نتایج جستجو برای: qsar study
تعداد نتایج: 3971037 فیلتر نتایج به سال:
Purpose: The purpose of this study was to explore a possible mechanism of eye irritation by constructing a corresponding general quantitative structure-activity relationship (QSAR) model using a genetic algorithm. The model was derived from a subset of diverse chemical structures found in the Draize eye irritation ECETOC data set. Methods: Molecular dynamic simulation (MDS) was used to generate...
Drug resistance to existing antibiotics poses alarming threats to global public health, which inspires heightened interests in searching for new antibiotics, including antimicrobial peptides (AMPs). Accurate prediction of antibacterial activities of AMPs may expedite novel AMP design and reduce the costs and efforts involved in laboratory screening. In the present study, a novel quantitative pr...
Despite highly active antiretroviral therapy (HAART) implementation, there is a continuous need to search for new anti-HIV agents. HIV-1 integrase (HIV-1 IN) is a recently validated biological target for AIDS therapy. In this work, a four-dimensional quantitative structure-activity relationship (4D-QSAR) study using the new methodology named LQTA-QSAR approach with a training set of 85 HIV-1 IN...
Membrane-interaction [MI]-QSAR analysis, which includes descriptors explicitly derived from simulations of solutes [drugs] interacting with phospholipid membrane models, was used to construct QSAR models for human oral intestinal drug absorption. A data set of 188 compounds, which are mainly drugs, was divided into a parent training set of 164 compounds and a test set of 24 compounds. Stable, b...
BACKGROUND A plethora of studies indicate that the development of multi-target drugs is beneficial for complex diseases like cancer. Accurate QSAR models for each of the desired targets assist the optimization of a lead candidate by the prediction of affinity profiles. Often, the targets of a multi-target drug are sufficiently similar such that, in principle, knowledge can be transferred betwee...
We report on the prediction accuracy of ligand-based (2D QSAR) and structure-based (MedusaDock) methods used both independently and in consensus for ranking the congeneric series of ligands binding to three protein targets (UK, ERK2, and CHK1) from the CSAR 2011 benchmark exercise. An ensemble of predictive QSAR models was developed using known binders of these three targets extracted from the ...
The estimation of accuracy and applicability of QSAR and QSPR models for biological and physicochemical properties represents a critical problem. The developed parameter of "distance to model" (DM) is defined as a metric of similarity between the training and test set compounds that have been subjected to QSAR/QSPR modeling. In our previous work, we demonstrated the utility and optimal performa...
Topological (2D) Fuzzy Pharmacophore Triplets (2DFPT), using the number of interposed bonds to measure separation between the atoms representing pharmacophore types, were employed to establish and validate Quantitative Structure-Activity Relationships (QSAR). Thirteen data sets for which state-of-the-art QSAR models were reported in literature were revisited in order to benchmark 2D-FPT biologi...
The data have been obtained from the Sigma-2 Receptor Selective Ligands Database (S2RSLDB) and refined according to the QSAR requirements. These data provide information about a set of 548 Sigma-2 (σ2) receptor ligands selective over Sigma-1 (σ1) receptor. The development of the QSAR model has been undertaken with the use of CORAL software using SMILES, molecular graphs and hybrid descriptors (...
Three different QSAR methods, Comparative Molecular Field Analysis (CoMFA), classical QSAR (utilizing the CODESSA program), and Hologram QSAR (HQSAR), are compared in terms of their potential for screening large data sets of chemicals as endocrine disrupting compounds (EDCs). While CoMFA and CODESSA (Comprehensive Descriptors for Structural and Statistical Analysis) have been commercially avail...
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