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Lee S, Park H, Choi C, Kim W, Kim KK, Han YK, Kang J, Kang CJ, Son Y. Multi-order graph attention network for water solubility prediction and interpretation. Sci Rep 2023; 13:957. [PMID: 36864064 PMCID: PMC9981901 DOI: 10.1038/s41598-022-25701-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/02/2022] [Indexed: 03/04/2023] Open
Abstract
The water solubility of molecules is one of the most important properties in various chemical and medical research fields. Recently, machine learning-based methods for predicting molecular properties, including water solubility, have been extensively studied due to the advantage of effectively reducing computational costs. Although machine learning-based methods have made significant advances in predictive performance, the existing methods were still lacking in interpreting the predicted results. Therefore, we propose a novel multi-order graph attention network (MoGAT) for water solubility prediction to improve the predictive performance and interpret the predicted results. We extracted graph embeddings in every node embedding layer to consider the information of diverse neighboring orders and merged them by attention mechanism to generate a final graph embedding. MoGAT can provide the atomic-specific importance scores of a molecule that indicate which atoms significantly influence the prediction so that it can interpret the predicted results chemically. It also improves prediction performance because the graph representations of all neighboring orders, which contain diverse range of information, are employed for the final prediction. Through extensive experiments, we demonstrated that MoGAT showed better performance than the state-of-the-art methods, and the predicted results were consistent with well-known chemical knowledge.
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Affiliation(s)
- Sangho Lee
- grid.255168.d0000 0001 0671 5021Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, 04620 South Korea ,grid.255168.d0000 0001 0671 5021Data Science Laboratory (DSLAB), Dongguk University-Seoul, Seoul, 04620 South Korea
| | - Hyunwoo Park
- grid.255168.d0000 0001 0671 5021Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, 04620 South Korea ,grid.255168.d0000 0001 0671 5021Data Science Laboratory (DSLAB), Dongguk University-Seoul, Seoul, 04620 South Korea
| | - Chihyeon Choi
- grid.255168.d0000 0001 0671 5021Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, 04620 South Korea ,grid.255168.d0000 0001 0671 5021Data Science Laboratory (DSLAB), Dongguk University-Seoul, Seoul, 04620 South Korea
| | - Wonjoon Kim
- grid.412059.b0000 0004 0532 5816Division of Future Convergence (HCI Science Major), Dongduk Women’s University, Seoul, 02748 South Korea
| | - Ki Kang Kim
- grid.264381.a0000 0001 2181 989XDepartment of Energy Science, Sungkyunkwan University (SKKU), Suwon, 16419 South Korea ,grid.264381.a0000 0001 2181 989XCenter for Integrated Nanostructure Physics (CINAP), Institute for Basic Science (IBS), Sungkyunkwan University (SKKU), Suwon, 16419 South Korea
| | - Young-Kyu Han
- grid.255168.d0000 0001 0671 5021Department of Energy and Materials Engineering, Dongguk University-Seoul, Seoul, 04620 South Korea
| | - Joohoon Kang
- grid.264381.a0000 0001 2181 989XSchool of Advanced Materials Science and Engineering, Sungkyunkwan University (SKKU), Suwon, 16419 South Korea ,grid.264381.a0000 0001 2181 989XKIST-SKKU Carbon-Neutral Research Center, Sungkyunkwan University (SKKU), Suwon, 16419 South Korea
| | - Chang-Jong Kang
- Department of Physics, Chungnam National University, Daejeon, 34134, South Korea.
| | - Youngdoo Son
- Department of Industrial and Systems Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea. .,Data Science Laboratory (DSLAB), Dongguk University-Seoul, Seoul, 04620, South Korea.
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2
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Sasaoka Y, Ito K. Amphiphilic Sugar Derivatives Linked with Gallic Acid Bearing Tris-alkoxy Groups through L-Lysine Linkage: Self-assembly and Efficient Dye Removal in Water-organic Solvent Biphasic System. CHEM LETT 2022. [DOI: 10.1246/cl.220328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Yuuki Sasaoka
- Graduate School of Science and Engineering, Yamagata University, 4-3-16 Jhonan, Yonezawa, Yamagata 992-8510, Japan
| | - Kazuaki Ito
- Graduate School of Science and Engineering, Yamagata University, 4-3-16 Jhonan, Yonezawa, Yamagata 992-8510, Japan
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3
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The role of herbal plants in the inhibition of SARS-CoV-2 main protease: A computational approach. J INDIAN CHEM SOC 2022. [PMCID: PMC9276541 DOI: 10.1016/j.jics.2022.100640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
COVID-19 has quickly spread across the globe, becoming a pandemic. This disease has a variable impact in different countries depending on their cultural norms, mitigation efforts and health infrastructure. This study aims to assess the herbal plants in the pursuit of potential SARS-CoV-2 Mpro inhibitors using in silico approaches. We have considered 16 extracted compounds of 10 different species of these plants. In order to explain their inhibition properties and chemical reactivity pattern, we have performed the density functional theory based calculations of frontier molecular orbitals, molecular electrostatic potential surface and chemical reactivity descriptors. Our calculated lipophilicity, aqueous solubility and binding affinity of the extracted compounds suggest that the inhibition potentials in the order; harsingar > aloe vera > giloy > turmeric > neem > ginger > red onion > tulsi > cannabis > black pepper. On comparing the binding affinity with hydroxychloroquine, we note that the inhibition potentials of the extracts of harsingar, aloe vera and giloy are very promising. In order to validate this, we have also performed MD simulation and MM-PBSA binding free energy analysis. Therefore, we believe that these findings will open further possibilities and accelerate the works towards finding an antidote for this malady.
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4
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Narayan V, Pandey AK, Dwivedi A, Mwankemwa BS, Maurya A, Sharma AK, Singh V. Comprehensive quantum chemical calculations and molecular docking analysis of uracil mustard by first principle. J INDIAN CHEM SOC 2022. [DOI: 10.1016/j.jics.2022.100580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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5
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Stone S, Newman DJ, Colletti SL, Tan DS. Cheminformatic analysis of natural product-based drugs and chemical probes. Nat Prod Rep 2022; 39:20-32. [PMID: 34342327 PMCID: PMC8792152 DOI: 10.1039/d1np00039j] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Covering: 1981 to 2019Natural products continue to play a major role in drug discovery, with half of new chemical entities based structurally on a natural product. Herein, we report a cheminformatic analysis of the structural and physicochemical properties of natural product-based drugs in comparison to top-selling brand-name synthetic drugs, and a selection of chemical probes recently discovered from diversity-oriented synthesis libraries. In this analysis, natural product-based drugs covered a broad range of chemical space based on size, polarity, and three-dimensional structure. Natural product-based structures were also more prevalent in top-selling drugs of 2018 compared to 2006. Further, the drugs clustered well according to biosynthetic origins, but less so based on therapeutic classes. Macrocycles occupied distinctive and relatively underpopulated regions of chemical space, while chemical probes largely overlapped with synthetic drugs. This analysis highlights the continued opportunities to leverage natural products and their pharmacophores in modern drug discovery.
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Affiliation(s)
- Samantha Stone
- Chemical Biology Program, Sloan Kettering Institute,
Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, New York 10021,
USA
| | | | | | - Derek S. Tan
- Chemical Biology Program, Sloan Kettering Institute,
Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, New York 10021,
USA,Tri-Institutional Research Program, Memorial Sloan
Kettering Cancer Center, 1275 York Avenue, New York, New York 10021, USA
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6
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Vital theoretical and inter molecular docking study of (E)-3-[(2,6-dimethylphenyl)diazenyl]-7-methyl-1H-indazole. J INDIAN CHEM SOC 2021. [DOI: 10.1016/j.jics.2021.100258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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7
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Prediction of Anti-Glioblastoma Drug-Decorated Nanoparticle Delivery Systems Using Molecular Descriptors and Machine Learning. Int J Mol Sci 2021; 22:ijms222111519. [PMID: 34768951 PMCID: PMC8584266 DOI: 10.3390/ijms222111519] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 10/08/2021] [Accepted: 10/22/2021] [Indexed: 12/22/2022] Open
Abstract
The theoretical prediction of drug-decorated nanoparticles (DDNPs) has become a very important task in medical applications. For the current paper, Perturbation Theory Machine Learning (PTML) models were built to predict the probability of different pairs of drugs and nanoparticles creating DDNP complexes with anti-glioblastoma activity. PTML models use the perturbations of molecular descriptors of drugs and nanoparticles as inputs in experimental conditions. The raw dataset was obtained by mixing the nanoparticle experimental data with drug assays from the ChEMBL database. Ten types of machine learning methods have been tested. Only 41 features have been selected for 855,129 drug-nanoparticle complexes. The best model was obtained with the Bagging classifier, an ensemble meta-estimator based on 20 decision trees, with an area under the receiver operating characteristic curve (AUROC) of 0.96, and an accuracy of 87% (test subset). This model could be useful for the virtual screening of nanoparticle-drug complexes in glioblastoma. All the calculations can be reproduced with the datasets and python scripts, which are freely available as a GitHub repository from authors.
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Pandey AK, Singh V, Dwivedi A. Comparative study of molecular docking, structural, electronic, vibrational and hydrogen bonding interactions on 4-hydroxy benzo hydrazide (4HBH) and its newly designed derivative [(E)–N′-((1H-Pyrrol-2-YL)methylene) –4-hydroxy benzo hydrazide and its isomers (I, II and III)] (potential inhibitors) for COVID-19 protease. MAIN GROUP CHEMISTRY 2021. [DOI: 10.3233/mgc-210039] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Studies have shown that hydrazides and thier derivatives are used for pharmaceutical and medicinal purposes. At present, the whole world is suffering for COVID-19 virus. There are some vaccines or medicines available to treat this disease all over the world. Today the one fourth of the world’s population is under lockdown condition. In this scenario, scientists from the whole world are doing different types of research on this disease. Being a molecular modeller, this inspires us to design new types of species (may be drugs) which may be capable for COVID-19 Protease. In the present effort, we have performed docking studies of title compounds with COVID-19 protein (6LU7) for anti-COVID-19 activity. A comparative quantum chemical calculations of molecular geometries (bond lengths and bond angles) of 4-Hydroxy Benzo Hydrazide (4HBH) and its newly designed derivatve [(E)-N′-((1H-Pyrrol-2-YL)Methylene) –4-Hydroxy Benzo Hydrazide and its isomers (I, II and III)] in the ground state have also been carried out due to its biological importance and compared with the similer type of compound found in literature i.e. benzohydrazide. The optimized geometry and wavenumber of the vibrational bands of the molecules have been calculated by density functional theory (DFT) using Becke’s three-parameters hybrid functional (B3LYP/CAM-B3LYP) with 6–311G (d, p) as the basis set. Vibrational wavenumbers are compared with the observed FT-IR and FTRaman spectra of 4-Hydroxy Benzo Hydrazide. TDDFT calculations are also done on the same level of theory and a theoretical UV-vis spectrum of title molecules are also drawn. HOMO-LUMO analysis has been done to describe the way the molecule interacts with other species. Natural bond orbitals (NBO) analysis has been carried out to inspect the intra- and inter- molecular hydrogen-bonding, conjugative and hyper conjugative interactions and their second order stabilization energy. Nonlinear optical (NLO) analysis has been performed to study the non-linear optical properties of the molecule by computing the first hyperpolarizability. The variation of thermodynamic properties with temperature has been studied. QATIM analysis shows that hydrogen bonding occurs in 4HBH, isomer II and III respectively.
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Affiliation(s)
- Anoop Kumar Pandey
- K. S. Saket Post Graduate College, Ram Manohar Lohia University, Ayodhya, India
| | | | - Apoorva Dwivedi
- Department of Applied Science and Huminities, Seth Vishambhar Nath Institute of Engineering and Technology, Barabanki, India
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9
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Wakchaure PD, Ganguly B. Tuning the electronic effects in designing ligands for the inhibition of rotamase activity of FK506 binding protein. Theor Chem Acc 2021. [DOI: 10.1007/s00214-020-02717-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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10
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Urista DV, Carrué DB, Otero I, Arrasate S, Quevedo-Tumailli VF, Gestal M, González-Díaz H, Munteanu CR. Prediction of Antimalarial Drug-Decorated Nanoparticle Delivery Systems with Random Forest Models. BIOLOGY 2020; 9:biology9080198. [PMID: 32751710 PMCID: PMC7465777 DOI: 10.3390/biology9080198] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 07/22/2020] [Accepted: 07/27/2020] [Indexed: 12/13/2022]
Abstract
Drug-decorated nanoparticles (DDNPs) have important medical applications. The current work combined Perturbation Theory with Machine Learning and Information Fusion (PTMLIF). Thus, PTMLIF models were proposed to predict the probability of nanoparticle–compound/drug complexes having antimalarial activity (against Plasmodium). The aim is to save experimental resources and time by using a virtual screening for DDNPs. The raw data was obtained by the fusion of experimental data for nanoparticles with compound chemical assays from the ChEMBL database. The inputs for the eight Machine Learning classifiers were transformed features of drugs/compounds and nanoparticles as perturbations of molecular descriptors in specific experimental conditions (experiment-centered features). The resulting dataset contains 107 input features and 249,992 examples. The best classification model was provided by Random Forest, with 27 selected features of drugs/compounds and nanoparticles in all experimental conditions considered. The high performance of the model was demonstrated by the mean Area Under the Receiver Operating Characteristics (AUC) in a test subset with a value of 0.9921 ± 0.000244 (10-fold cross-validation). The results demonstrated the power of information fusion of the experimental-centered features of drugs/compounds and nanoparticles for the prediction of nanoparticle–compound antimalarial activity. The scripts and dataset for this project are available in the open GitHub repository.
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Affiliation(s)
- Diana V. Urista
- Department of Organic Chemistry II, University of Basque Country (UPV/EHU), Sarriena w/n, 48940 Leioa, Spain; (D.V.U.); (S.A.); (H.G.-D.)
| | - Diego B. Carrué
- RNASA-IMEDIR, Computer Science Faculty, CITIC, University of A Coruna, Campus Elviña s/n, 15071 A Coruña, Spain; (D.B.C.); (I.O.); (V.F.Q.-T.); (M.G.)
| | - Iago Otero
- RNASA-IMEDIR, Computer Science Faculty, CITIC, University of A Coruna, Campus Elviña s/n, 15071 A Coruña, Spain; (D.B.C.); (I.O.); (V.F.Q.-T.); (M.G.)
| | - Sonia Arrasate
- Department of Organic Chemistry II, University of Basque Country (UPV/EHU), Sarriena w/n, 48940 Leioa, Spain; (D.V.U.); (S.A.); (H.G.-D.)
| | - Viviana F. Quevedo-Tumailli
- RNASA-IMEDIR, Computer Science Faculty, CITIC, University of A Coruna, Campus Elviña s/n, 15071 A Coruña, Spain; (D.B.C.); (I.O.); (V.F.Q.-T.); (M.G.)
- Universidad Estatal Amazónica UEA, Km. 2 1/2 vía Puyo a Tena (paso lateral), Puyo 160150, Pastaza, Ecuador
| | - Marcos Gestal
- RNASA-IMEDIR, Computer Science Faculty, CITIC, University of A Coruna, Campus Elviña s/n, 15071 A Coruña, Spain; (D.B.C.); (I.O.); (V.F.Q.-T.); (M.G.)
- Biomedical Research Institute of A Coruña (INIBIC), Hospital Teresa Herrera, Xubias de Arriba 84, 15006 A Coruña, Spain
| | - Humbert González-Díaz
- Department of Organic Chemistry II, University of Basque Country (UPV/EHU), Sarriena w/n, 48940 Leioa, Spain; (D.V.U.); (S.A.); (H.G.-D.)
- IKERBASQUE, Basque Foundation for Science, Alameda Urquijo 36, 48011 Bilbao, Spain
- Basque Centre for Biophysics CSIC-UPVEHU, University of Basque Country UPV/EHU, Barrio Sarriena, 48940 Leioa, Spain
| | - Cristian R. Munteanu
- RNASA-IMEDIR, Computer Science Faculty, CITIC, University of A Coruna, Campus Elviña s/n, 15071 A Coruña, Spain; (D.B.C.); (I.O.); (V.F.Q.-T.); (M.G.)
- Biomedical Research Institute of A Coruña (INIBIC), Hospital Teresa Herrera, Xubias de Arriba 84, 15006 A Coruña, Spain
- Correspondence:
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11
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Pandey AK, Shukla DV, Singh P, Dwivedi A. Molecular Docking of a Bio Material [1-{[(Z)-Cyclopentylidene] Amino}-3-Phenylthiourea] by First Principles Study. Polycycl Aromat Compd 2019. [DOI: 10.1080/10406638.2019.1692878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Affiliation(s)
- Anoop Kumar Pandey
- Department of Physics, Saket Mahavidhyalaya, Ayodhya, Utter Pradesh, India
| | - D. V. Shukla
- Department of Physics, GLA University, Mathura, Utter Pradesh, India
| | - Prashant Singh
- Department of Physics, Rajendra College, Chhapra, Bihar, India
| | - Apoorva Dwivedi
- Department of Physics, Marwar Business School, Gorakhpur, Utter Pradesh, India
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12
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Diez-Alarcia R, Yáñez-Pérez V, Muneta-Arrate I, Arrasate S, Lete E, Meana JJ, González-Díaz H. Big Data Challenges Targeting Proteins in GPCR Signaling Pathways; Combining PTML-ChEMBL Models and [ 35S]GTPγS Binding Assays. ACS Chem Neurosci 2019; 10:4476-4491. [PMID: 31618004 DOI: 10.1021/acschemneuro.9b00302] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
G-protein-coupled receptors (GPCRs), also known as 7-transmembrane receptors, are the single largest class of drug targets. Consequently, a large amount of preclinical assays having GPCRs as molecular targets has been released to public sources like the Chemical European Molecular Biology Laboratory (ChEMBL) database. These data are also very complex covering changes in drug chemical structure and assay conditions like c0 = activity parameter (Ki, IC50, etc.), c1 = target protein, c2 = cell line, c3 = assay organism, etc., making difficult the analysis of these databases that are placed in the borders of a Big Data challenge. One of the aims of this work is to develop a computational model able to predict new GPCRs targeting drugs taking into consideration multiple conditions of assay. Another objective is to perform new predictive and experimental studies of selective 5-HTA2 receptor agonist, antagonist, or inverse agonist in human comparing the results with those from the literature. In this work, we combined Perturbation Theory (PT) and Machine Learning (ML) to seek a general PTML model for this data set. We analyzed 343 738 unique compounds with 812 072 end points (assay outcomes), with 185 different experimental parameters, 592 protein targets, 51 cell lines, and/or 55 organisms (species). The best PTML linear model found has three input variables only and predicted 56 202/58 653 positive outcomes (sensitivity = 95.8%) and 470 230/550 401 control cases (specificity = 85.4%) in training series. The model also predicted correctly 18 732/19 549 (95.8%) of positive outcomes and 156 739/183 469 (85.4%) of cases in external validation series. To illustrate its practical use, we used the model to predict the outcomes of six different 5-HT2A receptor drugs, namely, TCB-2, DOI, DOB, altanserin, pimavanserin, and nelotanserin, in a very large number of different pharmacological assays. 5-HT2A receptors are altered in schizophrenia and represent drug target for antipsychotic therapeutic activity. The model correctly predicted 93.83% (76 of 86) experimental results for these compounds reported in ChEMBL. Moreover, [35S]GTPγS binding assays were performed experimentally with the same six drugs with the aim of determining their potency and efficacy in the modulation of G-proteins in human brain tissue. The antagonist ketanserin was included as inactive drug with demonstrated affinity for 5-HT2A/C receptors. Our results demonstrate that some of these drugs, previously described as serotonin 5-HT2A receptor agonists, antagonists, or inverse agonists, are not so specific and show different intrinsic activity to that previously reported. Overall, this work opens a new gate for the prediction of GPCRs targeting compounds.
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Affiliation(s)
- Rebeca Diez-Alarcia
- Centro de Investigación Biomédica en Red en Salud Mental, 48940 Leioa, Spain
| | | | | | | | | | - J. Javier Meana
- Centro de Investigación Biomédica en Red en Salud Mental, 48940 Leioa, Spain
| | - Humbert González-Díaz
- Biophysics Institute, CSIC-UPV/EHU, University of the Basque Country UPV/EHU, Leioa, 48940, Spain
- IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain
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13
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Design and Synthesis of Benzimidazole-Chalcone Derivatives as Potential Anticancer Agents. Molecules 2019; 24:molecules24183259. [PMID: 31500191 PMCID: PMC6767017 DOI: 10.3390/molecules24183259] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 09/04/2019] [Accepted: 09/05/2019] [Indexed: 11/17/2022] Open
Abstract
Numerous reports have shown that conjugated benzimidazole derivatives possess various kinds of biological activities, including anticancer properties. In this report, we designed and synthesized 24 new molecules comprising a benzimidazole ring, arene, and alkyl chain-bearing cyclic moieties. The results showed that the N-substituted benzimidazole derivatives bearing an alkyl chain and a nitrogen-containing 5- or 6-membered ring enhanced the cytotoxic effects on human breast adenocarcinoma (MCF-7) and human ovarian carcinoma (OVCAR-3) cell lines. Among the 24 synthesized compounds, (2E)-1-(1-(3-morpholinopropyl)-1H-benzimidazol-2 -yl)-3-phenyl-2-propen-1-one) (23a) reduced the proliferation of MCF-7 and OVCAR-3 cell lines demonstrating superior outcomes to those of cisplatin.
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14
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Guney T, Wenderski TA, Boudreau MW, Tan DS. Synthesis of Benzannulated Medium-ring Lactams via a Tandem Oxidative Dearomatization-Ring Expansion Reaction. Chemistry 2018; 24:13150-13157. [PMID: 29936701 PMCID: PMC6242278 DOI: 10.1002/chem.201802880] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2018] [Indexed: 12/19/2022]
Abstract
Medium-ring natural products exhibit diverse biological activities but such scaffolds are underrepresented in probe and drug discovery efforts due to the limitations of classical macrocyclization reactions. We report herein a tandem oxidative dearomatization-ring-expanding rearomatization (ODRE) reaction that generates benzannulated medium-ring lactams directly from simple bicyclic substrates. The reaction accommodates diverse aryl substrates (haloarenes, aryl ethers, aryl amides, heterocycles) and strategic incorporation of a bridgehead alcohol generates a versatile ketone moiety in the products amenable to downstream modifications. Cheminformatic analysis indicates that these medium rings access regions of chemical space that overlap with related natural products and are distinct from synthetic drugs, setting the stage for their use in discovery screening against novel biological targets.
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Affiliation(s)
- Tezcan Guney
- Dr. T. Guney, Dr. T. A. W enderski, Prof. Dr. D. S. Tan,
Chemical Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer
Center, 1275 York Avenue, Box 422, New York, New York, 10065, USA
| | - Todd A. Wenderski
- Dr. T. Guney, Dr. T. A. W enderski, Prof. Dr. D. S. Tan,
Chemical Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer
Center, 1275 York Avenue, Box 422, New York, New York, 10065, USA
| | - Matthew W. Boudreau
- M. W. Boudreau, Gerstner Sloan Kettering Summer
Undergraduate Research Program, Memorial Sloan Kettering Cancer Center, 1275 York
Avenue, Box 422, New York, New York, 10065, USA
| | - Derek S. Tan
- Dr. T. Guney, Dr. T. A. W enderski, Prof. Dr. D. S. Tan,
Chemical Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer
Center, 1275 York Avenue, Box 422, New York, New York, 10065, USA
- Prof. Dr. D. S. Tan, Tri-Institutional Research Program,
Memorial Sloan Kettering Cancer Center, 1275 York Avenue, Box 422, New York, New
York, 10065, USA
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15
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Bak A, Kozik V, Smolinski A, Jampilek J. In silico estimation of basic activity-relevant parameters for a set of drug absorption promoters. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2017; 28:427-449. [PMID: 28573881 DOI: 10.1080/1062936x.2017.1327459] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2017] [Accepted: 05/03/2017] [Indexed: 06/07/2023]
Abstract
Finding a balance between a desired drug's potency and its physicochemical properties that are important for its molecule pharmacokinetic or pharmacodynamics profile is still a challenging issue in rational drug discovery. Quantitative assessment of the lipophilic characteristics of potential drug molecules is indispensable for efficient development of Absorption, Distribution, Metabolism, Excretion, Toxicity-tailored structure-activity models; therefore reliable procedures for deriving log P from molecular structure are desirable. In the current work a range of various software log P predictors for estimation of the numerical lipophilic values for a set of cholic acid derivatives were employed and subsequently cross-compared with the experimental parameters. Thus, the empirical lipophilicity (RM) was compared with the corresponding log P characteristics calculated using alternative methods for deducing the lipophilic features. The mean values of the selected molecular descriptors that were averaged over the chosen calculation methods (consensus clog P) were subsequently correlated with the RM parameter. As an additional experiment, the iterative variable elimination partial least squares (IVE-PLS) methodology for an ensemble of descriptors retrieved from Dragon 6.0 software was applied for a set of drug transporters. To investigate the variations within the ensemble of cholic acid derivatives principal component analysis (PCA) and self-organizing neural network (SOM) procedures were used to visualize the major differences in the performance of drug promoters with respect to their lipophilic profile.
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Affiliation(s)
- A Bak
- a Department of Organic Chemistry , University of Silesia , Katowice , Poland
| | - V Kozik
- b Department of Synthesis Chemistry , University of Silesia , Katowice , Poland
| | - A Smolinski
- c Department of Energy Saving and Air Protection , Central Mining Institute , Katowice , Poland
| | - J Jampilek
- d Department of Pharmaceutical Chemistry , Comenius University , Bratislava , Slovakia
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16
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Tetko IV, Maran U, Tropsha A. Public (Q)SAR Services, Integrated Modeling Environments, and Model Repositories on the Web: State of the Art and Perspectives for Future Development. Mol Inform 2016; 36. [PMID: 27778468 DOI: 10.1002/minf.201600082] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Accepted: 10/03/2016] [Indexed: 01/08/2023]
Abstract
Thousands of (Quantitative) Structure-Activity Relationships (Q)SAR models have been described in peer-reviewed publications; however, this way of sharing seldom makes models available for the use by the research community outside of the developer's laboratory. Conversely, on-line models allow broad dissemination and application representing the most effective way of sharing the scientific knowledge. Approaches for sharing and providing on-line access to models range from web services created by individual users and laboratories to integrated modeling environments and model repositories. This emerging transition from the descriptive and informative, but "static", and for the most part, non-executable print format to interactive, transparent and functional delivery of "living" models is expected to have a transformative effect on modern experimental research in areas of scientific and regulatory use of (Q)SAR models.
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Affiliation(s)
- Igor V Tetko
- Institute of Structural Biology, Helmholtz Zentrum München -, German Research Center for Environmental Health (GmbH), Institute of Structural Biology, Ingolstädter Landstraße 1, D-, 85764, Neuherberg, Germany.,BigChem GmbH, Ingolstädter Landstraße 1, b. 60w, D-, 85764, Neuherberg, Germany
| | - Uko Maran
- Institute of Chemistry, University of Tartu, Ravila 14A, Tartu, 50411, Estonia
| | - Alexander Tropsha
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA.,Butlerov Institute of Chemistry, Kazan Federal University, Kremlyovskaya St. 18, 420008, Kazan, Russia
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17
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Colley HE, Muthana M, Danson SJ, Jackson LV, Brett ML, Harrison J, Coole SF, Mason DP, Jennings LR, Wong M, Tulasi V, Norman D, Lockey PM, Williams L, Dossetter AG, Griffen EJ, Thompson MJ. An Orally Bioavailable, Indole-3-glyoxylamide Based Series of Tubulin Polymerization Inhibitors Showing Tumor Growth Inhibition in a Mouse Xenograft Model of Head and Neck Cancer. J Med Chem 2015; 58:9309-33. [DOI: 10.1021/acs.jmedchem.5b01312] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Affiliation(s)
- Helen E. Colley
- School
of Clinical Dentistry, University of Sheffield, 19 Claremont Crescent, Sheffield S10 2TA, U.K
| | - Munitta Muthana
- Department
of Oncology, The University of Sheffield, Medical School, Beech
Hill Road, Sheffield S10
2RX, U.K
| | - Sarah J. Danson
- Academic
Unit of Clinical Oncology and Sheffield Experimental Medicine Centre, Weston Park Hospital, Whitham Road, Sheffield S10 2SJ, U.K
| | - Lucinda V. Jackson
- Department
of Chemistry, University of Sheffield, Brook Hill, Sheffield S3 7HF, U.K
| | - Matthew L. Brett
- Department
of Chemistry, University of Sheffield, Brook Hill, Sheffield S3 7HF, U.K
| | - Joanne Harrison
- Department
of Chemistry, University of Sheffield, Brook Hill, Sheffield S3 7HF, U.K
| | - Sean F. Coole
- Department
of Chemistry, University of Sheffield, Brook Hill, Sheffield S3 7HF, U.K
| | - Daniel P. Mason
- Department
of Chemistry, University of Sheffield, Brook Hill, Sheffield S3 7HF, U.K
| | - Luke R. Jennings
- School
of Clinical Dentistry, University of Sheffield, 19 Claremont Crescent, Sheffield S10 2TA, U.K
| | - Melanie Wong
- Charles River, 8−9 Spire
Green Centre, Harlow, Harlow, Essex CM19 5TR, U.K
| | - Vamshi Tulasi
- Charles River, 8−9 Spire
Green Centre, Harlow, Harlow, Essex CM19 5TR, U.K
| | - Dennis Norman
- Charles River, 8−9 Spire
Green Centre, Harlow, Harlow, Essex CM19 5TR, U.K
| | - Peter M. Lockey
- Charles River, 8−9 Spire
Green Centre, Harlow, Harlow, Essex CM19 5TR, U.K
| | - Lynne Williams
- Department
of Oncology, The University of Sheffield, Medical School, Beech
Hill Road, Sheffield S10
2RX, U.K
| | - Alexander G. Dossetter
- MedChemica Limited, Ebenezer House,
Ryecroft, Newcastle-Under-Lyme, Staffordshire ST5 2BE, U.K
| | - Edward J. Griffen
- MedChemica Limited, Ebenezer House,
Ryecroft, Newcastle-Under-Lyme, Staffordshire ST5 2BE, U.K
| | - Mark J. Thompson
- Department
of Chemistry, University of Sheffield, Brook Hill, Sheffield S3 7HF, U.K
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18
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Messina PV, Besada-Porto JM, González-Díaz H, Ruso JM. Self-Assembled Binary Nanoscale Systems: Multioutput Model with LFER-Covariance Perturbation Theory and an Experimental-Computational Study of NaGDC-DDAB Micelles. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2015; 31:12009-12018. [PMID: 26484726 DOI: 10.1021/acs.langmuir.5b03074] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Studies of the self-aggregation of binary systems are of both theoretical and practical importance. They provide an opportunity to investigate the influence of the molecular structure of the hydrophobe on the nonideality of mixing. On the other hand, linear free energy relationship (LFER) models, such as Hansch's equations, may be used to predict the properties of chemical compounds such as drugs or surfactants. However, the task becomes more difficult once we want to predict simultaneaously the effect over multiple output properties of binary systems of perturbations under multiple input experimental boundary conditions (b(j)). As a consequence, we need computational chemistry or chemoinformatics models that may help us to predict different properties of the autoaggregation process of mixed surfactants under multiple conditions. In this work, we have developed the first model that combines perturbation theory (PT) and LFER ideas. The model uses as input covariance PT operators (CPTOs). CPTOs are calculated as the difference between covariance ΔCov((i)μ(k)) functions before and after multiple perturbations in the binary system. In turn, covariances calculated as the product of two Box-Jenkins operators (BJO) operators. BJOs are used to measure the deviation of the structure of different chemical compounds from a set of molecules measured under a given subset of experimental conditions. The best CPT-LFER model found predicted the effects of 25,000 perturbations over 9 different properties of binary systems. We also reported experimental studies of different experimental properties of the binary system formed by sodium glycodeoxycholate and didodecyldimethylammonium bromide (NaGDC-DDAB). Last, we used our CPT-LFER model to carry out a 1000 data point simulation of the properties of the NaGDC-DDAB system under different conditions not studied experimentally.
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Affiliation(s)
- Paula V Messina
- Department of Chemistry, INQUISUR-CONICET, Universidad Nacional del Sur , 8000 Bahía Blanca, Argentina
| | - Jose Miguel Besada-Porto
- Soft Matter and Molecular Biophysics Group, Department of Applied Physics, University of Santiago de Compostela , Santiago de Compostela E-15782, Spain
| | - Humberto González-Díaz
- Department of Organic Chemistry II, Faculty of Science and Technology, University of the Basque Country UPV/EHU , 48940 Leioa, Spain
- IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain
| | - Juan M Ruso
- Soft Matter and Molecular Biophysics Group, Department of Applied Physics, University of Santiago de Compostela , Santiago de Compostela E-15782, Spain
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19
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Stratton CF, Newman DJ, Tan DS. Cheminformatic comparison of approved drugs from natural product versus synthetic origins. Bioorg Med Chem Lett 2015; 25:4802-4807. [PMID: 26254944 PMCID: PMC4607632 DOI: 10.1016/j.bmcl.2015.07.014] [Citation(s) in RCA: 112] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 07/08/2015] [Indexed: 11/27/2022]
Abstract
Despite the recent decline of natural product discovery programs in the pharmaceutical industry, approximately half of all new drug approvals still trace their structural origins to a natural product. Herein, we use principal component analysis to compare the structural and physicochemical features of drugs from natural product-based versus completely synthetic origins that were approved between 1981 and 2010. Drugs based on natural product structures display greater chemical diversity and occupy larger regions of chemical space than drugs from completely synthetic origins. Notably, synthetic drugs based on natural product pharmacophores also exhibit lower hydrophobicity and greater stereochemical content than drugs from completely synthetic origins. These results illustrate that structural features found in natural products can be successfully incorporated into synthetic drugs, thereby increasing the chemical diversity available for small-molecule drug discovery.
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Affiliation(s)
- Christopher F Stratton
- Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, Box 422, New York, NY 10065, USA
| | - David J Newman
- Natural Products Branch, Developmental Therapeutics Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Frederick, PO Box B, Frederick, MD 21702, USA
| | - Derek S Tan
- Tri-Institutional PhD Program in Chemical Biology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, Box 422, New York, NY 10065, USA; Chemical Biology Program and Tri-Institutional Research Program, Memorial Sloan Kettering Cancer Center, 1275 York Ave, Box 422, New York, NY 10065, USA
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20
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Liu Y, Buendía-Rodríguez G, Peñuelas-Rívas CG, Tan Z, Rívas-Guevara M, Tenorio-Borroto E, Munteanu CR, Pazos A, González-Díaz H. Experimental and computational studies of fatty acid distribution networks. MOLECULAR BIOSYSTEMS 2015; 11:2964-77. [DOI: 10.1039/c5mb00325c] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
A new PT-LFER model is useful for predicting a distribution network in terms of specific fatty acid distribution.
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Affiliation(s)
- Yong Liu
- Faculty of Veterinary Medicine and Animal Science
- Autonomous University of the State of Mexico
- Toluca
- Mexico
- Key Laboratory of Subtropical Agro-ecological Engineering
| | - Germán Buendía-Rodríguez
- National Center for Disciplinary Research on Animal Physiology and Breeding
- National Institute of Forestry
- Agriculture and Livestock Research
- Queretaro
- Mexico
| | | | - Zhiliang Tan
- Key Laboratory of Subtropical Agro-ecological Engineering
- Institute of Subtropical Agriculture, the Chinese Academy of Sciences
- Changsha
- P. R. China
| | - María Rívas-Guevara
- Ethnobiology and Biodiversity Research Center
- Chapingo Autonomous University
- Texcoco
- Mexico
| | - Esvieta Tenorio-Borroto
- Faculty of Veterinary Medicine and Animal Science
- Autonomous University of the State of Mexico
- Toluca
- Mexico
| | | | | | - Humberto González-Díaz
- Department of Organic Chemistry II
- Faculty of Science and Technology
- University of the Basque Country UPV/EHU
- Leioa
- Spain
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21
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Srivastava AK, Misra N. A comparative theoretical study on the biological activity, chemical reactivity, and coordination ability of dichloro-substituted (1,3-thiazol-2-yl)acetamides. CAN J CHEM 2014. [DOI: 10.1139/cjc-2013-0335] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
We present a theoretical study on three dichloro-substituted (1,3-thiazol-2-yl)acetamides using the first principle density functional approach. Natural bonding orbital analysis is used to discuss the coordination ability of molecules and various global reactivity descriptors are calculated to compare their chemical reactivity. Biological activities of all three molecules are also evaluated. We find that the present molecules show potential coordination ability and their chemical reactivity varies with the position of substitution. We also notice that all three molecules show remarkable biological activities and the (3,4)-dichloro-substituted molecule is relatively more active. The study suggests further investigations on these molecules for their pharmacological importance.
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Affiliation(s)
| | - Neeraj Misra
- Department of Physics, University of Lucknow, Lucknow-226007, India
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22
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Opletalová V, Kastner P, Kučerová-Chlupáčová M, Palát K. Study of hydrophobic properties of biologically active open analogues of flavonoids. J Mol Graph Model 2013; 39:61-4. [DOI: 10.1016/j.jmgm.2012.07.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2011] [Revised: 07/03/2012] [Accepted: 07/30/2012] [Indexed: 11/30/2022]
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23
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Wikoff WR, Nagle MA, Kouznetsova VL, Tsigelny IF, Nigam SK. Untargeted metabolomics identifies enterobiome metabolites and putative uremic toxins as substrates of organic anion transporter 1 (Oat1). J Proteome Res 2011; 10:2842-51. [PMID: 21476605 DOI: 10.1021/pr200093w] [Citation(s) in RCA: 138] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Untargeted metabolomics on the plasma and urine from wild-type and organic anion transporter-1 (Oat1/Slc22a6) knockout mice identified a number of physiologically important metabolites, including several not previously linked to Oat1-mediated transport. Several, such as indoxyl sulfate, derive from Phase II metabolism of enteric gut precursors and accumulate in chronic kidney disease (CKD). Other compounds included vitamins (pantothenic acid, 4-pyridoxic acid), urate, and metabolites in the tryptophan and nucleoside pathways. Three metabolites, indoxyl sulfate, kynurenine, and xanthurenic acid, were elevated in the plasma and interacted strongly and directly with Oat1 in vitro with IC50 of 18, 12, and 50 μM, respectively. A pharmacophore model based on several identified Oat1 substrates was used to screen the NCI database and candidate compounds interacting with Oat1 were validated in an in vitro assay. Together, the data suggest a complex, previously unidentified remote communication between the gut microbiome, Phase II metabolism in the liver, and elimination via Oats of the kidney, as well as indicating the importance of Oat1 in the handling of endogenous toxins associated with renal failure and uremia. The possibility that some of the compounds identified may be part of a larger remote sensing and signaling pathway is also discussed.
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24
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Ruggiu F, Marcou G, Varnek A, Horvath D. ISIDA Property-Labelled Fragment Descriptors. Mol Inform 2010; 29:855-68. [DOI: 10.1002/minf.201000099] [Citation(s) in RCA: 96] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2010] [Accepted: 11/19/2010] [Indexed: 11/08/2022]
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25
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Modelling, solubility and pK(a) of five sparingly soluble drugs. Int J Pharm 2010; 403:115-22. [PMID: 21034801 DOI: 10.1016/j.ijpharm.2010.10.034] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2010] [Revised: 10/11/2010] [Accepted: 10/19/2010] [Indexed: 11/23/2022]
Abstract
Drug solubility is an important aspect of drug development. The objective of this investigation was to measure solubilities of five drugs (cimetidine, phenylbutazone, fenbufen, nitrofurantoin, triamterene) at constant pH in range of temperature from 270 to 340K in three solvents: water, ethanol and 1-octanol with the dynamic-visual method and the saturation shake-flask method using spectrophotometric analysis. The Barton group contribution method was used for the calculations of molar volumes of solutes. The thermodynamic description of the solubility curves was made using the thermophysical properties obtained with the differential scanning microcalorimetry technique (DSC). The DSC measurements have shown different than existing in the literature enthalpies of melting for phenylbutazone and fenbufen. The experimental solubility data also differ from the literature data, normally measured at one, or two temperatures only. The solubility data have been correlated by means of three commonly known excess Gibbs energy, G(E) equations. The activity coefficients of drugs at saturated solutions were calculated from the experimental data. Reexamination of the pK(a) values using diluted solutions was made with the Bates-Schwarzenbach method for the pK(a) measurements. The association constants and corresponding pK(a) values of drugs were close to the most of the literature data. We hope that our new solubility data, thermophysical data, and pK(a) values will improve all prediction-methods and their precision.
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26
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Gozalbes R, Pineda-Lucena A. QSAR-based solubility model for drug-like compounds. Bioorg Med Chem 2010; 18:7078-84. [PMID: 20810286 DOI: 10.1016/j.bmc.2010.08.003] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2010] [Revised: 07/19/2010] [Accepted: 08/02/2010] [Indexed: 01/29/2023]
Abstract
Solubility plays a very important role in the selection of compounds for drug screening. In this context, a QSAR model was developed for predicting water solubility of drug-like compounds. First, a set of relevant parameters for establishing a drug-like chemical space was defined. The comparison of chemical structures from the FDAMDD and PHYSPROP databases allowed the selection of properties that were more efficient in discriminating drug-like compounds from other chemicals. These filters were later on applied to the PHYSPROP database and 1174 chemicals fulfilling these criteria and with experimental solubility information available at 25°C were retained. Several QSAR solubility models were developed from this set of compounds, and the best one was selected based on the accuracy of correct classifications obtained for randomly chosen training and validation subsets. Further validation of the model was performed with a set of 102 drugs for which experimental solubility data have been recently reported. A good agreement between the predictions and the experimental values confirmed the reliability of the QSAR model.
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Affiliation(s)
- Rafael Gozalbes
- Structural Biochemistry Laboratory, Department of Medicinal Chemistry, Centro de Investigación Príncipe Felipe, Avda. Autopista del Saler 16, 46012 Valencia, Spain.
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27
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Abstract
Chemical reactions that enable selective biomolecule labeling in living organisms offer a means to probe biological processes in vivo. Very few reactions possess the requisite bioorthogonality, and, among these, only the Staudinger ligation between azides and triarylphosphines has been employed for direct covalent modification of biomolecules with probes in the mouse, an important model organism for studies of human disease. Here we explore an alternative bioorthogonal reaction, the 1,3-dipolar cycloaddition of azides and cyclooctynes, also known as "Cu-free click chemistry," for labeling biomolecules in live mice. Mice were administered peracetylated N-azidoacetylmannosamine (Ac(4)ManNAz) to metabolically label cell-surface sialic acids with azides. After subsequent injection with cyclooctyne reagents, glycoconjugate labeling was observed on isolated splenocytes and in a variety of tissues including the intestines, heart, and liver, with no apparent toxicity. The cyclooctynes tested displayed various labeling efficiencies that likely reflect the combined influence of intrinsic reactivity and bioavailability. These studies establish Cu-free click chemistry as a bioorthogonal reaction that can be executed in the physiologically relevant context of a mouse.
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28
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Djaković-Sekulić T, Perišić-Janjić N, Djurendi E. Retention data from reverse-phase high-performance thin-layer chromatography in characterization of some bis-salicylic acid derivatives. Biomed Chromatogr 2009; 23:881-7. [DOI: 10.1002/bmc.1200] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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29
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Shiraishi Y, Tsukamoto D, Hirai T. Selective photocatalytic transformations on microporous titanosilicate ETS-10 driven by size and polarity of molecules. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2008; 24:12658-12663. [PMID: 18844379 DOI: 10.1021/la802513g] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Photocatalytic activity of microporous titanosilicate ETS-10 has been studied in water. The photoactivated ETS-10 shows catalytic activity driven by size and polarity of substrates. ETS-10 efficiently catalyzes a conversion of substrates with a size larger than the pore diameter of ETS-10. In contrast, the reactivity of small substrates depends strongly on substrate polarity; less polar substrates show higher reactivity on ETS-10. Electron spin resonance analysis reveals that large substrates or less polar substrates scarcely diffuse inside the highly polarized micropores of ETS-10 and, hence, react efficiently with hydroxyl radicals (*OH) formed on titanol (Ti-OH) groups exposed on the external surface of ETS-10. In contrast, small polar substrates diffuse easily inside the micropores of ETS-10 and scarcely react with *OH, resulting in low reactivity. The photocatalytic activity of ETS-10 is successfully applicable to selective transformations of large reactants or less polar reactants to small polar products, enabling highly selective dehalogenation and hydroxylation of aromatics.
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Affiliation(s)
- Yasuhiro Shiraishi
- Research Center for Solar Energy Chemistry, Graduate School of Engineering Science, Osaka University, Toyonaka, Japan.
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30
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Krzek J, Kwiecień A, Zylewski M. Stability of Atenolol, Acebutolol and Propranolol in Acidic Environment Depending on its Diversified Polarity. Pharm Dev Technol 2008; 11:409-16. [PMID: 17101511 DOI: 10.1080/10837450600770106] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
The main objective of this research was to investigate the relationship between the polarity of atenolol, acebutolol, and propranolol described by logP and kinetic and thermodynamic parameters characterizing their degradation process in acidic solution. Hydrolysis was carried out in hydrochloric acid at molal concentrations of 0.1 mol/L, 0.5 mol/L, and 1 mol/L for 2 hr at 40 degrees C, 60 degrees C, and 90 degrees C. Chromatographic-densitometric method was used for the determination of drugs under investigation. The identification of degradation products was carried out by using 1H NMR. The degradation processes that occurred in drugs under investigation are described with kinetic parameters (k, t0.1, and t0.5) and energy of activation (Ea). It has been found that the stability of drugs increases toward lipophilic propranolol in the assumed experimental model. The rate constants k decrease, contrary to t0.1, t0.5, and Ea, which vary comparably to logP, thus increasing from the most hydrophilic atenolol, through acebutolol, of lower polarity, to the most lipophilic propranolol. This study demonstrated that the stability of chosen beta-adrenergic blocking agents increases with their lipophilicity.
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Affiliation(s)
- Jan Krzek
- Collegium Medicum, Department of Inorganic and Analytical Chemistry, Jagiellonian University, Kraków, Poland.
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31
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Toropov A, Toropova A, Benfenati E. QSPR modeling for enthalpies of formation of organometallic compounds by means of SMILES-based optimal descriptors. Chem Phys Lett 2008. [DOI: 10.1016/j.cplett.2008.07.027] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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32
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Tetko IV, Gasteiger J, Todeschini R, Mauri A, Livingstone D, Ertl P, Palyulin VA, Radchenko EV, Zefirov NS, Makarenko AS, Tanchuk VY, Prokopenko VV. Virtual computational chemistry laboratory--design and description. J Comput Aided Mol Des 2008; 19:453-63. [PMID: 16231203 DOI: 10.1007/s10822-005-8694-y] [Citation(s) in RCA: 1020] [Impact Index Per Article: 63.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2005] [Accepted: 06/13/2005] [Indexed: 11/27/2022]
Abstract
Internet technology offers an excellent opportunity for the development of tools by the cooperative effort of various groups and institutions. We have developed a multi-platform software system, Virtual Computational Chemistry Laboratory, http://www.vcclab.org, allowing the computational chemist to perform a comprehensive series of molecular indices/properties calculations and data analysis. The implemented software is based on a three-tier architecture that is one of the standard technologies to provide client-server services on the Internet. The developed software includes several popular programs, including the indices generation program, DRAGON, a 3D structure generator, CORINA, a program to predict lipophilicity and aqueous solubility of chemicals, ALOGPS and others. All these programs are running at the host institutes located in five countries over Europe. In this article we review the main features and statistics of the developed system that can be used as a prototype for academic and industry models.
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Affiliation(s)
- Igor V Tetko
- Institute of Bioorganic & Petroleum Chemistry, Kyiv, Ukraine.
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33
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Abstract
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Biomolecules labeled with azides can be detected through Cu-free click chemistry with cyclooctyne probes, but their intrinsic hydrophobicity can compromise bioavailability. Here, we report the synthesis and evaluation of a novel azacyclooctyne, 6,7-dimethoxyazacyclooct-4-yne (DIMAC). Generated in nine steps from a glucose analogue, DIMAC reacted with azide-labeled proteins and cells similarly to cyclooctynes. However, its superior polarity and water solubility reduced nonspecific binding, thereby improving the sensitivity of azide detection.
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Affiliation(s)
- Ellen M Sletten
- Department of Chemistry and Molecular and Cell Biology and Howard Hughes Medical Institute, University of California, California, USA
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34
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Karthikeyan M, Krishnan S, Pandey AK, Bender A, Tropsha A. Distributed Chemical Computing Using ChemStar: An Open Source Java Remote Method Invocation Architecture Applied to Large Scale Molecular Data from PubChem. J Chem Inf Model 2008; 48:691-703. [DOI: 10.1021/ci700334f] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- M. Karthikeyan
- Digital Information Resource Center, Information Division, National Chemical Laboratory, Pune 411008, India
| | - S. Krishnan
- Digital Information Resource Center, Information Division, National Chemical Laboratory, Pune 411008, India
| | - Anil Kumar Pandey
- Munich Information Center for Protein Sequences (MIPS), Institute for Bioinformatics, Helmholtz Zentrum München German Research Center for Environmental Health (GmbH), Ingolstaedter Landstrasse 1, 85764 Neuherberg (bei Munich), Germany
| | - Andreas Bender
- Leiden/Amsterdam Center for Drug Research, Division of Medicinal Chemistry, Leiden University, Gorlaeus Laboratories, Einsteinweg 55, 2333 CC Leiden, The Netherlands
| | - Alexander Tropsha
- Laboratory for Molecular Modeling, School of Pharmacy and Department of Pharmacology, School of Medicine, University of North Carolina, Chapel Hill, North Carolina 27599
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35
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Molecular Actions of Propofol on Human 5-HT3A Receptors: Enhancement as Well as Inhibition by Closely Related Phenol Derivatives. Anesth Analg 2008; 106:846-57, table of contents. [DOI: 10.1213/ane.0b013e318162ca7c] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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36
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Buyukbingol E, Sisman A, Akyildiz M, Alparslan FN, Adejare A. Adaptive neuro-fuzzy inference system (ANFIS): A new approach to predictive modeling in QSAR applications: A study of neuro-fuzzy modeling of PCP-based NMDA receptor antagonists. Bioorg Med Chem 2007; 15:4265-82. [PMID: 17434739 DOI: 10.1016/j.bmc.2007.03.065] [Citation(s) in RCA: 53] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2006] [Accepted: 03/20/2007] [Indexed: 11/18/2022]
Abstract
This paper proposes a new method, Adaptive Neuro-Fuzzy Inference System (ANFIS) to evaluate physicochemical descriptors of certain chemical compounds for their appropriate biological activities in terms of QSAR models with the aid of artificial neural network (ANN) approach combined with the principle of fuzzy logic. The ANFIS was utilized to predict NMDA (N-methyl-d-Aspartate) receptor binding activities of phencyclidine (PCP) derivatives. A data set of 38 drug-like compounds was coded with 1244 calculated molecular structure descriptors (clustered in 20 data sets) which were obtained from several sources, mainly from Dragon software. Prior to the progress to the ANFIS system, descriptors from the best subsets were selected using unsupervised forward selection (UFS) to eliminate redundancy and multicollinearity followed by fuzzy linear regression algorithm (FLR) which was used for variable selection. ANFIS was applied to train the final descriptors (Mor22m, E3s, R3v+, and R1e+) using a hybrid algorithm consisting of back-propagation and least-square estimation while the optimum number and shape of related functions were obtained through the subtractive clustering algorithm. Comparison of the proposed method with traditional methods, that is, multiple linear regression (MLR) and partial least-square (PLS) was also studied and the results indicated that the ANFIS model obtained from data sets achieved satisfactory accuracy.
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Affiliation(s)
- Erdem Buyukbingol
- Ankara University, Faculty of Pharmacy (ECZACILIK), Department of Pharmaceutical Chemistry, Tandogan 06100, Ankara, Turkey.
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Montanari MLC, Gaudio AC, Leitão A, de Almeida TMG, Montanari CA. Chemometric Characterization of Chromatographic Retention Parameters of Mesoionic 1,3,4‐Thiadiazolium‐3‐Aminides by Molecular Interaction Fields. J LIQ CHROMATOGR R T 2007. [DOI: 10.1080/10826070500451830] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
| | - Anderson C. Gaudio
- b Departamento de Física , Universidade Federal do Espírito Santo , Vitória, ES, Brazil
| | - Andrei Leitão
- c Núcleo de Estudos em Química Medicinal‐NEQUIM , Universidade Federal de Minas Gerais , Belo Horizonte, MG, Brazil
| | - Tânia M. G. de Almeida
- c Núcleo de Estudos em Química Medicinal‐NEQUIM , Universidade Federal de Minas Gerais , Belo Horizonte, MG, Brazil
| | - Carlos A. Montanari
- d Departamento de Química e Física Molecular , Instituto de Química de São Carlos, Universidade de São Paulo , São Carlos, SP, Brazil
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Mornar A, Medić-Šarić M, Jasprica I. ADME Data for polyphenols characterized by reversed-phase thin-layer chromatography. JPC-J PLANAR CHROMAT 2006. [DOI: 10.1556/jpc.19.2006.6.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Tubic M, Wagner D, Spahn-Langguth H, Bolger MB, Langguth P. In Silico Modeling of Non-Linear Drug Absorption for the P-gp Substrate Talinolol and of Consequences for the Resulting Pharmacodynamic Effect. Pharm Res 2006; 23:1712-20. [PMID: 16832615 DOI: 10.1007/s11095-006-9020-7] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2005] [Accepted: 03/23/2006] [Indexed: 10/24/2022]
Abstract
PURPOSE The aim of the present work was to demonstrate P-glycoprotein's involvement in the non-linear talinolol pharmacokinetics using an advanced compartment and transit model (ACAT) and to compare the results predicted from the model to the finding of a phase I dose escalation study with oral talinolol doses increasing from 25 to 400 mg. MATERIALS AND METHODS Besides minimum input parameters for the compound (pKa(s), solubility at one or more pH's, Peff, doses, formulation, diffusivity), physiological and pharmacokinetic properties, transporter data are included in these predictions. The simulations assumed higher expression levels in lower gastrointestinal regions, in particular in the colon, which is in accordance with the results of intestinal rat perfusion studies and intestinal distribution data from rats, catfishes, micropigs and humans reported in the literature. Optimized values for P-glycoprotein (P-gp) Km and Vmax were used for the final simulation results and for a stochastic virtual trial with 12 patients. RESULTS Talinolol, a P-gp substrate, exhibits non-linear dose AUC relationship after administration of 25, 50, 100 and 400 mg immediate-release tablets. This dose dependency is due to a decrease of efflux transport caused by saturation of P-gp by talinolol. It was found that oral bioavailability increases after administration of higher doses of talinolol. The predicted bioavailability of the p.o. 25, 50, 100 and 400 mg doses of talinolol was 64, 76, 85, 94%, respectively. Pharmacokinetic parameters (AUC, Cmax) from in silico simulations are within acceptable range comparing with data, observed in vivo. However, the in vitro value of Km for talinolol's interactions with P-gp could not be used in the simulation and still reproduce the observed non-linear dose dependence. For each of the four doses, GastroPlus was used to model pharmacodynamic (PD) response and to optimize the values of CLe, Emax, and EC5o with the effect compartment linked indirectly to the central compartment. For all simulations, EC50 was 114 nM and E0 was 83 bpm. CONCLUSION Comparison between the results of the in vivo study and the in silico simulations determined the quality and reliability of the in silico predictions and demonstrate the simulation of dose dependent absorption. In contrast to previous simulation work for the non-linear dose dependence of interaction with intestinal transporters or enterocyte metabolism, optimized Km and Vmax values were required to reproduce the clinically observed non-linear dose dependence. The model developed may be useful in the prediction of absorption of other P-gp substrates including pharmacodynamic consequences.
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Affiliation(s)
- Marija Tubic
- Pharmazeutische Technologie und Biopharmazie, Institut fuer Pharmazie, Johannes Gutenberg-Universitaet, Staudinger Weg 5, 55099, Mainz, Germany
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Abstract
We describe an Oracle database application for general use within virtual chemistry. The application functions as a central hub and repository for chemical data with interfaces to external calculators. It deals with the general problems of merging data from disparate sources and with scheduling of computational tasks for parallel or sequential execution in a mixed environment. The central database is used for the storage of input, intermediary, and final data as well as for job control. A calculation job is split into distinct tasks, or units of work, which are put in a queue. Tasks are dequeued and handled by specialized calculators. These calculators are in-house or commercial programs for which adaptor modules for connection to the database must be written. Tasks are handled in a transactional fashion, so that uncompleted or failed tasks are left in the queue. This makes the system stable to many types of disturbances. Sorting, filtering, and merging operations are handled by the database itself. Usage is very general, but some specific examples are (1) as a back end for a chemical property calculator Web page, (2) in an automated quantitative structure-activity relationship system, and (3) in virtual screens.
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Affiliation(s)
- Peter Lind
- Medivir AB, Lunastigen 7, 144 44 Huddinge, Sweden.
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Abstract
High-resolution X-ray diffraction structures of integral membrane proteins have revealed various binding modes of lipids, but current spectroscopic studies still use uniform macroscopic binding constants to describe lipid binding. The Adair approach employing microscopic lipid-binding constants has previously been taken to explain the enhancement of agonist binding to the nicotinic acetylcholine receptor by general anaesthetics in terms of the competitive displacement of essential lipid activator molecules [Walcher S, Altschuh J & Sandermann H (2001) J. Biol. Chem.276, 42191-42195]. This approach was extended to tadpole narcosis induced by alcohols. A single class, or two different classes of lipid activator binding sites, are considered. Microscopic lipid and inhibitor binding constants are derived and allow a close fit to dose-response curves of tadpole narcosis on the basis of a preferential displacement of more loosely bound essential lipid activator molecules. This study illustrates the potential of the Adair approach to resolve protein-bound lipid populations.
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Affiliation(s)
- Joachim Altschuh
- Institute of Biomathematics and Biometry, GSF - National Research Center for Environment and Health, Neuherberg, Germany
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Voda K, Boh B, Vrtacnik M. A quantitative structure-antifungal activity relationship study of oxygenated aromatic essential oil compounds using data structuring and PLS regression analysis. J Mol Model 2003; 10:76-84. [PMID: 14689256 DOI: 10.1007/s00894-003-0174-5] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2003] [Accepted: 11/14/2003] [Indexed: 11/28/2022]
Abstract
Twenty two oxygenated aromatic essential oil compounds were chosen for the study of the antifungal activity against two wood-decaying fungi, the white-rot Trametes versicolor, which mainly metabolizes lignin, and the brown-rot Coniophoha puteana, which digests cellulose in plant cell walls. Minimal inhibitory concentrations (MICs) were determined by the agar dilution method, using dimethyl sulfoxide (DMSO) as the solvent for the selected compounds and potato-dextrose agar (PDA) as the growth medium for both fungi. The MICs were then used to generate a tree structure, which represents the structuring of the essential oil compounds by the nature and position of the substituents in their aromatic rings, and as dependent variables (log(1/MIC)) in the QSAR analysis. Data structuring proved that a relationship between the molecular structures of the essential oil compounds and their antifungal activity exists, and the hypotheses derived therefrom were complemented by performing a QSAR analysis using the partial least squares (PLS) method. Statistically significant PLS models were obtained with the 1-octanol-water partition coefficient (C log P), the energy of the highest occupied molecular orbital (E(HOMO)), and the number of hydrogen-bond donor atoms in the molecules of the compounds studied (Donor) for T. versicolor and with C log P and the fractional negative surface area (FNSA1) for C. puteana.
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Affiliation(s)
- Karmen Voda
- Department of Chemical Education and Informatics, Faculty of Natural Sciences and Engineering, University of Ljubljana, Vegova 4, 1000 Ljubljana, Slovenia.
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Taskinen J, Yliruusi J. Prediction of physicochemical properties based on neural network modelling. Adv Drug Deliv Rev 2003; 55:1163-83. [PMID: 12954197 DOI: 10.1016/s0169-409x(03)00117-0] [Citation(s) in RCA: 167] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
The literature describing neural network modelling to predict physicochemical properties of organic compounds from the molecular structure is reviewed from the perspective of pharmaceutical research. The standard three-layer, feed-forward neural network is the technique most frequently used, although the use of other techniques is increasing. Various approaches to describe the molecular structure have been successfully used, including molecular fragments, topological indices, and descriptors calculated by semi-empirical quantum chemical methods. Some physicochemical properties, such as octanol-water partition coefficient, water solubility, boiling point and vapour pressure, have been modelled by several research groups over the years using different approaches and structurally diverse large training sets. The prediction accuracy of most models seems to be rather close to the performance of the experimental measurements, when the accuracy is assessed with a test set from the working database. Results with independent test sets have been less satisfactory. Implications of this problem are discussed.
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Affiliation(s)
- Jyrki Taskinen
- Viikki Drug Discovery Technology Center, Department of Pharmacy, University of Helsinki, Helsinki, Finland.
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Tetko IV, Tanchuk VY. Application of associative neural networks for prediction of lipophilicity in ALOGPS 2.1 program. JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES 2002; 42:1136-45. [PMID: 12377001 DOI: 10.1021/ci025515j] [Citation(s) in RCA: 414] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
This article provides a systematic study of several important parameters of the Associative Neural Network (ASNN), such as the number of networks in the ensemble, distance measures, neighbor functions, selection of smoothing parameters, and strategies for the user-training feature of the algorithm. The performance of the different methods is assessed with several training/test sets used to predict lipophilicity of chemical compounds. The Spearman rank-order correlation coefficient and Parzen-window regression methods provide the best performance of the algorithm. If additional user data is available, an improved prediction of lipophilicity of chemicals up to 2-5 times can be calculated when the appropriate smoothing parameters for the neural network are selected. The detected best combinations of parameters and strategies are implemented in the ALOGPS 2.1 program that is publicly available at http://www.vcclab.org/lab/alogps.
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Affiliation(s)
- Igor V Tetko
- Virtual Computational Chemistry Laboratory Project, Biomedical Department, IBPC, Ukrainian Academy of Sciences, Murmanskaya 1, Kyiv, 02094, Ukraine.
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Van de Waterbeemd H, De Groot M. Can the Internet help to meet the challenges in ADME and e-ADME? SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2002; 13:391-401. [PMID: 12184380 DOI: 10.1080/10629360290014269] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
The high-throughput screening (HTS) of large proprietary compound collections and combinatorial libraries has put an increased pressure on getting pharmacokinetic and drug metabolism data as early as possible. Properties related to absorption, distribution, metabolism and excretion (ADME) can be estimated by a range of in vivo and in vitro methods. Most are now available or under development in high(er) throughput modus. In addition progress has been made in in silico methods using various QSAR and modeling techniques using a range of recently introduced descriptors tailored to e-ADME. These approaches are promising as a filter for virtual libraries to decide on synthesis as well as in the selection of compounds for acquisition and screening. This paper will discuss a number of Internet resources relevant to ADME studies and predictions. We have focused on areas related to metabolism including metabolic pathways and P450 metabolism, transporters, bioavailability and absorption, pharmacokinetics and pharmacodynamics, molecular properties and tools for data analysis.
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Affiliation(s)
- H Van de Waterbeemd
- Pfizer Global Research and Development, PDM, Department of Drug Metabolism, Sandwich, Kent, UK.
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Affiliation(s)
- T Sanghvi
- College of Pharmacy, Tucson, Arizona 85721, USA.
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Tetko IV, Tanchuk VY, Villa AE. Prediction of n-octanol/water partition coefficients from PHYSPROP database using artificial neural networks and E-state indices. JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES 2001; 41:1407-21. [PMID: 11604042 DOI: 10.1021/ci010368v] [Citation(s) in RCA: 272] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A new method, ALOGPS v 2.0 (http://www.lnh.unil.ch/~itetko/logp/), for the assessment of n-octanol/water partition coefficient, log P, was developed on the basis of neural network ensemble analysis of 12 908 organic compounds available from PHYSPROP database of Syracuse Research Corporation. The atom and bond-type E-state indices as well as the number of hydrogen and non-hydrogen atoms were used to represent the molecular structures. A preliminary selection of indices was performed by multiple linear regression analysis, and 75 input parameters were chosen. Some of the parameters combined several atom-type or bond-type indices with similar physicochemical properties. The neural network ensemble training was performed by efficient partition algorithm developed by the authors. The ensemble contained 50 neural networks, and each neural network had 10 neurons in one hidden layer. The prediction ability of the developed approach was estimated using both leave-one-out (LOO) technique and training/test protocol. In case of interseries predictions, i.e., when molecules in the test and in the training subsets were selected by chance from the same set of compounds, both approaches provided similar results. ALOGPS performance was significantly better than the results obtained by other tested methods. For a subset of 12 777 molecules the LOO results, namely correlation coefficient r(2)= 0.95, root mean squared error, RMSE = 0.39, and an absolute mean error, MAE = 0.29, were calculated. For two cross-series predictions, i.e., when molecules in the training and in the test sets belong to different series of compounds, all analyzed methods performed less efficiently. The decrease in the performance could be explained by a different diversity of molecules in the training and in the test sets. However, even for such difficult cases the ALOGPS method provided better prediction ability than the other tested methods. We have shown that the diversity of the training sets rather than the design of the methods is the main factor determining their prediction ability for new data. A comparative performance of the methods as well as a dependence on the number of non-hydrogen atoms in a molecule is also presented.
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Affiliation(s)
- I V Tetko
- Laboratoire de Neuro-Heuristique, Institut de Physiologie, Université de Lausanne, Rue du Bugnon 7, Lausanne, CH-1005, Switzerland.
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