Nano-QSPR modeling often requires considering variety of factors, if neglected, may lead to erroneous result the study. Frequently, data turned out be inaccurate, incomplete, or fragmentary. Obviously, quality experimental directly depends on many factors: laboratory equipment, organization internal regulations, skills researchers, and so on. As a violations algorithms protocols initial streams...

Many technological implementations in the field of nanotechnology have involved carbon nanomaterials, including fullerenes such as the buckminsterfullerene, C60. The unprecedented properties of such organic nanomaterials (in particular their large surface area) gained extensive attention for their potential use as organic pollutant sorbents. Sorption interactions can be very hazardous and usefu...

BACKGROUND In silico predictive models have proved to be valuable for the optimisation of compound potency, selectivity and safety profiles in the drug discovery process. RESULTS camb is an R package that provides an environment for the rapid generation of quantitative Structure-Property and Structure-Activity models for small molecules (including QSAR, QSPR, QSAM, PCM) and is aimed at both a...

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...

The relationship between the aqueous solubility of more than two thousand eight hundred organic compounds and their structures was investigated using a QSPR approach based on Simplex Representation of Molecular Structure (SiRMS). The dataset consists of 2537 diverse organic compounds. Multiple Linear Regression (MLR) and Random Forest (RF) methods were used for statistical modeling at the 2D le...

Quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies use statistical models to compute physical, chemical, or biological properties of a chemical substance from its molecular structure, encoded in a numerical form with the aid of various descriptors. Structural indices derived from molecular graph matrices represent an important gro...

A hierarchical hybrid method combining experimental-database-derived estimation of extraction performance, quantitative structure–property relationship (QSPR)-based assessment IL physical and environmental properties, liquid–liquid (LLE) measurement, process evaluation is proposed to screen practically suitable ionic liquid (IL) solvents for different extractions. From the literature, 47 424 in...