397 research outputs found

    Use of the R-group descriptor for alignment-free QSAR

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    An R-group descriptor characterises the distribution of some atom-based property, such as elemental type or partial atomic charge, at increasing numbers of bonds distant from the point of substitution on a parent ring system. Application of Partial Least Squares (PLS) to datasets for which bioactivity data and R-group descriptor information are available is shown to provide an effective way of generating QSAR models with a high level of predictive ability. The resulting models are competitive with the models produced by established QSAR approaches, are readily interpretable in structural terms, and are shown to be of value in the optimisation of a lead series

    Descriptor-and fragment-based QSAR models for a series of Schistosoma mansoni purine nucleoside inhibitors

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    The enzyme purine nucleoside phosphorylase from Schistosoma mansoni (SmPNP) is an attractive molecular target for the treatment of major parasitic infectious diseases, with special emphasis on its role in the discovery of new drugs against schistosomiasis, a tropical disease that affects millions of people worldwide. In the present work, we have determined the inhibitory potency and developed descriptor- and fragment-based quantitative structure-activity relationships (QSAR) for a series of 9-deazaguanine analogs as inhibitors of SmPNP. Significant statistical parameters (descriptor-based model: r² = 0.79, q² = 0.62, r²pred = 0.52; and fragment-based model: r² = 0.95, q² = 0.81, r²pred = 0.80) were obtained, indicating the potential of the models for untested compounds. The fragment-based model was then used to predict the inhibitory potency of a test set of compounds, and the predicted values are in good agreement with the experimental resultsA enzima purina nucleosídeo fosforilase de Schistosoma mansoni (SmPNP) é um alvo molecular atrativo para o tratamento de importantes doenças infecciosas parasitárias, com especial ênfase para o seu papel na descoberta de novos fármacos contra a esquistossomose, uma doença tropical que afeta cerca de 200 milhões de pessoas em 74 áreas endêmicas no mundo todo. No presente trabalho, a potência inibitória foi determinada e estudos das relações quantitativas entre a estrutura e atividade (QSAR), baseados em descritores e fragmentos, foram desenvolvidos para uma série de 9-deazaguaninas que atuam como inibidores da SmPNP. Parâmetros estatísticos significantes (modelo baseado em descritor: r² = 0,79; q² = 0,62, r²pred = 0,52; e modelo baseado em fragmento: r² = 0,95; q² = 0,81; r²pred = 0,80) foram obtidos, indicando o potencial dos modelos para compostos ainda não testados. O modelo baseado em fragmento foi então usado para predizer a potência inibitória de um conjunto teste de compostos, e os valores preditos estão em boa concordância com os resultados experimentais.Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB)(FAPESP) São Paulo Research Foundation(CNPq) National Council for Scientific and Technological Developmen

    QSAR-Driven Discovery of Novel Chemical Scaffolds Active against Schistosoma mansoni.

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    Schistosomiasis is a neglected tropical disease that affects millions of people worldwide. Thioredoxin glutathione reductase of Schistosoma mansoni (SmTGR) is a validated drug target that plays a crucial role in the redox homeostasis of the parasite. We report the discovery of new chemical scaffolds against S. mansoni using a combi-QSAR approach followed by virtual screening of a commercial database and confirmation of top ranking compounds by in vitro experimental evaluation with automated imaging of schistosomula and adult worms. We constructed 2D and 3D quantitative structure-activity relationship (QSAR) models using a series of oxadiazoles-2-oxides reported in the literature as SmTGR inhibitors and combined the best models in a consensus QSAR model. This model was used for a virtual screening of Hit2Lead set of ChemBridge database and allowed the identification of ten new potential SmTGR inhibitors. Further experimental testing on both shistosomula and adult worms showed that 4-nitro-3,5-bis(1-nitro-1H-pyrazol-4-yl)-1H-pyrazole (LabMol-17) and 3-nitro-4-{[(4-nitro-1,2,5-oxadiazol-3-yl)oxy]methyl}-1,2,5-oxadiazole (LabMol-19), two compounds representing new chemical scaffolds, have high activity in both systems. These compounds will be the subjects for additional testing and, if necessary, modification to serve as new schistosomicidal agents

    Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings

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    This paper compares 22 different similarity coefficients when they are used for searching databases of 2D fragment bit-strings. Experiments with the National Cancer Institute's AIDS and IDAlert databases show that the coefficients fall into several well-marked clusters, in which the members of a cluster will produce comparable rankings of a set of molecules. These clusters provide a basis for selecting combinations of coefficients for use in data fusion experiments. The results of these experiments provide a simple way of increasing the effectiveness of fragment-based similarity searching systems

    Grouping of coefficients for the calculation of inter-molecular similarity and dissimilarity using 2D fragment bit-strings

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    This paper compares 22 different similarity coefficients when they are used for searching databases of 2D fragment bit-strings. Experiments with the National Cancer Institute's AIDS and IDAlert databases show that the coefficients fall into several well-marked clusters, in which the members of a cluster will produce comparable rankings of a set of molecules. These clusters provide a basis for selecting combinations of coefficients for use in data fusion experiments. The results of these experiments provide a simple way of increasing the effectiveness of fragment-based similarity searching systems

    Whey-derived peptides interactions with ACE by molecular docking as a potential predictive tool of natural ACE inhibitors

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    Several milk/whey derived peptides possess high in vitro angiotensin I-converting enzyme (ACE) inhibitory activity. However, in some cases, poor correlation between the in vitro ACE inhibitory activity and the in vivo antihypertensive activity has been observed. The aim of this study is to gain insight into the structure-activity relationship of peptide sequences present in whey/milk protein hydrolysates with high ACE inhibitory activity, which could lead to a better understanding and prediction of their in vivo antihypertensive activity. The potential interactions between peptides produced from whey proteins, previously reported as high ACE inhibitors such as IPP, LIVTQ, IIAE, LVYPFP, and human ACE were assessed using a molecular docking approach. The results show that peptides IIAE, LIVTQ, and LVYPFP formed strong H bonds with the amino acids Gln 259, His 331, and Thr 358 in the active site of the human ACE. Interestingly, the same residues were found to form strong hydrogen bonds with the ACE inhibitory drug Sampatrilat. Furthermore, peptides IIAE and LVYPFP interacted with the amino acid residues Gln 259 and His 331, respectively, also in common with other ACE-inhibitory drugs such as Captopril, Lisinopril and Elanapril. Additionally, IIAE interacted with the amino acid residue Asp 140 in common with Lisinopril, and LIVTQ interacted with Ala 332 in common with both Lisinopril and Elanapril. The peptides produced naturally from whey by enzymatic hydrolysis interacted with residues of the human ACE in common with potent ACE-inhibitory drugs which suggests that these natural peptides may be potent ACE inhibitors

    Non-peptidic Cruzain Inhibitors with Trypanocidal Activity Discovered by Virtual Screening and in Vitro Assay

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    A multi-step cascade strategy using integrated ligand-and target-based virtual screening methods was developed to select a small number of compounds from the ZINC database to be evaluated for trypanocidal activity. Winnowing the database to 23 selected compounds, 12 non-covalent binding cruzain inhibitors with affinity values (K-i) in the low micromolar range (3-60 mu M) acting through a competitive inhibition mechanism were identified. This mechanism has been confirmed by determining the binding mode of the cruzain inhibitor Nequimed176 through X-ray crystallographic studies. Cruzain, a validated therapeutic target for new chemotherapy for Chagas disease, also shares high similarity with the mammalian homolog cathepsin L. Because increased activity of cathepsin L is related to invasive properties and has been linked to metastatic cancer cells, cruzain inhibitors from the same library were assayed against it. Affinity values were in a similar range (4-80 mu M), yielding poor selectivity towards cruzain but raising the possibility of investigating such inhibitors for their effect on cell proliferation. in order to select the most promising enzyme inhibitors retaining trypanocidal activity for structure-activity relationship (SAR) studies, the most potent cruzain inhibitors were assayed against T. cruzi-infected cells. Two compounds were found to have trypanocidal activity. Using compound Nequimed42 as precursor, an SAR was established in which the 2-acetamidothiophene-3-carboxamide group was identified as essential for enzyme and parasite inhibition activities. the IC50 value for compound Nequimed42 acting against the trypomastigote form of the Tulahuen lacZ strain was found to be 10.6 +/- 0.1 mu M, tenfold lower than that obtained for benznidazole, which was taken as positive control. in addition, by employing the strategy of molecular simplification, a smaller compound derived from Nequimed42 with a ligand efficiency (LE) of 0.33 kcal mol(-1) atom(-1) (compound Nequimed176) is highlighted as a novel non-peptidic, non-covalent cruzain inhibitor as a trypanocidal agent candidate for optimization.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ Fed Sao Carlos, Dept Quim, BR-13560 Sao Carlos, SP, BrazilUniv São Paulo, Inst Quim Sao Carlos, Grp Quim Med IQSC USP, Sao Carlos, SP, BrazilUniv Calif San Francisco, Dept Pathol, Ctr Discovery & Innovat Parasit Dis, San Francisco, CA 94140 USAUniv São Paulo, Fac Med Ribeirao Preto, Dept Bioquim & Imunol, BR-14049 Ribeirao Preto, SP, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Biofis, São Paulo, BrazilUniversidade Federal de São Paulo, Escola Paulista Med, Dept Biofis, São Paulo, BrazilFAPESP: 2011/01893-3,CNPq: 301614/2010-5CAPES: 5985/11-0Web of Scienc

    Review of QSAR Models and Software Tools for predicting Biokinetic Properties

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    In the assessment of industrial chemicals, cosmetic ingredients, and active substances in pesticides and biocides, metabolites and degradates are rarely tested for their toxicologcal effects in mammals. In the interests of animal welfare and cost-effectiveness, alternatives to animal testing are needed in the evaluation of these types of chemicals. In this report we review the current status of various types of in silico estimation methods for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their metabolites/degradation products. The review was performed in a broad sense, with emphasis on QSARs and rule-based approaches and their applicability to estimation of oral bioavailability, human intestinal absorption, blood-brain barrier penetration, plasma protein binding, metabolism and. This revealed a vast and rapidly growing literature and a range of software tools. While it is difficult to give firm conclusions on the applicability of such tools, it is clear that many have been developed with pharmaceutical applications in mind, and as such may not be applicable to other types of chemicals (this would require further research investigation). On the other hand, a range of predictive methodologies have been explored and found promising, so there is merit in pursuing their applicability in the assessment of other types of chemicals and products. Many of the software tools are not transparent in terms of their predictive algorithms or underlying datasets. However, the literature identifies a set of commonly used descriptors that have been found useful in ADME prediction, so further research and model development activities could be based on such studies.JRC.DG.I.6-Systems toxicolog
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