Search results for "Screen"
showing 10 items of 1374 documents
Convolutional architectures for virtual screening
2020
Abstract Background A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% …
Improving structural similarity based virtual screening using background knowledge
2013
Background Virtual screening in the form of similarity rankings is often applied in the early drug discovery process to rank and prioritize compounds from a database. This similarity ranking can be achieved with structural similarity measures. However, their general nature can lead to insufficient performance in some application cases. In this paper, we provide a link between ranking-based virtual screening and fragment-based data mining methods. The inclusion of binding-relevant background knowledge into a structural similarity measure improves the quality of the similarity rankings. This background knowledge in the form of binding relevant substructures can either be derived by hand selec…
Filtered circular fingerprints improve either prediction or runtime performance while retaining interpretability.
2016
Background Even though circular fingerprints have been first introduced more than 50 years ago, they are still widely used for building highly predictive, state-of-the-art (Q)SAR models. Historically, these structural fragments were designed to search large molecular databases. Hence, to derive a compact representation, circular fingerprint fragments are often folded to comparatively short bit-strings. However, folding fingerprints introduces bit collisions, and therefore adds noise to the encoded structural information and removes its interpretability. Both representations, folded as well as unprocessed fingerprints, are often used for (Q)SAR modeling. Results We show that it can be prefer…
Application of molecular topology to the prediction of inhibition of Trypanosoma cruzi Hexokinase by bisphosphonates
2008
Se ha desarrollado un modelo topológico-matemático para la búsqueda de nuevos derivados bisfosfonatos activos frente a la hexokinasa de Trypanosoma cruzi. Utilizando el análisis lineal discriminante se ha seleccionado una función con cuatro variables capaz de predecir adecuadamente la CI50 para cada compuesto de las series de entrenamiento y test. El modelo propuesto se ha aplicado a una librería molecular y se han propuesto nuevas estructuras potencialmente activas frente a T. cruzi.
Applying pattern recognition methods plus quantum and physico-chemical molecular descriptors to analyze the anabolic activity of structurally diverse…
2008
The great cost associated with the development of new anabolic-androgenic steroid (AASs) makes necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, quantum, and physicochemical molecular descriptors, plus linear discriminant analysis (LDA) were used to analyze the anabolic/androgenic activity of structurally diverse steroids and to discover novel AASs, as well as also to give a structural interpretation of their anabolic-androgenic ratio (AAR). The obtained models are able to correctly classify 91.67% (86.27%) of the AASs in the training (test) sets, respectively. The results of predictions on the 10% full-out cross-validation test al…
In Silico Prediction of Caco-2 Cell Permeability by a Classification QSAR Approach
2011
In the present study, 21 validated QSAR models that discriminate compounds with high Caco-2 permeability (Papp ≥8×10(-6) cm/s) from those with moderate-poor permeability (Papp <8×10(-6) cm/s) were developed on a novel large dataset of 674 compounds. 20 DRAGON descriptor families were used. The global accuracies of obtained models were ranking between 78-82 %. A general model combining all types of molecular descriptors was developed and it classified correctly 81.56 % and 83.94 % for training and test sets, respectively. An external set of 10 compounds was predicted and 80 % was correctly assessed by in vitro Caco-2 assays. The potential use of the final model was evaluated by a virtual s…
Computational discovery of novel trypanosomicidal drug-like chemicals by using bond-based non-stochastic and stochastic quadratic maps and linear dis…
2009
Herein we present results of a quantitative structure-activity relationship (QSAR) studies to classify and design, in a rational way, new antitrypanosomal compounds by using non-stochastic and stochastic bond-based quadratic indices. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop QSAR models based on linear discriminant analysis (LDA). Non-stochastic model correctly classifies more than 93% and 95% of chemicals in both training and external prediction groups, respectively. On the other hand, the stochastic model shows an accuracy of about the 87% for both series. As an experiment of virtual lead generation, the …
Modeling anti-allergic natural compounds by molecular topology.
2013
Molecular topology has been applied to the search of QSAR models able to identify the anti-allergic activity of a wide group of heterogeneous compounds. Through the linear discriminant analysis and artificial neural networks, correct classification percentages above 85% for both the training set and the test set have been obtained. After carrying out a virtual screening with a natural product library, about thirty compounds with theoretical anti-allergic activity have been selected. Among them, hesperidin, naringin, salinomycin, sorbitol, curcumol, myricitrin, diosmin and kinetin stand out. Some of these compounds have already been referenced as having anti-allergic activity.
In silicoAntibacterial Activity Modeling Based on the TOMOCOMD-CARDD Approach
2015
In the recent times, the race to cope with the increasing multidrug resistance of pathogenic bacteria has lost much of its momentum and health professionals are grasping for solutions to deal with the unprecedented resistance levels. As a result, there is an urgent need for a concerted effort towards the development of new antimicrobial drugs to stay ahead in the fight against the ever adapting bacteria. In the present report, antibacterial classification functions (models) based on the topological molecular computational design-computer aided >rational> drug design (TOMOCOMD-CARDD) atom-based non-stochastic and stochastic bilinear indices are presented. These models were built using the li…
The waiting time for prostate cancer treatment in Italy: analysis from the PROS-IT CNR Study.
2022
Background Prostate cancer (PCa) is the second most common neoplasm in male patients. To date, there's no certain indication about the maximum waiting time (WT) acceptable for treatment beginning and the impact on oncological and functional outcomes has not been well established. Methods Data from the National Research Council PCa monitoring multicenter project in Italy (Pros-IT CNR) were prospectively collected and analyzed. WT was defined as the time from the bioptical diagnosis of PCa to the first treatment received. Patients were divided in two groups, using a time frame of 90 days. Quality of life was measured through the Italian version of the University of California Los Angeles-Pros…