of HIV-1 encephalitis and brain virus burdens. Depending on treatment compliance, brain transcriptomes from patients on ART had 83% to 93% fewer dysregulated genes and significantly lower dysregulation of biological pathways compared to untreated patients, with particular improvement indicated for nervous system functions. However a core of about 100 genes remained similarly dysregulated in both treated and untreated patient brain tissues. These genes participate in adaptive immune responses, and in interferon, cell cycle, and myelin pathways. Fluctuations of cellular gene expression in the brain correlated in Pearson's formula analysis with plasma but not brain virus burden. Our results define for the first time an aberrant genome-wide brain transcriptome of untreated HAND and they suggest that antiretroviral treatment can be broadly effective in reducing pathophysiological changes in the brain associated with HAND. Aberrantly expressed transcripts common to untreated and treated HAND may contribute to neurocognitive changes defying ART