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Avram SI, Pacureanu LM, Bora A, Crisan L, Avram S, Kurunczi L. ColBioS-FlavRC: a collection of bioselective flavonoids and related compounds filtered from high-throughput screening outcomes. J Chem Inf Model 2014; 54:2360-70. [PMID: 25026200 DOI: 10.1021/ci5002668] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Flavonoids, the vastest class of natural polyphenols, are extensively investigated for their multiple benefits on human health. Due to their physicochemical or biological properties, many representatives are considered to exhibit low selectivity among various protein targets or to plague high-throughput screening (HTS) outcomes. The aim of this study is to highlight reliable, bioselective compounds sharing flavonoidic scaffolds in HTS experiments. A filtering scheme was applied to remove undesired flavonoids (and related compounds) from confirmatory PubChem bioassays. A number of 433 compounds addressing various protein targets form the core of the collection of bioselective flavonoids and related compounds (ColBioS-FlavRC). With an additional set of 2908 inactive related compounds, ColBioS-FlavRC offers the grounds for method optimization and validation. We exemplified the use of ColBioS-FlavRC by pharmacophore modeling, subsequently (externally) validated for virtual screening purposes. The early enrichment capabilities of the pharmacophore hypotheses were measured by means of the median exponential retriever operating curve enrichment (MeROCE), a suited metric in comparative evaluations of virtual screening methods. ColBioS-FlavRC is available in the Supporting Information and is freely accessible for further studies.
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Affiliation(s)
- Sorin I Avram
- Department of Computational Chemistry, Institute of Chemistry Timisoara of Romanian Academy , Mihai Viteazul Avenue, 24, Timisoara, 300223, Romania
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Avram SI, Crisan L, Pacureanu LM, Bora A, Seclaman E, Balint M, Kurunczi LG. Challenges in docking 2′-hydroxy and 2′,4′-dihydroxychalcones into the binding site of ALR2. Med Chem Res 2012. [DOI: 10.1007/s00044-012-0367-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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Avram S, Pacureanu LM, Seclaman E, Bora A, Kurunczi L. PLS-DA - Docking Optimized Combined Energetic Terms (PLSDA-DOCET) protocol: a brief evaluation. J Chem Inf Model 2011; 51:3169-79. [PMID: 22066983 DOI: 10.1021/ci2002268] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Docking studies have become popular approaches in drug design, where the binding energy of the ligand in the active site of the protein is estimated by a scoring function. Many promising techniques were developed to enhance the performance of scoring functions including the fusion of multiple scoring functions outcomes into a so-called consensus scoring function. Hereby, we evaluated the target oriented consensus technique using the energetic terms of several scoring functions. The approach was denoted PLSDA-DOCET. Optimization strategies for consensus energetic terms and scoring functions based on ROC metric were compared to classical rigid docking and to ligand-based similarity search methods comprising 2D fingerprints and ROCS. The ROCS results indicate large performance variations depending on the biological target. The AUC-based strategy of PLSDA-DOCET outperformed the other docking approaches regarding simple retrieval and scaffold-hopping. The superior performance of PLSDA-DOCET protocol relative to single and combined scoring functions was validated on an external test set. We found a relative low mean correlation of the ranks of the chemotypes retrieved by the PLSDA-DOCET protocol and all the other methods employed here.
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Affiliation(s)
- Sorin Avram
- Department of Computational Chemistry, Institute of Chemistry of Romanian Academy, Timisoara, Mihai Viteazul Avenue, 24, 300223 Timisoara, Romania
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Katritzky AR, Pacureanu LM, Slavov SH, Dobchev DA, Karelson M. QSPR Study of Critical Micelle Concentrations of Nonionic Surfactants. Ind Eng Chem Res 2008. [DOI: 10.1021/ie800954k] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Alan R. Katritzky
- Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, Florida 32611, Institute of Chemistry of Romanian Academy, M. Viteazul 24, Timisoara 300223, Romania, Institute of Chemistry, Tallinn University of Technology, Ehitajate tee 5, Tallinn 19086, Estonia, and MolCode Ltd., Soola 8, Tartu 51013, Estonia
| | - Liliana M. Pacureanu
- Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, Florida 32611, Institute of Chemistry of Romanian Academy, M. Viteazul 24, Timisoara 300223, Romania, Institute of Chemistry, Tallinn University of Technology, Ehitajate tee 5, Tallinn 19086, Estonia, and MolCode Ltd., Soola 8, Tartu 51013, Estonia
| | - Svetoslav H. Slavov
- Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, Florida 32611, Institute of Chemistry of Romanian Academy, M. Viteazul 24, Timisoara 300223, Romania, Institute of Chemistry, Tallinn University of Technology, Ehitajate tee 5, Tallinn 19086, Estonia, and MolCode Ltd., Soola 8, Tartu 51013, Estonia
| | - Dimitar A. Dobchev
- Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, Florida 32611, Institute of Chemistry of Romanian Academy, M. Viteazul 24, Timisoara 300223, Romania, Institute of Chemistry, Tallinn University of Technology, Ehitajate tee 5, Tallinn 19086, Estonia, and MolCode Ltd., Soola 8, Tartu 51013, Estonia
| | - Mati Karelson
- Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, Florida 32611, Institute of Chemistry of Romanian Academy, M. Viteazul 24, Timisoara 300223, Romania, Institute of Chemistry, Tallinn University of Technology, Ehitajate tee 5, Tallinn 19086, Estonia, and MolCode Ltd., Soola 8, Tartu 51013, Estonia
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Katritzky AR, Pacureanu LM, Slavov S, Dobchev DA, Karelson M. QSAR study of antiplatelet agents. Bioorg Med Chem 2006; 14:7490-500. [PMID: 16945540 DOI: 10.1016/j.bmc.2006.07.022] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2006] [Revised: 07/05/2006] [Accepted: 07/07/2006] [Indexed: 11/24/2022]
Abstract
A QSAR methodology that involves multilinear (Hansch-type) and nonlinear (ANN backpropagation) approaches was developed to correlate the antiplatelet activity of 60 benzoxazinone derivatives against factor Xa. The statistical characteristics provided by multilinear model (R2 = 0.821) indicated satisfactory stability and predictive ability, while the ANN predictive ability is somewhat superior (R2 = 0.909). The multilinear model provided insight into the main factors that modulate the inhibitory activity of the investigated compounds.
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Affiliation(s)
- Alan R Katritzky
- Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, FL 32611, USA.
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Katritzky AR, Pacureanu LM, Dobchev DA, Fara DC, Duchowicz PR, Karelson M. QSAR modeling of the inhibition of Glycogen Synthase Kinase-3. Bioorg Med Chem 2006; 14:4987-5002. [PMID: 16650999 DOI: 10.1016/j.bmc.2006.03.009] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2006] [Revised: 03/07/2006] [Accepted: 03/07/2006] [Indexed: 10/24/2022]
Abstract
Quantitative structure-activity relationship (QSAR) models of the biological activity (pIC50) of 277 inhibitors of Glycogen Synthase Kinase-3 (GSK-3) are developed using geometrical, topological, quantum mechanical, and electronic descriptors calculated by CODESSA PRO. The linear (multilinear regression) and nonlinear (artificial neural network) models obtained link the structures to their reported activity pIC50. The results are discussed in the light of the main factors that influence the inhibitory activity of the GSK-3 enzyme.
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Affiliation(s)
- Alan R Katritzky
- Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, FL 32611, USA.
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