Search results for "Computer Science Application"
showing 10 items of 3998 documents
Singlet-Triplet States Interaction Regions in DNA/RNA Nucleobase Hypersurfaces.
2010
The present study provides new insight into the intrinsic mechanisms for the population of the triplet manifold in DNA nucleobases by determining, at the multiconfigurational CASSCF/CASPT2 level, the singlet-triplet states crossing regions and the main decay paths for their lowest singlet and triplet states after near-UV irradiation. The studied singlet-triplet interacting regions are accessible along the minimum energy path of the initially populated singlet bright (1)ππ* state. In particular, all five natural DNA/RNA nucleobases have, at the end of the main minimum energy path and near a conical intersection of the ground and (1)ππ* states, a low-energy, easily accessible, singlet-triplet…
Quantitative Structure–Activity Relationship of the 4,5α-Dihydrotestosterone Steroid Family
2006
Predictive Quantitative Structure - Activity Relationship (QSAR) models of Anabolic/ Androgenic (A/A) activities for the 4,5a-dihydrotestosterone steroid family were obtained by means of multilinear regression using quantum and physicochemical Molecular Descriptors (MDs) as well as a genetic algorithm for the selection of the best subset of MDs. MDs included in our QSAR models allow the structural interpretation of the biological process, evidencing the main role of the shape of molecules, hydrophobicity, and electronic properties. Attempts were made to include lipophilicity (octanol-water partition coefficient) as well as electronic (lowest unoccupied molecular orbital properties and dipol…
Quantitative Structure-Antioxidant Activity Models of Isoflavonoids: A Theoretical Study
2015
Seventeen isoflavonoids from isoflavone, isoflavanone and isoflavan classes are selected from Dalbergia parviflora. The ChEMBL database is representative from these molecules, most of which result highly drug-like. Binary rules appear risky for the selection of compounds with high antioxidant capacity in complementary xanthine/xanthine oxidase, ORAC, and DPPH model assays. Isoflavonoid structure-activity analysis shows the most important properties (log P, log D, pKa, QED, PSA, NH + OH ≈ HBD, N + O ≈ HBA). Some descriptors (PSA, HBD) are detected as more important than others (size measure Mw, HBA). Linear and nonlinear models of antioxidant potency are obtained. Weak nonlinear relationship…
Discrimination and Molecular Design of New Theoretical Hypolipaemic Agents Using the Molecular Connectivity Functions
2000
The molecular topology model and discriminant analysis have been applied to the prediction and QSAR interpretation of some pharmacological properties of hypolipaemic drugs using multivariable regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies done on the selected prediction models confirmed the goodness of the fits. The method used for hypolipaemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and design of new hypolip…
Multi-target QSPR assemble of a Complex Network for the distribution of chemicals to biphasic systems and biological tissues
2008
Abstract Chemometrics, that based prediction on the probability of chemical distribution to different systems, is highly important for physicochemical, environmental, and life sciences. However, the amount of information is huge and difficult to analyze. A multi-system partition Complex Network (MSP-CN) may be very useful in this sense. We define MSP-CNs as large graphs composed by nodes (chemicals) interconnected by arcs if a pair of chemicals have similar partition in a given system. Experimental quantification of partition in many systems is expensive, so we can use a Quantitative Structure–Partition Relationship (QSPR) model. Unfortunately, with classic QSPR we need to use one model for…
Similarity boosted quantitative structure-activity relationship--a systematic study of enhancing structural descriptors by molecular similarity.
2013
The concept of molecular similarity is one of the most central in the fields of predictive toxicology and quantitative structure-activity relationship (QSAR) research. Many toxicological responses result from a multimechanistic process and, consequently, structural diversity among the active compounds is likely. Combining this knowledge, we introduce similarity boosted QSAR modeling, where we calculate molecular descriptors using similarities with respect to representative reference compounds to aid a statistical learning algorithm in distinguishing between different structural classes. We present three approaches for the selection of reference compounds, one by literature search and two by…
Combined use of PCA and QSAR/QSPR to predict the drugs mechanism of action. An application to the NCI ACAM Database
2009
During the years the National Cancer Institute (NCI) accumulated an enormous amount of information through the application of a complex protocol of drugs screening involving several tumor cell lines, grouped into panels according to the disease class. The Anti-cancer Agent Mechanism (ACAM) database is a set of 122 compounds with anti-cancer activity and a reasonably well known mechanism of action, for which are available drug screening data that measure their ability to inhibit growth of a panel of 60 human tumor lines, explicitly designed as a training set for neural network and multivariate analysis. The aim of this work is to adapt a methodology (previously developed for the analysis of …
QSAR models for tyrosinase inhibitory activity description applying modern statistical classification techniques: A comparative study
2010
Abstract Cluster analysis (CA), Linear and Quadratic Discriminant Analysis (L(Q)DA), Binary Logistic Regression (BLR) and Classification Tree (CT) are applied on two datasets for description of tyrosinase inhibitory activity from molecular structures. The first set included 701 tyrosinase inhibitors (TI) that are used for performance of inhibitory and non-inhibitory activity and the second one is for potency estimation of active compounds. 2D TOMOCOMD-CARDD atom-based quadratic indices are computed as molecular descriptors. CA is used to “rational” design of training (TS) and prediction set (PS) but it shows of not being adequate as classification technique. On the first data, the overall a…
Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands
2015
Telomeres and telomerase are key players in tumorogenesis. Among the various strategies proposed for telomerase inhibition or telomere uncapping, the stabilization of telomeric G-quadruplex (G4) structures is a very promising one. Additionally, G4 stabilizing ligands also act over tumors mediated by the alternative elongation of telomeres. Accordingly, the discovery of novel compounds able to act on telomeres and/or inhibit the telomerase enzyme by stabilizing DNA telomeric G4 structures as well as the development of approaches efficiently prioritizing such compounds constitute active areas of research in computational medicinal chemistry and anticancer drug discovery. In this direction, we…
Applications of Bond-Based 3D-Chiral Quadratic Indices in QSAR Studies Related to Central Chirality Codification
2009
The concept of bond-based quadratic indices is generalized to codify chemical structure information for chiral drugs, making use of a trigonometric 3D-chirality correction factor. In order to evaluate the effectiveness of this novel approach in drug design, we have modeled several well-known data sets. In particularly, Cramer's steroid data set has become a benchmark for the assessment of novel QSAR methods. This data set has been used by several researchers using 3D-QSAR approaches. Therefore, it is selected by us for the shake of comparability. In addition, to evaluate the effectiveness of this novel approach in drug design, we model the angiotensin-converting enzyme inhibitory activity o…