Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data

Background: This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. Results: The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. Conclusions: We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.

Automatic aspect discrimination in data clustering

The attributes describing a data set may often be arranged in meaningful subsets, each of which corresponds to a different aspect of the data. An unsupervised algorithm (SCAD) that simultaneously performs fuzzy clustering and aspects weighting was proposed in the literature. However, SCAD may fail and halt given certain conditions. To fix this problem, its steps are modified and then reordered to reduce the number of parameters required to be set by the user. In this paper we prove that each step of the resulting algorithm, named ASCAD, globally minimizes its cost-function with respect to the argument being optimized. The asymptotic analysis of ASCAD leads to a time complexity which is the same as that of fuzzy c-means. A hard version of the algorithm and a novel validity criterion that considers aspect weights in order to estimate the number of clusters are also described. The proposed method is assessed over several artificial and real data sets.

Postural adjustment after an unexpected perturbation in children with haemophilia

. Children with haemophilia often bleed inside joints and muscles, which may impair postural adjustments. These postural adjustments are necessary to control postural balance during daily activities. The inability to quickly recover postural balance could elevate the risk of bleeding. To determine whether children with haemophilia have impaired postural adjustment after an unexpected perturbation compared with healthy children. Twenty children with haemophilia comprised the haemophilic group (HG), and 20 healthy, age-paired children comprised the control group (CG). Subjects stood on a force plate, and 4% of the subjects body weight was applied via a pulley system to a belt around the subjects trunks. The centre of pressure (COP) displacement was measured after the weight was unexpectedly released to produce a controlled postural perturbation followed by postural adjustment to recover balance. The subjects postural adjustments in eight subsequent intervals of 1 s (t1t8), beginning with the moment of weight removal, were compared among intervals and between groups. The applied perturbation magnitudes were the same for both groups, and no difference was observed between the groups in t1. However, the COP displacement in t2 in the HG was significantly higher than in the CG. No differences were observed between the groups in the other intervals. Within-group analysis showed that the COP was higher in t2 than in t4 (P = 0.016), t5 (P = 0.001) and t8 (P = 0.050) in the HG. No differences were observed among intervals in the CG. Children with haemophilia demonstrated differences in postural adjustment while undergoing unexpected balance perturbations when compared with healthily children.