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ABSTRACT: In the present study both classification and correlation techniques of diverse nature were successfully employed for the development of models for the prediction of human immunodeficiency virus (HIV) integrase inhibitory activity using a dataset comprising 50 analogs of quinolone carboxylic acid. The values of various molecular descriptors (MDs) for each analog in the dataset were computed using the MDS V-life science QSAR plus module. The values of other MDs which are not part of MDS V-life science were computed using an in-house computer program. A decision tree (DT) was constructed for the HIV integrase inhibitory activity to determine the importance of MDs. The DT learned the information from the input data with an accuracy of 98% and correctly predicted the cross-validated (10 fold) data with an accuracy of 96%. Three MDs, E-state contribution descriptor (SssOHE), molecular connectivity topochemical index ($\chi {}^{{\rm A}} $), and eccentric connectivity topochemical index ($\xi _{{\rm C}}^{{\rm C}} $), were used to develop the models using moving average analysis (MAA). The accuracy of classification of single descriptor based models using MAA was found to vary from a minimum of 96% to a maximum of 98%. The statistical significance of the models was assessed through specificity, sensitivity, overall accuracy, Mathew's correlation coefficient, and intercorrelation analysis. The widely used methods like multiple linear regression, partial least squares, and principal component regression were employed for development of correlation models. The models were generated on a training set of 36 molecules. The models had a correlation coefficient (r(2) ) of 0.86 to 0.92, significant cross validated correlation coefficient (q(2) ) of 0.79 to 0.85, F-test from 63.2 to 93.06, r(2) for external test set (pred_r(2) ) from 0.69, coefficient of correlation of predicted dataset (pred_ r(2) Se) of 0.77, and degree of freedom from 27 to 30. Alignment independent descriptors, SsOHE-index, SaaCHE index, SssCH2, and x log P were found to be the most important descriptors for the development of correlation models for the prediction of HIV integrase inhibitory activity.
Archiv der Pharmazie 09/2012; · 1.71 Impact Factor
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ABSTRACT: Four highly discriminating fourth-generation topological indices (TIs), termed as superaugmented eccentric distance sum connectivity indices, as well as their topochemical versions (denoted by , , and ), have been conceptualized in this study. The values of these indices for all possible structures with three, four, and five vertices containing one heteroatom were computed using an in-house computer program. The proposed superaugmented eccentric distance sum connectivity topochemical indices exhibited exceptionally high discriminating power, low degeneracy, and high sensitivity toward both the presence and the relative position of heteroatom(s) for all possible structures with five vertices containing at least one heteroatom. Intercorrelation analysis revealed the absence of correlation of proposed indices with Zagreb indices and the molecular connectivity index. Subsequently, the proposed TIs were successfully utilized for the development of models for the prediction of checkpoint kinase inhibitory activity of 2-arylbenzimidazoles. A data set comprising 47 differently substituted analogs of 2-arylbenzimidazoles was selected for the study. The values of various TIs for each analog in the data set were computed using an in-house computer program. The resulting data were analyzed, and suitable models were developed through decision tree (DT), random forest (RF), and moving average analysis (MAA). The performance of the models was assessed by calculating the specificity, sensitivity, overall accuracy, and Mathew's correlation coefficient. A decision tree was constructed for the checkpoint kinase inhibitory activity to determine the importance of topological indices. The decision tree identified the proposed TIs -, - as the most important indices. The decision tree learned the information from the input data with an accuracy of 96% and correctly predicted the cross-validated (10-fold) data with an accuracy of 77%. Random forest correctly predicted the checkpoint kinase inhibitory activity with an accuracy of 83%. The single index-based models were also developed for the prediction of checkpoint kinase inhibitory activity using MAA. The accuracy of prediction of single index-based models derived through MAA was found to vary from a minimum of 90% to a maximum of 95%. Exceptionally high discriminating power, low degeneracy, and high sensitivity toward branching and presence of heteroatom of proposed indices can be of immense use in drug design, isomer discrimination, similarity/dissimilarity studies, quantitative structure activity/property relationships, lead optimization, and combinatorial library design.
Chemical Biology & Drug Design 01/2012; 79(1):38-52. · 2.28 Impact Factor
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ABSTRACT: The inhibition of tumor angiogenesis has become a compelling approach in the development of anticancer drugs. In the present study, topological models were developed through decision tree and moving average analysis using a data set comprising 42 analogues of 3-aminoindazoles. A total of 22 descriptors (distance based, adjacency based, pendenticity and distance-cum-adjacency based) were used. The values of all 22 topological indices for each analogue in the dataset were computed using an in-house computer program. A decision tree was constructed for the receptor tyrosine kinase KDR (kinase insert domain receptor) inhibitory activity to determine the importance of topological indices. The decision tree learned the information from the input data with an accuracy of 88%. Three independent topological models were also developed for prediction of receptor tyrosine kinase inhibitory (KDR) activity using moving average analysis. The models developed were also found to be sensitive towards the prediction of other receptor tyrosine kinases i.e. FLT3 (fms-like tyrosine kinase-3) and cKIT inhibitory activity. The accuracy of classification of single index based models using moving average analysis was found to be 88%. The performance of models was assessed by calculating precision, sensitivity, overall accuracy and Mathew's correlation coefficient (MCC). The significance of the models was also assessed by intercorrelation analysis.
Scientia Pharmaceutica 06/2011; 79(2):239-57.
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ABSTRACT: The relationship between topological indices and antitubercular activity of 5â-O-[(N-Acyl)sulfamoyl]adenosines has been investigated. A data set consisting of 31 analogues of 5â-O-[(N-Acyl)sulfamoyl]adenosines was selected for the present study. The values of numerous topostructural and topochemical indices for each of 31 differently substituted analogues of the data set were computed using an in-house computer program. Resulting data was analyzed and suitable models were developed through decision tree, random forest and moving average analysis (MAA). The goodness of the models was assessed by calculating overall accuracy of prediction, sensitivity, specificity and Mathews correlation coefficient. Pendentic eccentricity index â a novel highly discriminating, non-correlating pendenticity based topochemical descriptor â was also conceptualized and successfully utilized for the development of a model for antitubercular activity of 5â-O-[(N-Acyl)sulfamoyl]adenosines. The proposed index exhibited not only high sensitivity towards both the presence as well as relative position(s) of pendent/heteroatom(s) but also led to significant reduction in degeneracy. Random forest correctly classified the analogues into active and inactive with an accuracy of 67.74%. A decision tree was also employed for determining the importance of molecular descriptors. The decision tree learned the information from the input data with an accuracy of 100% and correctly predicted the cross-validated (10 fold) data with accuracy up to 77.4%. Statistical significance of proposed models was also investigated using intercorrelation analysis. Accuracy of prediction of proposed MAA models ranged from 90.4 to 91.6%.
Scientia Pharmaceutica 01/2010; 78(4):791-820.
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ABSTRACT: In this study, relationship between the topochemical indices and anti-HIV activity of dimethylaminopyridin-2-ones has been investigated. Three topochemical indices of diverse nature, i.e. Wiener's topochemical index--a distance-based topochemical descriptor, molecular connectivity topochemical index--an adjacency based topochemical descriptor and augmented eccentric connectivity topochemical index--an adjacency-cum-distance-based topochemical descriptor, were used for the present investigations. The values of the Wiener's topochemical index, molecular connectivity topochemical index and augmented eccentric connectivity topochemical index for each of the 103 analogues comprising the data set were computed using an in-house computer program. Resulting data were analyzed and suitable models were developed after the identification of the active ranges. Subsequently, a biological activity was assigned to each compound using these models, which was then compared with the reported anti-HIV activity. Statistical significance of proposed models was further investigated using chi-squared test and intercorrelation analysis. Accuracy of prediction of anti-HIV activity was found to vary from 81 to 85% using these models.
Chemical Biology & Drug Design 03/2009; 73(2):258-70. · 2.28 Impact Factor
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ABSTRACT: Recently published topochemical models for permeability through the blood-brain barrier were validated and cross-validated in the present study. Five models based on three topochemical indices, Wiener's topochemical index - a distance-based topochemical descriptor, molecular connectivity topochemical index - an adjacency-based topochemical descriptor and eccentric connectivity topochemical index - an adjacency-cum-distance based topochemical descriptor, for permeability of structurally and chemically diverse molecules through blood-brain barrier were used in the present investigation. A data set comprising 62 structurally and chemically diverse compounds was selected. This data set was divided into two sets of 31 compounds each - one to serve as the validation set and other as the cross-validation set. The values of all the three-topochemical indices in the original as well as in the normalized form for each of the 31 compounds of the validation set were computed using an in-house computer program. Resultant data was analyzed and each compound was assigned a permeability characteristic using topochemical models, which was then compared with the reported permeability through the blood-brain barrier. Accuracy of prediction of these models was calculated. The same procedure was similarly followed for the cross-validation set. Studies revealed accuracy of prediction of the order of 70-80% during validation. Surprisingly, very high predictability of the order of 77-91% was observed during cross-validation. High predictability observed during validation as well as cross-validation authenticates topochemical models for prediction of permeability through the blood-brain barrier.
Acta Pharmaceutica 01/2008; 57(4):451-67. · 0.91 Impact Factor
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ABSTRACT: In the present study, the relationship between the topochemical indices and telomerase inhibitory activity of flavonoids has been investigated. Three topochemical indices, Wiener's topochemical index (a distance-based topochemical descriptor), molecular connectivity topochemical index (an adjacency-based topochemical descriptor) and superadjacency topochemical index (an adjacency cum distance-based topochemical descriptor) were used for the present investigation. The values of the Wiener's topochemical index, molecular connectivity topochemical index and superadjacency topochemical index for each of the 30 analogues comprising the data set were computed using an in-house computer program. Resultant data was analysed and suitable models were developed after identification of the active ranges. Subsequently, a biological activity was assigned to each analogue involved in the data set using these models, which was then compared with the reported telomerase inhibitory activity. Statistical significance of proposed models was investigated using intercorrelation analysis. Accuracy of prediction using proposed models was found to vary from 80% to 83%.
Chemical Biology & Drug Design 08/2007; 70(1):47-52. · 2.28 Impact Factor
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ABSTRACT: The relationship of Wiener's topochemical index-a distance based topochemical index, molecular connectivity topochemical index-an adjacency based topochemical index and eccentric connectivity topochemical index-an adjacency-cum-distance based topochemical index with sodium channel binding activity has been investigated. A dataset comprising 50 hydantoins and related non-hydantoins was selected. The dataset was divided equally into training and test sets. The values of the three topochemical indices for all the compounds present in both the training and test sets were computed using an in-house computer program. The resulting data was analyzed and suitable models were developed after identification of the active ranges in the training set. Subsequently, a biological activity was assigned to each compound involved in the training set using these models, which was then compared with the reported sodium channel binding activity. An accuracy of prediction of the order of >99% was observed using the proposed models. Cross-validation of these models using the test set revealed an exceptionally high accuracy of approximately 95%.
Journal of Molecular Modeling 02/2007; 13(1):137-45. · 1.80 Impact Factor
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ABSTRACT: The relationship between the topochemical indices and cyclin-dependent kinase 2 (CDK2) inhibitory activity of indole-2-ones has been investigated. The relationship of topochemical versions of well known topological indices of Wiener's index--a distance-based topological descriptor, molecular connectivity index, an adjacency-based topological descriptor and eccentric connectivity index--an adjacency-cum-distance based topological descriptor with CDK2 inhibitory activity of indole-2-ones has been investigated. A data set comprising 67 analogues of substituted indole-2-ones was selected for the present investigation. The values of the Wiener's topochemical index, molecular connectivity topochemical index and eccentric connectivity topochemical index for each of 67 analogues comprising the data set were computed. The resulting data was analyzed and suitable models developed after identification of the active ranges. Subsequently, a biological activity was assigned to each analogue in the data set using these models, which was then compared with the reported CDK2 inhibitory activity. Accuracy of prediction was found to vary from a minimum of 88% for a model based upon molecular connectivity topochemical index to a maximum of approximately 90% for model based upon eccentric connectivity topochemical index.
Journal of Molecular Modeling 12/2005; 11(6):525-31. · 1.80 Impact Factor
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ABSTRACT: Relationship between topochemical indices and inhibition of CDK2/cyclin A by 3-aminopyrazoles was investigated using a data set comprising of 42 3-aminopyrazoles. Three topochemical indices--the Wiener's topochemical index--a distance based topochemical index, atomic molecular connectivity index--an adjacency based topochemical index and superadjacency topochemical index--an adjacency-cum-distance based topochemical index were used for the present investigations. The values of Wiener's topochemical index, atomic molecular connectivity index and superadjacency topochemical index for each of the 42 compounds comprising the data set were computed using an in-house computer program. Resultant data was subsequently analyzed and suitable models were developed after identification of the active ranges. Subsequently, a biological activity was assigned to each of the compounds using these models, which was then compared with the reported CDK2/cyclin A inhibitory activity. High accuracy of prediction ranging from 86 to 89% was observed using these models.
CHEMICAL & PHARMACEUTICAL BULLETIN 07/2005; 53(6):611-5. · 1.59 Impact Factor
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ABSTRACT: The eccentric connectivity index, which has recently been employed successfully for the development of numerous mathematical models for the prediction of biological activities of diverse nature, has been reformed to overcome its limitations caused by degeneracy and insensitivity towards heteroatoms. The reformed eccentric connectivity index, termed the eccentric connectivity topochemical index, overcomes the limitations of the eccentric connectivity index by exhibiting very low degeneracy and displaying sensitivity to both the presence and relative position of heteroatoms without compromizing the discriminating power of the eccentric connectivity index. The relationship of the eccentric connectivity topochemical index, eccentric connectivity index and Wiener's index with regard to the anti-HIV activity of 2, 3-diaryl-1, 3-thiazolidin-4-one derivatives was subsequently investigated. The values of the eccentric connectivity topochemical index, the eccentric connectivity index and Wiener's index of each of 31 analogues comprizing the data set were computed using in-house computer program. Resultant data was analyzed and suitable models developed after identification of active ranges. Subsequently, each derivative was assigned a biological activity using these models, which was then compared with the reported anti-HIV activity. The accuracy of prediction using these models was found to vary from 81 to 90%. The proposed index offers a vast potential for virtual screening of combinatorial libraries, structure property/activity studies and drug design. [figure]. Basic structure of 2,3-diaryl-1, 3-thiazoidin-4-ones.
Journal of Molecular Modeling 01/2005; 10(5-6):399-407. · 1.80 Impact Factor
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ABSTRACT: A novel highly discriminating adjacency-cum-distance-based topological descriptor, termed the adjacent eccentric distance sum index, has been conceptualized and its discriminating power investigated with regard to the anti-HIV activity of 4,5,6,7-tetrahydro-imidazo-[4,5,1- jk] [1,4] benzodiazepin-2 (1 H)-one (TIBO) derivatives. The discriminating power of the adjacent eccentric distance sum index was compared with that of the eccentric connectivity index - another adjacency-cum-distance-based topological descriptor. The values of the eccentric connectivity index and the adjacent eccentric distance sum index of each of 121 analogues comprising the data set were computed and active ranges were identified. Subsequently, a biological activity was assigned to each analogue involved in the data set and this was then compared with the reported anti-HIV activity. Excellent correlations were observed between anti-HIV activity and both the topological descriptors. Although the overall accuracy of prediction was found to be approximately 84% in case of the eccentric connectivity index and approximately 86% in case of adjacent eccentric distance sum index, the predictability using the adjacent eccentric distance sum index in the active range itself was >92%. The proposed index offers a vast potential for structure-activity/property studies.
Journal of Molecular Modeling 08/2002; 8(8):258-65. · 1.80 Impact Factor
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ABSTRACT: Zagreb indices M1 and M2 have been refined to significantly reduce their degeneracy. The refined indices are sensitive to both the presence as well as relative position of the heteroatoms and have been termed as Zagreb topochemical indices M1 c and M2 c. The discriminating power of M1 c and M2 c was investigated and compared with that of Zagreb indices M1 and M2. Both M1 c and M2 c exhibited much lower degeneracy without compromising with the discriminating power of M1 and M2. Relationship between the anti-inflammatory activity of N-arylanthranilic acids and Zagreb indices and Zagreb topochemical indices was investigated. The values of all the four indices for each of the 112 compounds were calculated using an in-house computer program. The resulting data was analyzed and suitable models were developed after identification of the active ranges. Subsequently, biological activity was assigned to each of the compounds using these models, which was then compared with the reported anti-inflammatory activity. High accuracy of prediction was obtained using models based upon Zagreb indices and Zagreb topochemical indices.
Croatica Chemica Acta (CCA@chem.pmf.hr); Vol.78 No.2.
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ABSTRACT: An amalgamation of solid dispersion and cube sugar or sintering technologies was utilized for preparing a high dissolution rate, fast-release dosage form for poorly water soluble drug(s). Famotidine was employed as a model drug. Solid dispersion particles of famotidine were prepared using the fusion method employing xylitol as an hydrophilic carrier, and the particles' solid state performance was characterized by means of differential scanning calorimetry, Fourier transformed infrared spectroscopy, and X-ray powder diffractometry. Solid dispersion particles of famotidine were encompassed directly into tablets in a manner similar to that adopted for cube sugar production and sintering technology. The effect of different particle sizes of solid dispersion was also studied in relation to tablet disintegration. The resulting tablets were only rapidly disintegrating owing to capillarity but also ensure the rapid dissolution of poorly water-soluble drug when compared to other marketed products.
PDA journal of pharmaceutical science and technology / PDA 63(1):58-70.
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ABSTRACT: Recently published topochemical models for permeability through the blood-brain barrier were validated and cross-validated in the present study. Five models based on three topochemical indices, Wiener’s topochemical index - a distance-based topochemical descriptor, molecular connectivity topochemical index - an adjacency-based topochemical descriptor and eccentric connectivity topochemical index - an adjacency-cum-distance based topochemical descriptor, for permeability of structurally and chemically diverse molecules through blood-brain barrier were used in the present investigation. A data set comprising 62 structurally and chemically diverse compounds was selected. This data set was divided into two sets of 31 compounds each - one to serve as the validation set and other as the cross-validation set. The values of all the three-topochemical indices in the original as well as in the normalized form for each of the 31 compounds of the validation set were computed using an in house computer program. Resultant data was analyzed and each compound was assigned a permeability characteristic using topochemical models, which was then compared with the reported permeability through the blood-brain barrier. Accuracy of prediction of these models was calculated. The same procedure was similarly followed for the cross-validation set. Studies revealed accuracy of prediction of the order of 7080% during validation. Surprisingly, very high predictability of the order of 7791% was observed during cross-validation. High predictability observed during validation as well as cross-validation authenticates topochemical models for prediction of permeability through the blood-brain barrier.
Acta pharmaceutica (hfd-fg-ap@zg.htnet.hr); Vol.57 No.4.
