RESUMEN

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. The utility of SiRMS is demonstrated not only in the standard QSAR/QSPR applications, but also for mixtures, polymers, materials, and other complex systems. In addition to many different types of biological activity (antiviral, antimicrobial, antitumor, psychotropic, analgesic, etc.), toxicity and bioavailability, the review examines the simulation of important properties, such as water solubility, lipophilicity, as well as luminescence, and thermodynamic properties (melting and boiling temperatures, critical parameters, etc.). This review focuses on the stereochemical description of molecules within the simplex approach and details the possibilities of universal molecular stereo-analysis and stereochemical configuration description, along with stereo-isomerization mechanism and molecular fragment "topography" identification.

RESUMEN

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. The most active derivatives (27e, 29e and 35e) against coxsackievirus B1 were tested in vivo in newborn mice experimentally infected with 20 MLD50 of coxsackievirus B1. Compound 29e showed promising in vivo activity (protection index 26% and 4 days lengthening of mean survival time). QSAR analysis of the substituent effects on the in vitro cytotoxicity (CC50) and anti-viral activity of the nitrobenzonitrile derivatives was carried out and adequate QSAR models for the anti-viral activity of the compounds against poliovirus 1 and coxsackievirus B1 were constructed.

Asunto(s)

Antivirales/farmacología , Nitrilos/farmacología , Poliovirus/efectos de los fármacos , Antivirales/síntesis química , Antivirales/química , Línea Celular , Cristalografía por Rayos X , Humanos , Pruebas de Sensibilidad Microbiana , Estructura Molecular , Nitrilos/síntesis química , Nitrilos/química , Relación Estructura-Actividad Cuantitativa

RESUMEN

This paper describes computer-aided design of new anti-viral agents against Vaccinia virus (VACV) potentially acting as nucleic acid intercalators. Earlier obtained experimental data for DNA intercalation affinities and activities against Vesicular stomatitis virus (VSV) have been used to build, respectively, pharmacophore and QSAR models. These models were used for virtual screening of a database of 245 molecules generated around typical scaffolds of known DNA intercalators. This resulted in 12 hits which then were synthesized and tested for antiviral activity against VaV together with 43 compounds earlier studied against VSV. Two compounds displaying high antiviral activity against VaV and low cytotoxicity were selected for further antiviral activity investigations.

Asunto(s)

Antivirales/farmacología , ADN/efectos de los fármacos , Virus de la Estomatitis Vesicular Indiana/efectos de los fármacos , Antivirales/síntesis química , Antivirales/química , Línea Celular , Supervivencia Celular/efectos de los fármacos , Relación Dosis-Respuesta a Droga , Evaluación Preclínica de Medicamentos , Humanos , Pruebas de Sensibilidad Microbiana , Estructura Molecular , Relación Estructura-Actividad Cuantitativa

RESUMEN

This paper describes the Structural and Physico-Chemical Interpretation (SPCI) approach, which is an extension of a recently reported method for interpretation of quantitative structure-activity relationship (QSAR) models. This approach can efficiently be used to reveal structural motifs and the major physicochemical factors affecting the investigated properties. Its efficacy was demonstrated both on the classical Free-Wilson data set and on several data sets with different end points (permeability of the blood-brain barrier, fibrinogen receptor antagonists, acute oral toxicity). Structure-activity patterns extracted from QSAR models with SPCI were in good correspondence with experimentally observed relationships and molecular docking, regardless of the machine learning method used. Comparison of SPCI with the matched molecular pair (MMP) method clearly shows an advantage of our approach over MMP, especially for small or structurally diverse data sets. The developed approach has been implemented in the SPCI software tool with a graphical user interface, which is publicly available at http://qsar4u.com/pages/sirms_qsar.php .

Asunto(s)

Fenómenos Químicos , Biología Computacional/métodos , Relación Estructura-Actividad Cuantitativa , Administración Oral , Animales , Barrera Hematoencefálica/metabolismo , Minería de Datos , Diseño de Fármacos , Oligopéptidos/química , Peptidomiméticos/química , Peptidomiméticos/metabolismo , Peptidomiméticos/farmacología , Peptidomiméticos/toxicidad , Permeabilidad , Ratas , Receptores Fibrinógenos/antagonistas & inhibidores , Programas Informáticos , Pruebas de Toxicidad , Interfaz Usuario-Computador

RESUMEN

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. The second step uses Random Forest technique to create high-efficiency QSPR model. The performance of the model is assessed using cross-validation and external test set prediction. Predictive capacity of developed model is compared with COSMO-RS approximation, which has quantum chemical and thermodynamic foundations. The comparison shows slightly better prediction ability for the QSPR model presented in this publication. © 2016 Wiley Periodicals, Inc.

RESUMEN

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. We demonstrate that contrary to the common perception of QSAR models as "black boxes" they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. We show through several case studies, however, that the mere presence of structural alerts in a chemical, irrespective of the derivation method (expert-based or QSAR-based), should be perceived only as hypotheses of possible toxicological effect. We propose a new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals.

RESUMEN

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Asunto(s)

Algoritmos , Sistema Enzimático del Citocromo P-450/química , Sistema Enzimático del Citocromo P-450/metabolismo , Interacciones Farmacológicas , Modelos Moleculares , Relación Estructura-Actividad Cuantitativa , Bases de Datos Factuales , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Humanos , Modelos Biológicos

RESUMEN

This article describes design, virtual screening, synthesis, and biological tests of novel αIIbß3 antagonists, which inhibit platelet aggregation. Two types of αIIbß3 antagonists were developed: those binding either closed or open form of the protein. At the first step, available experimental data were used to build QSAR models and ligand- and structure-based pharmacophore models and to select the most appropriate tool for ligand-to-protein docking. Virtual screening of publicly available databases (BioinfoDB, ZINC, Enamine data sets) with developed models resulted in no hits. Therefore, small focused libraries for two types of ligands were prepared on the basis of pharmacophore models. Their screening resulted in four potential ligands for open form of αIIbß3 and four ligands for its closed form followed by their synthesis and in vitro tests. Experimental measurements of affinity for αIIbß3 and ability to inhibit ADP-induced platelet aggregation (IC50) showed that two designed ligands for the open form 4c and 4d (IC50 = 6.2 nM and 25 nM, respectively) and one for the closed form 12b (IC50 = 11 nM) were more potent than commercial antithrombotic Tirofiban (IC50 = 32 nM).

Asunto(s)

Inhibidores de Agregación Plaquetaria/química , Inhibidores de Agregación Plaquetaria/farmacología , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/antagonistas & inhibidores , Relación Estructura-Actividad Cuantitativa , Técnicas de Química Sintética , Diseño de Fármacos , Evaluación Preclínica de Medicamentos/métodos , Humanos , Concentración 50 Inhibidora , Modelos Moleculares , Simulación del Acoplamiento Molecular , Oligopéptidos/química , Peptidomiméticos/química , Peptidomiméticos/farmacología , Inhibidores de Agregación Plaquetaria/síntesis química , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/química , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/metabolismo , Bibliotecas de Moléculas Pequeñas/química , Bibliotecas de Moléculas Pequeñas/farmacología

RESUMEN

Many metal oxide nanoparticles are able to cause persistent stress to live organisms, including humans, when discharged to the environment. To understand the mechanism of metal oxide nanoparticles' toxicity and reduce the number of experiments, the development of predictive toxicity models is important. In this study, performed on a series of nanoparticles, the comparative quantitative-structure activity relationship (nano-QSAR) analyses of their toxicity towards E. coli and HaCaT cells were established. A new approach for representation of nanoparticles' structure is presented. For description of the supramolecular structure of nanoparticles the "liquid drop" model was applied. It is expected that a novel, proposed approach could be of general use for predictions related to nanomaterials. In addition, in our study fragmental simplex descriptors and several ligand-metal binding characteristics were calculated. The developed nano-QSAR models were validated and reliably predict the toxicity of all studied metal oxide nanoparticles. Based on the comparative analysis of contributed properties in both models the LDM-based descriptors were revealed to have an almost similar level of contribution to toxicity in both cases, while other parameters (van der Waals interactions, electronegativity and metal-ligand binding characteristics) have unequal contribution levels. In addition, the models developed here suggest different mechanisms of nanotoxicity for these two types of cells.

Asunto(s)

Ensayo de Materiales/métodos , Nanopartículas del Metal/clasificación , Nanopartículas del Metal/toxicidad , Modelos Químicos , Óxidos/toxicidad , Pruebas de Toxicidad/métodos , Células Cultivadas , Biología Computacional/métodos , Escherichia coli , Humanos , Ensayo de Materiales/instrumentación , Nanopartículas del Metal/química , Técnicas Microbiológicas , Óxidos/química , Relación Estructura-Actividad Cuantitativa , Pruebas de Toxicidad/instrumentación

RESUMEN

Quantitative structure-activity relationship modeling is one of the major computational tools employed in medicinal chemistry. However, throughout its entire history it has drawn both praise and criticism concerning its reliability, limitations, successes, and failures. In this paper, we discuss (i) the development and evolution of QSAR; (ii) the current trends, unsolved problems, and pressing challenges; and (iii) several novel and emerging applications of QSAR modeling. Throughout this discussion, we provide guidelines for QSAR development, validation, and application, which are summarized in best practices for building rigorously validated and externally predictive QSAR models. We hope that this Perspective will help communications between computational and experimental chemists toward collaborative development and use of QSAR models. We also believe that the guidelines presented here will help journal editors and reviewers apply more stringent scientific standards to manuscripts reporting new QSAR studies, as well as encourage the use of high quality, validated QSARs for regulatory decision making.

Asunto(s)

Diseño de Fármacos , Modelos Moleculares , Relación Estructura-Actividad Cuantitativa , Péptidos Catiónicos Antimicrobianos/química , Inteligencia Artificial , Mezclas Complejas/química , Bases de Datos Factuales , Historia del Siglo XX , Historia del Siglo XXI , Nanoestructuras/química , Farmacocinética , Teoría Cuántica , Toxicología/métodos

RESUMEN

A series of novel RGD mimetics containing phthalimidine fragment was designed and synthesized. Their antiaggregative activity determined by Born's method was shown to be due to inhibition of fibrinogen binding to αIIbß3. Molecular docking of RGD mimetics to αIIbß3 receptor showed the key interactions in this complex, and also some correlations have been observed between values of biological activity and docking scores. The single crystal X-ray data were obtained for five mimetics.

Asunto(s)

Materiales Biomiméticos/química , Isoindoles/química , Oligopéptidos/química , Ftalimidas/química , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/química , Sitios de Unión , Materiales Biomiméticos/metabolismo , Materiales Biomiméticos/farmacología , Cristalografía por Rayos X , Fibrinógeno/antagonistas & inhibidores , Fibrinógeno/metabolismo , Humanos , Isoindoles/metabolismo , Isoindoles/farmacología , Ligandos , Modelos Moleculares , Simulación del Acoplamiento Molecular , Estructura Molecular , Oligopéptidos/metabolismo , Oligopéptidos/farmacología , Ftalimidas/metabolismo , Ftalimidas/farmacología , Agregación Plaquetaria/efectos de los fármacos , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/antagonistas & inhibidores , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/metabolismo , Unión Proteica

RESUMEN

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., it can be applied to any QSAR/QSPR model irrespective of chemical descriptors and machine learning methods applied. This universality was achieved by using only the information obtained from substructures of the compounds of interest to interpret model outcomes. Reliability of the offered approach was confirmed by the results of three case studies, including end-points of different types (continuous and binary classification) and nature (solubility, mutagenicity, and inhibition of Transglutaminase 2), various fragment and whole-molecule descriptors (Simplex and Dragon), and multiple modeling techniques (partial least squares, random forest, and support vector machines). We compared the global contributions of molecular fragments obtained using our methodology with known SAR rules derived experimentally. In all cases high concordance between our interpretation and results published by others was observed. Although the proposed interpretation approach could be easily extended to any type of descriptors, we would recommend using Simplex descriptors to achieve a larger variety of investigated molecular fragments. The developed approach is a good tool for interpretation of such "black box" models like random forest, neural networks, etc. Analysis of fragment global contributions and their deviation across a dataset could be useful for the identification of key fragments and structural alerts. This information could be helpful to maximize the positive influence of structural surroundings on the given fragment and to decrease the negative effects.

RESUMEN

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. Various mixture descriptors are used for the modeling of different endpoints. However, these descriptors have certain disadvantages, such as applicability only to 1 : 1 binary mixtures, and additive nature. The field of QSAR of mixtures is still under development, and existing efforts could be considered as a foundation for future approaches and studies. The usage of non-additive mixture descriptors, which are sensitive to interaction effects, in combination with best practices of QSAR model development (e.g., thorough data collection and curation, rigorous external validation, etc.) will significantly improve the quality of QSAR studies of mixtures.

RESUMEN

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. Developed models are adequate and successfully validated with external test sets. Proposed models have clear interpretation due to the use of simplex representation of molecular structure and predict the LogKow values with the accuracy of the best modern models. Thus QSPR models proposed in this study represent powerful and easy-to use virtual screening tool that can be recommended for prediction of octanol-water partition coefficient.

RESUMEN

The novel RGD mimetics with phthalimidine central fragment were synthesized with the use of 4-piperidine-4-yl-butyric, 4-piperidine-4-yl-benzoic, 4-piperazine-4-yl-benzoic and 1,2,3,4-tetrahydroisoquinoline-7-carboxylic acids as surrogates of Arg motif. The synthesized compounds potently inhibited platelet aggregation in vitro and blocked FITC-Fg binding to α(IIb)ß(3) integrin in a suspension of washed human platelets. The key α(IIb)ß(3) protein-ligand interactions were determined in docking experiments.

Asunto(s)

Diseño de Fármacos , Ftalimidas/síntesis química , Inhibidores de Agregación Plaquetaria/síntesis química , Inhibidores de Agregación Plaquetaria/farmacología , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/antagonistas & inhibidores , Receptores Fibrinógenos/antagonistas & inhibidores , Arginina/análogos & derivados , Arginina/metabolismo , Plaquetas/metabolismo , Evaluación Preclínica de Medicamentos , Fibrinógeno/metabolismo , Fluoresceína-5-Isotiocianato/metabolismo , Humanos , Isoquinolinas/química , Isoquinolinas/metabolismo , Ligandos , Oligopéptidos/química , Oligopéptidos/metabolismo , Inhibidores de Agregación Plaquetaria/química , Complejo GPIIb-IIIa de Glicoproteína Plaquetaria/metabolismo , Unión Proteica , Receptores Fibrinógenos/metabolismo , Programas Informáticos , Estereoisomerismo , Relación Estructura-Actividad , Tirofibán , Tirosina/análogos & derivados , Tirosina/química , Tirosina/metabolismo

RESUMEN

BACKGROUND: Antiviral drugs are urgently needed for the treatment of acute and chronic diseases caused by enteroviruses such as coxsackievirus B3 (CVB3). The main goal of this study is quantitative structure-activity relationship (QSAR) analysis of anti-CVB3 activity (clinical CVB3 isolate 97927 [log IC50, µM]) and investigation of the selectivity of 25 ([biphenyloxy]propyl)isoxazoles, followed by computer-aided design and virtual screening of novel active compounds. DISCUSSION: The 2D QSAR obtained models are quite satisfactory (R(2) = 0.84-0.99, Q(2) = 0.76-0.92, R(2)(ext) = 0.62-0.79). Compounds with high antiviral activity and selectivity have to contain 5-trifluoromethyl-[1,2,4]oxadiazole or 2,4-difluorophenyl fragments. Insertion of 2,5-dimethylbenzene, napthyl and especially biphenyl substituents into investigated compounds substantially decreases both their antiviral activity and selectivity. Several compounds were proposed as a result of design and virtual screening. A high level of activity of 2-methoxy-1-phenyl-1H-imidazo[4,5-c]pyridine (sm428) was confirmed experimentally. CONCLUSION: Simplex representation of molecular structure allows successful QSAR analysis of anti-CVB3 activity of ([biphenyloxy]propyl)isoxazole derivatives. Two possible ways of battling CVB3 are considered as a future perspective.

Asunto(s)

Antivirales/química , Antivirales/farmacología , Infecciones por Coxsackievirus/tratamiento farmacológico , Enterovirus Humano B/efectos de los fármacos , Isoxazoles/química , Isoxazoles/farmacología , Relación Estructura-Actividad Cuantitativa , Diseño de Fármacos , Células HeLa , Humanos , Modelos Moleculares

RESUMEN

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. Such information can be used for the design of new compounds with a predefined property value. The proposed measure of descriptor contributions is not an alternative to the importance of Breiman's variable, but it characterizes the contribution of a particular explanatory variable to the calculated response value.

RESUMEN

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 performance of DM metrics that have been based on the standard deviation within an ensemble of QSAR models. The current study applies such analysis to 30 QSAR models for the Ames mutagenicity data set that were previously reported within the 2009 QSAR challenge. We demonstrate that the DMs based on an ensemble (consensus) model provide systematically better performance than other DMs. The presented approach identifies 30-60% of compounds having an accuracy of prediction similar to the interlaboratory accuracy of the Ames test, which is estimated to be 90%. Thus, the in silico predictions can be used to halve the cost of experimental measurements by providing a similar prediction accuracy. The developed model has been made publicly available at http://ochem.eu/models/1 .

Asunto(s)

Benchmarking/métodos , Clasificación/métodos , Pruebas de Mutagenicidad/métodos , Relación Estructura-Actividad Cuantitativa , Pruebas de Mutagenicidad/normas , Análisis de Componente Principal

RESUMEN

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. SiRMS methodology was employed to develop PLS models based on 135 training compounds and predictive accuracy was tested for 155 compounds selected for that purpose. The use of descriptors calculated only from the 2D level of representation of molecular structure produces a well-fitted and robust QSPR model (R(2)=0.90; Q(2)=0.87). Predictive ability for the model produced in this study on external test set (R(test)(2)=0.81) is comparable to the predictive ability of EPI Suite 4.0. Consensus solubility predictions using SiRMS and EPI models for 25 compounds of military interest (not included into the training set) have been completed.

Asunto(s)

Monitoreo del Ambiente/métodos , Sustancias Explosivas/química , Modelos Químicos , Relación Estructura-Actividad Cuantitativa , Azocinas/química , Estructura Molecular , Nitrocompuestos/química , Oxazinas/química , Quinolinas/química , Solubilidad

RESUMEN

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). The main advantages of SiRMS are consideration of the different physical-chemical properties of atoms, high adequacy and good interpretability of models obtained and clear procedures for molecular design. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the basis of directed drug design was validated by subsequent synthetic and biological experiments. The SiRMS approach is realized as the complex of the computer program 'HiT QSAR', which is available on request.

Asunto(s)

Antivirales/química , Antivirales/farmacología , Diseño de Fármacos , Relación Estructura-Actividad Cuantitativa , Virosis/tratamiento farmacológico , Animales , Humanos , Modelos Biológicos , Modelos Moleculares