Systematic Optimization of Liquid-Liquid Extraction for Isolation of Unidentified Components

Characterizing lipid constituents of B. moojeni snake venom: a comparative approach for chemical and biological investigations

Snake venoms are complex mixtures majorly composed of proteins with well-studied biological effects. However, the exploration of non-protein components, especially lipids, remains limited despite their potential for discovering bioactive molecules. This study compares three liquid-liquid lipid extraction methods for both chemical and biological analyses of Bothrops moojeni snake venom. The methods evaluated include the Bligh and Dyer method (methanol, chloroform, water), considered standard; the Acunha method, a modification of the Bligh and Dyer protocol; and the Matyash method (MTBE/methanol/water), featuring an organic phase less dense than the aqueous phase. Lipidomic analysis using liquid chromatography with high-resolution mass spectrometry (LC-HRMS) system revealed comparable values of lipid constituents' peak intensity across different extraction methods. Our results show that all methods effectively extracted a similar quantity of lipid species, yielding approximately 17-18 subclasses per method. However, the Matyash and Acunha methods exhibited notably higher proportions of biologically active lipids compared to the Bligh and Dyer method, particularly in extracting lipid species crucial for cellular structure and function, such as sphingomyelins and phosphatidylinositol-phosphate. In conclusion, when selecting a lipid extraction method, it is essential to consider the study's objectives. For a biological approach, it is crucial to evaluate not only the total quantity of extracted lipids but also their quality and biological activity. The Matyash and Acunha methods show promise in this regard, potentially offering a superior option for extracting biologically active lipids compared to the Bligh and Dyer method.

Assessment of liquid-liquid partition for the assignment of descriptors for the solvation parameter model

The solvation parameter model uses five system independent descriptors to characterize compound properties defined as excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity, A, hydrogen-bond basicity, B, and McGowan's characteristic volume, V, to model transfer properties between condensed phases. The V descriptor is assigned from structure. For compounds liquid at 20 °C the E descriptor can be assigned from the characteristic volume and its refractive index. The E descriptor for compounds solid at 20 °C and the S, A, and B descriptors are experimental properties traditionally assigned from chromatographic, liquid-liquid partition, and solubility measurements. In this report liquid-liquid partition constants in totally organic and aqueous biphasic systems are evaluated as a standalone technique for descriptor assignments. Using six totally organic biphasic systems the S, A, and B descriptors were assigned with an average absolute deviation (AAD) of about 0.04, 0.03, and 0.04, respectively, compared with the best estimate of the true descriptor values for 65 compounds. The E descriptor for compounds solid at 20 °C can only be estimated with an AAD of approximately 0.1. For six aqueous biphasic systems the B descriptor is assigned with a lower AAD of 0.028 and higher AAD of 0.08 and 0.05 for the S and A descriptors, respectively, than for the totally organic biphasic systems for compounds with a reliable value for the E descriptor. The preferred system for descriptor assignments utilizes both totally organic biphasic systems (heptane-1,1,1-trifluoroethanol, isopentyl ether-propylene carbonate, isopentyl ether-ethanolamine, heptane-ethylene glycol, heptane-formamide, and 1,2-dichloroethane-ethylene glycol) and aqueous biphasic systems (octanol-water, cyclohexane-water) with the possible substitution of some systems with alternative systems of similar selectivity. For 55 varied compounds this combination of eight organic and aqueous biphasic systems resulted in an AAD of approximately 0.03, 0.02, and 0.02 for the S, A, and B descriptors compared to the best estimate of the true descriptor value. For 30 compounds solid at 20 °C the AAD for the E descriptor of 0.11 is poorly assigned. The relative average absolute deviation in percent (RAAD) corresponds to 9.7 %, 3.1 %. 4.0 % and 8.3 % for E, S, A, and B, respectively, for the eight biphasic systems. Liquid-liquid partition is compared to reversed-phase liquid and gas chromatography as a standalone technique for descriptor assignments.

Advances in Natural Product Extraction Techniques, Electrospun Fiber Fabrication, and the Integration of Experimental Design: A Comprehensive Review

The present review explores the growing interest in the techniques employed for extracting natural products. It emphasizes the limitations of conventional extraction methods and introduces superior non-conventional alternatives, particularly ultrasound-assisted extraction. Characterization and quantification of bioactive constituents through chromatography coupled with spectroscopy are recommended, while the importance of method development and validation for biomarker quantification is underscored. At present, electrospun fibers provide a versatile platform for incorporating bioactive extracts and have extensive potential in diverse fields due to their unique structural and functional characteristics. Thus, the review also highlights the fabrication of electrospun fibers containing bioactive extracts. The preparation of biologically active extracts under optimal conditions, including the selection of safe solvents and cost-effective equipment, holds promising potential in the pharmaceutical, food, and cosmetic industries. Integration of experimental design into extraction procedures and formulation development is essential for the efficient production of health products. The review explores potential applications of encapsulating natural product extracts in electrospun fibers, such as wound healing, antibacterial activity, and antioxidant properties, while acknowledging the need for further exploration and optimization in this field. The findings discussed in this review are anticipated to serve as a valuable resource for the processing industry, enabling the utilization of affordable and environmentally friendly, natural, and raw materials.

Prediction of toluene/water partition coefficients in the SAMPL9 blind challenge: assessment of machine learning and IEF-PCM/MST continuum solvation models

In recent years the use of partition systems other than the widely used biphasic n-octanol/water has received increased attention to gain insight into the molecular features that dictate the lipophilicity of compounds. Thus, the difference between n-octanol/water and toluene/water partition coefficients has proven to be a valuable descriptor to study the propensity of molecules to form intramolecular hydrogen bonds and exhibit chameleon-like properties that modulate solubility and permeability. In this context, this study reports the experimental toluene/water partition coefficients (log P_tol/w) for a series of 16 drugs that were selected as an external test set in the framework of the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) blind challenge. This external set has been used by the computational community to calibrate their methods in the current edition (SAMPL9) of this contest. Furthermore, the study also investigates the performance of two computational strategies for the prediction of log P_tol/w. The first relies on the development of two machine learning (ML) models, which are built up by combining the selection of 11 molecular descriptors in conjunction with either the multiple linear regression (MLR) or the random forest regression (RFR) model to target a dataset of 252 experimental log P_tol/w values. The second consists of the parametrization of the IEF-PCM/MST continuum solvation model from B3LYP/6-31G(d) calculations to predict the solvation free energies of 163 compounds in toluene and benzene. The performance of the ML and IEF-PCM/MST models has been calibrated against external test sets, including the compounds that define the SAMPL9 log P_tol/w challenge. The results are used to discuss the merits and weaknesses of the two computational approaches.

Ionization and lipophilicity in nonpolar media mimicking the cell membrane interior

Ionization and lipophilicity may vary with the environment. Therefore, in this study we provide some insight in the performances of different experimental techniques (potentiometry, UV-vis, shake-flask and chromatography) to determine ionization and lipophilicity in more nonpolar systems than those commonly used in drug discovery. To this purpose a pool of 11 compounds of pharmaceutical interest was firstly submitted to a few experimental techniques to measure pK_a in water, water/acetonitrile mixtures and pure acetonitrile. Then we measured logP/logD with shake-flask and potentiometry in octanol/water and toluene/water and also determined a chromatographic lipophilicity index (log k'80 PLRP-S) in a nonpolar system. Results show that ionization decreases for both acids and bases in a coherent, significant but not dramatical extent when water is present in the system, but the picture is completely different in pure acetonitrile. Lipophilicity may vary or not with the environment according to the chemical structure of the investigated compounds as also revealed by electrostatic potential maps. Since the internal core of cell membranes is largely nonpolar, our results support the need of extending the pool of physicochemical descriptors to be determined in the various stages of drug discovery programs and indicate some experimental strategies for their determination.

One Hundred Carboxylate Receptors

This work presents a compilation of binding constant (logKass) values in DMSO-d6/H2O (0.5% m/m) for a variety of receptors with 12 carboxylate anions (formate, acetate, lactate, pivalate, sorbate, hexanoate, benzoate, glyphosate, glucuronate, ibuprofen, naproxen, and ketoprofen). A total of 489 logKass values are listed for 100 anion receptor molecules. Most logKass values originate from previously published articles, along with some values for previously unpublished receptor molecules, spanning a workflow of 8 years. The purpose of this study is to serve as a comprehensive information source for selecting suitable receptor candidates to be used in practical carboxylate sensing applications, such as constructing ion-selective electrodes (ISE-s). To support such decision making, all receptors are presented together with lipophilicity (logPo/w) data.

The isolation of water-soluble natural products - challenges, strategies and perspectives

Covering period: up to 2019Water-soluble natural products constitute a relevant group of secondary metabolites notably known for presenting potent biological activities. Examples are aminoglycosides, β-lactam antibiotics, saponins of both terrestrial and marine origin, and marine toxins. Although extensively investigated in the past, particularly during the golden age of antibiotics, hydrophilic fractions have been less scrutinized during the last few decades. This review addresses the possible reasons on why water-soluble metabolites are now under investigated and describes approaches and strategies for the isolation of these natural compounds. It presents examples of several classes of hydrosoluble natural products and how they have been isolated. Novel stationary phases and chromatography techniques are also reviewed, providing a perspective towards a renaissance in the investigation of water-soluble natural products.

Synthesis and Physicochemical Properties of 2-SF5-(Aza)Indoles, a New Family of SF5 Heterocycles

Structural diversity in heterocyclic chemistry is key to unlocking new properties and modes of action. In this regard, heterocycles embedding emerging fluorinated substituents hold great promise. Herein is described a strategy to access 2-SF₅-(aza)indoles for the first time. The sequence relies on the radical addition of SF₅Cl to the alkynyl π-system of 2-ethynyl anilines followed by a cyclization reaction. A telescoped sequence is proposed, making this strategy very appealing and reproducible on a gram scale. Downstream functionalizations are also demonstrated, allowing an easy diversification of N- and C3-positions. Ames test, pK _a, log P, and differential scanning calorimetry measurements of several fluorinated 2-Rf-indoles are also disclosed. These studies highlight the strategic advantages that a C2-pentafluorosulfanylated motif impart to a privileged scaffold such as an indole.

ExtractionScore: A Quantitative Framework for Evaluating Synthetic Routes on Predicted Liquid-Liquid Extraction Performance

A multitude of metrics exist to assign scores to synthetic routes within computer-aided synthesis planning (CASP) tools. A quantitative scoring method is necessary to identify the most promising synthetic approaches to a molecule. However, current CASP tools are limited in their capacity to evaluate reaction selectivity and are unable to fully account for the effect of side products on the purification sequences associated with chemical syntheses. We develop a novel quantitative metric called ExtractionScore for evaluating synthetic routes based on the predicted identities of side products as well as the separability of major and side products by liquid-liquid extraction based on chemical property prediction. By comparing industrially practiced routes to a collection of 200 pharmaceutically relevant compounds with routes suggested by state-of-the-art CASP software, we show that ExtractionScore may improve retrosynthetic recommendations by incorporating information about the formation of side products.

High-throughput screening for high-efficiency small-molecule biosynthesis

Systems metabolic engineering faces the formidable task of rewiring microbial metabolism to cost-effectively generate high-value molecules from a variety of inexpensive feedstocks for many different applications. Because these cellular systems are still too complex to model accurately, vast collections of engineered organism variants must be systematically created and evaluated through an enormous trial-and-error process in order to identify a manufacturing-ready strain. The high-throughput screening of strains to optimize their scalable manufacturing potential requires execution of many carefully controlled, parallel, miniature fermentations, followed by high-precision analysis of the resulting complex mixtures. This review discusses strategies for the design of high-throughput, small-scale fermentation models to predict improved strain performance at large commercial scale. Established and promising approaches from industrial and academic groups are presented for both cell culture and analysis, with primary focus on microplate- and microfluidics-based screening systems.

LogP determination for highly lipophilic hydrogen-bonding anion receptor molecules

Lipophilicity, usually expressed as octanol-water partition coefficient (logP_o/w), is an important property in biomedical research, drug design and technology. However, high logP_o/w values of complex hydrogen-bonding molecules are not easy to measure or calculate. Exemplary problematic molecules are prospective active components (ionophores) of polymeric sensor membranes - the working elements of ion-selective electrodes. High lipophilicities of the membrane components are crucial for the sensor lifetime. In this work, lipophilicities of a wide range of urea-, carbazole- and indolocarbazole-based anion receptor molecules (some newly synthesized) and two common plasticizers were determined using a chromatography-based approach and/or the COSMO-RS method. Very high logP_o/w values, up to around 20, i.e. far beyond directly experimentally accessible range, were obtained. The agreement between the two approaches ranged from very good to satisfactory. Based on these results, simple fragment-based equations were developed for quick lipophilicity estimation without any specialized software. Membrane-water partition coefficients for the studied compounds were modeled. Limitations and biases of the used methods are discussed.

Antibiotic drug discovery: Challenges and perspectives in the light of emerging antibiotic resistance

Amid a rising threat of antimicrobial resistance in a global scenario, our huge investments and high-throughput technologies injected for rejuvenating the key therapeutic scaffolds to suppress these rising superbugs has been diminishing severely. This has grasped world-wide attention, with increased consideration being given to the discovery of new chemical entities. Research has now proven that the relatively tiny and simpler microbes possess enhanced capability of generating novel and diverse chemical constituents with huge therapeutic leads. The usage of these beneficial organisms could help in producing new chemical scaffolds that govern the power to suppress the spread of obnoxious superbugs. Here in this review, we have explicitly focused on several appealing strategies employed for the generation of new chemical scaffolds. Also, efforts on providing novel insights on some of the unresolved questions in the production of metabolites, metabolic profiling and also the serendipity of getting "hit molecules" have been rigorously discussed. However, we are highly aware that biosynthetic pathway of different classes of secondary metabolites and their biosynthetic route is a vast topic, thus we have avoided discussion on this topic.

Prediction of partition and distribution coefficients in various solvent pairs with COSMO-RS

Performance of COSMO-RS method as a tool for partition and distribution modeling in 20 solvent pairs-composed of neutral or acidic aqueous solution and organic solvents of different polarity, ranging from alcohols to toluene and hexane-was evaluated. Experimental partition/distribution data of lignin-related and drug-like compounds (neutral, acidic, moderately basic) were used as reference. Several aspects of partition modeling were addressed: accounting for mutual saturation of aqueous and organic phases, variability of systematic prediction errors across solvent pairs, taking solute ionization into account. COSMO-RS was found to predict extraction outcome for both ligneous and drug-like compounds in various solvent pairs fairly well without any additional empirical input. The solvent-specific systematic errors were found to be moderate, despite being statistically significant, and related to the solvent hydrophobicity. Accounting for mutual solubilities of the two liquids was proven crucial in cases where water was considerably soluble in the organic solvent. The root mean square error of a priori logP prediction varied, depending mainly on the solvent pair, from 0.2 to 0.7, overall value being 0.6 log units. The accuracy was higher in case of hydrophilic than hydrophobic solvents. The logD predictions were less accurate, due to pK_a prediction being an additional source of error, and also because of the complexity of modeling the behaviour of ionic species in the two-phase system. A simple correction for partitioning of free ions was found to notably improve logD prediction accuracy in case of the most hydrophilic organic phase (butanol/water).