Fast 3D shape screening of large chemical databases through alignment-recycling

<p>Abstract</p> <p>Background</p> <p>Large chemical databases require fast, efficient, and simple ways of looking for similar structures. Although such tasks are now fairly well resolved for graph-based similarity queries, they remain an issue for 3D approaches, particularly for those based on 3D shape overlays. Inspired by a recent technique developed to compare molecular shapes, we designed a hybrid methodology, alignment-recycling, that enables efficient retrieval and alignment of structures with similar 3D shapes.</p> <p>Results</p> <p>Using a dataset of more than one million PubChem compounds of limited size (< 28 heavy atoms) and flexibility (< 6 rotatable bonds), we obtained a set of a few thousand diverse structures covering entirely the 3D shape space of the conformers of the dataset. Transformation matrices gathered from the overlays between these diverse structures and the 3D conformer dataset allowed us to drastically (100-fold) reduce the CPU time required for shape overlay. The alignment-recycling heuristic produces results consistent with <it>de novo </it>alignment calculation, with better than 80% hit list overlap on average.</p> <p>Conclusion</p> <p>Overlay-based 3D methods are computationally demanding when searching large databases. Alignment-recycling reduces the CPU time to perform shape similarity searches by breaking the alignment problem into three steps: selection of diverse shapes to describe the database shape-space; overlay of the database conformers to the diverse shapes; and non-optimized overlay of query and database conformers using common reference shapes. The precomputation, required by the first two steps, is a significant cost of the method; however, once performed, querying is two orders of magnitude faster. Extensions and variations of this methodology, for example, to handle more flexible and larger small-molecules are discussed.</p

Computational approaches for modeling human intestinal absorption and permeability

Human intestinal absorption (HIA) is an important roadblock in the formulation of new drug substances. Computational models are needed for the rapid estimation of this property. The measurements are determined via in vivo experiments or in vitro permeability studies. We present several computational models that are able to predict the absorption of drugs by the human intestine and the permeability through human Caco-2 cells. The training and prediction sets were derived from literature sources and carefully examined to eliminate compounds that are actively transported. We compare our results to models derived by other methods and find that the statistical quality is similar. We believe that models derived from both sources of experimental data would provide greater consistency in predictions. The performance of several QSPR models that we investigated to predict outside the training set for either experimental property clearly indicates that caution should be exercised while applying any of the models for quantitative predictions. However, we are able to show that the qualitative predictions can be obtained with close to a 70% success rate

Abuse and other correlates of common mental disorders in youth: a cross-sectional study in Goa, India.

PURPOSE: There is a paucity of known correlates of common mental disorders (CMDs) among the youth age group in India. This analysis aims to determine risk factors associated with a probable diagnosis of CMD in a youth sample in India. METHODS: This is a secondary analysis of data collected via a door-to-door (community) survey of 3,662 youth (aged 16-24 years) in selected urban and rural areas in Goa. The urban and rural areas were selected based on their engagement with a Goan-based mental health charity organisation, Sangath. Point prevalence of CMD was estimated using the general health questionnaire-12 (GHQ-12). Multivariate logistic regression analyses determined factors associated with CMD and associations were stratified by gender. RESULTS: In total, 3,649 (1,796 urban; 1,853 rural) youth were assessed for probable diagnosis of CMD. There was an almost equal ratio of males (49 %) to females (51 %) in the sample. During the time of the survey, 91 % of the sample was residing with parents, with 83 % being between the ages of 22 and 24 years living with parents. A small proportion of the sample never attended school (1.1 %) with the rest either educated, employed or unemployed. The point prevalence of probable CMD in the sample was 7.87 %; 95 % CI 7.01-8.80 %. Those living in urban areas had a higher prevalence of CMD (9.12 %; 95 % CI 7.90-10.52 %) compared to those living in rural areas (6.60 %; 95 % CI 5.50-7.82 %). After adjusting for a range of potential confounders, independent risk factors for CMD were being older, i.e., between 22- and 24-years old, (OR 1.60; 95 % CI 1.10-2.24; p = 0.015), residing in urban areas (OR 1.51; 95 % CI 1.12-2.04; p = 0.007), physical abuse (beaten in the last 3 months) by parents, teachers or others (OR 3.10; 95 % CI 2.11-4.51; p < 0.001), sexual harassment (OR 2.01; 95 % CI 1.30-3.20; p = 0.003) and sexual abuse (OR 2.54; 95 % CI 1.94-3.33; p < 0.001). Being able to talk about personal problems (OR 0.52; 95 % CI 0.34-0.80; p = 0.003) was a protective factor. After stratifying by gender, sexual harassment, physical and sexual abuse were associated with a likely CMD diagnosis in females and males. CONCLUSIONS: Sexual and recent physical abuses were independent risk factors for CMD in both genders. In addition, being older and being able to discuss problems were associated with CMD diagnosis in females but not in males