Controlling release of astaxanthin in ß-sitosterol oleogel-based emulsions via different self-assembled mechanisms and composition of the oleogelators.

In this study, three types of ß-sitosterol-based oleogels (ß-sitosterol + Î³-oryzanol oleogels, ß-sitosterol + lecithin, oleogels and ß-sitosterol + monostearate oleogels), loaded with astaxanthin, were employed as the oil phase to create oleogel-based emulsions (SO, SL, and SM) using high-pressure homogenization. The microstructure revealed that fine-scale crystals were dispersed within the oil phase of the droplets in the ß-sitosterol oleogel-based emulsion. The bioaccessibility of astaxanthin was found to be 58.13 %, 51.24 %, 36.57 %, and 45.72 % for SM, SL, SO, and the control group, respectively. Interestingly, the release of fatty acids was positively correlated with the availability of astaxanthin (P = 0.981). Further analysis of FFAs release and kinetics indicated that the structural strength of the oil-phase in the emulsions influenced the degree and rate of lipolysis. Additionally, the micellar fraction analysis suggested that the nature and composition of the oleogelators in SM and SL also impacted lipolysis and the bioaccessibility of astaxanthin. Furthermore, interfacial binding of lipase and isothermal titration calorimetry (ITC) measurements revealed that the oleogel network within the oil phase of the emulsion acted as a physical barrier, hindering the interaction between lipase and lipid. Overall, ß-sitosterol oleogel-based emulsions offer a versatile platform for delivering hydrophobic molecules, enhancing the bioavailability of active compounds, and achieving sustained release.

Fostering a Holistic Understanding of the Full Volatility Spectrum of Organic Compounds from Benzene Series Precursors through Mechanistic Modeling.

A comprehensive understanding of the full volatility spectrum of organic oxidation products from the benzene series precursors is important to quantify the air quality and climate effects of secondary organic aerosol (SOA) and new particle formation (NPF). However, current models fail to capture the full volatility spectrum due to the absence of important reaction pathways. Here, we develop a novel unified model framework, the integrated two-dimensional volatility basis set (I2D-VBS), to simulate the full volatility spectrum of products from benzene series precursors by simultaneously representing first-generational oxidation, multigenerational aging, autoxidation, dimerization, nitrate formation, etc. The model successfully reproduces the volatility and O/C distributions of oxygenated organic molecules (OOMs) as well as the concentrations and the O/C of SOA over wide-ranging experimental conditions. In typical urban environments, autoxidation and multigenerational oxidation are the two main pathways for the formation of OOMs and SOA with similar contributions, but autoxidation contributes more to low-volatility products. NOx can reduce about two-thirds of OOMs and SOA, and most of the extremely low-volatility products compared to clean conditions, by suppressing dimerization and autoxidation. The I2D-VBS facilitates a holistic understanding of full volatility product formation, which helps fill the large gap in the predictions of organic NPF, particle growth, and SOA formation.

Do Chemformers Dream of Organic Matter? Evaluating a Transformer Model for Multistep Retrosynthesis.

Synthesis planning of new pharmaceutical compounds is a well-known bottleneck in modern drug design. Template-free methods, such as transformers, have recently been proposed as an alternative to template-based methods for single-step retrosynthetic predictions. Here, we trained and evaluated a transformer model, called the Chemformer, for retrosynthesis predictions within drug discovery. The proprietary data set used for training comprised ∼18 M reactions from literature, patents, and electronic lab notebooks. Chemformer was evaluated for the purpose of both single-step and multistep retrosynthesis. We found that the single-step performance of Chemformer was especially good on reaction classes common in drug discovery, with most reaction classes showing a top-10 round-trip accuracy above 0.97. Moreover, Chemformer reached a higher round-trip accuracy compared to that of a template-based model. By analyzing multistep retrosynthesis experiments, we observed that Chemformer found synthetic routes, leading to commercial starting materials for 95% of the target compounds, an increase of more than 20% compared to the template-based model on a proprietary compound data set. In addition to this, we discovered that Chemformer suggested novel disconnections corresponding to reaction templates, which are not included in the template-based model. These findings were further supported by a publicly available ChEMBL compound data set. The conclusions drawn from this work allow for the design of a synthesis planning tool where template-based and template-free models work in harmony to optimize retrosynthetic recommendations.

Toxicity of individual and mixture of organic compounds to P. Phosphoreum and S. Capricornutum using interpretable simple structural parameters.

Human and environmental ecosystem beings are exposed to multicomponent compound mixtures but the toxicity nature of compound mixtures is not alike to the individual chemicals. This work introduces four models for the prediction of the negative logarithm of median effective concentration (pEC50) of individual chemicals to marine bacteria Photobacterium Phosphoreum (P. Phosphoreum) and algal test species Selenastrum Capricornutum (S. Capricornutum) as well as their mixtures to P. Phosphoreum, and S. Capricornutum. These models provide the simplest approaches for the forecast of pEC50 of some classes of organic compounds from their interpretable structural parameters. Due to the lack of adequate toxicity data for chemical mixtures, the largest available experimental data of individual chemicals (55 data) and their mixtures (99 data) are used to derive the new correlations. The models of individual chemicals are based on two simple structural parameters but chemical mixture models require further interaction terms. The new model's results are compared with the outputs of the best accessible quantitative structure-activity relationships (QSARs) models. Various statistical parameters are done on the new and comparative complex QSAR models, which confirm the higher reliability and simplicity of the new correlations.

Dissolved organic matter isolates obtained by solid phase extraction exhibit higher absorption and lower photo-reactivity: Effect of components.

Notable differences in photo-physical and chemical properties were found between bulk water and solid phase extraction (SPE) isolates for dissolved organic matter (DOM). The moieties extracted using modified styrene divinylbenzene cartridges, which predominantly consist of conjugated aromatic molecules like humic acids, contribute mainly to light absorption but exhibit lower quantum yields of fluorescence and photo-produced reactive intermediates (PPRIs). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) revealed lignin as the moieties displaying most significant variance in abundance. In Van Krevelen-Spearman plot, we observed molecules positively or negatively correlated with DOM's optical and photochemical properties (including SUVA254, steady-state concentrations of ·OH, 1O2 quantum yield, etc.) were confined to specific regions, which can be delineated using a threshold modified aromaticity index (AImod) of 0.3. Based on the relationships between optical properties and PPRI production, it is suggested that the energy gap between ground state and excited singlet state (△ES1→S0), governing the inner conversion rate, serves as a determinant for apparent quantum yield of PPRIs in DOM, with intra-molecular charge transfer (CT) interactions potentially playing a pivotal role. Regarding DOM's photoreactivity with pollutants, this study has revealed, for the first time, that protein/amino sugars/amino acids could act as antioxidant groups in addition to phenols on the photolysis of sulfadiazine. These findings provide valuable insights into DOM photochemistry and are expected to stimulate further research in this area.

Meta-Analysis of Optical Surrogates for the Characterization of Dissolved Organic Matter.

Optical surrogates, derived from absorbance and fluorescence spectra, are widely used to infer dissolved organic matter (DOM) composition (molecular weight, aromaticity) and genesis (autochthonous vs allochthonous). Despite the broad adoption of optical surrogates, several limitations exist, such as context- and sample-specific factors. These limitations create uncertainty about how compositional interpretations based on optical surrogates are generalized across contexts, specifically if there is duplicative or contradictory information in those interpretations. To explore these limitations, we performed a meta-analysis of optical surrogates for DOM from diverse sources, both from natural systems and after water treatment processes (n = 762). Prior to analysis, data were screened using a newly developed, standardized methodology that applies systematic quality control criteria before reporting surrogates. There was substantial overlap in surrogate values from natural and treated samples, suggesting that the gradients governing the surrogate variability can be generated in both contexts. This overlap provides justification for using optical surrogates originally developed in the context of natural systems to describe DOM changes in engineered systems, although the interpretations may change. Absorbance-based surrogates that describe the amount of spectral tailing (e.g., E2:E3 and S275-295) had a high frequency of strong correlations with one another but not to specific absorbance (SUVA254) or absorbance slope ratio (SR). The fluorescence index (FI) and biological index (ß/α) were strongly correlated with one another and to the peak emission wavelength but not to the humification index (HIX). Although SUVA254 and FI have both been correlated to DOM aromaticity in prior research, there was a lack of reciprocity between these optical surrogates across this data set. Additionally, there were patterns of deviations in the wastewater subset, suggesting that effluent organic matter may not follow conventional interpretations, urging caution in the use of optical surrogates to track DOM in water reuse applications. Finally, the meta-analysis highlights that three aspects should be captured when optical spectra are used for DOM interpretation: specific absorbance, absorbance tailing, and the extent of red-shifted fluorescence. We recommend that SUVA254, E2:E3, and FI or ß/α be prioritized in future DOM studies to capture these aspects, respectively.

Analysis of carbon nanotube levels in organic matter: an inter-laboratory comparison to determine best practice.

Carbon nanotubes (CNTs) are increasingly being used in industrial applications, but their toxicological data in animals and humans are still sparse. To assess the toxicological dose-response of CNTs and to evaluate their pulmonary biopersistence, their quantification in tissues, especially lungs, is crucial. There are currently no reference methods or reference materials for low levels of CNTs in organic matter. Among existing analytical methods, few have been fully and properly validated. To remedy this, we undertook an inter-laboratory comparison on samples of freeze-dried pig lung, ground and doped with CNTs. Eight laboratories were enrolled to analyze 3 types of CNTs at 2 concentration levels each in this organic matrix. Associated with the different analysis techniques used (specific to each laboratory), sample preparation may or may not have involved prior digestion of the matrix, depending on the analysis technique and the material being analyzed. Overall, even challenging, laboratories' ability to quantify CNT levels in organic matter is demonstrated. However, CNT quantification is often overestimated. Trueness analysis identified effective methods, but systematic errors persisted for some. Choosing the assigned value proved complex. Indirect analysis methods, despite added steps, outperform direct methods. The study emphasizes the need for reference materials, enhanced precision, and organized comparisons.

Molecular-weight dependent promotion and competition effects of natural organic matter on dissolved black carbon removal by coagulation.

Dissolved black carbon (DBC) is the ubiquitous component of dissolved organic matter pools with the high reactivity for disinfection byproducts formation. However, it is unknown that the influence of molecular weight (MW) of natural organic matter (NOM) on the DBC removal from potable water sources. Therefore, it was studied that the DBC removal by coagulation in the presence of the NOM with various molecular weights. The DBC removal was promoted due to the presence of NOM and the promotion degree decreased with decreasing MW of NOM. Furthermore, the removal ratio of humic-like component increased as the MW of NOM decreased, suggesting that the competition between DBC and NOM increased with decreasing MW. The functional groups after coagulation were the same with that before coagulation as the MW of NOM varied, suggesting that the molecular structure was not the key factor of influencing the DBC removal. This study will give the deep insight into the prediction of the DBC removal ratio by coagulation based on the MW of NOM in water sources.

Correlation of the Molecular Cross-Sectional Area of Organic Monofunctional Compounds with Topological Descriptors.

The molecular cross-sectional area (σ) has proved to be an interesting molecular measure not only in the field of adsorption phenomena on solids but also in biochemistry, physiology, or surfactant chemistry. The existing methods to estimate the cross-sectional areas are either not readily applicable or can only be applied to a limited number of compounds. The aim of this work was to describe a method, as general as possible, quick and easy to perform. To that end, the molecular cross-sectional areas were correlated with topological indices. The Emmett-Brunauer formula was used to calculate the reference cross-sectional areas (σEB) of 431 compounds. The correlations of the Wiener (W), hyper-Wiener (WW), Balaban (J), and Randic (χ) indices with σEB were compared for n-alkanes as well as branched and cyclic alkanes. Only the Wiener and hyper-Wiener indices correlated well with σEB, with the data being best fitted by power law regression curves. The lower degeneracy of the hyper-Wiener index did not translate into any significant gain of performance when correlated with σEB. Following the parsimony principle, the less complex Wiener index was thus selected to correlate with the σEB of compounds representing 31 other monofunctional and structural families. The integration of all the compound families into a single curve allowed a quick rough estimation of the cross-sectional areas. The specific reference equations σEB = qWp were determined for the 34 selected families, allowing the fast and reliable calculation of the cross-sectional area of any monofunctional compound.

Assessing the Chemical-Free Oxidation of Trace Organic Chemicals by VUV/UV as an Alternative to Conventional UV/H2O2.

Low-pressure mercury lamps with high-purity quartz can emit both vacuum-UV (VUV, 185 nm) and UV (254 nm) and are commercially available and promising for eliminating recalcitrant organic pollutants. The feasibility of VUV/UV as a chemical-free oxidation process was verified and quantitatively assessed by the concept of H2O2 equivalence (EQH2O2), at which UV/H2O2 showed the same performance as VUV/UV for the degradation of trace organic contaminants (TOrCs). Although VUV showed superior H2O activation and oxidation performance, its performance highly varied as a function of light path length (Lp) in water, while that of UV/H2O2 proportionally decreased with decreasing H2O2 dose regardless of Lp. On increasing Lp from 1.0 to 3.0 cm, the EQH2O2 of VUV/UV decreased from 0.81 to 0.22 mM H2O2. Chloride and nitrate hardly influenced UV/H2O2, but they dramatically inhibited VUV/UV. The competitive absorbance of VUV by chloride and nitrate was verified as the main reason. The inhibitory effect was partially compensated by •OH formation from the propagation reactions of chloride or nitrate VUV photolysis, which was verified by kinetic modeling in Kintecus. In water with an Lp of 2.0 cm, the EQH2O2 of VUV/UV decreased from 0.43 to 0.17 mM (60.8% decrease) on increasing the chloride concentration from 0 to 15 mM and to 0.20 mM (53.5% decrease) at 4 mM nitrate. The results of this study provide a comprehensive understanding of VUV/UV oxidation in comparison to UV/H2O2, which underscores the suitability and efficiency of chemical-free oxidation with VUV/UV.

Nature-inspired polymer photocatalysts for green NADH regeneration and nitroarene transformation.

Photocatalysis has emerged as a promising approach for generating solar chemical and organic transformations under the solar light spectrum, employing polymer photocatalysts. In this study, our aim is to achieve the regeneration of NADH and fixation of nitroarene compounds, which hold significant importance in various fields such as pharmaceuticals, biology, and chemistry. The development of an in-situ nature-inspired artificial photosynthetic pathway represents a challenging task, as it involves harnessing solar energy for efficient solar chemical production and organic transformation. In this work, we have successfully synthesized a novel artificial photosynthetic polymer, named TFc photocatalyst, through the Friedel-Crafts alkylation reaction between triptycene (T) and a ferrocene motif (Fc). The TFC photocatalyst is a promising material with excellent optical properties, an appropriate band gap, and the ability to facilitate the regeneration of NADH and the fixation of nitroarene compounds through photocatalysis. These characteristics are necessary for several applications, including organic synthesis and environmental remediation. Our research provides a significant step forward in establishing a reliable pathway for the regeneration and fixation of solar chemicals and organic compounds under the solar light spectrum.

Interfacial crystallized oleogel emulsion with improved freeze-thaw stability and tribological properties: Influence of cooling rate.

In this study, the influence of cooling rate on the freeze-thaw stability, rheological and tribological properties of interfacial crystalized oleogel emulsion was investigated. Results showed that slower cooling rate could promote formation of larger crystals and stronger network in oleogels. Additionally, oleogel emulsions showed higher freeze-thaw stability than those stabilized solely by emulsifiers. The slower cooling rate resulted in larger crystals adsorbed at the droplet surface. This led to greater steric hindrance that prevented the migration of oil droplets with higher resistance to disruption by ice crystals. The rheological and tribological measurements suggested that with appropriate amount of crystals, the tribological properties were better maintained for emulsions prepared at slow cooling rate after freeze-thaw treatment. This strategy greatly enriched oleogel emulsion formulations and provided important clues for potential applications in food products involved with freeze-thaw treatment.

Exploring Diacylglycerol Oil-Based Oleogels as Effective Stabilizers in Peanut Butter: Performance, Structural Insights, and Sensory Evaluation.

In the pursuit of reducing oil separation in peanut butter, oleogels synthesized from diacylglycerol (DAG)-rich peanut oils, using glycerol monostearate (GMS) as the gelator, were examined as alternative stabilizers. In comparison to triacylglycerol (TAG)-rich peanut oils, the DAG oil-based oleogels exhibited better oil-binding capacities across increasing GMS concentrations. Intriguingly, thermal and rheological assessments pointed to a weaker network structure in DAG oil oleogels, as evidenced by their lower crystallization temperatures and reduced viscoelastic parameters (G' and G''). Insight from infrared spectroscopy revealed that this could stem from heightened intermolecular hydrogen bonding between the DAG oil and the gelator. When applied to peanut butter, DAG oil oleogels demonstrated efficacy in minimizing oil separation. Extended storage trials affirmed the long-term stability of peanut butter formulations incorporating these oleogels. Furthermore, sensory evaluations by panelists underscored favorable impressions, suggesting potential consumer acceptance. Overall, this study illuminates the promising role of DAG oleogels as effective, alternative stabilizers in peanut butter formulations.

Novel bigels based on walnut oil oleogel and chitosan hydrogel: Preparation, characterization, and application as food spread.

This study developed new biphasic gel systems containing a walnut oil-based oleogel and a chitosan hydrogel and evaluated the application on food spread. The effects of different oleogelators [γ-oryzanol/ß-sitosterol (γ-ORY/ß-SIT), candelilla wax/span 65 (CW/SA), and mono- and diglycerides of fatty acids] were explored. Rheological analysis showed that γ-ORY/ß-SIT-based bigel had the strongest gel strength, but XRD confirmed that ß' crystal form (d = 3.72 Å, 4.12 Å) was predominantly in the CW/SA-based bigel, which was more appropriate for application as spread. The characteristics of CW/SA-based bigel with different oleogel fractions (40-80 wt%) were investigated. The microscopic images indicated that the hydrogels were dispersed as small droplets in the oleogels after oleogel fraction reaching 60 %. The highest crystallinity was achieved when the oleogel fraction was 60 %, and its oil binding capacity was 96.49 %. Textural analysis showed that the CW/SA-based bigel (OG-60 %) had similar properties with commercial spread B, and can be used as a partial replacement for spread B. Replacing 75 % of the commercial spread B with the bigel was found to be optimal and displayed acceptable sensory features. This study developed a healthy bigel based on walnut oil and provided the in-depth information for bigels as an alternative to plastic fats.

Life after a fiery death: Fire and plant biomass loading affect dissolved organic matter in experimental ponds.

Drier and hotter conditions linked with anthropogenic climate change can increase wildfire frequency and severity, influencing terrestrial and aquatic carbon cycles at broad spatial and temporal scales. The impacts of wildfire are complex and dependent on several factors that may increase terrestrial deposition and the influx of dissolved organic matter (DOM) from plants into nearby aquatic systems, resulting in the darkening of water color. We tested the effects of plant biomass quantity and its interaction with fire (burned vs. unburned plant biomass) on dissolved organic carbon (DOC) concentration and degradation (biological vs. photochemical) and DOM composition in 400 L freshwater ponds using a gradient experimental design. DOC concentration increased nonlinearly with plant biomass loading in both treatments, with overall higher concentrations (>56 mg/L) in the unburned treatment shortly after plant addition. We also observed nonlinear trends in fluorescence and UV-visible absorbance spectroscopic indices as a function of fire treatment and plant biomass, such as greater humification and specific UV absorbance at 254 nm (a proxy for aromatic DOM) over time. DOM humification occurred gradually over time with less humification in the burned treatment compared to the unburned treatment. Both burned and unburned biomass released noncolored, low molecular weight carbon compounds that were rapidly consumed by microbes. DOC decomposition exhibited a unimodal relationship with plant biomass, with microbes contributing more to DOC loss than photodegradation at intermediate biomass levels (100-300 g). Our findings demonstrate that the quantity of plant biomass leads to nonlinear responses in the dynamics and composition of DOM in experimental ponds that are altered by fire, indicating how disturbances interactively affect DOM processing and its role in aquatic environments.

Effect of the gelling mechanism on the physical properties of bigels based on whey protein isolate.

The effect of the cold-set and heat-set gelling mechanism of whey protein isolate on bigel production was assessed. For this purpose, hydrogel phase was produced with whey protein isolated (10 % w/v) and for oleogel sunflower oil and glycerol monostearate (7.5 % w/v) were used. Bigels were produced by hot emulsification of different hydrogel:oleogel ratios (from 90:10 up to 10:90). For cold-set bigels (CSB) NaCl (200 mM) was added to the aqueous phase prior to the emulsification and the emulsion was cooled to promote the 3D network formation. On the other hand, heat-set bigels (HSB) were produced by heating the emulsion (80 °C, 60 min). Bigels were evaluated through microscopy, FTIR, thermal and texture analyzes. Results showed that depending on the hydrogel:oleogel ratio and gelling mechanism different structures organization were obtained. CSB were more organized, showing that the rate of gelation was the mechanism responsible for the structure. However, for HSB the heat treatment destabilized the emulsion and disorganized structures were observed for high oleogel content. FTIR corroborates the visual observation and showed that the arrangement was purely physical. In addition, the structural arrangement led to different mechanical properties. In general, HSB produced gels with rubber-like behavior, higher elasticity modulus and the presence of a breaking point. In contrast, CSB behaves as squeezing gel, with no breaking point and lower values of elasticity modulus. Moreover, for O/W bigels the dispersed oleogel particles disrupted the WPI network decreasing the gel strength in comparison to pure hydrogels. However, for systems where oleogel was the continuous phase, the gel strength was recovered due to the metastable and dynamic character of these systems. Thus, results showed that the gelling mechanism of the protein exerted an effect on the physical properties of bigels. In addition, the mechanical properties also can be modulated according to the bigel composition, allowing its application in products with different sensorial characteristics.

Natural oleogelators for the formulation of oleogels by considering their rheological and textural perspective; a review.

A well-known method for reducing or swapping out undesirable and controversial fats in food is oleogelation. To quantify the effects of droplets-particle inclusion on the textural aspects of gelled systems, a thorough understanding of rheological behavior of oleogels (OGs) is necessary. Otherwise stated, a rational grasp of rheological characterization is essential for food development, optimization, and processing (when touching or putting food into the mouth, rheological flow qualities influence our perception). This narrative review primarily intends to investigate rheological and textural characteristics of various oleogelator-based OGs, such as operative connection between hardness, distortion, stresses, and rheological parameters like viscosity, elasticity, and viscoelasticity, as well as flow behavior and recovery. Expanding oleogelators concentration and synergistic interactions between them increase robustness and moduli values, as compared to single oleogelators. However, given the lack of information on the connection between the OGs' macroscopic rheological characteristics and their microstructural characteristics, this review presents state-of-the-art overview of various oleogelator-based OGs, highlighting the importance of structure-rheology relationships of OGs to provide advanced knowledge on the development of innovative OGs.

Recent advances in biocatalytic C-N bond-forming reactions.

Molecules containing C-N bonds are of paramount importance in a diverse array of organic-based materials, natural products, pharmaceutical compounds, and agricultural chemicals. Biocatalytic C-N bond-forming reactions represent powerful strategies for producing these valuable targets, and their significance in the field of synthetic chemistry has steadily increased over the past decade. In this review, we provide a concise overview of recent advancements in the development of C-N bond-forming enzymes, with a particular emphasis on the inherent chemistry involved in these enzymatic processes. Overall, these enzymatic systems have proven their potential in addressing long-standing challenges in traditional small-molecule catalysis.

Paper-based electrodes as a tool for detecting ligninolytic enzymatic activities.

Lignin is the most important natural source of aromatic compounds. The valorisation of lignin into aromatics requires fractionation steps that can be catalysed by ligninolytic enzymes. However, one of the main limitations of biological lignin fractionation is the low efficiency of biocatalysts; it is therefore crucial to enhance or to identify new ligninolytic enzymes. Currently, the screening of ligninolytic activities on lignin polymers represents a technological bottenleck and hinders the characterization and the discovery of efficient ligninolytic biocatalysts. An efficient and fast method for the measurement of such enzymatic activities is therefore required. In this work, we present a new electrochemical tool based on lignin-coated paper electrodes for the detection and the characterization of ligninolytic activity. The suitability of this method is demonstrated using a catalase-peroxidase isolated from Thermobacillus xylanilyticus.

The use of simple structural parameters of organic compounds to assess their PUF-air partition coefficients.

A novel approach is introduced for the reliable prediction of PUF-air partition coefficients of organic compounds, which can determine the environmental fate of organic compounds during interactions with air, soil, and water. The biggest accessible measured data of PUF-air partition coefficients for 170 chemicals are used to develop and test the novel model. In comparison to available quantitative structure-property relationship (QSPR) methods for the prediction of PUF-air partition coefficients that need complex descriptors, the here used descriptors are simpler. The assessed various statistical factors of the simple method containing 147 (training) and 23 (test) organic compounds can verify the external and internal cross-validations. Various statistical parameters confirm the high reliability of the novel model as compared with the outputs of complex multiple linear regression (MLR), artificial neural network (ANN) and support vector machine (SVM) methods. The values of R-squared (R2), and root mean square error (RMSE) of the new model are for training/test sets are 0.924/0.894 and 0.374/0.318, respectively. Meanwhile, R2 and RMSE values for three comparative models training/test sets are (i) MLR: 0.848/0.670 (R2) and 0.531/0.573 (RMSE); (ii) ANN: 0.902/0.664 (R2) and 0.425/0.560 (RMSE); (iii) SVM: 0.935/0.794 (R2) and 0.351/0.419 (RMSE). Thus, the new model the simplest approach with higher reliability in comparison to the best available methods.