In Silico and In Vitro Studies of Terpenes from the Fabaceae Family Using the Phenotypic Screening Model against the SARS-CoV-2 Virus.

In 2019, the emergence of the seventh known coronavirus to cause severe illness in humans triggered a global effort towards the development of new drugs and vaccines for the SARS-CoV-2 virus. These efforts are still ongoing in 2024, including the present work where we conducted a ligand-based virtual screening of terpenes with potential anti-SARS-CoV-2 activity. We constructed a Quantitative Structure-Activity Relationship (QSAR) model from compounds with known activity against SARS-CoV-2 with a model accuracy of 0.

Simplex representation of molecular structure as universal QSAR/QSPR tool.

We review the development and application of the Simplex approach for the solution of various QSAR/QSPR problems. The general concept of the simplex method and its varieties are described. The advantages of utilizing this methodology, especially for the interpretation of QSAR/QSPR models, are presented in comparison to other fragmentary methods of molecular structure representation.

Development and characterization of chitosan/polyvinyl alcohol polymer material with elastolytic and collagenolytic activities.

The biologically active polymeric material with entrapped peptidase Bacillus thuringiensis var. israelensis with caseinolytic, collagenase and elastase activities was developed as a promising product for medical use. We have evaluated and reported here the following physical-chemical and biochemical characteristics of entrapped enzyme: peptidase/polymer interaction and morphology analyses, film thickness, water content, time of dissolution in water and physiological saline, kinetic of casein hydrolysis and pH- and thermoprofiles of proteolytic activity.

Anti-enteroviral activity of new MDL-860 analogues: Synthesis, in vitro/in vivo studies and QSAR analysis.

A series of 60 nitrobenzonitrile analogues of the anti-viral agent MDL-860 were synthesized (50 of which are new) and evaluated for their activity against three types of enteroviruses (coxsackievirus B1, coxsackievirus B3 and poliovirus 1). Among them, six diaryl ethers (20e, 27e, 28e, 29e, 33e and 35e) demonstrated high in vitro activity (SI > 50) towards at least one of the tested viruses and very low cytotoxicity against human cells. Compound 27e possesses the broadest spectrum of activity towards all tested viruses in the same way as MDL-860 does.

Characterization and influence of hydroxyapatite nanopowders on living cells.

Nanomaterials, such as hydroxyapatite nanoparticles show a great promise for medical applications due to their unique properties at the nanoscale. However, there are concerns about the safety of using these materials in biological environments. Despite a great number of published studies of nanoobjects and their aggregates or agglomerates, the impact of their physicochemical properties (such as particle size, surface area, purity, details of structure and degree of agglomeration) on living cells is not yet fully understood.

Alarms about structural alerts.

Structural alerts are widely accepted in chemical toxicology and regulatory decision support as a simple and transparent means to flag potential chemical hazards or group compounds into categories for read-across. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. Conversely, the rigorously developed and properly validated statistical QSAR models can accurately and reliably predict the toxicity of a chemical; however, their use in regulatory toxicology has been hampered by the lack of transparency and interpretability.

Novel enhanced applications of QSPR models: Temperature dependence of aqueous solubility.

A model developed to predict aqueous solubility at different temperatures has been proposed based on quantitative structure-property relationships (QSPR) methodology. The prediction consists of two steps. The first one predicts the value of k parameter in the linear equation lgSw=kT+c, where Sw is the value of solubility and T is the value of temperature.

Gelatin/carboxymethyl cellulose mucoadhesive films with lysozyme: Development and characterization.

The goal of our study is to develop and characterize mucoadhesive films with entrapped lysozyme based on gelatin/sodium carboxymethyl cellulose as perspective antimicrobial preparation. Lysozyme in mucoadhesive films retains more than 95% of its initial activity for 3 years of storage. Different physical-chemical and biochemical characteristics of entrapped enzyme were evaluated, such as film thickness, weight, time of dissolution in water, bioadhesive force, in vitro lysozyme release, pH- and thermoprofiles of hydrolytic activity, effect of γ-sterilization, etc.

QSAR Modeling and Prediction of Drug-Drug Interactions.

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year.

Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds.

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals.

Predicting chemically-induced skin reactions. Part II: QSAR models of skin permeability and the relationships between skin permeability and skin sensitization.

Skin permeability is widely considered to be mechanistically implicated in chemically-induced skin sensitization. Although many chemicals have been identified as skin sensitizers, there have been very few reports analyzing the relationships between molecular structure and skin permeability of sensitizers and non-sensitizers. The goals of this study were to: (i) compile, curate, and integrate the largest publicly available dataset of chemicals studied for their skin permeability; (ii) develop and rigorously validate QSAR models to predict skin permeability; and (iii) explore the complex relationships between skin sensitization and skin permeability.

Universal Approach for Structural Interpretation of QSAR/QSPR Models.

In this paper we offer a novel approach for the structural interpretation of QSAR models. The major advantage of our developed methodology is its universality, i.e.

QSPR Approach to Predict Nonadditive Properties of Mixtures. Application to Bubble Point Temperatures of Binary Mixtures of Liquids.

This paper is devoted to the development of methodology for QSPR modeling of mixtures and its application to vapor/liquid equilibrium diagrams for bubble point temperatures of binary liquid mixtures. Two types of special mixture descriptors based on SiRMS and ISIDA approaches were developed. SiRMS-based fragment descriptors involve atoms belonging to both components of the mixture, whereas the ISIDA fragments belong only to one of these components.

QSPR Prediction of Lipophilicity for Organic Compounds Using Random Forest Technique on the Basis of Simplex Representation of Molecular Structure.

The relationship between the octanol-water partition coefficient for more than twelve thousand organic compounds and their structures was investigated using a QSPR approach based on Simplex Representation of Molecular Structure (SiRMS). The dataset used in our study included 10973 compounds with experimental values of lipophilicity (LogKow ) for different chemical compounds. Random Forest (RF) method was used for statistical modeling at the 2D level of representation of molecular structure.

Existing and Developing Approaches for QSAR Analysis of Mixtures.

This review is devoted to the critical analysis of advantages and disadvantages of existing mixture descriptors and their usage in various QSAR/QSPR tasks. We describe good practices for the QSAR modeling of mixtures, data sources for mixtures, a discussion of various mixture descriptors and their application, recommendations about proper external validation specific for mixture QSAR modeling, and future perspectives of this field. The biggest problem in QSAR of mixtures is the lack of reliable data about the mixtures' properties.

QSAR analysis of the toxicity of nitroaromatics in Tetrahymena pyriformis: structural factors and possible modes of action.

The Hierarchical Technology for Quantitative Structure-Activity Relationships (HiT QSAR) was applied to 95 diverse nitroaromatic compounds (including some widely known explosives) tested for their toxicity (50% inhibition growth concentration, IGC₅₀) against the ciliate Tetrahymena pyriformis. The dataset was divided into subsets according to putative mechanisms of toxicity. The Classification and Regression Trees (CART) approach implemented within HiT QSAR has been used for prediction of mechanism of toxicity for new compounds.

Interpretation of QSAR Models Based on Random Forest Methods.

A new algorithm for the interpretation of Random Forest models has been developed. It allows to calculate the contribution of each descriptor to the calculated property value. In case of the simplex representation of a molecular structure, contributions of individual atoms can be calculated, and thus it becomes possible to estimate the influence of separate molecular fragments on the investigated property.

Per aspera ad astra: application of Simplex QSAR approach in antiviral research.

This review explores the application of the Simplex representation of molecular structure (SiRMS) QSAR approach in antiviral research. We provide an introduction to and description of SiRMS, its application in antiviral research and future directions of development of the Simplex approach and the whole QSAR field. In the Simplex approach every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality and symmetry).

Application of Random Forest and Multiple Linear Regression Techniques to QSPR Prediction of an Aqueous Solubility for Military Compounds.

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 level of representation of molecular structure.

New QSPR equations for prediction of aqueous solubility for military compounds.

The development of a new quantitative structure-property relationship (QSPR) model to predict aqueous solubility (S(w)) accurately for compounds of military interest is presented. The ability of the new model to predict solubility is assessed and compared to available experimental data. A large set of structurally diverse organic compounds was used in this analysis.

Application of random forest approach to QSAR prediction of aquatic toxicity.

This work is devoted to the application of the random forest approach to QSAR analysis of aquatic toxicity of chemical compounds tested on Tetrahymena pyriformis. The simplex representation of the molecular structure approach implemented in HiT QSAR Software was used for descriptors generation on a two-dimensional level. Adequate models based on simplex descriptors and the RF statistical approach were obtained on a modeling set of 644 compounds.

Quantitative structure-affinity relationship of 5-HT1A receptor ligands by the classification tree method.

The influence of molecular structure of 346 ligands on their affinity for 5-HT1A receptors was investigated. It was shown that the effectiveness of the proposed novel approach for interpretation of decision tree models compared favourably with the PLS method. In the context of the proposed approach, molecular fragments and their values of the relative influence on the affinity for 5-HT1A receptors were defined.

Quantitative structure-activity relationship studies of [(biphenyloxy)propyl]isoxazole derivatives. Inhibitors of human rhinovirus 2 replication.

The 50% cytotoxic concentration (CC50) in HeLa cells, the 50% inhibitory concentration (IC50) against human rhinovirus 2 (HRV-2), and the selectivity index (SI = CC50/IC50) of [(biphenyloxy)propyl]isoxazole derivatives were used to develop quantitative structure-activity relationships (QSAR) based on simplex representation of molecular structure. Statistic characteristics for partial least-squares models are quite satisfactory (R2 = 0.838 - 0.

Identification of individual structural fragments of N,N'-(bis-5-nitropyrimidyl)dispirotripiperazine derivatives for cytotoxicity and antiherpetic activity allows the prediction of new highly active compounds.

Objectives: The objectives of this study were (i) to apply computer-based technologies to evaluate the structure of 48 N,N'-(bis-5-nitropyrimidyl)dispirotripiperazines which belong to a new class of highly active antiviral compounds binding to cell surface heparan sulphates, (ii) to understand the chemical- biological interactions governing their activities, and (iii) to design new compounds with strong antiviral activity.

Methods: The logarithm of 50% cytotoxic concentration (CC(50)) in GMK cells, of 50% inhibitory concentration (IC(50)) against herpes simplex virus type 1, and of selectivity index (SI = CC(50)/IC(50)) was used to develop quantitative structure-activity relationships (QSARs) based on simplex representation of molecular structure. The QSAR model was applied to design new compounds.