Homology modeling and metabolism prediction of human carboxylesterase-2 using docking analyses by GriDock: a parallelized tool based on AutoDock 4.0.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

The Brief Psychiatric Rating Scale (version 4.0) factorial structure and its sensitivity in the treatment of outpatients with unipolar depression.

The 24-item Brief Psychiatric Rating Scale (BPRS, version 4.0) enables the rater to measure psychopathology severity. Still, little is known about the BPRS's reliability and validity outside of the psychosis spectrum. The aim of this study was to examine the factorial structure and sensitivity to change of the BPRS in patients with unipolar depression. Two hundred and forty outpatients with unipolar depression were administered the 24-item BPRS. Assessments were conducted at intake and at post-treatment in a Crisis Intervention Centre. An exploratory factor analysis of the 24-item BPRS produced a six-factor solution labelled "Mood disturbance", "Reality distortion", "Activation", "Apathy", "Disorganization", and "Somatization". The reduction of the total BPRS score and dimensional scores, except for "Activation", indicates that the 24-item BPRS is sensitive to change as shown in patients that appeared to have benefited from crisis treatment. The findings suggest that the 24-item BPRS could be a useful instrument to measure symptom severity and change in symptom status in outpatients presenting with unipolar depression.