[QSAR investigation of acute toxicity of organic compounds during oral administration to mice].

The effect of the structure of organic compounds on the acute toxicity upon oral injection in mice was studied using 2D simplex representation of the molecular structure and Random forest (RF) methods. Satisfactory quantitative structure-activity relationship (QSAR) models were constructed (R2 test = 0,61-0,62). The interpretation of the obtained QSAR models was carried out.

Contribution assessment of multiparameter optimization descriptors in CNS penetration.

Assessment of the influence of six physicochemical properties used in the multiparameter optimization (MPO) approach for chemical penetration of the blood-brain barrier was carried out by means of application of logistic regression and multiple linear regression, using a data set of 578 diverse chemicals. It was found that use of an aggregation MPO-score descriptor did not give satisfactory results with central nervous system (CNS)/non-CNS classification. Thus an application of the MPO approach for CNS penetration is ambiguous.

Classification (Agonist/Antagonist) and Regression "Structure-Activity" Models of Drug Interaction with 5-HT6.

Introduction: One promising target for novel psychotropic drugs is the 5-HT6 receptor, GProtein- Coupled Receptor (GPCR) family, displaying seven transmembrane domains. There is considerable interest in how both 5-HT6 receptor agonist and antagonist compounds can have marked procognitive effects.

Methods: An exact structure of the 5-HT6 receptor is not available, so application of powerful methods of (Q)SAR and molecular modelling, which play an essential role in modern drug design, are currently limited to structure-based homology models.

Aqueous Drug Solubility: What Do We Measure, Calculate and QSPR Predict?

Detailed critical analysis of publications devoted to QSPR of aqueous solubility is presented in the review with discussion of four types of aqueous solubility (three different thermodynamic solubilities with unknown solute structure, intrinsic solubility, solubility in physiological media at pH=7.4 and kinetic solubility), variety of molecular descriptors (from topological to quantum chemical), traditional statistical and machine learning methods as well as original QSPR models.

Applications of Multi-Target Computer-Aided Methodologies in Molecular Design of CNS Drugs.

The discovery of drugs for diseases of the central nervous system (CNS) faces high attrition rates in clinical trials. Neural diseases are extremely complex in nature and typically associated with multiple drug targets. A conception of multi-target directed ligands (MTDL), widely applied to the discovery of cancer pharmaceuticals, may be a perspective solution for CNS diseases.

Six global and local QSPR models of aqueous solubility at pH = 7.4 based on structural similarity and physicochemical descriptors.

Aqueous solubility at pH = 7.4 is a very important property for medicinal chemists because this is the pH value of physiological media. The present work describes the application of three different methods (support vector machine (SVM), random forest (RF) and multiple linear regression (MLR)) and three local quantitative structure-property relationship (QSPR) models (regression corrected by nearest neighbours (RCNN), arithmetic mean property (AMP) and local regression property (LoReP)) to construct stable QSPRs with clear mechanistic interpretation.

On the mechanism of substrate/non-substrate recognition by P-glycoprotein.

P-Glycoprotein (P-gp, multi-drug resistance protein, MDR1) plays a gatekeeper role, interfering delivery of multiple pharmaceuticals to the target tissues and cells. We performed Molecular Dynamics (MD) simulations to generate fifty side-chain variants for P-gp (PDB ID: 4Q9H-L) followed by docking of 31 drugs (0.6≤ER≤22.

CNS Multiparameter Optimization Approach: Is it in Accordance with Occam's Razor Principle?

A detailed analysis of the possibility of using the Multiparameter Optimization approach (MPO) for CNS/non-CNS classification of drugs was carried out. This work has shown that MPO descriptors are able to describe only part of chemical transport in the CNS connected with transmembrane diffusion. Hence the "intuitive" CNS MPO approach with arbitrary selection of descriptors and calculations of score functions, search of thresholds of classification, and absence of any chemometric procedures, leads to rather modest accuracy of CNS/non-CNS classification models.

Assessment of the classification abilities of the CNS multi-parametric optimization approach by the method of logistic regression.

Assessment of "CNS drugs/CNS candidates" classification abilities of the multi-parametric optimization (CNS MPO) approach was performed by logistic regression. It was found that the five out of the six separately used physical-chemical properties (topological polar surface area, number of hydrogen-bonded donor atoms, basicity, lipophilicity of compound in neutral form and at pH = 7.4) provided accuracy of recognition below 60%.

[Classification models of structure - P-glycoprotein activity of drugs].

Thirty three classification models of substrate specificity of 177 drugs to P-glycoprotein have been created using of the linear discriminant analysis, random forest and support vector machine methods. QSAR modeling was carried out using 2 strategies. The first strategy consisted in search of all possible combinations from 1÷5 descriptors on the basis of 7 most significant molecular descriptors with clear physico-chemical interpretation.

Physicochemical property profile for brain permeability: comparative study by different approaches.

A comparative study of classification models of brain penetration by different approaches was carried out on a training set of 1000 chemicals and drugs, and an external test set of 100 drugs. Ten approaches were applied in this work: seven medicinal chemistry approaches (including "rule of 5" and multiparameter optimization) and also three SAR techniques: logistic regression (LR), random forest (RF) and support vector machine (SVM). Forty-one different medicinal chemistry descriptors representing diverse physicochemical properties were used in this work.

In silico Prediction of Aqueous Solubility: a Comparative Study of Local and Global Predictive Models.

32 Quantitative Structure-Property Relationship (QSPR) models were constructed for prediction of aqueous intrinsic solubility of liquid and crystalline chemicals. Data sets contained 1022 liquid and 2615 crystalline compounds. Multiple Linear Regression (MLR), Support Vector Machine (SVM) and Random Forest (RF) methods were used to construct global models, and k-nearest neighbour (kNN), Arithmetic Mean Property (AMP) and Local Regression Property (LoReP) were used to construct local models.

Calculation of aqueous solubility of crystalline un-ionized organic chemicals and drugs based on structural similarity and physicochemical descriptors.

Solubilities of crystalline organic compounds calculated according to AMP (arithmetic mean property) and LoReP (local one-parameter regression) models based on structural and physicochemical similarities are presented. We used data on water solubility of 2615 compounds in un-ionized form measured at 25±5 °C. The calculation results were compared with the equation based on the experimental data for lipophilicity and melting point.

Prediction of Acute Rodent Toxicity on the Basis of Chemical Structure and Physicochemical Similarity.

A development of the Arithmetic Mean Toxicity (AMT) approach is presented in this article. Twenty six physicochemical descriptors, calculated by using the HYBOT program, along with molecular weight and lipophilicity were included in the selection of structural and physicochemical neighbours (analogues). Toxicity predictions of 906 chemicals from the REACH Pre-Registration Substance (PRS) list were carried out with the application of six nearest structural neighbours and three pairs of structural/physicochemical neighbours on the basis of molecular polarizability, the sum of negative atomic charges in a molecule, the sum of H-bond acceptor and donor factors and the octanol-water partition coefficient.

Thermodynamic aspects of solubility process of some sulfonamides.

The thermodynamic aspects of solubility process of sulfonamides with the general structures C(6)H(5)-SO(2)NH-C(6)H(4)-R (R=4-NO(2); 4-Cl) and 4-NH(2)-C(6)H(4)-SO(2)NH-C(6)H(4)-R (R=4-NO(2); 4-CN; 4-Cl; 4-OMe; 4-C(2)H(5)) in water, phosphate buffer with pH 7.4 and n-octanol (as phases modeling various drug delivery pathways) were studied using the isothermal saturated method.

Prediction of acute toxicity to mice by the Arithmetic Mean Toxicity (AMT) modelling approach.

A modelling approach based on the structural and physicochemical similarity of chemicals to their nearest neighbours is proposed for toxicity estimation. This approach, called Arithmetic Mean Toxicity (AMT) modelling, is illustrated by means of an AMT model for predicting acute rodent toxicity. The AMT approach uses one or a few pairs of nearest structural neighbours.

Thermodynamics of organic chemical hydration: QSPR models using physicochemical HYBOT descriptors.

Stable and predictive quantitative structure-property relationship (QSPR) models of thermodynamics of chemical hydration (changes in Gibbs energy, DeltaG(air/water), enthalpy, DeltaH(air/water) and entropy DeltaS(air/water)) were obtained on the basis of physicochemical descriptors calculated by the HYBOT program. The structurally diverse training set (n = 151) and test set (n = 37) included 13 mono-functional chemical classes. The applied HYBOT descriptors comprise molecular polarizability alpha (as a volume-related term), the sum of partial negative charges on all atoms in a molecule SigmaQ(-) (as an electrostatic term) and the sum of H-bond acceptor and donor factors SigmaC(a) and SigmaC(d) (as H-bond terms).

Thermodynamic and structural aspects of sulfonamide crystals and solutions.

The crystal structures of three sulfonamides with the general structure 4-NH(2)-C(6)H(4)-SO(2)NH-C(6)H(4/3)-R (R = 4-Et; 4-OMe; 5-Cl-2-Me) have been determined by X-ray diffraction. On the basis of our previous data and the results obtained a comparative analysis of crystal properties was performed: molecular conformational states, packing architecture, and hydrogen bond networks using graph set notations. The thermodynamic aspects of the sulfonamide sublimation process have been studied by investigating the temperature dependence of vapor pressure using the transpiration method.

Sulfonamides as a subject to study molecular interactions in crystals and solutions: sublimation, solubility, solvation, distribution and crystal structure.

Crystal structures of 4-amino-N-(4-chlorophenyl)-benzene-sulfonamide (IV), 4-amino-N-(2,3-dichlorophenyl)-benzene-sulfonamide (V), 4-amino-N-(3,4-dichlorophenyl)-benzene-sulfonamide (VI) and 4-amino-N-(2,5-dichlorophenyl)-benzene-sulfonamide (VII) were solved by X-ray diffraction method. Temperature dependencies of saturated vapour pressure and thermodynamic functions of sublimation process were calculated (IV: delta Gsub298=74.0 kJ mol(-1), delta Hsub298=134.

Physicochemical properties/descriptors governing the solubility and partitioning of chemicals in water-solvent-gas systems. Part 2. Solubility in 1-octanol.

On the basis of octanol solubility data (log S(o)) for 218 structurally diverse solid chemicals it was shown that the exclusive consideration of melting points did not provide satisfactory results in the quantitative prediction of this parameter (s = 0.92). The application of HYBOT physicochemical descriptors separately (s = 0.

Studying thermodynamic aspects of sublimation, solubility and solvation processes and crystal structure analysis of some sulfonamides.

Crystal structures of N-(2-chlorophenyl)-benzene-sulfonamide (I), N-(2,3-dichlorophenyl)-benzene-sulfonamide (II), N-(4-chlorophenyl)-benzene-sulfonamide (III) were solved by X-ray diffraction method. Temperature dependencies of saturated vapor pressure and thermodynamic functions of sublimation process were calculated (I: DeltaG(sub)(298)=50.4kJmol(-1); DeltaH(sub)(298)=114+/-1kJmol(-1); DeltaS(sub)(298)=213+/-3Jmol(-1)K(-1); II: DeltaG(sub)(298)=54.

Physicochemical properties/descriptors governing the solubility and partitioning of chemicals in water-solvent-gas systems. Part 1. Partitioning between octanol and air.

QSPR analyses of a data set containing experimental partition coefficients in the three systems octanol-water, water-gas, and octanol-gas for 98 chemicals have shown that it is possible to calculate any partition coefficient in the system 'gas phase/octanol/water' by three different approaches: (1) from experimental partition coefficients obtained in the corresponding two other subsystems. However, in many cases these data may not be available. Therefore, a solution may be approached (2), a traditional QSPR analysis based on e.

QSPR analysis of the partitioning of vaporous chemicals in a water-gas phase system and the water solubility of liquid and solid chemicals on the basis of fragment and physicochemical similarity and hybot descriptors.

QSPR analyses of the solubility in water of 558 vapors, 786 liquids and 2045 solid organic neutral chemicals and drugs are presented. Simultaneous consideration of H-bond acceptor and donor factors leads to a good description of the solubility of vapors and liquids. A volume-related term was found to have an essential negative contribution to the solubility of liquids.

Quantifying hydrogen bonding in QSAR and molecular modeling.

Quantitative descriptions of hydrogen bonding for use in QSAR and molecular modeling by means of H-bond descriptors have been analyzed in detail in this paper. Ten new H-bond surface and enthalpy integral descriptors were proposed. The usefulness of these new descriptors, as well as previously developed descriptors was verified using a set of 154 drugs for which data for intestinal absorption in humans were available.

Creation of predictive models of aquatic toxicity of environmental pollutants with different mechanisms of action on the basis of molecular similarity and HYBOT descriptors.

Over half of known industrial pollutants have minimal toxic effect, in line with the concept of "baseline toxicity"; such toxicity usually correlates well with lipophilicity. The remainder require additional descriptors in order to model their toxicity by the QSAR approach. Hence, it has not been possible, to date, to develop common stable QSAR models for the toxicity of diverse chemicals with various modes of action on the basis of simple regression relationships.