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1.
Biomed Res Int ; 2020: 5324560, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-33029513

RESUMO

The ongoing global pandemic caused by the human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected millions of people and claimed hundreds of thousands of lives. The absence of approved therapeutics to combat this disease threatens the health of all persons on earth and could cause catastrophic damage to society. New drugs are therefore urgently required to bring relief to people everywhere. In addition to repurposing existing drugs, natural products provide an interesting alternative due to their widespread use in all cultures of the world. In this study, alkaloids from Cryptolepis sanguinolenta have been investigated for their ability to inhibit two of the main proteins in SARS-CoV-2, the main protease and the RNA-dependent RNA polymerase, using in silico methods. Molecular docking was used to assess binding potential of the alkaloids to the viral proteins whereas molecular dynamics was used to evaluate stability of the binding event. The results of the study indicate that all 13 alkaloids bind strongly to the main protease and RNA-dependent RNA polymerase with binding energies ranging from -6.7 to -10.6 kcal/mol. In particular, cryptomisrine, cryptospirolepine, cryptoquindoline, and biscryptolepine exhibited very strong inhibitory potential towards both proteins. Results from the molecular dynamics study revealed that a stable protein-ligand complex is formed upon binding. Alkaloids from Cryptolepis sanguinolenta therefore represent a promising class of compounds that could serve as lead compounds in the search for a cure for the corona virus disease.


Assuntos
Alcaloides/farmacologia , Betacoronavirus/efeitos dos fármacos , Infecções por Coronavirus/tratamento farmacológico , Cryptolepis/química , Pneumonia Viral/tratamento farmacológico , Proteínas Virais/antagonistas & inibidores , Alcaloides/química , Antivirais/química , Antivirais/farmacologia , Betacoronavirus/enzimologia , Simulação por Computador , Infecções por Coronavirus/virologia , Cisteína Endopeptidases , Avaliação Pré-Clínica de Medicamentos , Humanos , Alcaloides Indólicos/química , Alcaloides Indólicos/farmacologia , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Pandemias , Pneumonia Viral/virologia , Relação Quantitativa Estrutura-Atividade , Quinolinas/química , Quinolinas/farmacologia , RNA Replicase/antagonistas & inibidores , Proteínas não Estruturais Virais/antagonistas & inibidores
2.
SAR QSAR Environ Res ; 31(10): 717-739, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32930630

RESUMO

Aedes aegypti is the primary vector of several infectious viruses that cause yellow, dengue, chikungunya, and Zika fevers. Recently, plant-derived products have been tested as safe and eco-friendly larvicides against Ae. aegypti. The present study aimed to improve QSAR models for 62 larvicidal phytocompounds against Ae. aegypti via the Monte Carlo method based on the index of the ideality of correlation (IIC) criterion. The representation of structures was done with SMILES. Three splits were prepared randomly and three QSAR models were constructed using IIC target function. The molecular descriptors were selected from SMILES descriptors and the hydrogen-filled molecular graphs. The predictability of three models was evaluated on the validation sets, the r 2 of which was 0.9770, 0.8660, and 0.8565 for models 1 to 3, respectively. The statistical results of three randomized splits indicated that robust, simple, predictive, and reliable models were obtained for different sets. From the modelling results, important descriptors were identified to enhance and reduce the larvicidal activity of compounds. Based on the identified important descriptors, some new structures of larvicidal compounds were proposed. The larvicidal activity of novel molecules designed further was supported by docking studies. Using the simple QSAR model, one can predict pLC50 of new similarity larvicidal phytocompounds.


Assuntos
Aedes/efeitos dos fármacos , Inseticidas/farmacologia , Mosquitos Vetores/efeitos dos fármacos , Relação Quantitativa Estrutura-Atividade , Aedes/crescimento & desenvolvimento , Animais , Inseticidas/química , Larva/efeitos dos fármacos , Mosquitos Vetores/crescimento & desenvolvimento
3.
Anticancer Res ; 40(9): 4885-4894, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32878776

RESUMO

AIM: The aim of this study was to investigate the antitumor potential of guaiazulene-3-carboxylate derivatives against oral malignant cells. MATERIALS AND METHODS: Twelve guaiazulene-3-carboxylate derivatives were synthesized by introduction of either with alkyl group [1-5], alkoxy group [6, 7], hydroxyl group [8, 9] or primary amine [10-12] at the end of sidechains. Tumor-specificity (TS) was calculated by the ratio of mean 50% cytotoxic concentration (CC50) against 3 human oral mesenchymal cell lines to that against 4 human oral squamous cell carcinoma (OSCC) cell lines. Potency-selectivity expression (PSE) was calculated by dividing TS value by CC50value against OSCC cell lines. Cell cycle analysis was performed by cell sorter. RESULTS: [6, 7] showed the highest TS and PSE values, and induced the accumulation of both subG1 and G2/M cell populations in HSC-2 OSCC cells. Quantitative structure-activity relationship analysis demonstrated that their tumor-specificity was correlated with chemical descriptors that explain the 3D shape, electric state and ionization potential. CONCLUSION: Alkoxyl guaiazulene-3-carboxylates [6, 7] can be potential candidates of lead compound for developing novel anticancer drugs.


Assuntos
Antineoplásicos/química , Antineoplásicos/farmacologia , Azulenos/química , Azulenos/farmacologia , Carcinoma de Células Escamosas/tratamento farmacológico , Neoplasias Bucais/tratamento farmacológico , Sesquiterpenos de Guaiano/química , Sesquiterpenos de Guaiano/farmacologia , Antineoplásicos/síntese química , Apoptose/efeitos dos fármacos , Azulenos/síntese química , Carcinoma de Células Escamosas/patologia , Ciclo Celular/efeitos dos fármacos , Linhagem Celular , Linhagem Celular Tumoral , Sobrevivência Celular/efeitos dos fármacos , Humanos , Estrutura Molecular , Neoplasias Bucais/patologia , Relação Quantitativa Estrutura-Atividade , Sesquiterpenos de Guaiano/síntese química
4.
Ecotoxicol Environ Saf ; 203: 111046, 2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-32888614

RESUMO

Agricultural pesticides serve as effective controls of unwanted weeds and pests. However, these same chemicals can exert toxic effects in non-target organisms. To determine chemical modes of action, the toxicity ratio (TR) and critical body residues (CBRs) of 57 pesticides were calculated for Daphnia magna. Results showed that the CBR values of inert compounds were close to a constant while the CBR values of pesticides varied over a wider range. Although herbicides are categorized as specifically-acting compounds to plants, herbicides did not exhibit excess toxicity to Daphnia magna and were categorized as inert compounds with an average logTR = 0.41, which was less than a threshold of one. Conversely, fungicides and insecticides exhibited strong potential for toxic effects to Daphnia magna with an average logTR >2. Many of these chemicals act via disruption of the nervous, respiratory, or reproductive system, with high ligand-receptor binding activity which leads to higher toxicity for Daphnia magna. Molecular docking using acetylcholinesterase revealed that fungicides and insecticides bind more easily with the biological macromolecule when compared with inert compounds. Quantitative structure-activity relationship (QSAR) analysis revealed that the toxicity of fungicides was mainly dependent upon the heat of formation and polar surface area, while the toxicity of insecticides was more related to hydrogen-bond properties. This comprehensive analysis reveals that there are specific differences in toxic mechanisms between fungicides and insecticides. These results are useful for determining relative risk associated with pesticide exposure to aquatic crustaceans, such as Daphnia magna.


Assuntos
Daphnia/efeitos dos fármacos , Modelos Biológicos , Praguicidas/química , Praguicidas/toxicidade , Poluentes Químicos da Água/química , Poluentes Químicos da Água/toxicidade , Acetilcolinesterase/metabolismo , Animais , Daphnia/metabolismo , Relação Dose-Resposta a Droga , Fungicidas Industriais/química , Fungicidas Industriais/toxicidade , Herbicidas/química , Herbicidas/toxicidade , Ligação de Hidrogênio , Inseticidas/química , Inseticidas/toxicidade , Simulação de Acoplamento Molecular , Resíduos de Praguicidas/metabolismo , Relação Quantitativa Estrutura-Atividade
5.
Ecotoxicol Environ Saf ; 203: 110946, 2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-32888619

RESUMO

Zebrafish embryos are highly sensitive to toxicant exposure and have been used to evaluate the potential eco-toxicity caused by organic pollutants in the aquatic environment. This study was to develop four quantitative structure-activity relationship (QSAR) models based on norm descriptors for acute toxicity of different exposure times toward zebrafish embryo of organic compounds with various structures. Norm descriptors were obtained by calculating the norm index of the atomic distribution matrix, which was composed of atomic spatial distribution and atomic properties. These norm index-based QSAR models presented satisfactory results with R2 of 0.8549, 0.9162, 0.8335 and 0.8119 for 48, 96, 120 and 132 h, respectively. Validation results including cross validation, external validation, Y-randomized test and applicability domain analysis indicated that the proposed models were stable, robust and reliable. Accordingly, these norm descriptors might be effective in predicting the acute toxicity of various organics to zebrafish embryos, which might be useful for evaluating the potential hazards of organic pollutants to aquatic environment.


Assuntos
Embrião não Mamífero/efeitos dos fármacos , Compostos Orgânicos , Relação Quantitativa Estrutura-Atividade , Peixe-Zebra , Animais , Compostos Orgânicos/química , Compostos Orgânicos/toxicidade , Testes de Toxicidade Aguda
6.
SAR QSAR Environ Res ; 31(10): 761-784, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32867537

RESUMO

The free COOH group of conventional NSAIDs is a structural feature for non-selective cyclooxygenase (COX) inhibition and the molecular cause of their gastrointestinal (GI) toxicity. In this context, an in house database of synthesizable ester prodrugs of some well-known NSAIDs was developed by combining their -COOH group with -OH of a newly identified antioxidant 4-(1H-benzo[d]imidazol-2-yl)phenol (BZ). The antioxidant potential of BZ was unveiled through in silico PASS prediction and in vitro/in vivo evaluation. The in house database of NSAIDs-BZ prodrugs was first subjected to screening with our previously reported pharmacophore models of hCES1 (AAHRR.430) and hCES2 (AHHR.21) for determining hydrolytic susceptibility. Biotransformation behaviour of screened prodrugs was then assessed by using QM/MM and sterimol parameterization, followed by ADMET calculations to predict the drug likeness. On the basis of in silico results, five prodrugs were duly synthesized and the best three were subject to the in vivo evaluation for their anti-inflammatory, analgesic, antioxidant activities, and ulcerogenic index. Among these prodrugs, BN2 and BN5 displayed better anti-inflammatory and analgesics potential in comparison to their parent drugs. All the prodrugs were found to be gastro sparing in the rat model and significantly improved the levels of oxidative stress biomarkers in both blood plasma as well as gastric homogenate.


Assuntos
Anti-Inflamatórios não Esteroides/síntese química , Imidazóis/química , Fenóis/química , Pró-Fármacos/síntese química , Relação Quantitativa Estrutura-Atividade , Simulação por Computador
7.
SAR QSAR Environ Res ; 31(10): 785-801, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32878491

RESUMO

Reviewing the toxicological literature for over the past decades, the key elements of QSAR modelling have been the mechanisms of toxic action and chemical classes. As a result, it is often hard to design an acceptable single model for a particular endpoint without clustering compounds. The main aim here was to develop a Pass-Pass Quantitative Structure-Activity-Activity Relationship (PP QSAAR) model for direct prediction of the toxicity of a larger set of compounds, combing the application of an already predicted model for another species, and molecular descriptors. We investigated a large acute toxicity data set of five aquatic organisms, fish, Daphnia magna, and algae from the VEGA-Hub, as well as Tetrahymena pyriformis and Vibrio fischeri. The statistical quality of the models encouraged us to consider this alternative for the prediction of toxicity using interspecies extrapolation QSAAR models without regard to the toxicity mechanism or chemical class. In the case of algae, the use of activity values from a second species did not improve the models. This can be attributed to the weak interspecies relationships, due to different aquatic toxicity mechanisms in species.


Assuntos
Organismos Aquáticos/efeitos dos fármacos , Relação Quantitativa Estrutura-Atividade , Testes de Toxicidade Aguda , Poluentes Químicos da Água/toxicidade , Aliivibrio fischeri/efeitos dos fármacos , Animais , Daphnia/efeitos dos fármacos , Peixes , Regulamentação Governamental , Microalgas/efeitos dos fármacos , Modelos Químicos , Medição de Risco , Tetrahymena pyriformis/efeitos dos fármacos
8.
SAR QSAR Environ Res ; 31(9): 697-715, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32878494

RESUMO

Azo dyes are a group of chemical moieties joined by azo (-N=N-) group with potential usefulness in different industrial applications. But these dyes are not devoid of hazardous consequence because of poor affinity for the fibre and discharge into the water stream. The chemical aspects of 72 azo dyes towards cellulose fibre in terms of their affinity by QSPR have been explored in the present work. We have employed two approaches, namely balance of correlation without IIC (TF1) and balance of correlation with IIC (TF2), to generate 16 QSAR models from 8 splits. The determination coefficient of calibration and validation set was found higher when the QSPR models were developed using the index of ideality correlation (IIC) parameter (TF2). The model developed with TF2 for split 3 was considered as a prominent model because the determination coefficient of the validation set was maximum (r 2 = 0.9468). The applicability domain (AD) was also analysed based on 'statistical defect', d(A) for a SMILES attribute. The mechanistic interpretation was done by identifying the SMILES attributes responsible for the promoter of endpoint increase and promoter of endpoint decrease. These SMILES attributes were applied to design 15 new dyes with higher affinity for cellulose fibre.


Assuntos
Compostos Azo/química , Celulose/química , Corantes/química , Relação Quantitativa Estrutura-Atividade , Adsorção , Simulação por Computador , Método de Monte Carlo
9.
SAR QSAR Environ Res ; 31(10): 741-759, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32892643

RESUMO

The human immunodeficiency virus is a lethal pathology considered as a worldwide problem. The search for new strategies for the treatment of this disease continues to be a great challenge in the scientific community. In this study, a series of 107 derivatives of 1-[(2-hydroxyethoxy)methyl]-6-(phenylthio)thymine, previously evaluated experimentally against HIV-I reverse transcriptase, was used to model antiretroviral activity. A model of linear regression, implemented in the QSARINS software, was developed with a genetic algorithm for variable selection. The fit of its parameters was good and exhaustive validation, according to the OECD regulatory principles, was performed. Also, the applicability domain was established. In addition, its robustness (r 2 = 0.84), stability (Q 2 LOO = 0.81; Q 2 LMO = 0.80) and good predictive power (r 2 EXT = 0.85) is proved. So, it was used to predict the antiretroviral activity of eight compounds obtained by rational drug design. Finally, it can be affirmed that the proposed tools allow the rapid and economic identification of potential antiretroviral drugs.


Assuntos
Antirretrovirais/química , Relação Quantitativa Estrutura-Atividade , Timina/análogos & derivados , Modelos Químicos , Organização para a Cooperação e Desenvolvimento Econômico/normas , Timina/química
10.
Ecotoxicol Environ Saf ; 202: 110936, 2020 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-32800219

RESUMO

Developmental toxicity refers to the occurrence of adverse effects on a developing organism as a consequence of exposure to hazardous chemicals. The assessment of developmental toxicity has become relevant to the safety assessment process of chemicals. The zebrafish embryo developmental toxicology assay is an emerging test used to screen the teratogenic potential of chemicals and it is proposed as a promising test to replace teratogenic assays with animals. Supported by the increased availability of data from this test, the developmental toxicity assay with zebrafish has become an interesting endpoint for the in silico modelling. The purpose of this study was to build up quantitative structure-activity relationship (QSAR) models. In this work, new in silico models for the evaluation of developmental toxicity were built using a well-defined set of data from the ToxCastTM Phase I chemical library on the zebrafish embryo. Categorical and continuous QSAR models were built by gradient boosting machine learning and the Monte Carlo technique respectively, in accordance with Organization for Economic Co-operation and Development principles and their statistical quality was satisfactory. The classification model reached balanced accuracy 0.89 and Matthews correlation coefficient 0.77 on the test set. The regression model reached correlation coefficient R2 0.70 in external validation and leave-one-out cross-validated Q2 0.73 in internal validation.


Assuntos
Embrião não Mamífero/efeitos dos fármacos , Testes de Toxicidade/métodos , Poluentes Químicos da Água/toxicidade , Animais , Simulação por Computador , Substâncias Perigosas , Aprendizado de Máquina , Relação Quantitativa Estrutura-Atividade , Teratogênios , Peixe-Zebra/embriologia
11.
SAR QSAR Environ Res ; 31(9): 643-654, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32847369

RESUMO

A quantitative structure-activity relationship (QSAR) model was built from a dataset of 54 peptide-type compounds as SARS-CoV inhibitors. The analysis was executed to identify prominent and hidden structural features that govern anti-SARS-CoV activity. The QSAR model was derived from the genetic algorithm-multi-linear regression (GA-MLR) methodology. This resulted in the generation of a statistically robust and highly predictive model. In addition, it satisfied the OECD principles for QSAR validation. The model was validated thoroughly and fulfilled the threshold values of a battery of statistical parameters (e.g. r 2 = 0.87, Q 2 loo = 0.82). The derived model is successful in identifying many atom-pairs as important structural features that govern the anti-SARS-CoV activity of peptide-type compounds. The newly developed model has a good balance of descriptive and statistical approaches. Consequently, the present work is useful for future modifications of peptide-type compounds for SARS-CoV and SARS-CoV-2 activity.


Assuntos
Antivirais , Betacoronavirus/efeitos dos fármacos , Peptídeos , Relação Quantitativa Estrutura-Atividade , Antivirais/química , Antivirais/farmacologia , Betacoronavirus/enzimologia , Cisteína Endopeptidases , Concentração Inibidora 50 , Modelos Lineares , Estrutura Molecular , Peptídeos/química , Peptídeos/farmacologia , Proteínas não Estruturais Virais/antagonistas & inibidores
12.
J Chromatogr A ; 1628: 461439, 2020 Sep 27.
Artigo em Inglês | MEDLINE | ID: mdl-32822979

RESUMO

Numerous structurally different amides and imides including succinimide derivatives exhibit diverse bioactive potential. The development of new compounds requires rationalization in the design in order to provide structural changes that guarantee favorable physico-chemical properties, pharmacological activity and safety. In the present research, a comprehensive study with comparison of the chromatographic lipophilicity and other physico-chemical properties of five groups of 1-arylsuccinimide derivatives was conducted. The chemometric analysis of their physico-chemical properties was carried out by using unsupervised (hierarchical cluster analysis and principal component analysis) and supervised pattern recognition methods (linear discriminant analysis), while the correlations between the in silico molecular features and chromatographic lipophilicity were examined applying linear and non-linear Quantitative Structure-Retention Relationship (QSRR) approaches. The main aim of the conducted research was to determine similarities and dissimilarities among the studied 1-arylsuccinimides, to point out the molecular features which have significant influence on their lipophilicity, as well as to establish high-quality QSRR models which can be used in prediction of chromatographic lipophilicity of structurally similar 1-arylsuccinimides. This study is a continuation of analysis and determination of the physico-chemical properties of 1-arylsuccinimides which could be important guidelines in further in vitro and eventually in vivo studies of their biological potential.


Assuntos
Técnicas de Química Analítica/métodos , Cromatografia em Camada Delgada , Relação Quantitativa Estrutura-Atividade , Solventes/química , Succinimidas/química , Análise por Conglomerados , Simulação por Computador , Análise de Componente Principal
13.
SAR QSAR Environ Res ; 31(9): 655-675, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32799684

RESUMO

We report new consensus models estimating acute toxicity for algae, Daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSEext = 0.56-0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/ColorAtom utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracy and data coverage. Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending the applicability domain and relevance for application in an industrial context. Generated models and collected public data are made freely available.


Assuntos
Daphnia/efeitos dos fármacos , Peixes , Microalgas/efeitos dos fármacos , Relação Quantitativa Estrutura-Atividade , Testes de Toxicidade Aguda , Poluentes Químicos da Água/toxicidade , Animais , Máquina de Vetores de Suporte
14.
SAR QSAR Environ Res ; 31(9): 677-695, 2020 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-32854545

RESUMO

A set of 23 steroidal 1,2,4,5-tetraoxane analogues were studied using quantum-chemical method (B3LYP/6-31 G*) and multivariate analyses (PCA, HCA, KNN and SIMCA) in order to calculate the properties and correlate them with antimalarial activity (log RA) against Plasmodium falciparum clone D-6 from Sierra Leone. PCA results indicated 99.94% of the total variance and it was possible to divide the compounds into two classes: less and more active. Descriptors responsible for separating were: highest occupied molecular orbital energy (HOMO), bond length (O1-O2), Mulliken electronegativity (χ) and Bond information content (BIC0). We use HCA, KNN and SIMCA to explain relationships between molecular properties and biological activity of a training set and to predict antimalarial activity (log RA) of 13 compounds (#24-36) with unknown biological activity. We apply molecular docking simulations to identify intermolecular interactions with a selected biological target. The results obtained in multivariate analysis aided in the understanding of the activity of the new compound's design (#24-36). Thus, through chemometric analyses and docking molecular study, we propose theoretical synthetic routes for the most promising compounds 28, 30, 32 and 36 that can proceed to synthesis steps and in vitro and in vivo assays.


Assuntos
Antimaláricos/química , Desenho de Fármacos , Plasmodium falciparum/efeitos dos fármacos , Tetraoxanos/química , Simulação de Acoplamento Molecular , Relação Quantitativa Estrutura-Atividade
15.
Aquat Toxicol ; 227: 105589, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32841884

RESUMO

Pesticides have an impact on the aquatic environment, with ecological effects. The regulation of this impact is of key importance. One of the components of the planning of agricultural and industrial activities is the development of databases and models in order to identify substances that may cause damage. In this study, a quantitative structure-activity relationship (QSAR) approach was established for the prediction of acute toxicity toward rainbow trout of various pesticides. The so-called index of ideality of correlation is the main component of this approach. The validation of this approach has been carried out with three random splits into the training and validation sets. The range of statistical quality of models obtained here for the validation set is R2 = [0.81-0.86] and RMSE = [0.55-0.65].


Assuntos
Modelos Teóricos , Oncorhynchus mykiss , Praguicidas/toxicidade , Poluentes Químicos da Água/toxicidade , Animais , Bases de Dados Factuais , Método de Monte Carlo , Praguicidas/química , Relação Quantitativa Estrutura-Atividade , Poluentes Químicos da Água/química
16.
BMC Bioinformatics ; 21(1): 309, 2020 Jul 14.
Artigo em Inglês | MEDLINE | ID: mdl-32664863

RESUMO

BACKGROUND: Despite continued efforts using chemical similarity methods in virtual screening, currently developed approaches suffer from time-consuming multistep procedures and low success rates. We recently developed a machine learning-based chemical binding similarity model considering common structural features from molecules binding to the same, or evolutionarily related targets. The chemical binding similarity measures the resemblance of chemical compounds in terms of binding site similarity to better describe functional similarities that arise from target binding. In this study, we have shown how the chemical binding similarity could be used in virtual screening together with the conventional structure-based methods. RESULTS: The chemical binding similarity, receptor-based pharmacophore, chemical structure similarity, and molecular docking methods were evaluated to identify an effective virtual screening procedure for desired target proteins. When we tested the chemical binding similarity method with test sets of 51 kinases, it outperformed the traditional structural similarity-based methods as well as structure-based methods, such as molecular docking and receptor-based pharmacophore modeling, in terms of finding active compounds. We further validated the results by performing virtual screening (using the chemical binding similarity and receptor-based pharmacophore methods) against a completely blind dataset for mitogen-activated protein kinase kinase 1 (MEK1), ephrin type-B receptor 4 (EPHB4) and wee1-like protein kinase (WEE1). The in vitro kinase binding assay confirmed that 6 out of 13 (46.2%) for MEK1 and 2 out of 12 (16.7%) for EPHB4 were newly identified only by the chemical binding similarity model. CONCLUSIONS: We report that the virtual screening results could further be improved by combining the chemical binding similarity model with 3D-QSAR pharmacophore and molecular docking models. Not only the new inhibitors are identified in this study, but also many of the identified molecules have low structural similarity scores against already reported inhibitors and that show the revelation of novel scaffolds.


Assuntos
Simulação de Acoplamento Molecular , Relação Quantitativa Estrutura-Atividade , Área Sob a Curva , Sítios de Ligação , Humanos , Aprendizado de Máquina , Compostos Orgânicos/química , Compostos Orgânicos/metabolismo , Preparações Farmacêuticas/química , Preparações Farmacêuticas/metabolismo , Ligação Proteica , Proteínas Quinases/química , Proteínas Quinases/metabolismo , Curva ROC
17.
SAR QSAR Environ Res ; 31(8): 585-596, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32613864

RESUMO

The n-octanol/buffer solution distribution coefficient (or n-octanol/water partition coefficient) is of critical importance for measuring lipophilicity of drug candidates. After 4885 molecular descriptor generation, 15 molecular descriptors were selected to develop quantitative structure-property relationship (QSPR) models for distribution coefficients at pH 7.4 (log D 7.4) of a large data set consisting of 1043 organic compounds, which was divided into a training set (600 compounds) and a test set (443 compounds). Support vector machine (SVM) based on genetic algorithm was used to develop a model for log D 7.4 that has coefficient of determination r 2 of 0.919 for the training set and 0.893 for the test set. The results suggest that the SVM model is accurate in predicting log D 7.4.


Assuntos
Compostos Orgânicos/química , Relação Quantitativa Estrutura-Atividade , Máquina de Vetores de Suporte
18.
SAR QSAR Environ Res ; 31(6): 457-475, 2020 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-32627677

RESUMO

In silico methods are often used for predicting pharmacokinetic properties of drugs due to their simplicity and cost-effectiveness. This study evaluates the penetration of 83 active pharmaceutical ingredients into human breast milk with an experimental milk-to-plasma ratio (M/P) obtained from the literature. Multiple linear regression (MLR), partial least squares (PLS) and random forest (RF) regression methods were compared to uncover the relationship between physicochemical, pharmacokinetic and membrane crossing properties of active pharmaceutical ingredients (APIs) using their rapid reference measurement value (Rf values), thin-layer chromatography (TLC) data from albumin-impregnated plates. Molecular descriptors of APIs proven to be important for their crossing into breast milk, including protein binding, ionisation state and lipophilicity and TLC data, have been included in the development of the prediction models. The best regression results were achieved by MLR (r 2 = 0.83 and r 2 = 0.86, n = 28) and RF (r 2 = 0.85, n = 58). In addition, the discriminant function analysis (DFA) was performed on acidic, basic and neutral drugs separately and showed a prediction accuracy of 93%, with M/P included as the discriminating variable.


Assuntos
Análise dos Mínimos Quadrados , Modelos Lineares , Leite Humano/química , Preparações Farmacêuticas/metabolismo , Relação Quantitativa Estrutura-Atividade , Preparações Farmacêuticas/química
19.
SAR QSAR Environ Res ; 31(8): 571-583, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32628042

RESUMO

One of the most challenging issues when facing a Quantitative structure-activity relationship (QSAR) classification model is to deal with the descriptor selection. Penalized methods have been adapted and have gained popularity as a key for simultaneously performing descriptor selection and QSAR classification model estimation. However, penalized methods have drawbacks such as having biases and inconsistencies that make they lack the oracle properties. This paper proposes an adaptive penalized logistic regression (APLR) to overcome these drawbacks. This is done by employing a ratio (BWR) of the descriptors between-groups sum of squares (BSS) to the within-groups sum of squares (WSS) for each descriptor as a weight inside the L1-norm. The proposed method was applied to one dataset that consists of a diverse series of antimicrobial agents with their respective bioactivities against Candida albicans. By experimental study, it has been shown that the proposed method (APLR) was more efficient in the selection of descriptors and classification accuracy than the other competitive methods that could be used in developing QSAR classification models. Another dataset was also successfully experienced. Therefore, it can be concluded that the APLR method had significant impact on QSAR analysis and studies.


Assuntos
Antifúngicos/química , Candida albicans/efeitos dos fármacos , Relação Quantitativa Estrutura-Atividade , Modelos Logísticos , Modelos Moleculares
20.
SAR QSAR Environ Res ; 31(8): 597-613, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32646236

RESUMO

Here we report a new predictive model for autoignition temperature (AIT), an important physical parameter widely used to assess potential safety hazards of combustible materials. Available structure-AIT data extracted from different sources were critically analysed. Support vector regression (SVR) models on different data subsets were built in order to identify a reliable compound set on which a realistic model could be built. This led to a selection of the dataset containing 875 compounds annotated with AIT values. The thereupon-based SVR model performs reasonably well in cross-validation with the determination coefficient r 2 = 0.77 and mean absolute error MAE = 37.8°C. External validation on 20 industrial compounds missing in the training set confirmed its good predictive power (MAE = 28.7°C).


Assuntos
Fogo , Relação Quantitativa Estrutura-Atividade , Temperatura , Fenômenos Químicos , Análise de Dados , Modelos Químicos
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