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Klimoszek D, Jeleń M, Morak-Młodawska B, Dołowy M. Evaluation of the Lipophilicity of Angularly Condensed Diquino- and Quinonaphthothiazines as Potential Candidates for New Drugs. Molecules 2024; 29:1683. [PMID: 38611961 PMCID: PMC11013424 DOI: 10.3390/molecules29071683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 03/24/2024] [Accepted: 04/05/2024] [Indexed: 04/14/2024] Open
Abstract
Lipophilicity is one of the most important properties of compounds required to estimate the absorption, distribution, and transport in biological systems, in addition to solubility, stability, and acid-base nature. It is crucial in predicting the ADME profile of bioactive compounds. The study assessed the usefulness of computational and chromatographic methods (thin-layer chromatography in a reversed-phase system, RP-TLC) for estimating the lipophilicity of 21 newly synthesized compounds belonging to diquinothiazines and quinonaphthiazines. In order to obtain reliable values of the relative lipophilicities of diquinothiazines and quinonaphthiazines, the partition coefficients obtained using different algorithms such as AlogPs, AClogP, AlogP, MLOGP, XLOGP2, XLOGP3, logP, and ClogP were compared with the chromatographic RM0 values of all the tested compounds measured by the experimental RP-TLC method (logPTLC). Additionally, logPTLC values were also correlated with other descriptors, as well as the predicted ADME and drug safety profiling parameters. The linear correlations of logPTLC values of the tested compounds with other calculated molecular descriptors such as molar refractivity, as well as ADME parameters (Caco-2 substrates, P-gp inhibitors, CYP2C19, and CYP3A4) generally show poor predictive power. Therefore, in silico ADME profiling can only be helpful at the initial step of designing these new candidates for drugs. The compliance of all discussed diquinothiazines and naphthoquinothiazines with the rules of Lipiński, Veber, and Egan suggests that the tested pentacyclic phenothiazine analogs have a chance to become therapeutic drugs, especially orally active drugs.
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Affiliation(s)
- Daria Klimoszek
- Faculty of Pharmaceutical Sciences in Sosnowiec, Doctoral School, Medical University of Silesia in Katowice, 40-007 Katowice, Poland;
| | - Małgorzata Jeleń
- Department of Organic Chemistry, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia in Katowice, Jagiellońska Street 4, 41-200 Sosnowiec, Poland;
| | - Beata Morak-Młodawska
- Department of Organic Chemistry, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia in Katowice, Jagiellońska Street 4, 41-200 Sosnowiec, Poland;
| | - Małgorzata Dołowy
- Department of Analytical Chemistry, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia in Katowice, 41-200 Sosnowiec, Poland;
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Esaki T, Yonezawa T, Ikeda K. A new workflow for the effective curation of membrane permeability data from open ADME information. J Cheminform 2024; 16:30. [PMID: 38481269 PMCID: PMC10938840 DOI: 10.1186/s13321-024-00826-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 03/10/2024] [Indexed: 03/17/2024] Open
Abstract
Membrane permeability is an in vitro parameter that represents the apparent permeability (Papp) of a compound, and is a key absorption, distribution, metabolism, and excretion parameter in drug development. Although the Caco-2 cell lines are the most used cell lines to measure Papp, other cell lines, such as the Madin-Darby Canine Kidney (MDCK), LLC-Pig Kidney 1 (LLC-PK1), and Ralph Russ Canine Kidney (RRCK) cell lines, can also be used to estimate Papp. Therefore, constructing in silico models for Papp estimation using the MDCK, LLC-PK1, and RRCK cell lines requires collecting extensive amounts of in vitro Papp data. An open database offers extensive measurements of various compounds covering a vast chemical space; however, concerns were reported on the use of data published in open databases without the appropriate accuracy and quality checks. Ensuring the quality of datasets for training in silico models is critical because artificial intelligence (AI, including deep learning) was used to develop models to predict various pharmacokinetic properties, and data quality affects the performance of these models. Hence, careful curation of the collected data is imperative. Herein, we developed a new workflow that supports automatic curation of Papp data measured in the MDCK, LLC-PK1, and RRCK cell lines collected from ChEMBL using KNIME. The workflow consisted of four main phases. Data were extracted from ChEMBL and filtered to identify the target protocols. A total of 1661 high-quality entries were retained after checking 436 articles. The workflow is freely available, can be updated, and has high reusability. Our study provides a novel approach for data quality analysis and accelerates the development of helpful in silico models for effective drug discovery. Scientific Contribution: The cost of building highly accurate predictive models can be significantly reduced by automating the collection of reliable measurement data. Our tool reduces the time and effort required for data collection and will enable researchers to focus on constructing high-performance in silico models for other types of analysis. To the best of our knowledge, no such tool is available in the literature.
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Affiliation(s)
- Tsuyoshi Esaki
- Faculty of Data Science, Shiga University, 1-1-1 Banba, Hikone, Shiga, 522-8522, Japan.
- Faculty of Culture and Information Science, Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto, 610-0394, Japan.
| | - Tomoki Yonezawa
- Faculty of Pharmacy, Keio University, 1-5-30 Shibakoen, Minato-ku, Tokyo, 105-8512, Japan
| | - Kazuyoshi Ikeda
- Faculty of Pharmacy, Keio University, 1-5-30 Shibakoen, Minato-ku, Tokyo, 105-8512, Japan
- HPC-and AI-Driven Drug Development Platform Division, RIKEN Center for Computational Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 4230-0045, Japan
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Tyagi S, Mishra R, Mazumder A, Mazumder R, Singh G, Pandey P. Synthesis, in silico screening, and biological evaluation of novel pyridine congeners as anti-epileptic agents targeting AMPA (α-amino-3-hydroxy-5-methylisoxazole) receptors. Chem Biol Drug Des 2024; 103:e14498. [PMID: 38453241 DOI: 10.1111/cbdd.14498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Revised: 12/23/2023] [Accepted: 02/26/2024] [Indexed: 03/09/2024]
Abstract
The research involves the synthesis of a series of new pyridine analogs 5(i-x) and their evaluation for anti-epileptic potential using in silico and in vivo models. Synthesis of the compounds was accomplished by using the Vilsmeier-Haack reaction principle. AutoDock 4.2 was used for their in silico screening against AMPA (-amino-3-hydroxy-5-methylisoxazole) receptor (PDB ID:3m3f). For in vivo testing, the maximal electroshock seizure (MES) model was used. The physicochemical, pharmacokinetic, drug-like, and drug-score features of all synthesized compounds were assessed using the online Swiss ADME and Protein Plus software. The in silico results showed that all the synthesized compounds 5(i-x) had 1-3 interactions and affinities ranging from -6.5 to -8.0 kJ/mol with the targeted receptor compared to the binding affinities of the standard drug phenytoin and the original ligand of the target (P99), which were -7.6 and -6.8 kJ/mol, respectively. In vivo study results showed that the compound 5-Carbamoyl-2-formyl-1-[2-(4-nitrophenyl)-2-oxo-ethyl]-pyridinium gave 60% protection against epileptic seizures compared to 59% protection afforded by regular phenytoin. All of them met Lipinski's rule of five and had drug-likeness and drug score values of 0.55 and 0.8, respectively, making them chemically and functionally like phenytoin. According to the findings of the studies, the synthesized derivatives have the potential to be employed as a stepping stone in the development of novel anti-epileptic drugs.
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Affiliation(s)
- Shivani Tyagi
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, Uttar Pradesh, India
| | - Rakhi Mishra
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, Uttar Pradesh, India
| | - Avijit Mazumder
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, Uttar Pradesh, India
| | - Rupa Mazumder
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, Uttar Pradesh, India
| | - Gurvinder Singh
- School of Pharmaceutical Science, Lovely Professional University, Phagwara, Punjab, India
| | - Pratibha Pandey
- Noida Institute of Engineering and Technology (Pharmacy Institute), Greater Noida, Uttar Pradesh, India
- Noida Institute of Engineering and Technology, Biotechnology Department, Greater Noida, Uttar Pradesh, India
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Redka M, Baumgart S, Kupczyk D, Kosmalski T, Studzińska R. Lipophilic Studies and In Silico ADME Profiling of Biologically Active 2-Aminothiazol-4(5 H)-one Derivatives. Int J Mol Sci 2023; 24:12230. [PMID: 37569606 PMCID: PMC10418735 DOI: 10.3390/ijms241512230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 07/26/2023] [Accepted: 07/29/2023] [Indexed: 08/13/2023] Open
Abstract
Pseudothiohydantoin derivatives have a wide range of biological activities and are widely used in the development of new pharmaceuticals. Lipophilicity is a basic, but very important parameter in the design of potential drugs, as it determines solubility in lipids, nonpolar solvents, and makes it possible to predict the ADME profile. The aim of this study was to evaluate the lipophilicity of 28 pseudothiohydantoin derivatives showing the inhibition of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) using chromatographic methods. Experimentally, lipophilicity was determined by reverse phase thin layer chromatography (RP-TLC) and reverse phase high-performance liquid chromatography (RP-HPLC). In both methods, methanol was used as the organic modifier of the mobile phase. For each 2-aminothiazol-4(5H)-one derivative, a relationship was observed between the structure of the compound and the values of the lipophilicity parameters (log kw, RM0). Experimental lipophilicity values were compared with computer calculated partition coefficient (logP) values. A total of 27 of the 28 tested compounds had a lipophilicity value < 5, which therefore met the condition of Lipinski's rule. In addition, the in silico ADME assay showed favorable absorption, distribution, metabolism, and excretion parameters for most of the pseudothiohydantoin derivatives tested. The study of lipophilicity and the ADME analysis indicate that the tested compounds are good potential drug candidates.
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Affiliation(s)
- Małgorzata Redka
- Department of Organic Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 2 Jurasza Str., 85-089 Bydgoszcz, Poland; (M.R.); (S.B.); (T.K.)
| | - Szymon Baumgart
- Department of Organic Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 2 Jurasza Str., 85-089 Bydgoszcz, Poland; (M.R.); (S.B.); (T.K.)
| | - Daria Kupczyk
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 24 Karłowicza Str., 85-092 Bydgoszcz, Poland;
| | - Tomasz Kosmalski
- Department of Organic Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 2 Jurasza Str., 85-089 Bydgoszcz, Poland; (M.R.); (S.B.); (T.K.)
| | - Renata Studzińska
- Department of Organic Chemistry, Faculty of Pharmacy, Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 2 Jurasza Str., 85-089 Bydgoszcz, Poland; (M.R.); (S.B.); (T.K.)
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Afolabi OB, Olasehinde OR, Olanipon DG, Mabayoje SO, Familua OM, Jaiyesimi KF, Agboola EK, Idowu TO, Obafemi OT, Olaoye OA, Oloyede OI. Antioxidant evaluation and computational prediction of prospective drug-like compounds from polyphenolic-rich extract of Hibiscus cannabinus L. seed as antidiabetic and neuroprotective targets: assessment through in vitro and in silico studies. BMC Complement Med Ther 2023; 23:203. [PMID: 37337198 DOI: 10.1186/s12906-023-04023-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 06/03/2023] [Indexed: 06/21/2023] Open
Abstract
BACKGROUND Reports have implicated diabetes mellitus (DM) and Alzheimer's disease (AD) as some of the global persistent health challenges with no lasting solutions, despite of significant inputs of modern-day pharmaceutical firms. This study therefore, aimed to appraise the in vitro antioxidant potential, enzymes inhibitory activities, and as well carry out in silico study on bioactive compounds from polyphenolic-rich extract of Hibiscus cannabinus seed (PEHc). METHODS In vitro antioxidant assays were performed on PEHc using standard methods while the identification of phytoconstituents was carried out with high performance liquid chromatography (HPLC). For the in silico molecular docking using Schrodinger's Grid-based ligand docking with energetics software, seven target proteins were retrieved from the database ( https://www.rcsb.org/ ). RESULTS HPLC technique identified twelve chemical compounds in PEHc, while antioxidant quantification revealed higher total phenolic contents (243.5 ± 0.71 mg GAE/g) than total flavonoid contents (54.06 ± 0.09 mg QE/g) with a significant (p < 0.05) inhibition of ABTS (IC50 = 218.30 ± 0.87 µg/ml) and 1, 1-diphenyl-2-picrylhydrazyl free radicals (IC50 = 227.79 ± 0.74 µg/ml). In a similar manner, the extract demonstrated a significant (p < 0.05) inhibitory activity against α-amylase (IC50 = 256.88 ± 6.15 µg/ml) and α-glucosidase (IC50 = 183.19 ± 0.23 µg/ml) as well as acetylcholinesterase (IC50 = 262.95 ± 1.47 µg/ml) and butyrylcholinesterase (IC50 = 189.97 ± 0.82 µg/ml), respectively. Furthermore, In silico study showed that hibiscetin (a lead) revealed a very strong binding affinity energies for DPP-4, (PDB ID: 1RWQ) and α-amylase (PDB ID: 1SMD), gamma-tocopherol ( for peptide-1 receptor; PDB ID: 3C59, AChE; PDB ID: 4EY7 and BChE; PDB ID: 7B04), cianidanol for α-glucosidase; PDB ID: 7KBJ and kaempferol for Poly [ADP-ribose] polymerase 1 (PARP-1); PDB ID: 6BHV, respectively. More so, ADMET scores revealed drug-like potentials of the lead compounds identified in PEHc. CONCLUSION As a result, the findings of this study point to potential drug-able compounds in PEHc that could be useful for the management of DM and AD.
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Affiliation(s)
- Olakunle Bamikole Afolabi
- Phytomedicine and Toxicology Unit, Biochemistry Programme, Department of Chemical Sciences, College of Sciences, Afe-Babalola University, P.M.B 5454, Ado-Ekiti, Ekiti State, Nigeria.
| | - Oluwaseun Ruth Olasehinde
- Department of Medical Biochemistry, College of Medicine and Health Sciences, Afe Babalola University, P.M.B 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Damilola Grace Olanipon
- Department of Biological Sciences, College of Sciences, Afe Babalola University, P.M.B. 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Samson Olatunde Mabayoje
- Department of Biological Sciences, College of Sciences, Afe Babalola University, P.M.B. 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Olufemi Michael Familua
- Department of Pharmacology and Toxicology, College of Pharmacy, Afe Babalola University, P.M.B. 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Kikelomo Folake Jaiyesimi
- Phytomedicine and Toxicology Unit, Biochemistry Programme, Department of Chemical Sciences, College of Sciences, Afe-Babalola University, P.M.B 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Esther Kemi Agboola
- Phytomedicine and Toxicology Unit, Biochemistry Programme, Department of Chemical Sciences, College of Sciences, Afe-Babalola University, P.M.B 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Tolulope Olajumoke Idowu
- Medicinal Plant Unit, Chemistry Programme, Department of Chemical Sciences, College of Sciences, Afe-Babalola University, P.M.B 5454, Ado- Ekiti, Ekiti State, Nigeria
| | - Olabisi Tajudeen Obafemi
- Phytomedicine and Toxicology Unit, Biochemistry Programme, Department of Chemical Sciences, College of Sciences, Afe-Babalola University, P.M.B 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Oyindamola Adeniyi Olaoye
- Phytomedicine and Toxicology Unit, Biochemistry Programme, Department of Chemical Sciences, College of Sciences, Afe-Babalola University, P.M.B 5454, Ado-Ekiti, Ekiti State, Nigeria
| | - Omotade Ibidun Oloyede
- Department of Biochemistry, Ekiti State University, P.M.B 5363, Ado-Ekiti, Ekiti State, Nigeria
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Bourouai MA, Si Larbi K, Bouchoucha A, Terrachet-Bouaziz S, Djebbar S. New Ni(II) and Pd(II) complexes bearing derived sulfa drug ligands: synthesis, characterization, DFT calculations, and in silico and in vitro biological activity studies. Biometals 2023; 36:153-188. [PMID: 36427181 DOI: 10.1007/s10534-022-00469-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 11/16/2022] [Indexed: 11/26/2022]
Abstract
In the present study, the synthesis of six new Ni(II) and Pd(II) complexes with three derived sulfamethoxazole drug ligands is reported. The coordination mode, geometry, and chemical formula of all the synthesized compounds have been determined by elemental analysis, mass spectrometry, emission atomic spectroscopy, conductivity measurements, magnetic susceptibility, FTIR, TGA, 1H-NMR, electronic absorption spectroscopy, SEM-EDX along with DFT calculations. The Schiff Base ligands were found to be bidentate and coordinated to the metal ions through sulfonamidic nitrogen and oxazolic nitrogen atoms leading to a square planar geometry for palladium (II) while a distorted octahedral geometry around Nickel (II) ion was suggested. Biological applications of the new complexes including in vitro antimicrobial, antioxidant and anticancer properties were investigated. The results showed that the new metal (II) compounds exhibit remarkable antibacterial inhibition activity against both Gram-positive and Gram-negative bacteria, in addition to noticeable DPPH free radical scavenging activity. The in vitro cytotoxicity assay of the complexes against cell lines of chronic myelogenous leukaemia (K562) showed promising potential for the application of the coordination compounds in antitumor therapy. Subsequently, to evaluate the pharmaceutical potential of the metal-containing compounds, pharmacokinetics and toxicity were studied by ADMET simulations while interactions between the complexes and bacterial proteins were evaluated by molecular docking.
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Affiliation(s)
- Mohamed Amine Bourouai
- Hydrometallurgy and Molecular Inorganic Chemistry Laboratory, Faculty of Chemistry, University of Science and Technology Houari Boumediene, BP 32 El Alia, 16111, Algiers, Algeria
| | - Karima Si Larbi
- Hydrometallurgy and Molecular Inorganic Chemistry Laboratory, Faculty of Chemistry, University of Science and Technology Houari Boumediene, BP 32 El Alia, 16111, Algiers, Algeria
| | - Afaf Bouchoucha
- Hydrometallurgy and Molecular Inorganic Chemistry Laboratory, Faculty of Chemistry, University of Science and Technology Houari Boumediene, BP 32 El Alia, 16111, Algiers, Algeria.
| | | | - Safia Djebbar
- Hydrometallurgy and Molecular Inorganic Chemistry Laboratory, Faculty of Chemistry, University of Science and Technology Houari Boumediene, BP 32 El Alia, 16111, Algiers, Algeria
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Reliable Prediction of Caco-2 Permeability by Supervised Recursive Machine Learning Approaches. Pharmaceutics 2022; 14:pharmaceutics14101998. [PMID: 36297432 PMCID: PMC9610902 DOI: 10.3390/pharmaceutics14101998] [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] [Received: 08/19/2022] [Revised: 09/15/2022] [Accepted: 09/17/2022] [Indexed: 11/16/2022] Open
Abstract
The heterogeneity of the Caco-2 cell line and differences in experimental protocols for permeability assessment using this cell-based method have resulted in the high variability of Caco-2 permeability measurements. These problems have limited the generation of large datasets to develop accurate and applicable regression models. This study presents a QSPR approach developed on the KNIME analytical platform and based on a structurally diverse dataset of over 4900 molecules. Interpretable models were obtained using random forest supervised recursive algorithms for data cleaning and feature selection. The development of a conditional consensus model based on regional and global regression random forest produced models with RMSE values between 0.43–0.51 for all validation sets. The potential applicability of the model as a surrogate for the in vitro Caco-2 assay was demonstrated through blind prediction of 32 drugs recommended by the International Council for the Harmonization of Technical Requirements for Pharmaceuticals (ICH) for validation of in vitro permeability methods. The model was validated for the preliminary estimation of the BCS/BDDCS class. The KNIME workflow developed to automate new drug prediction is freely available. The results suggest that this automated prediction platform is a reliable tool for identifying the most promising compounds with high intestinal permeability during the early stages of drug discovery.
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Coordination of new palladium (II) complexes with derived furopyran-3,4‑dione ligands: Synthesis, characterization, redox behaviour, DFT, antimicrobial activity, molecular docking and ADMET studies. J Mol Struct 2022. [DOI: 10.1016/j.molstruc.2022.132611] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Selvaraj C, Chandra I, Singh SK. Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries. Mol Divers 2021; 26:1893-1913. [PMID: 34686947 PMCID: PMC8536481 DOI: 10.1007/s11030-021-10326-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 09/24/2021] [Indexed: 12/27/2022]
Abstract
The global spread of COVID-19 has raised the importance of pharmaceutical drug development as intractable and hot research. Developing new drug molecules to overcome any disease is a costly and lengthy process, but the process continues uninterrupted. The critical point to consider the drug design is to use the available data resources and to find new and novel leads. Once the drug target is identified, several interdisciplinary areas work together with artificial intelligence (AI) and machine learning (ML) methods to get enriched drugs. These AI and ML methods are applied in every step of the computer-aided drug design, and integrating these AI and ML methods results in a high success rate of hit compounds. In addition, this AI and ML integration with high-dimension data and its powerful capacity have taken a step forward. Clinical trials output prediction through the AI/ML integrated models could further decrease the clinical trials cost by also improving the success rate. Through this review, we discuss the backend of AI and ML methods in supporting the computer-aided drug design, along with its challenge and opportunity for the pharmaceutical industry. From the available information or data, the AI and ML based prediction for the high throughput virtual screening. After this integration of AI and ML, the success rate of hit identification has gained a momentum with huge success by providing novel drugs.
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Affiliation(s)
- Chandrabose Selvaraj
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India.
| | - Ishwar Chandra
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India
| | - Sanjeev Kumar Singh
- CADD and Molecular Modelling Lab, Department of Bioinformatics, Alagappa University, Science Block, Karaikudi, Tamil Nadu, 630004, India.
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Price E, Kalvass JC, DeGoey D, Hosmane B, Doktor S, Desino K. Global Analysis of Models for Predicting Human Absorption: QSAR, In Vitro, and Preclinical Models. J Med Chem 2021; 64:9389-9403. [PMID: 34152772 DOI: 10.1021/acs.jmedchem.1c00669] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Models intended to predict intestinal absorption are an essential part of the drug development process. Although many models exist for capturing intestinal absorption, many questions still exist around the applicability of these models to drug types like "beyond rule of 5" (bRo5) and low absorption compounds. This presents a challenge as current models have not been rigorously tested to understand intestinal absorption. Here, we assembled a large, structurally diverse dataset of ∼1000 compounds with known in vitro, preclinical, and human permeability and/or absorption data. In silico (quantitative structure-activity relationship), in vitro (Caco-2), and in vivo (rat) models were statistically evaluated for predictive performance against this human intestinal absorption dataset. We expect this evaluation to serve as a resource for DMPK scientists and medicinal/computational chemists to increase their understanding of permeability and absorption model utility and applications for academia and industry.
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Affiliation(s)
- Edward Price
- Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - J Cory Kalvass
- Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - David DeGoey
- Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Balakrishna Hosmane
- Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Stella Doktor
- Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
| | - Kelly Desino
- Research and Development, AbbVie Inc., 1 North Waukegan Road, North Chicago, Illinois 60064, United States
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11
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Rybenkov VV, Zgurskaya HI, Ganguly C, Leus IV, Zhang Z, Moniruzzaman M. The Whole Is Bigger than the Sum of Its Parts: Drug Transport in the Context of Two Membranes with Active Efflux. Chem Rev 2021; 121:5597-5631. [PMID: 33596653 PMCID: PMC8369882 DOI: 10.1021/acs.chemrev.0c01137] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Cell envelope plays a dual role in the life of bacteria by simultaneously protecting it from a hostile environment and facilitating access to beneficial molecules. At the heart of this ability lie the restrictive properties of the cellular membrane augmented by efflux transporters, which preclude intracellular penetration of most molecules except with the help of specialized uptake mediators. Recently, kinetic properties of the cell envelope came into focus driven on one hand by the urgent need in new antibiotics and, on the other hand, by experimental and theoretical advances in studies of transmembrane transport. A notable result from these studies is the development of a kinetic formalism that integrates the Michaelis-Menten behavior of individual transporters with transmembrane diffusion and offers a quantitative basis for the analysis of intracellular penetration of bioactive compounds. This review surveys key experimental and computational approaches to the investigation of transport by individual translocators and in whole cells, summarizes key findings from these studies and outlines implications for antibiotic discovery. Special emphasis is placed on Gram-negative bacteria, whose envelope contains two separate membranes. This feature sets these organisms apart from Gram-positive bacteria and eukaryotic cells by providing them with full benefits of the synergy between slow transmembrane diffusion and active efflux.
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Affiliation(s)
- Valentin V Rybenkov
- Department of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Helen I Zgurskaya
- Department of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Chhandosee Ganguly
- Department of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Inga V Leus
- Department of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Zhen Zhang
- Department of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
| | - Mohammad Moniruzzaman
- Department of Chemistry and Biochemistry, Stephenson Life Sciences Research Center, University of Oklahoma, 101 Stephenson Parkway, Norman, Oklahoma 73019, United States
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12
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Belkhir-Talbi D, Ghemmit-Doulache N, Terrachet-Bouaziz S, Makhloufi-Chebli M, Rabahi A, Ismaili L, Silva AM. Transition-metal complexes of N,N′-di(4-bromophenyl)-4-hydroxycoumarin-3-carboximidamide: synthesis, characterization, biological activities, ADMET and drug-likeness analysis. INORG CHEM COMMUN 2021. [DOI: 10.1016/j.inoche.2021.108509] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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13
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Hadhoum N, Zohra Hadjadj-Aoul F, Hocine S, Bouaziz-Terrachet S, Seklaoui N, Boubrit F, Abderrahim W, Redouane Mekacher L. Design and One-Pot Synthesis of Some New [3,5-Di(4’,5’-diphenyl-2’-substituted)-1H-imidazol-1-yl)]-1H-1,2,4-triazole Derivatives: in silico ADMET and Docking Study, Antibacterial and Antifungal Activities Evaluation. HETEROCYCLES 2021. [DOI: 10.3987/com-21-14503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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14
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Mardianingrum R, Yusuf M, Hariono M, Mohd Gazzali A, Muchtaridi M. α-Mangostin and its derivatives against estrogen receptor alpha. J Biomol Struct Dyn 2020; 40:2621-2634. [PMID: 33155528 DOI: 10.1080/07391102.2020.1841031] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Estrogen receptor alpha (ERα) acts as the transcription factor and the main therapeutic target against breast cancer. One of the compounds that has been shown to act as an ERα is α-mangostin. However, it still has weaknesses due to its low solubility and low potent activity. In this study, α-mangostin was modified by substituting -OH group at C6 using benzoyl derivatives through a step by step in silico study, namely pharmacokinetic prediction (https://preadmet.bmdrc.kr/adme/), pharmacophore modeling (LigandScout 4.1), molecular docking simulation (AutoDock 4.2), molecular dynamics simulation (AMBER 16) and a binding free energy analysis using MM-PBSA method. From the computational studies, three compounds which are derived from α-mangostin (AMB-1 (-9.84 kcal/mol), AMB-2 (-6.80 kcal/mol) and AMB-10 (-12.42 kcal/mol)) have lower binding free energy than α-mangostin (-1.77 kcal/mol), as evidenced by the binding free energy calculation using the MM-PBSA method. They can then be predicted to have potent activities as ERα antagonists.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Richa Mardianingrum
- Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Jatinangor, Indonesia.,Department of Pharmacy, Universitas Perjuangan, Tasikmalaya, Indonesia
| | - Muhammad Yusuf
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jatinangor, Indonesia
| | - Maywan Hariono
- Faculty of Pharmacy, Universitas Sanata Dharma, Yogyakarta, Indonesia
| | - Amira Mohd Gazzali
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia
| | - Muchtaridi Muchtaridi
- Department of Pharmaceutical Analysis and Medicinal Chemistry, Faculty of Pharmacy, Universitas Padjadjaran, Jatinangor, Indonesia
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15
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Hsiao Y, Su BH, Tseng YJ. Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development. Brief Bioinform 2020; 22:5881374. [PMID: 32770190 DOI: 10.1093/bib/bbaa160] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 06/22/2020] [Accepted: 06/24/2020] [Indexed: 12/27/2022] Open
Abstract
In drug development, preclinical safety and pharmacokinetics assessments of candidate drugs to ensure the safety profile are a must. While in vivo and in vitro tests are traditionally used, experimental determinations have disadvantages, as they are usually time-consuming and costly. In silico predictions of these preclinical endpoints have each been developed in the past decades. However, only a few web-based tools have integrated different models to provide a simple one-step platform to help researchers thoroughly evaluate potential drug candidates. To efficiently achieve this approach, a platform for preclinical evaluation must not only predict key ADMET (absorption, distribution, metabolism, excretion and toxicity) properties but also provide some guidance on structural modifications to improve the undesired properties. In this review, we organized and compared several existing integrated web servers that can be adopted in preclinical drug development projects to evaluate the subject of interest. We also introduced our new web server, Virtual Rat, as an alternative choice to profile the properties of drug candidates. In Virtual Rat, we provide not only predictions of important ADMET properties but also possible reasons as to why the model made those structural predictions. Multiple models were implemented into Virtual Rat, including models for predicting human ether-a-go-go-related gene (hERG) inhibition, cytochrome P450 (CYP) inhibition, mutagenicity (Ames test), blood-brain barrier penetration, cytotoxicity and Caco-2 permeability. Virtual Rat is free and has been made publicly available at https://virtualrat.cmdm.tw/.
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16
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Exploring Multicompartment Plug Flow–Based Model Approach in Biopharmaceutics: Impact of Stomach Setting and the Estimation of the Fraction Absorbed of Orally Administered Basic Drugs. J Pharm Sci 2020; 109:1261-1269. [DOI: 10.1016/j.xphs.2019.11.021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 11/21/2019] [Accepted: 11/22/2019] [Indexed: 11/23/2022]
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17
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García-Jacas CR, Marrero-Ponce Y, Cortés-Guzmán F, Suárez-Lezcano J, Martinez-Rios FO, García-González LA, Pupo-Meriño M, Martinez-Mayorga K. Enhancing Acute Oral Toxicity Predictions by using Consensus Modeling and Algebraic Form-Based 0D-to-2D Molecular Encodes. Chem Res Toxicol 2019; 32:1178-1192. [PMID: 31066547 DOI: 10.1021/acs.chemrestox.9b00011] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Quantitative structure-activity relationships (QSAR) are introduced to predict acute oral toxicity (AOT), by using the QuBiLS-MAS (acronym for quadratic, bilinear and N-Linear maps based on graph-theoretic electronic-density matrices and atomic weightings) framework for the molecular encoding. Three training sets were employed to build the models: EPA training set (5931 compounds), EPA-full training set (7413 compounds), and Zhu training set (10 152 compounds). Additionally, the EPA test set (1482 compounds) was used for the validation of the QSAR models built on the EPA training set, while the ProTox (425 compounds) and T3DB (284 compounds) external sets were employed for the assessment of all the models. The k-nearest neighbor, multilayer perceptron, random forest, and support vector machine procedures were employed to build several base (individual) models. The base models with REPA-training ≥ 0.75 ( R = correlation coefficient) and MAEEPA-training ≤ 0.5 (MAE = mean absolute error) were retained to build consensus models. As a result, two consensus models based on the minimum operator and denoted as M19 and M22, as well as a consensus model based on the weighted average operator and denoted as M24, were selected as the best ones for each training set considered. According to the applicability domain (AD) analysis performed, model M19 (built on the EPA training set) has MAEtest-AD = 0.4044, MAEProTox-AD = 0.4067 and MAET3DB-AD = 0.2586 on the EPA test set, ProTox external set, and T3DB external set, respectively; whereas model M22 (built on the EPA-full set) and model M24 (built on the Zhu set) present MAEProTox-AD = 0.3992 and MAET3DB-AD = 0.2286, and MAEProTox-AD = 0.3773 and MAET3DB-AD = 0.2471 on the two external sets accounted for, respectively. These outcomes were compared and statistically validated with respect to 14 QSAR methods (e.g., admetSAR, ProTox-II) from the literature. As a result, model M22 presents the best overall performance. In addition, a retrospective study on 261 withdrawn drugs due to their toxic/side effects was performed, to assess the usefulness of prospectively using the QSAR models proposed in the labeling of chemicals. A comparison with regard to the methods from the literature was also made. As a result, model M22 has the best ability of labeling a compound as toxic according to the globally harmonized system of classification and labeling of chemicals. Therefore, it can be concluded that the models proposed, especially model M22, constitute prominent tools for studying AOT, at providing the best results among all the methods examined. A freely available software was also developed to be used in virtual screening tasks ( http://tomocomd.com/apps/ptoxra ).
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Affiliation(s)
- César R García-Jacas
- Departamento de Ciencias de la Computación , Centro de Investigación Científica y de Educación Superior de Ensenada , Ensenada , Baja California , México
| | - Yovani Marrero-Ponce
- Universidad San Francisco de Quito, Grupo de Medicina Molecular y Traslacional, Colegio de Ciencias de la Salud , Escuela de Medicina, Edificio de Especialidades Médicas , Quito , Pichincha , Ecuador.,Grupo de Investigación Ambiental, Programas Ambientales, Facultad de Ingenierías , Fundacion Universitaria Tecnologico Comfenalco-Cartagena , Cr44 DN 30 A, 91 , Cartagena , Bolívar , Colombia
| | - Fernando Cortés-Guzmán
- Instituto de Química , Universidad Nacional Autónoma de México , Ciudad de México , México
| | - José Suárez-Lezcano
- Pontificia Universidad Católica del Ecuador Sede Esmeraldas , Esmeraldas , Ecuador
| | | | - Luis A García-González
- Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas , La Habana , Cuba
| | - Mario Pupo-Meriño
- Grupo de Investigación de Bioinformática , Universidad de las Ciencias Informáticas , La Habana , Cuba
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18
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Pham-The H, Cabrera-Pérez MÁ, Nam NH, Castillo-Garit JA, Rasulev B, Le-Thi-Thu H, Casañola-Martin GM. In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling. Curr Top Med Chem 2019; 18:2209-2229. [PMID: 30499410 DOI: 10.2174/1568026619666181130140350] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 10/16/2018] [Accepted: 11/19/2018] [Indexed: 11/22/2022]
Abstract
One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues.
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Affiliation(s)
- Hai Pham-The
- Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hanoi, Vietnam
| | - Miguel Á Cabrera-Pérez
- Unit of Modeling and Experimental Biopharmaceutics, Chemical Bioactive Center, Central University of Las Villas, Santa Clara, 54830, Villa Clara, Cuba.,Department of Engineering, Area of Pharmacy and Pharmaceutical Technology, Miguel Hernández University, 03550 Sant Juan d'Alacant, Alicante, Spain
| | - Nguyen-Hai Nam
- Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hanoi, Vietnam
| | - Juan A Castillo-Garit
- Unidad de Toxicologia Experimental, Universidad de Ciencias Medicas "Dr. Serafín Ruiz de Zarate Ruiz" de Villa Clara, Santa Clara, 50200, Villa Clara, Cuba
| | - Bakhtiyor Rasulev
- Department of Coatings and Polymer Materials, North Dakota State University, Fargo, ND, 58102, United States
| | - Huong Le-Thi-Thu
- School of Medicine and Pharmacy, Vietnam National University, 144 Xuan Thuy, Hanoi, Vietnam
| | - Gerardo M Casañola-Martin
- Department of Coatings and Polymer Materials, North Dakota State University, Fargo, ND, 58102, United States
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19
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Exploring a Kinetic Model Approach in Biopharmaceutics: Estimating the Fraction Absorbed of Orally Administered Drugs in Humans. J Pharm Sci 2018; 107:1798-1805. [DOI: 10.1016/j.xphs.2018.03.015] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2018] [Revised: 02/23/2018] [Accepted: 03/14/2018] [Indexed: 11/23/2022]
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20
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Shin M, Jang D, Nam H, Lee KH, Lee D. Predicting the Absorption Potential of Chemical Compounds Through a Deep Learning Approach. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2018; 15:432-440. [PMID: 26930688 DOI: 10.1109/tcbb.2016.2535233] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The human colorectal carcinoma cell line (Caco-2) is a commonly used in-vitro test that predicts the absorption potential of orally administered drugs. In-silico prediction methods, based on the Caco-2 assay data, may increase the effectiveness of the high-throughput screening of new drug candidates. However, previously developed in-silico models that predict the Caco-2 cellular permeability of chemical compounds use handcrafted features that may be dataset-specific and induce over-fitting problems. Deep Neural Network (DNN) generates high-level features based on non-linear transformations for raw features, which provides high discriminant power and, therefore, creates a good generalized model. We present a DNN-based binary Caco-2 permeability classifier. Our model was constructed based on 663 chemical compounds with in-vitro Caco-2 apparent permeability data. Two hundred nine molecular descriptors are used for generating the high-level features during DNN model generation. Dropout regularization is applied to solve the over-fitting problem and the non-linear activation. The Rectified Linear Unit (ReLU) is adopted to reduce the vanishing gradient problem. The results demonstrate that the high-level features generated by the DNN are more robust than handcrafted features for predicting the cellular permeability of structurally diverse chemical compounds in Caco-2 cell lines.
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21
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Yang M, Chen J, Xu L, Shi X, Zhou X, Xi Z, An R, Wang X. A novel adaptive ensemble classification framework for ADME prediction. RSC Adv 2018; 8:11661-11683. [PMID: 35542768 PMCID: PMC9079056 DOI: 10.1039/c8ra01206g] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 03/20/2018] [Indexed: 12/20/2022] Open
Abstract
AECF is a GA based ensemble method. It includes four components which are (1) data balancing, (2) generating individual models, (3) combining individual models, and (4) optimizing the ensemble.
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Affiliation(s)
- Ming Yang
- Department of Pharmacy
- Longhua Hospital Affiliated to Shanghai University of TCM
- Shanghai
- People's Republic of China
- Department of Chemistry
| | - Jialei Chen
- Department of Pharmacy
- Longhua Hospital Affiliated to Shanghai University of TCM
- Shanghai
- People's Republic of China
| | - Liwen Xu
- Department of Pharmacy
- Longhua Hospital Affiliated to Shanghai University of TCM
- Shanghai
- People's Republic of China
| | - Xiufeng Shi
- Department of Pharmacy
- Longhua Hospital Affiliated to Shanghai University of TCM
- Shanghai
- People's Republic of China
| | - Xin Zhou
- Department of Pharmacy
- Longhua Hospital Affiliated to Shanghai University of TCM
- Shanghai
- People's Republic of China
| | - Zhijun Xi
- Department of Pharmacy
- Longhua Hospital Affiliated to Shanghai University of TCM
- Shanghai
- People's Republic of China
| | - Rui An
- Department of Chemistry
- College of Pharmacy
- Shanghai University of Traditional Chinese Medicine
- Shanghai
- People's Republic of China
| | - Xinhong Wang
- Department of Chemistry
- College of Pharmacy
- Shanghai University of Traditional Chinese Medicine
- Shanghai
- People's Republic of China
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22
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Valdés-Martiní JR, Marrero-Ponce Y, García-Jacas CR, Martinez-Mayorga K, Barigye SJ, Vaz d'Almeida YS, Pham-The H, Pérez-Giménez F, Morell CA. QuBiLS-MAS, open source multi-platform software for atom- and bond-based topological (2D) and chiral (2.5D) algebraic molecular descriptors computations. J Cheminform 2017; 9:35. [PMID: 29086120 PMCID: PMC5462671 DOI: 10.1186/s13321-017-0211-5] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Accepted: 04/07/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In previous reports, Marrero-Ponce et al. proposed algebraic formalisms for characterizing topological (2D) and chiral (2.5D) molecular features through atom- and bond-based ToMoCoMD-CARDD (acronym for Topological Molecular Computational Design-Computer Aided Rational Drug Design) molecular descriptors. These MDs codify molecular information based on the bilinear, quadratic and linear algebraic forms and the graph-theoretical electronic-density and edge-adjacency matrices in order to consider atom- and bond-based relations, respectively. These MDs have been successfully applied in the screening of chemical compounds of different therapeutic applications ranging from antimalarials, antibacterials, tyrosinase inhibitors and so on. To compute these MDs, a computational program with the same name was initially developed. However, this in house software barely offered the functionalities required in contemporary molecular modeling tasks, in addition to the inherent limitations that made its usability impractical. Therefore, the present manuscript introduces the QuBiLS-MAS (acronym for Quadratic, Bilinear and N-Linear mapS based on graph-theoretic electronic-density Matrices and Atomic weightingS) software designed to compute topological (0-2.5D) molecular descriptors based on bilinear, quadratic and linear algebraic forms for atom- and bond-based relations. RESULTS The QuBiLS-MAS module was designed as standalone software, in which extensions and generalizations of the former ToMoCoMD-CARDD 2D-algebraic indices are implemented, considering the following aspects: (a) two new matrix normalization approaches based on double-stochastic and mutual probability formalisms; (b) topological constraints (cut-offs) to take into account particular inter-atomic relations; (c) six additional atomic properties to be used as weighting schemes in the calculation of the molecular vectors; (d) four new local-fragments to consider molecular regions of interest; (e) number of lone-pair electrons in chemical structure defined by diagonal coefficients in matrix representations; and (f) several aggregation operators (invariants) applied over atom/bond-level descriptors in order to compute global indices. This software permits the parallel computation of the indices, contains a batch processing module and data curation functionalities. This program was developed in Java v1.7 using the Chemistry Development Kit library (version 1.4.19). The QuBiLS-MAS software consists of two components: a desktop interface (GUI) and an API library allowing for the easy integration of the latter in chemoinformatics applications. The relevance of the novel extensions and generalizations implemented in this software is demonstrated through three studies. Firstly, a comparative Shannon's entropy based variability study for the proposed QuBiLS-MAS and the DRAGON indices demonstrates superior performance for the former. A principal component analysis reveals that the QuBiLS-MAS approach captures chemical information orthogonal to that codified by the DRAGON descriptors. Lastly, a QSAR study for the binding affinity to the corticosteroid-binding globulin using Cramer's steroid dataset is carried out. CONCLUSIONS From these analyses, it is revealed that the QuBiLS-MAS approach for atom-pair relations yields similar-to-superior performance with regard to other QSAR methodologies reported in the literature. Therefore, the QuBiLS-MAS approach constitutes a useful tool for the diversity analysis of chemical compound datasets and high-throughput screening of structure-activity data.
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Affiliation(s)
- José R Valdés-Martiní
- StreelBridge Laboratories, SteelBridge Consulting Technology Solutions, Miami, FL, USA
| | - Yovani Marrero-Ponce
- Universidad San Francisco de Quito (USFQ), Grupo de Medicina Molecular y Traslacional (MeM&T), Colegio de Ciencias de la Salud (COCSA), Escuela de Medicina, Edificio de Especialidades Médicas, Quito, Ecuador. .,Universidad San Francisco de Quito (USFQ), Instituto de Simulación Computacional (ISC-USFQ), Diego de Robles y vía Interoceánica, 170157, Quito, Pichincha, Ecuador. .,Computer-Aided Molecular "Biosilico" Discovery and Bioinformatics Research International Network (CAMD-BIR IN), Cumbayá, Quito, Ecuador. .,Grupo de Investigación Ambiental (GIA), Fundación Universitaria Tecnológico de Comfenalco, Facultad de Ingenierías, Programa de Ingeniería de Procesos, Cartagena de Indias, Bolívar, Colombia. .,Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Valencia, Spain.
| | - César R García-Jacas
- Instituto de Química, Universidad Nacional Autónoma de México (UNAM), Ciudad de México, México.,Escuela de Sistemas y Computación, Pontificia Universidad Católica del Ecuador Sede Esmeraldas (PUCESE), Esmeraldas, Ecuador.,Grupo de Investigación de Bioinformática, Universidad de las Ciencias Informáticas (UCI), Havana, Cuba
| | - Karina Martinez-Mayorga
- Instituto de Química, Universidad Nacional Autónoma de México (UNAM), Ciudad de México, México
| | - Stephen J Barigye
- Facultad de Medicina, Universidad de Las Américas, Quito, Pichincha, Ecuador
| | | | - Hai Pham-The
- Department of Pharmaceutical Chemistry, Hanoi University of Pharmacy, 13-15 Le Thanh Tong, Hoan Kiem, Hanoi, Vietnam
| | - Facundo Pérez-Giménez
- Unidad de Investigación de Diseño de Fármacos y Conectividad Molecular, Departamento de Química Física, Facultad de Farmacia, Universitat de València, Valencia, Spain
| | - Carlos A Morell
- Laboratorio de Inteligencia Artificial, Centro de Estudios de Informática (CEI), Facultad de Matemática, Física y Computación, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, Villa Clara, Cuba
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23
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Fragment-based in silico modeling of multi-target inhibitors against breast cancer-related proteins. Mol Divers 2017; 21:511-523. [PMID: 28194627 DOI: 10.1007/s11030-017-9731-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Accepted: 01/16/2017] [Indexed: 10/20/2022]
Abstract
Breast cancer is the most frequent cancer reported in women, being responsible for hundreds of thousands of deaths. Chemotherapy has proven to be effective against this malignant neoplasm depending on different biological factors such as the histopathology, grade, and stage, among others. However, breast cancer cells have become resistant to current chemotherapeutic regimens, urging the discovery of new anti-breast cancer drugs. Computational approaches have the potential to offer promising alternatives to accelerate the search for potent and versatile anti-breast cancer agents. In the present work, we introduce the first multitasking (mtk) computational model devoted to the in silico fragment-based design of new molecules with high inhibitory activity against 19 different proteins involved in breast cancer. The mtk-computational model was created from a dataset formed by 24,285 cases, and it exhibited accuracy around 93% in both training and prediction (test) sets. Several molecular fragments were extracted from the molecules present in the dataset, and their quantitative contributions to the inhibitory activities against all the proteins under study were calculated. The combined use of the fragment contributions and the physicochemical interpretations of the different molecular descriptors in the mtk-computational model allowed the design of eight new molecular entities not reported in our dataset. These molecules were predicted as potent multi-target inhibitors against all the proteins, and they exhibited a desirable druglikeness according to the Lipinski's rule of five and its variants.
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24
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Brox S, Seiwert B, Küster E, Reemtsma T. Toxicokinetics of Polar Chemicals in Zebrafish Embryo (Danio rerio): Influence of Physicochemical Properties and of Biological Processes. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:10264-72. [PMID: 27571242 DOI: 10.1021/acs.est.6b04325] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The time-resolved uptake of 17 nonionic and ionic polar compounds (logD ≤ 2) with a diversity of functional groups into zebrafish embryos (ZFE) was studied over 96 h of exposure. Among them were pharmaceuticals, pesticides and plant active ingredients. Uptake rates for the diffusion controlled passive uptake through the ZFE membrane ranged from 0.02 to 24 h(-1) for the nonionic compounds and were slower for ionic compounds (<0.008-0.08 h(-1)). The study compounds did not enrich much in the ZFE (median bioconcentration factor of 1, max. 7). Biotransformation significantly influenced the internal concentration of some of the test compounds over time (benzocaine, phenacetin, metribuzin, phenytoin, thiacloprid, valproic acid). For benzocaine, valproic acid and phenacetin several transformation products (TPs) were observed by LC-MS already at early life-stages (before 28 hpf); for benzocaine the TPs comprised >90% of the initial amount taken up into the ZFE. For six compounds internal concentrations remained very low (rel. int. conc. < 0.2). Besides biotransformation (sulfamethoxazole), poor membrane permeability (cimetidine, colchicine) and also affinity to efflux transporters (atropine and chloramphenicol) are the likely reasons for these low internal concentrations. This study outlines that the uptake of polar compounds into ZFE is influenced by their physicochemical properties. However, biological processes, biotransformation and, likely, efflux can strongly affect the internal concentrations already in early developmental stages of the ZFE. This should be considered in future toxicokinetic modeling. The evaluation of the toxicity of chemicals by ZFE requires toxicokinetic studies of the test compounds and their TPs to increase comparability to effects in fish.
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Affiliation(s)
- Stephan Brox
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research - UFZ , Permoserstrasse 15, 04318 Leipzig, Germany
| | - Bettina Seiwert
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research - UFZ , Permoserstrasse 15, 04318 Leipzig, Germany
| | - Eberhard Küster
- Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research - UFZ , Permoserstrasse 15, 04318 Leipzig, Germany
| | - Thorsten Reemtsma
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research - UFZ , Permoserstrasse 15, 04318 Leipzig, Germany
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25
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Matsson P, Doak BC, Over B, Kihlberg J. Cell permeability beyond the rule of 5. Adv Drug Deliv Rev 2016; 101:42-61. [PMID: 27067608 DOI: 10.1016/j.addr.2016.03.013] [Citation(s) in RCA: 186] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Revised: 03/25/2016] [Accepted: 03/31/2016] [Indexed: 11/17/2022]
Abstract
Drug discovery for difficult targets that have large and flat binding sites is often better suited to compounds beyond the "rule of 5" (bRo5). However, such compounds carry higher pharmacokinetic risks, such as low solubility and permeability, and increased efflux and metabolism. Interestingly, recent drug approvals and studies suggest that cell permeable and orally bioavailable drugs can be discovered far into bRo5 space. Tactics such as reduction or shielding of polarity by N-methylation, bulky side chains and intramolecular hydrogen bonds may be used to increase cell permeability in this space, but often results in decreased solubility. Conformationally flexible compounds can, however, combine high permeability and solubility, properties that are keys for cell permeability and intestinal absorption. Recent developments in computational conformational analysis will aid design of such compounds and hence prediction of cell permeability. Transporter mediated efflux occurs for most investigated drugs in bRo5 space, however it is commonly overcome by high local intestinal concentrations on oral administration. In contrast, there is little data to support significant impact of transporter-mediated intestinal absorption in bRo5 space. Current knowledge of compound properties that govern transporter effects of bRo5 drugs is limited and requires further fundamental and comprehensive studies.
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Affiliation(s)
- Pär Matsson
- Department of Pharmacy, BMC, Uppsala University, Box 580, SE-751 23 Uppsala, Sweden
| | - Bradley C Doak
- Department of Medicinal Chemistry, MIPS, Monash University, 381 Royal Parade, Parkville, Victoria, Australia
| | - Björn Over
- Cardiovascular and Metabolic Diseases, Innovative Medicines and Early Development Biotech Unit, AstraZeneca, Pepparedsleden 1, SE-431 83 Mölndal, Sweden
| | - Jan Kihlberg
- Department of Chemistry - BMC, Uppsala University, Box 576, SE-751 23 Uppsala, Sweden.
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Wang NN, Dong J, Deng YH, Zhu MF, Wen M, Yao ZJ, Lu AP, Wang JB, Cao DS. ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting. J Chem Inf Model 2016; 56:763-73. [DOI: 10.1021/acs.jcim.5b00642] [Citation(s) in RCA: 98] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ning-Ning Wang
- School
of Pharmaceutical Sciences, Central South University, Changsha 410013, P. R. China
| | - Jie Dong
- School
of Pharmaceutical Sciences, Central South University, Changsha 410013, P. R. China
| | - Yin-Hua Deng
- School
of Pharmaceutical Sciences, Central South University, Changsha 410013, P. R. China
| | - Min-Feng Zhu
- School
of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China
| | - Ming Wen
- College
of Chemistry and Chemical Engineering, Central South University, Changsha 410083, P. R. China
| | - Zhi-Jiang Yao
- School
of Pharmaceutical Sciences, Central South University, Changsha 410013, P. R. China
- College
of Chemistry and Chemical Engineering, Central South University, Changsha 410083, P. R. China
| | - Ai-Ping Lu
- Institute for Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, P. R. China
| | - Jian-Bing Wang
- College
of Chemistry and Chemical Engineering, Central South University, Changsha 410083, P. R. China
| | - Dong-Sheng Cao
- School
of Pharmaceutical Sciences, Central South University, Changsha 410013, P. R. China
- Institute for Advancing Translational Medicine in Bone & Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, P. R. China
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Setlur AS, Naik SY, Skariyachan S. Herbal Lead as Ideal Bioactive Compounds Against Probable Drug Targets of Ebola Virus in Comparison with Known Chemical Analogue: A Computational Drug Discovery Perspective. Interdiscip Sci 2016; 9:254-277. [DOI: 10.1007/s12539-016-0149-8] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2015] [Revised: 01/05/2016] [Accepted: 01/25/2016] [Indexed: 12/17/2022]
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Milanetti E, Raimondo D, Tramontano A. Prediction of the permeability of neutral drugs inferred from their solvation properties. Bioinformatics 2015; 32:1163-9. [PMID: 26656568 PMCID: PMC4824127 DOI: 10.1093/bioinformatics/btv725] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2015] [Accepted: 12/04/2015] [Indexed: 12/26/2022] Open
Abstract
Motivation: Determination of drug absorption is an important component of the drug discovery and development process in that it plays a key role in the decision to promote drug candidates to clinical trials. We have developed a method that, on the basis of an analysis of the dynamic distribution of water molecules around a compound obtained by molecular dynamics simulations, can compute a parameter-free value that correlates very well with the compound permeability measured using the human colon adenocarcinoma (Caco-2) cell line assay. Results: The method has been tested on twenty-three neutral drugs for which a consistent set of experimental data is available. We show here that our method reproduces the experimental data better than other existing tools. Furthermore it provides a detailed view of the relationship between the hydration and the permeability properties of molecules. Contact:anna.tramontano@uniroma1.it Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Edoardo Milanetti
- Department of Physics, Sapienza Università di Roma, Rome 00185, Italy
| | - Domenico Raimondo
- Department of Physics, Sapienza Università di Roma, Rome 00185, Italy
| | - Anna Tramontano
- Department of Physics, Sapienza Università di Roma, Rome 00185, Italy Institute Pasteur - Fondazione Cenci Bolognetti, Rome, 00161, Italy Center for Life Nano Science @Sapienza, Istituto Italiano di Tecnologia, Sapienza Università di Roma, Rome, 00185, Italy
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29
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Chatzizacharia K, Hatziavramidis D. New frames of reference for mapping drugs in the four classes of the BCS and BDDCS into regions with clear boundaries. AIChE J 2015. [DOI: 10.1002/aic.15017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Affiliation(s)
- Kalliopi Chatzizacharia
- School of Chemical Engineering; National Technical University of Athens; Heroon Polytechniou 9, Zografou 15780 Athens Greece
| | - Dimitris Hatziavramidis
- School of Chemical Engineering; National Technical University of Athens; Heroon Polytechniou 9, Zografou 15780 Athens Greece
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Cherian PT, Wu X, Yang L, Scarborough JS, Singh AP, Alam ZA, Lee RE, Hurdle JG. Gastrointestinal localization of metronidazole by a lactobacilli-inspired tetramic acid motif improves treatment outcomes in the hamster model of Clostridium difficile infection. J Antimicrob Chemother 2015; 70:3061-9. [PMID: 26286574 DOI: 10.1093/jac/dkv231] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2015] [Accepted: 07/07/2015] [Indexed: 01/30/2023] Open
Abstract
OBJECTIVES Metronidazole, a mainstay treatment for Clostridium difficile infection (CDI), is often ineffective for severe CDI. Whilst this is thought to arise from suboptimal levels of metronidazole in the colon due to rapid absorption, empirical validation is lacking. In contrast, reutericyclin, an antibacterial tetramic acid from Lactobacillus reuteri, concentrates in the gastrointestinal tract. In this study, we modified metronidazole with reutericyclin's tetramic acid motif to obtain non-absorbed compounds, enabling assessment of the impact of pharmacokinetics on treatment outcomes. METHODS A series of metronidazole-bearing tetramic acid substituents were synthesized and evaluated in terms of anti-C. difficile activities, gastric permeability, in vivo pharmacokinetics, efficacy in the hamster model of CDI and mode of action. RESULTS Most compounds were absorbed less than metronidazole in cell-based Caco-2 permeability assays. In hamsters, lead compounds compartmentalized in the colon rather than the bloodstream with negligible levels detected in the blood, in direct contrast with metronidazole, which was rapidly absorbed into the blood and was undetectable in caecum. Accordingly, four leads were more efficacious (P < 0.05) than metronidazole in C. difficile-infected animals. Improved efficacy was not due to an alternative mode of action, as the leads retained the mode of action of metronidazole. CONCLUSIONS This study provides the clearest empirical evidence that the high absorption of metronidazole lowers treatment outcomes for CDI and suggests a role for the tetramic acid motif for colon-specific drug delivery. This approach also has the potential to lower systemic toxicity and drug interactions of nitroheterocyclic drugs for treating gastrointestine-specific diseases.
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Affiliation(s)
- Philip T Cherian
- Department of Chemical Biology and Therapeutics, St Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Xiaoqian Wu
- Department of Biology, University of Texas, Arlington, TX 76019, USA Center for Infectious and Inflammatory Diseases, Institute of Biosciences and Technology, Texas A&M Health Science Center, Houston, TX 77030, USA
| | - Lei Yang
- Department of Chemical Biology and Therapeutics, St Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Jerrod S Scarborough
- Department of Chemical Biology and Therapeutics, St Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Aman P Singh
- Department of Chemical Biology and Therapeutics, St Jude Children's Research Hospital, Memphis, TN 38105, USA Biomedical Sciences Program, Graduate Health Sciences, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Zahidul A Alam
- Department of Biology, University of Texas, Arlington, TX 76019, USA
| | - Richard E Lee
- Department of Chemical Biology and Therapeutics, St Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Julian G Hurdle
- Department of Biology, University of Texas, Arlington, TX 76019, USA Center for Infectious and Inflammatory Diseases, Institute of Biosciences and Technology, Texas A&M Health Science Center, Houston, TX 77030, USA Department of Microbial and Molecular Pathogenesis, Texas A&M Health Science Center, College of Medicine, Bryan, TX 77807, USA
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Bosgra S, Vlaming MLH, Vaes WHJ. To Apply Microdosing or Not? Recommendations to Single Out Compounds with Non-Linear Pharmacokinetics. Clin Pharmacokinet 2015; 55:1-15. [DOI: 10.1007/s40262-015-0308-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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32
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Castillo-Garit JA, del Toro-Cortés O, Vega MC, Rolón M, Rojas de Arias A, Casañola-Martin GM, Escario JA, Gómez-Barrio A, Marrero-Ponce Y, Torrens F, Abad C. Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening. Eur J Med Chem 2015; 96:238-44. [PMID: 25884114 DOI: 10.1016/j.ejmech.2015.03.063] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2014] [Revised: 02/27/2015] [Accepted: 03/27/2015] [Indexed: 11/25/2022]
Abstract
Two-dimensional bond-based bilinear indices and linear discriminant analysis are used in this report to perform a quantitative structure-activity relationship study to identify new trypanosomicidal compounds. A data set of 440 organic chemicals, 143 with antitrypanosomal activity and 297 having other clinical uses, is used to develop the theoretical models. Two discriminant models, computed using bond-based bilinear indices, are developed and both show accuracies higher than 86% for training and test sets. The stochastic model correctly indentifies nine out of eleven compounds of a set of organic chemicals obtained from our synthetic collaborators. The in vitro antitrypanosomal activity of this set against epimastigote forms of Trypanosoma cruzi is assayed. Both models show a good agreement between theoretical predictions and experimental results. Three compounds showed IC50 values for epimastigote elimination (AE) lower than 50 μM, while for the benznidazole the IC50 = 54.7 μM which was used as reference compound. The value of IC50 for cytotoxicity of these compounds is at least 5 times greater than their value of IC50 for AE. Finally, we can say that, the present algorithm constitutes a step forward in the search for efficient ways of discovering new antitrypanosomal compounds.
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Affiliation(s)
- Juan Alberto Castillo-Garit
- Centro de Estudio de Química Aplicada, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba; Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba; Departament de Bioquímica i Biologia Molecular, Universitat de València, E-46100, Burjassot, Spain; Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain.
| | - Oremia del Toro-Cortés
- Centro de Estudio de Química Aplicada, Facultad de Química-Farmacia, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba
| | - Maria C Vega
- Centro para el Desarrollo de la Investigacion Cientifica (CEDIC) and Fundación Moisés Bertoni/Laboratorios Díaz Gill, Pai Perez 265 casi Mariscal Estigarribia, Asuncion, Paraguay
| | - Miriam Rolón
- Centro para el Desarrollo de la Investigacion Cientifica (CEDIC) and Fundación Moisés Bertoni/Laboratorios Díaz Gill, Pai Perez 265 casi Mariscal Estigarribia, Asuncion, Paraguay
| | - Antonieta Rojas de Arias
- Centro para el Desarrollo de la Investigacion Cientifica (CEDIC) and Fundación Moisés Bertoni/Laboratorios Díaz Gill, Pai Perez 265 casi Mariscal Estigarribia, Asuncion, Paraguay
| | - Gerardo M Casañola-Martin
- Unit of Computer-Aided Molecular "Biosilico" Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy, Universidad Central "Marta Abreu" de Las Villas, Santa Clara, 54830, Villa Clara, Cuba; Departament de Bioquímica i Biologia Molecular, Universitat de València, E-46100, Burjassot, Spain; Centro de Información y Gestión Tecnológica, Ministerio de Ciencia Tecnología y Medio Ambiente (CITMA), 65100, Ciego de Ávila, Cuba
| | - José A Escario
- Departamento de Parasitología, Facultad de Farmacia, UCM, Pza. Ramón y Cajal s/n, 28040, Madrid, Spain
| | - Alicia Gómez-Barrio
- Departamento de Parasitología, Facultad de Farmacia, UCM, Pza. Ramón y Cajal s/n, 28040, Madrid, Spain
| | - Yovani Marrero-Ponce
- Enviromental and Computational Chemistry Group, Facultad de Química Farmacéutica, Universidad de Cartagena,Cartagena de Indias, Bolivar, Colombia
| | - Francisco Torrens
- Institut Universitari de Ciència Molecular, Universitat de València, Edifici d'Instituts de Paterna, P.O. Box 22085, E-46071, València, Spain
| | - Concepción Abad
- Departament de Bioquímica i Biologia Molecular, Universitat de València, E-46100, Burjassot, Spain
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Da Silva LC, Da Silva TL, Antunes AH, Rezende KR. A Sensitive Medium-Throughput Method to Predict Intestinal Absorption in Humans Using Rat Intestinal Tissue Segments. J Pharm Sci 2015; 104:2807-12. [PMID: 25690454 DOI: 10.1002/jps.24372] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2014] [Revised: 12/09/2014] [Accepted: 01/08/2015] [Indexed: 11/08/2022]
Abstract
A range of in vitro, ex vivo, and in vivo approaches are currently used for drug development. Highly predictive human intestinal absorption models remain lagging behind the times because of numerous variables concerning permeability through gastrointestinal tract in humans. However, there is a clear need for a drug permeability model early in the drug development process that can balance the requirements for high throughput and effective predictive potential. The present study developed a medium throughput screening Snapwell (MTS-Snapwell) ex vivo model to provide an alternative method to classify drug permeability. Rat small intestine tissue segments were mounted in commercial Snapwell™ inserts. Unidirectional drug transport (A-B) was measured by collecting samples at different time points. Viability of intestinal tissue segments was measured by examining transepithelial electric resistance (TEER) and phenol red and caffeine transport. As a result, the apparent permeability (Papp; ×10(-6) cm/s) was determined for atenolol (10.7 ± 1.2), caffeine (17.6 ± 3.1), cimetidine (6.9 ± 0.1), metoprolol (12.6 ± 0.7), theophylline (15.3 ± 1.6) and, ranitidine (3.8 ± 0.4). All drugs were classified in high/low permeability according to Biopharmaceutics Classification System showing high correlation with human data (r = 0.89). These findings showed a high correlation with human data (r = 0.89), suggesting that this model has potential predictive capacity for paracellular and transcellular passively absorbed molecules.
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Affiliation(s)
- Laís Cristina Da Silva
- Laboratory of Biopharmacy and Pharmacokinetics, School of Pharmacy, Federal University of Goiás, Goiânia, Brazil
| | - Taynara Lourenço Da Silva
- Laboratory of Biopharmacy and Pharmacokinetics, School of Pharmacy, Federal University of Goiás, Goiânia, Brazil
| | - Alisson Henrique Antunes
- Laboratory of Biopharmacy and Pharmacokinetics, School of Pharmacy, Federal University of Goiás, Goiânia, Brazil
| | - Kênnia Rocha Rezende
- Laboratory of Biopharmacy and Pharmacokinetics, School of Pharmacy, Federal University of Goiás, Goiânia, Brazil
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Rojas-Aguirre Y, Medina-Franco JL. Analysis of structure-Caco-2 permeability relationships using a property landscape approach. Mol Divers 2014; 18:599-610. [DOI: 10.1007/s11030-014-9514-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Accepted: 02/28/2014] [Indexed: 12/14/2022]
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Ferreira AP, Tobyn M. Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era. Pharm Dev Technol 2014; 20:513-27. [DOI: 10.3109/10837450.2014.898656] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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36
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Huang C, Zheng C, Li Y, Wang Y, Lu A, Yang L. Systems pharmacology in drug discovery and therapeutic insight for herbal medicines. Brief Bioinform 2013; 15:710-33. [DOI: 10.1093/bib/bbt035] [Citation(s) in RCA: 142] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Brito-Sánchez Y, Castillo-Garit JA, Le-Thi-Thu H, González-Madariaga Y, Torrens F, Marrero-Ponce Y, Rodríguez-Borges JE. Comparative study to predict toxic modes of action of phenols from molecular structures. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2013; 24:235-251. [PMID: 23437773 DOI: 10.1080/1062936x.2013.766260] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. Most of them showed global accuracy of over 90%, and false alarm rate values were below 2.9% for the training set. Cross-validation, complementary subsets and external test set were performed, with good behaviour in all cases. Our models compare favourably with other previously published models, and in general the models obtained with ML techniques show better results than those developed with linear techniques. We developed unsupervised and supervised consensus, and these results were better than our ML models, the results of rule-based approach and other ensemble models previously published. This investigation highlights the merits of ML-based techniques as an alternative to other more traditional methods for modelling MOA.
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Affiliation(s)
- Y Brito-Sánchez
- Unit of Computer-Aided Molecular Biosilico Discovery and Bioinformatic Research, Faculty of Chemistry-Pharmacy, Universidad Central Marta Abreu de Las Villas, Santa Clara, Cuba
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Larregieu CA, Benet LZ. Drug discovery and regulatory considerations for improving in silico and in vitro predictions that use Caco-2 as a surrogate for human intestinal permeability measurements. AAPS JOURNAL 2013; 15:483-97. [PMID: 23344793 DOI: 10.1208/s12248-013-9456-8] [Citation(s) in RCA: 95] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2012] [Accepted: 01/10/2013] [Indexed: 11/30/2022]
Abstract
There is a growing need for highly accurate in silico and in vitro predictive models to facilitate drug discovery and development. Results from in vitro permeation studies across the Caco-2 cell monolayer are commonly used for drug permeability screening in industry and are also accepted as a surrogate for human intestinal permeability measurements by the US FDA to support new drug applications. Countless studies carried out in this cell line with published permeability measurements have enabled the development of many in silico prediction models. We identify several common cases that illustrate how using Caco-2 permeability measurements in these in silico and in vitro predictive models will not correlate with human intestinal permeability and will further lead to inaccuracies in these models. We provide guidelines and recommendations for improving these models to more accurately predict clinically relevant information, thereby enhancing the drug discovery, development, and regulatory approval processes.
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Affiliation(s)
- Caroline A Larregieu
- Department of Bioengineering & Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, 533 Parnassus Avenue, Room U-68, San Francisco, CA 94143-0912, USA
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Abstract
Frequent failure of drug candidates during development stages remains the major deterrent for an early introduction of new drug molecules. The drug toxicity is the major cause of expensive late-stage development failures. An early identification/optimization of the most favorable molecule will naturally save considerable cost, time, human efforts and minimize animal sacrifice. (Quantitative) Structure Activity Relationships [(Q)SARs] represent statistically derived predictive models correlating biological activity (including desirable therapeutic effect and undesirable side effects) of chemicals (drugs/toxicants/environmental pollutants) with molecular descriptors and/or properties. (Q)SAR models which categorize the available data into two or more groups/classes are known as classification models. Numerous techniques of diverse nature are being presently employed for development of classification models. Though there is an increasing use of classification models for prediction of either biological activity or toxicity, the future trend will naturally be towards the development of classification models capable of simultaneous prediction of biological activity, toxicity, and pharmacokinetic parameters so as to accelerate development of bioavailable safe drug molecules.
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Duffy BC, Zhu L, Decornez H, Kitchen DB. Early phase drug discovery: cheminformatics and computational techniques in identifying lead series. Bioorg Med Chem 2012; 20:5324-42. [PMID: 22938785 DOI: 10.1016/j.bmc.2012.04.062] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2012] [Revised: 04/24/2012] [Accepted: 04/27/2012] [Indexed: 01/31/2023]
Abstract
Early drug discovery processes rely on hit finding procedures followed by extensive experimental confirmation in order to select high priority hit series which then undergo further scrutiny in hit-to-lead studies. The experimental cost and the risk associated with poor selection of lead series can be greatly reduced by the use of many different computational and cheminformatic techniques to sort and prioritize compounds. We describe the steps in typical hit identification and hit-to-lead programs and then describe how cheminformatic analysis assists this process. In particular, scaffold analysis, clustering and property calculations assist in the design of high-throughput screening libraries, the early analysis of hits and then organizing compounds into series for their progression from hits to leads. Additionally, these computational tools can be used in virtual screening to design hit-finding libraries and as procedures to help with early SAR exploration.
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Affiliation(s)
- Bryan C Duffy
- AMRI, 26 Corporate Circle, PO Box 15098, Albany, NY 12212-5098, USA
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41
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Castillo-Garit JA, del Toro-Cortés O, Kouznetsov VV, Puentes CO, Romero Bohórquez AR, Vega MC, Rolón M, Escario JA, Gómez-Barrio A, Marrero-Ponce Y, Torrens F, Abad C. Identification In Silico and In Vitro of Novel Trypanosomicidal Drug-Like Compounds. Chem Biol Drug Des 2012; 80:38-45. [DOI: 10.1111/j.1747-0285.2012.01378.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Sherer EC, Verras A, Madeira M, Hagmann WK, Sheridan RP, Roberts D, Bleasby K, Cornell WD. QSAR Prediction of Passive Permeability in the LLC-PK1 Cell Line: Trends in Molecular Properties and Cross-Prediction of Caco-2 Permeabilities. Mol Inform 2012; 31:231-45. [DOI: 10.1002/minf.201100157] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2011] [Accepted: 01/06/2012] [Indexed: 01/16/2023]
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Abstract
The human colon adenocarcinoma Caco-2 and Madin–Darby canine kidney epithelial cell lines provide in vitro tools to assess a drug’s permeability and transporter interactions during discovery and development. The cells, when cultured on semiporous filters, form confluent monolayers that model the intestinal epithelial barrier for permeability, transporter and drug-interaction assays. The applications of these assays in pharmaceutical research include qualitative prediction and ranking of absorption, determining mechanism(s) of permeability, formulation effects on drug permeability, and the potential for transporter-mediated drug–drug interactions. This review focuses on recent examples of Caco-2 and Madin–Darby canine kidney cells assays for drug permeability including transfected and knock-down cells, miniaturization and automation, and assay combinations to better understand and predict intestinal drug absorption.
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Ligand-based discovery of novel trypanosomicidal drug-like compounds: In silico identification and experimental support. Eur J Med Chem 2011; 46:3324-30. [DOI: 10.1016/j.ejmech.2011.04.057] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2010] [Revised: 04/26/2011] [Accepted: 04/26/2011] [Indexed: 01/08/2023]
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Han C, Zhang J, Zheng M, Xiao Y, Li Y, Liu G. An integrated drug-likeness study for bicyclic privileged structures: from physicochemical properties to in vitro ADME properties. Mol Divers 2011; 15:857-76. [DOI: 10.1007/s11030-011-9317-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2011] [Accepted: 04/15/2011] [Indexed: 11/24/2022]
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QSAR-based permeability model for drug-like compounds. Bioorg Med Chem 2011; 19:2615-24. [DOI: 10.1016/j.bmc.2011.03.011] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2010] [Revised: 03/04/2011] [Accepted: 03/05/2011] [Indexed: 11/23/2022]
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Pham The H, González-Álvarez I, Bermejo M, Mangas Sanjuan V, Centelles I, Garrigues TM, Cabrera-Pérez MÁ. In Silico Prediction of Caco-2 Cell Permeability by a Classification QSAR Approach. Mol Inform 2011; 30:376-85. [DOI: 10.1002/minf.201000118] [Citation(s) in RCA: 66] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2010] [Accepted: 01/16/2011] [Indexed: 11/09/2022]
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Rescigno A, Casañola-Martin GM, Sanjust E, Zucca P, Marrero-Ponce Y. Vanilloid derivatives as tyrosinase inhibitors driven by virtual screening-based QSAR models. Drug Test Anal 2010; 3:176-81. [PMID: 21125547 DOI: 10.1002/dta.187] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2010] [Revised: 08/19/2010] [Accepted: 08/19/2010] [Indexed: 11/06/2022]
Abstract
A number of vanilloids have been tested as tyrosinase inhibitors using Ligand-Based Virtual Screening (LBVS) driven by QSAR (Quantitative Structure-Activity Relationship) models as the multi-agent classification system. A total of 81 models were used to screen this family. Then, a preliminary cluster analysis of the selected chemicals was carried out based on their bioactivity to detect possible similar substructural features among these compounds and the active database used in the QSAR model construction. The compounds identified were tested in vitro to corroborate the results obtained in silico. Among them, two chemicals, isovanillin (K(M) (app) = 1.08 mM) near to kojic acid (reference drug) in one cluster and isovanillyl alcohol (K(M) (app) = 0.88 mM) at the same distance as hydroquinone (reference drug) in another cluster showed inhibitory activity against tyrosinase. The algorithm proposed here could result in a suitable approach for faster and more effective identification of hit and/or lead compounds with tyrosinase inhibitory activity, helping to shorten the long pipeline in the research of novel depigmenting agents to treat skin disorders.
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Affiliation(s)
- Antonio Rescigno
- Dipartimento di Scienze e Tecnologie Biomediche, Università di Cagliari, Cittadella Universitaria, Monserrato (CA), Italy
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Prediction of the in vitro permeability determined in Caco-2 cells by using artificial neural networks. Eur J Pharm Sci 2010; 41:107-17. [DOI: 10.1016/j.ejps.2010.05.014] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2010] [Revised: 05/12/2010] [Accepted: 05/30/2010] [Indexed: 11/24/2022]
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Castillo-Garit J, Marrero-Ponce Y, Torrens F, García-Domenech R, Rodríguez-Borges J. Applications of Bond-Based 3D-Chiral Quadratic Indices in QSAR Studies Related to Central Chirality Codification. ACTA ACUST UNITED AC 2009. [DOI: 10.1002/qsar.200960085] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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