4D-QSAR Model for Compounds with Binding Affinity Towards Dopamine D&lt;sub&gt;2&lt;/sub&gt; Receptors

Silva, Daniela Rodrigues; Ramalho, Teodorico C.; Cunha, Elaine F. F. da

doi:10.2174/1570180810666131113213448

Cited by 5 publications

(9 citation statements)

References 21 publications

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“…These functions include motor activity, cognition and positive reinforcement. Additionally, in the periphery dopamine acts as a modulator of the cardiovascular and renal functions, among others [17]. In two steps that occur in the cytosol, dopamine is synthesized from the amino acid tyrosine.…”

Section: Dopamine Agonistsmentioning

confidence: 99%

“…Silva et al [17] have performed 4D-QSAR analysis using 73 compounds from tetracyclic tetrahydrofuran derivatives containing a cyclic amine side chain in the 2-position (Fig. 2 ), and with binding affinity towards dopamine D2 receptors; related to locomotor activity [20].…”

Section: Dopamine Agonistsmentioning

confidence: 99%

“…Fig. ( 3 ) illustrates a graphic representation of the 3D-pharmacophore embedded in the 4D-QSAR model using Compound 5-((1-(4-fluorophenyl)-3-[4-[[(2 R ,3a R ,12b S )-11-fluoro-3,3a,8,12b-tetrahydro-2 H -dibenzo [3,4:6,7]cyclohepta [1,2-b]furan-2-yl]methyl]-1-piperazinyl]-1-propanone) as a reference [17].…”

Section: Dopamine Agonistsmentioning

confidence: 99%

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Computer-aided Drug Design Applied to Parkinson Targets

Ishiki

Barbosa-Filho

Silva

et al. 2018

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Section: Dopamine Agonistsmentioning

confidence: 99%

Section: Dopamine Agonistsmentioning

confidence: 99%

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Computer-aided Drug Design Applied to Parkinson Targets

Ishiki

Barbosa-Filho

Silva

et al. 2018

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“…The QSAR modeling paradigm is comprised of several approaches ranging from simple evaluations of molecular similarity to more complex methods such as 3D/4D QSAR methods, which incorporate information on the conformational behavior of ligands as well as their target‐ligand interaction modes through molecular dynamics simulations . The utility of these techniques in the predicting of biological properties of molecules has been extensively reported in the literature . The 4D‐QSAR method provides information on the 3D molecular conformations and interaction modes, thus constituting an important advantage over other 0D‐3D QSAR methods.…”

Section: Introductionmentioning

confidence: 99%

Multi‐objective Optimization of Benzamide Derivatives as Rho Kinase Inhibitors

Gajo

Silva

Barigye

et al. 2017

Molecular Informatics

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Despite recent advances in Computer Aided Drug Discovery and High Throughput Screening, the attrition rates of drug candidates continue to be high, underscoring the inherent complexity of the drug discovery paradigm. Indeed, a compromise between several objectives is often required to obtain successful clinical drugs. The present manuscript details a multi-objective workflow that integrates the 4D-QSAR and molecular docking methods in the simultaneous modeling of the Rho Kinase inhibitory activity and acute toxicity of Benzamide derivatives. To this end, the pIC /pLD ratio is considered as the response variable, permitting the concurrent modeling of both properties and representing a shift from classical step-by-step evaluations. The 4D-QSAR strategy is used to generate the Grid Cell Occupancy Descriptors (GCODs), and Stochastic Gradient Boosting (SGB) and Partial Least Squares (PLS) methods as the model fitting techniques. While the statistical parameters for the PLS model do not meet established criteria for acceptability, the SGB model yields satisfactory performance, with correlation coefficients r =0.95 and r pred=0.65 for the training and test set, respectively. Posteriorly, the structural interpretation of the most relevant GCODs according to the SGB model is performed, allowing for the proposal of 139 novel benzamide derivatives, which are then screened using the same model. Of these 9 compounds were predicted to possess pIC /pLD ratio values higher than those for the employed dataset. Finally, in order to corroborate the results obtained with the SGB model, a docking simulation was formed to evaluate the binding affinity of the proposed molecules to the ROCK2 active site and 3 chemical structures (i. e. p6, p14 and p131) showed higher binding affinity than the most active compound in the training set, while the rest generally demonstrated comparable behavior. It may therefore be concluded that the consensus models that intertwine the 4D-QSAR and molecular docking methods contribute to more reliable virtual screening and compound optimization experiments. Additionally, the use of multi-objective modeling schemes permits the simultaneous evaluation of different chemical and biological profiles, which should contribute to the control a priori of causative factors for the high attrition rates in later drug discovery phases.

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“…With the advent of molecular modeling, three-dimensional (3D) descriptors have replaced didactical physicochemical and bidimensional descriptors (12). In those studies, methods that can incorporate molecular flexibility, such as 4D-QSAR methods, proposed by Hopfinger and co-workers (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23), proved advantageous, as they allowed the identification of a conformation that maximized the activity of 3D-QSAR models. Therefore, the main purpose of this study is to use the 4D-QSAR method to propose structural changes in heteroaryl derivatives to make them future candidates for hypoglycemic drugs.…”

mentioning

confidence: 99%

QSAR Models Guided by Molecular Dynamics Applied to Human Glucokinase Activators

et al. 2015

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In this study, quantitative structure-activity relationship studies which make use of molecular dynamics trajectories were performed on a set of 54 glucokinase protein activators. The conformations obtained by molecular dynamics simulation were superimposed according to the twelve alignments tested in a virtual three-dimensional box comprised of 2 Å cells. The models were generated by the technique that combines genetic algorithms and partial least squares. The best alignment models generated with a determination coefficient (r(2)) between 0.674 and 0.743 and cross-validation (q(2)) between 0.509 and 0.610, indicating good predictive capacity. The 4D-QSAR models developed in this study suggest novel molecular regions to be explored in the search for better glucokinase activators.

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4D-QSAR Model for Compounds with Binding Affinity Towards Dopamine D<sub>2</sub> Receptors

Cited by 5 publications

References 21 publications

Computer-aided Drug Design Applied to Parkinson Targets

Computer-aided Drug Design Applied to Parkinson Targets

Multi‐objective Optimization of Benzamide Derivatives as Rho Kinase Inhibitors

QSAR Models Guided by Molecular Dynamics Applied to Human Glucokinase Activators

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