QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations

Valdés-Martiní, José R.; Marrero-Ponce, Yovani; García-Jacas, César R.; Martínez‐Mayorga, Karina; Barigye, Stephen J.; d‘Almeida, Yasser Silveira Vaz; Pham-The, Hai; Pérez-Giménez, Facundo; Morell, Carlos

doi:10.1186/s13321-017-0211-5

Cited by 62 publications

(60 citation statements)

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“…At the same time, this cut-off prevents excessive imbalance between active and inactive compounds. The software QUBILs-MAS v1.0 [30] was employed to calculate the molecular descriptors known as the atom-based quadratic indices, which have been earlier proved to be highly efficient for developing mt-QSAR models [27,31,32,33,34,35]. A detailed description of how these descriptors are calculated is provided in the Materials and Methods section.…”

Section: Resultsmentioning

confidence: 99%

Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents

2019

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Two isoforms of extracellular regulated kinase (ERK), namely ERK-1 and ERK-2, are associated with several cellular processes, the aberration of which leads to cancer. The ERK-1/2 inhibitors are thus considered as potential agents for cancer therapy. Multitarget quantitative structure–activity relationship (mt-QSAR) models based on the Box–Jenkins approach were developed with a dataset containing 6400 ERK inhibitors assayed under different experimental conditions. The first mt-QSAR linear model was built with linear discriminant analysis (LDA) and provided information regarding the structural requirements for better activity. This linear model was also utilised for a fragment analysis to estimate the contributions of ring fragments towards ERK inhibition. Then, the random forest (RF) technique was employed to produce highly predictive non-linear mt-QSAR models, which were used for screening the Asinex kinase library and identify the most potential virtual hits. The fragment analysis results justified the selection of the hits retrieved through such virtual screening. The latter were subsequently subjected to molecular docking and molecular dynamics simulations to understand their possible interactions with ERK enzymes. The present work, which utilises in-silico techniques such as multitarget chemometric modelling, fragment analysis, virtual screening, molecular docking and dynamics, may provide important guidelines to facilitate the discovery of novel ERK inhibitors.

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Section: Resultsmentioning

confidence: 99%

Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents

2019

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“…Several weighted MDs can be calculated from these previous definitions, for instance: (1) from

F M D_{C_{μ}}^{1}

for α′ = λ′ =1, the weighted DIVATI 2D‐MDs, the weighted GT‐STAF 2D‐MDs and the weighted atom‐based QuBiLS‐MAS 2D‐MDs can be obtained, when vector

L

is computed with some of these families; (2) if vector

L

is computed with the vertex degree invariant, then from

F M D_{C_{μ}}^{1}

for α′ =1 and λ′ =2, from

F M D_{C_{μ}}^{4}

for α′ = λ′ =1, and from

F M D_{C_{μ}}^{4}

for α′ =1 and λ′ =−1/2, the weighted first Zagreb index, the weighted second Zagreb index and the weighted Randic connectivity index can be calculated, respectively; (3) from

F M D_{C_{μ}}^{4}

for

α^{'} = \frac{B}{C + 1}

(B is the number of edges and C is the number of rings) and λ′ =−1/2, weighted Balaban‐like indices can be determined; (4) from

F M D_{C_{μ}}^{6}

for α′ =1 and λ′ =−1/2, weighted Kier‐Hall connectivity indices can be obtained; and (5) from

F M D_{C_{μ}}^{7}

, weighted autocorrelation descriptors can be computed. Below, a practical example is presented.…”

Section: Extending Several Traditional Procedures To Derive Gowawa Opmentioning

confidence: 99%

GOWAWA Aggregation Operator‐based Global Molecular Characterizations: Weighting Atom/bond Contributions (LOVIs/LOEIs) According to their Influence in the Molecular Encoding

García-Jacas

Cabrera-Leyva

Marrero-Ponce

et al. 2018

Molecular Informatics

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A different perspective to compute global weighted definitions of molecular descriptors from the contributions of each atom (LOVIs) or covalent bond (LOEIs) within a molecule is presented, using the generalized ordered weighted averaging - weighted averaging (GOWAWA) aggregation operator. This operator is rather different from the other norm-, mean- and statistic-based operators used up to date for the descriptors calculation from LOVIs/LOEIs. GOWAWA unifies the generalized ordered weighted averaging (GOWA) and the weighted generalized mean (WGM) functions and, in addition, it uses a smoothing parameter to assign different importance values to both functions depending on the problem under study. With the GOWAWA operator, diversity of novel global aggregations of molecular descriptors can be determined, where the influence that each atom (or covalent bond) has on the molecular characterization is taken into account. Therefore, this approach is completely different from the ones reported in the literature, where the values of LOVIs/LOEIs are considered equally important. To demonstrate the feasibility of using this operator, the QuBiLS-MIDAS descriptors (http://tomocomd.com/qubils-midas) were used and, as a result, a module was built into the corresponding software to compute them, being thus the only software reported in the literature that can be employed to determine weighted descriptors. Moreover, several modeling studies were performed on eight chemical datasets, which demonstrated that, with the GOWAWA aggregation operator, weighted QuBiLS-MIDAS descriptors that contribute to develop models with greater predictive power can be computed, if compared to the models based on the non-weighted descriptors calculated from the other operators used up to date. A non-parametric statistical assessment confirmed that the GOWAWA-based predictions are significantly superior to the others obtained. Therefore, all in all, it can be concluded that, from the results achieved, the GOWAWA operator constitutes a prominent alternative to codify relevant chemical information of the molecules, ultimately useful in improving the modeling ability of several old and recent descriptors whose definition is based on the LOVIs/LOEIs calculation.

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“…From these fuzzy formulations, several specific descriptors can be computed, for instance: (1) from for , fuzzy DIVATI MDs [41], fuzzy GT-STAF MDs [34] and fuzzy QuBiLS-MAS MDs [37] can be obtained, when the LOVIs vector is computed with some of those families; (2) if vector is computed with the vertex degree invariant, then from for and , from for and from for and , the fuzzy first Zagreb index [65], the fuzzy second Zagreb index [65] and the fuzzy Randic connectivity index [68] can be obtained, respectively; (3) from for (B is the number of graph edges (covalent edges) and C is the number of rings) and , the fuzzy Balaban-like indices can be determined [32]; (4) from for and , the fuzzy Kier–Hall connectivity indices can be obtained [69]; and (5) from , fuzzy autocorrelation MDs can be computed. A practical example is presented below.…”

Section: Extending Traditional Functions To Derive Choquet Integral-bmentioning

confidence: 99%

Choquet integral-based fuzzy molecular characterizations: when global definitions are computed from the dependency among atom/bond contributions (LOVIs/LOEIs)

et al. 2018

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BackgroundSeveral topological (2D) and geometric (3D) molecular descriptors (MDs) are calculated from local vertex/edge invariants (LOVIs/LOEIs) by performing an aggregation process. To this end, norm-, mean- and statistic-based (non-fuzzy) operators are used, under the assumption that LOVIs/LOEIs are independent (orthogonal) values of one another. These operators are based on additive and/or linear measures and, consequently, they cannot be used to encode information from interrelated criteria. Thus, as LOVIs/LOEIs are not orthogonal values, then non-additive (fuzzy) measures can be used to encode the interrelation among them.ResultsGeneral approaches to compute fuzzy 2D/3D-MDs from the contribution of each atom (LOVIs) or covalent bond (LOEIs) within a molecule are proposed, by using the Choquet integral as fuzzy aggregation operator. The Choquet integral-based operator is rather different from the other operators often used for the 2D/3D-MDs calculation. It performs a reordering step to fuse the LOVIs/LOEIs according to their magnitudes and, in addition, it considers the interrelation among them through a fuzzy measure. With this operator, fuzzy definitions can be derived from traditional or recent MDs; for instance, fuzzy Randic-like connectivity indices, fuzzy Balaban-like indices, fuzzy Kier–Hall connectivity indices, among others. To demonstrate the feasibility of using this operator, the QuBiLS-MIDAS 3D-MDs were used as study case and, as a result, a module was built into the corresponding software to compute them (http://tomocomd.com/qubils-midas). Thus, it is the only software reported in the literature that can be employed to determine Choquet integral-based fuzzy MDs. Moreover, regression models were created on eight chemical datasets. In this way, a comparison between the results achieved by the models based on the non-fuzzy QuBiLS-MIDAS 3D-MDs with regard to the ones achieved by the models based on the fuzzy QuBiLS-MIDAS 3D-MDs was made. As a result, the models built with the fuzzy QuBiLS-MIDAS 3D-MDs achieved the best performance, which was statistically corroborated through the Wilcoxon signed-rank test.ConclusionsAll in all, it can be concluded that the Choquet integral constitutes a prominent alternative to compute fuzzy 2D/3D-MDs from LOVIs/LOEIs. In this way, better characterizations of the compounds can be obtained, which will be ultimately useful in enhancing the modelling ability of existing traditional 2D/3D-MDs.Electronic supplementary materialThe online version of this article (10.1186/s13321-018-0306-7) contains supplementary material, which is available to authorized users.

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QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations

Cited by 62 publications

References 77 publications

Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents

Multi-Target Chemometric Modelling, Fragment Analysis and Virtual Screening with ERK Inhibitors as Potential Anticancer Agents

GOWAWA Aggregation Operator‐based Global Molecular Characterizations: Weighting Atom/bond Contributions (LOVIs/LOEIs) According to their Influence in the Molecular Encoding

Choquet integral-based fuzzy molecular characterizations: when global definitions are computed from the dependency among atom/bond contributions (LOVIs/LOEIs)

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