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Zhang Y, Wu W, Li Q, Zhou P, Wen K, Shen J, Wang Z. The hapten rigidity improves antibody performances in immunoassay for rifamycins: Immunovalidation and molecular mechanism. JOURNAL OF HAZARDOUS MATERIALS 2024; 469:133977. [PMID: 38492395 DOI: 10.1016/j.jhazmat.2024.133977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 02/24/2024] [Accepted: 03/05/2024] [Indexed: 03/18/2024]
Abstract
The immunogenicity of haptens determines the performance of the resultant antibody for small molecules. Rigidity is one of the basic physicochemical properties of haptens. However, few studies have investigated the effect of hapten rigidity on the strength of an immune response and overall antibody performance. Herein, we introduce three molecular descriptors that quantify hapten rigidity. By using of these descriptors, four rifamycin haptens with varied rigidity were designed. The structural and physicochemical feasibility of the designed haptens was then assessed by computational chemistry. Immunization demonstrated that the strength of induced immune responses, i.e., the titer and affinity of antiserum, was significantly increased with increased rigidity of haptens. Furthermore, molecular dynamic simulations demonstrated conformation constraint of rigid haptens contributed to the initial binding and activation of naïve B cells. Finally, a highly sensitive indirect competitive enzyme-linked immunosorbent assay was developed for detection of rifaximin, with an IC50 of 1.1 μg/L in buffer and a limit of detection of 0.2-11.3 μg/L in raw milk, river water, and soil samples. This work provides new insights into the effect of hapten rigidity on immunogenicity and offers new hapten design strategies for antibody discovery and vaccine development of small molecules.
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Affiliation(s)
- Yingjie Zhang
- National Key Laboratory of Veterinary Public Health and Safety, Beijing Key Laboratory of Detection Technology for Animal-Derived Food, College of Veterinary Medicine, China Agricultural University, 100193 Beijing, People's Republic of China
| | - Weilin Wu
- National Key Laboratory of Veterinary Public Health and Safety, Beijing Key Laboratory of Detection Technology for Animal-Derived Food, College of Veterinary Medicine, China Agricultural University, 100193 Beijing, People's Republic of China
| | - Qing Li
- National Key Laboratory of Veterinary Public Health and Safety, Beijing Key Laboratory of Detection Technology for Animal-Derived Food, College of Veterinary Medicine, China Agricultural University, 100193 Beijing, People's Republic of China
| | - Penghui Zhou
- National Key Laboratory of Veterinary Public Health and Safety, Beijing Key Laboratory of Detection Technology for Animal-Derived Food, College of Veterinary Medicine, China Agricultural University, 100193 Beijing, People's Republic of China
| | - Kai Wen
- National Key Laboratory of Veterinary Public Health and Safety, Beijing Key Laboratory of Detection Technology for Animal-Derived Food, College of Veterinary Medicine, China Agricultural University, 100193 Beijing, People's Republic of China
| | - Jianzhong Shen
- National Key Laboratory of Veterinary Public Health and Safety, Beijing Key Laboratory of Detection Technology for Animal-Derived Food, College of Veterinary Medicine, China Agricultural University, 100193 Beijing, People's Republic of China
| | - Zhanhui Wang
- National Key Laboratory of Veterinary Public Health and Safety, Beijing Key Laboratory of Detection Technology for Animal-Derived Food, College of Veterinary Medicine, China Agricultural University, 100193 Beijing, People's Republic of China.
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2
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Alshehri MM, Kumar N, Kuthi NA, Olaide Z, Alshammari MK, Bello RO, Alghazwni MK, Alshehri AM, Alshlali OM, Ashimiyu-Abdusalam Z, Umar HI. Computer-aided drug discovery of c-Abl kinase inhibitors from plant compounds against chronic myeloid leukemia. J Biomol Struct Dyn 2024:1-21. [PMID: 38517058 DOI: 10.1080/07391102.2024.2329297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 03/06/2024] [Indexed: 03/23/2024]
Abstract
Chronic myeloid leukemia (CML) is a hematological malignancy characterized by the neoplastic transformation of hematopoietic stem cells, driven by the Philadelphia (Ph) chromosome resulting from a translocation between chromosomes 9 and 22. This Ph chromosome harbors the breakpoint cluster region (BCR) and the Abelson (ABL) oncogene (BCR-ABL1) which have a constitutive tyrosine kinase activity. However, the tyrosine kinase activity of BCR-ABL1 have been identified as a key player in CML initiation and maintenance through c-Abl kinase. Despite advancements in tyrosine kinase inhibitors, challenges such as efficacy, safety concerns, and recurring drug resistance persist. This study aims to discover potential c-Abl kinase inhibitors from plant compounds with anti-leukemic properties, employing drug-likeness assessment, molecular docking, in silico pharmacokinetics (ADMET) screening, density function theory (DFT), and molecular dynamics simulations (MDS). Out of 58 screened compounds for drug-likeness, 44 were docked against c-Abl kinase. The top hit compound (isovitexin) and nilotinib (control drug) were subjected to rigorous analyses, including ADMET profiling, DFT evaluation, and MDS for 100 ns. Isovitexin demonstrated a notable binding affinity (-15.492 kcal/mol), closely comparable to nilotinib (-16.826 kcal/mol), showcasing a similar binding pose and superior structural stability and reactivity. While these findings suggest isovitexin as a potential c-Abl kinase inhibitor, further validation through urgent in vitro and in vivo experiments is imperative. This research holds promise for providing an alternative avenue to address existing CML treatment and management challenges.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mohammed M Alshehri
- Pharmaceutical Care Department, Ministry of National Guard-Health Affairs, Riyadh, Kingdom of Saudi Arabia
| | - Neeraj Kumar
- Department of Pharmaceutical Chemistry, Bhupal Nobles' College of Pharmacy, Udaipur, India
| | - Najwa Ahmad Kuthi
- Department of Chemistry, Faculty of Science, Universiti Teknologi Malaysia (UTM), Johor, Malaysia
| | - Zainab Olaide
- Department of Biochemistry, Ibrahim Badamasi Babangida University, Lapai, Nigeria
| | | | - Ridwan Opeyemi Bello
- Computer-Aided Therapeutic Discovery and Design Platform, Federal University of Technology, Akure, Nigeria
| | | | | | | | - Zainab Ashimiyu-Abdusalam
- Computer-Aided Therapeutic Discovery and Design Platform, Federal University of Technology, Akure, Nigeria
- Department of Biochemistry and Nutrition, Nigerian Institute of Medical Research, Yaba, Nigeria
| | - Haruna Isiyaku Umar
- Computer-Aided Therapeutic Discovery and Design Platform, Federal University of Technology, Akure, Nigeria
- Department of Biochemistry, Federal University of Technology, Akure, Nigeria
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3
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Tichotová MC, Tučková L, Kocek H, Růžička A, Straka M, Procházková E. Exploring the impact of alignment media on RDC analysis of phosphorus-containing compounds: a molecular docking approach. Phys Chem Chem Phys 2024; 26:2016-2024. [PMID: 38126374 DOI: 10.1039/d3cp04099b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Residual dipolar couplings (RDCs) are employed in NMR analysis when conventional methods, such as J-couplings and nuclear Overhauser effects (NOEs) fail. Low-energy (optimized) conformers are often used as input structures in RDC analysis programs. However, these low-energy structures do not necessarily resemble conformations found in anisotropic environments due to interactions with the alignment medium, especially if the analyte molecules are flexible. Considering interactions with alignment media in RDC analysis, we developed and evaluated a molecular docking-based approach to generate more accurate conformer ensembles for compounds in the presence of the poly-γ-benzyl-L-glutamate alignment medium. We designed chiral phosphorus-containing compounds that enabled us to utilize 31P NMR parameters for the stereochemical analysis. Using P3D/PALES software to evaluate diastereomer discrimination, we found that our conformer ensembles outperform moderately the standard, low-energy conformers in RDC analysis. To further improve our results, we (i) averaged the experimental values of the molecular docking-based conformers by applying the Boltzmann distribution and (ii) optimized the structures through normal mode relaxation, thereby enhancing the Pearson correlation factor R and even diastereomer discrimination in some cases. Nevertheless, we presume that significant differences between J-couplings in isotropic and in anisotropic environments may preclude RDC measurements for flexible molecules. Therefore, generating conformer ensembles based on molecular docking enhances RDC analysis for mildly flexible systems while flexible molecules may require applying more advanced approaches, in particular approaches including dynamical effects.
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Affiliation(s)
- Markéta Christou Tichotová
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.
- Department of Physical and Macromolecular Chemistry, Faculty of Science, Charles University, 116 28 Prague, Czech Republic
| | - Lucie Tučková
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.
| | - Hugo Kocek
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.
| | - Aleš Růžička
- Department of General and Inorganic Chemistry, Faculty of Chemical Technology, University of Pardubice, Pardubice 532 10, Czech Republic
| | - Michal Straka
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.
| | - Eliška Procházková
- Institute of Organic Chemistry and Biochemistry, Czech Academy of Sciences, 160 00 Prague, Czech Republic.
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4
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Folmsbee D, Koes DR, Hutchison GR. Systematic Comparison of Experimental Crystallographic Geometries and Gas-Phase Computed Conformers for Torsion Preferences. J Chem Inf Model 2023; 63:7401-7411. [PMID: 38000780 PMCID: PMC10716907 DOI: 10.1021/acs.jcim.3c01278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 11/07/2023] [Accepted: 11/13/2023] [Indexed: 11/26/2023]
Abstract
We performed exhaustive torsion sampling on more than 3 million compounds using the GFN2-xTB method and performed a comparison of experimental crystallographic and gas-phase conformers. Many conformer sampling methods derive torsional angle distributions from experimental crystallographic data, limiting the torsion preferences to molecules that must be stable, synthetically accessible, and able to be crystallized. In this work, we evaluate the differences in torsional preferences of experimental crystallographic geometries and gas-phase computed conformers from a broad selection of compounds to determine whether torsional angle distributions obtained from semiempirical methods are suitable priors for conformer sampling. We find that differences in torsion preferences can be mostly attributed to a lack of available experimental crystallographic data with small deviations derived from gas-phase geometry differences. GFN2 demonstrates the ability to provide accurate and reliable torsional preferences that can provide a basis for new methods free from the limitations of experimental data collection. We provide Gaussian-based fits and sampling distributions suitable for torsion sampling and propose an alternative to the widely used "experimental torsion and knowledge distance geometry" (ETKDG) method using quantum torsion-derived distance geometry (QTDG) methods.
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Affiliation(s)
- Dakota
L. Folmsbee
- Department
of Chemistry, University of Pittsburgh, 219 Parkman Avenue, Pittsburgh, Pennsylvania 15260, United States
- Department
of Anesthesiology & Perioperative Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States
| | - David R. Koes
- Department
of Computational & Systems Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States
| | - Geoffrey R. Hutchison
- Department
of Chemistry, University of Pittsburgh, 219 Parkman Avenue, Pittsburgh, Pennsylvania 15260, United States
- Department
of Chemical & Petroleum Engineering, University of Pittsburgh, 3700 O’Hara Street, Pittsburgh, Pennsylvania 15261, United States
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5
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Jablonka K, Rosen AS, Krishnapriyan AS, Smit B. An Ecosystem for Digital Reticular Chemistry. ACS CENTRAL SCIENCE 2023; 9:563-581. [PMID: 37122448 PMCID: PMC10141625 DOI: 10.1021/acscentsci.2c01177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The vastness of the materials design space makes it impractical to explore using traditional brute-force methods, particularly in reticular chemistry. However, machine learning has shown promise in expediting and guiding materials design. Despite numerous successful applications of machine learning to reticular materials, progress in the field has stagnated, possibly because digital chemistry is more an art than a science and its limited accessibility to inexperienced researchers. To address this issue, we present mofdscribe, a software ecosystem tailored to novice and seasoned digital chemists that streamlines the ideation, modeling, and publication process. Though optimized for reticular chemistry, our tools are versatile and can be used in nonreticular materials research. We believe that mofdscribe will enable a more reliable, efficient, and comparable field of digital chemistry.
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Affiliation(s)
- Kevin
Maik Jablonka
- Laboratory of molecular simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, CH-1951 Sion, Switzerland
| | - Andrew S. Rosen
- Department of Materials
Science and Engineering, University of California, Berkeley, California 94720, United States
- Miller Institute for Basic Research in Science, University of California, Berkeley, California 94720, United States
- Materials Science Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Aditi S. Krishnapriyan
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California 94720, United States
- Department of Electrical Engineering and
Computer Science, University of California, Berkeley, California 94720, United States
- Computational
Research Division, Lawrence Berkeley National
Laboratory, Berkeley, California 94720, United States
| | - Berend Smit
- Laboratory of molecular simulation (LSMO), Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), Rue de l’Industrie 17, CH-1951 Sion, Switzerland
- E-mail:
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6
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In Silico Study Approach on a Series of 50 Polyphenolic Compounds in Plants; A Comparison on the Bioavailability and Bioactivity Data. Molecules 2022; 27:molecules27041413. [PMID: 35209203 PMCID: PMC8878759 DOI: 10.3390/molecules27041413] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/31/2022] [Accepted: 02/17/2022] [Indexed: 11/17/2022] Open
Abstract
Fifty (50) phytocompounds from several subclasses of polyphenols, chosen based on their abundance in the plant world, were analyzed through density functional methods, using computational tools to evaluate their oral availability and particular bioactivity on several cell modulators; key descriptors and molecular features related to the electron density and electrostatic potential for the lowest energy conformers of the investigated molecules were computed. An analysis of the bioactivity scores towards six cell modulators (GPCR ligand, ion channel modulator, kinase inhibitor, nuclear receptor ligand, protease inhibitor and enzyme inhibitor) was also achieved, in the context of investigating their potential side effects on the human digestive processes. Summarizing, computational results confirmed in vivo and in vitro data regarding the high bioavailability of soy isoflavones and better bioavailability of free aglycones in comparison with their esterified and glycosylated forms. However, by a computational approach analyzing Lipinski’s rule, apigenin and apigenin-7-O-rhamnoside, naringenin, hesperetin, genistein, daidzin, biochanin A and formonetin in the flavonoid series and all hydroxycinnamic acids and all hydroxybenzoic acids excepting ellagic acid were proved to have the best bioavailability data; rhamnoside derivatives, the predominant glycosides in green plants, which were reported to have the lowest bioavailability values by in vivo studies, were revealed to have the best bioavailability data among the studied flavonoids in the computational approach. Results of in silico screening on the phenolic derivatives series also revealed their real inhibitory potency on the six parameters studied, showing a remarkable similitude between the flavonoid series, while flavonoids were more powerful natural cell modulators than the phenyl carboxylic acids tested. Thus, it can be concluded that there is a need for supplementation with digestive enzymes, mainly in the case of individuals with low digestive efficiency, to obtain the best health benefits of polyphenols in humans.
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7
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Kalpana K, Syed R, Saranya J, Rafi M, Kiran BR. Synthesis and Theoretical Study of Novel Imidazo[4,5-b]pyrazine-Conjugated Benzamides as Potential Anticancer Agents. RUSSIAN JOURNAL OF ORGANIC CHEMISTRY 2021. [DOI: 10.1134/s1070428021090153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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8
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Jensen Z, Kwon S, Schwalbe-Koda D, Paris C, Gómez-Bombarelli R, Román-Leshkov Y, Corma A, Moliner M, Olivetti EA. Discovering Relationships between OSDAs and Zeolites through Data Mining and Generative Neural Networks. ACS CENTRAL SCIENCE 2021; 7:858-867. [PMID: 34079901 PMCID: PMC8161479 DOI: 10.1021/acscentsci.1c00024] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Indexed: 05/03/2023]
Abstract
Organic structure directing agents (OSDAs) play a crucial role in the synthesis of micro- and mesoporous materials especially in the case of zeolites. Despite the wide use of OSDAs, their interaction with zeolite frameworks is poorly understood, with researchers relying on synthesis heuristics or computationally expensive techniques to predict whether an organic molecule can act as an OSDA for a certain zeolite. In this paper, we undertake a data-driven approach to unearth generalized OSDA-zeolite relationships using a comprehensive database comprising of 5,663 synthesis routes for porous materials. To generate this comprehensive database, we use natural language processing and text mining techniques to extract OSDAs, zeolite phases, and gel chemistry from the scientific literature published between 1966 and 2020. Through structural featurization of the OSDAs using weighted holistic invariant molecular (WHIM) descriptors, we relate OSDAs described in the literature to different types of cage-based, small-pore zeolites. Lastly, we adapt a generative neural network capable of suggesting new molecules as potential OSDAs for a given zeolite structure and gel chemistry. We apply this model to CHA and SFW zeolites generating several alternative OSDA candidates to those currently used in practice. These molecules are further vetted with molecular mechanics simulations to show the model generates physically meaningful predictions. Our model can automatically explore the OSDA space, reducing the amount of simulation or experimentation needed to find new OSDA candidates.
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Affiliation(s)
- Zach Jensen
- Department
of Materials Science and Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Soonhyoung Kwon
- Department
of Chemical Engineering, Massachusetts Institute
of Technology, Cambridge, Massachusetts 02139, United States
| | - Daniel Schwalbe-Koda
- Department
of Materials Science and Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Cecilia Paris
- Instituto
de Tecnología Química, Universitat
Politècnica de València-Consejo Superior de Investigaciones
Científicas, Avenida de los Naranjos s/n, 46022 Valencia, Spain
| | - Rafael Gómez-Bombarelli
- Department
of Materials Science and Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Yuriy Román-Leshkov
- Department
of Chemical Engineering, Massachusetts Institute
of Technology, Cambridge, Massachusetts 02139, United States
| | - Avelino Corma
- Instituto
de Tecnología Química, Universitat
Politècnica de València-Consejo Superior de Investigaciones
Científicas, Avenida de los Naranjos s/n, 46022 Valencia, Spain
| | - Manuel Moliner
- Instituto
de Tecnología Química, Universitat
Politècnica de València-Consejo Superior de Investigaciones
Científicas, Avenida de los Naranjos s/n, 46022 Valencia, Spain
| | - Elsa A. Olivetti
- Department
of Materials Science and Engineering, Massachusetts
Institute of Technology, Cambridge, Massachusetts 02139, United States
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9
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Malik MS, Asghar BH, Syed R, Alsantali RI, Morad M, Altass HM, Moussa Z, Althagafi II, Jassas RS, Ahmed SA. Novel Pyran-Linked Phthalazinone-Pyrazole Hybrids: Synthesis, Cytotoxicity Evaluation, Molecular Modeling, and Descriptor Studies. Front Chem 2021; 9:666573. [PMID: 34109154 PMCID: PMC8181751 DOI: 10.3389/fchem.2021.666573] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 04/29/2021] [Indexed: 12/20/2022] Open
Abstract
A series of novel pyran-linked phthalazinone-pyrazole hybrids were designed and synthesized by a facile one-pot three-component reaction employing substituted phthalazinone, 1H-pyrazole-5-carbaldehyde, and active methylene compounds. Optimization studies led to the identification of L-proline and ethanol as efficient catalyst and solvent, respectively. This was followed by evaluation of anticancer activity against solid tumor cell lines of lung and cervical carcinoma that displayed IC50 values in the range of 9.8–41.6 µM. Molecular modeling studies were performed, and crucial interactions with the target protein were identified. The drug likeliness nature of the compounds and molecular descriptors such as molecular flexibility, complexity, and shape index were also calculated to understand the potential of the synthesized molecules to act as lead-like molecule upon further detailed biological investigations as well as 3D-QSAR studies.
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Affiliation(s)
- M Shaheer Malik
- Department of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Basim H Asghar
- Department of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Riyaz Syed
- Department of Chemistry, Jawaharlal Nehru Technological University, Hyderabad, India
| | - Reem I Alsantali
- Department of Pharmaceutical Chemistry, Pharmacy College, Taif University, Makkah, Saudi Arabia
| | - Moataz Morad
- Department of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Hatem M Altass
- Department of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.,Research Laboratories Unit, Faculty of Applied Science, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Ziad Moussa
- Department of Chemistry, College of Science, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Ismail I Althagafi
- Department of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Rabab S Jassas
- Department of Chemistry, Jamoum University College, Umm Al-Qura University, Makkah, Saudi Arabia
| | - Saleh A Ahmed
- Department of Chemistry, Faculty of Applied Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.,Department of Chemistry, Faculty of Science, Assiut University, Assiut, Egypt
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10
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Malik MS, Adil SF, Seddigi ZS, Morad M, Jassas RS, Thagafi II, Altass HM, Sajid Jamal QM, Riyaz S, Alsantali RI, Al-Warthan AA, Ansari MA, Ahmed SA. Molecular modelling assisted design of napthalimide-dihydropyrimidinone conjugates as potential cytotoxic agents. JOURNAL OF SAUDI CHEMICAL SOCIETY 2021. [DOI: 10.1016/j.jscs.2021.101226] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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11
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Vriza A, Canaj AB, Vismara R, Kershaw Cook LJ, Manning TD, Gaultois MW, Wood PA, Kurlin V, Berry N, Dyer MS, Rosseinsky MJ. One class classification as a practical approach for accelerating π-π co-crystal discovery. Chem Sci 2020; 12:1702-1719. [PMID: 34163930 PMCID: PMC8179233 DOI: 10.1039/d0sc04263c] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The implementation of machine learning models has brought major changes in the decision-making process for materials design. One matter of concern for the data-driven approaches is the lack of negative data from unsuccessful synthetic attempts, which might generate inherently imbalanced datasets. We propose the application of the one-class classification methodology as an effective tool for tackling these limitations on the materials design problems. This is a concept of learning based only on a well-defined class without counter examples. An extensive study on the different one-class classification algorithms is performed until the most appropriate workflow is identified for guiding the discovery of emerging materials belonging to a relatively small class, that being the weakly bound polyaromatic hydrocarbon co-crystals. The two-step approach presented in this study first trains the model using all the known molecular combinations that form this class of co-crystals extracted from the Cambridge Structural Database (1722 molecular combinations), followed by scoring possible yet unknown pairs from the ZINC15 database (21 736 possible molecular combinations). Focusing on the highest-ranking pairs predicted to have higher probability of forming co-crystals, materials discovery can be accelerated by reducing the vast molecular space and directing the synthetic efforts of chemists. Further on, using interpretability techniques a more detailed understanding of the molecular properties causing co-crystallization is sought after. The applicability of the current methodology is demonstrated with the discovery of two novel co-crystals, namely pyrene-6H-benzo[c]chromen-6-one (1) and pyrene-9,10-dicyanoanthracene (2). Machine learning using one class classification on a database of existing co-crystals enables the identification of co-formers which are likely to form stable co-crystals, resulting in the synthesis of two co-crystals of polyaromatic hydrocarbons.![]()
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Affiliation(s)
- Aikaterini Vriza
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK .,Leverhulme Research Centre for Functional Materials Design, University of Liverpool Oxford Street Liverpool L7 3NY UK
| | - Angelos B Canaj
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK
| | - Rebecca Vismara
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK
| | - Laurence J Kershaw Cook
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK
| | - Troy D Manning
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK
| | - Michael W Gaultois
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK .,Leverhulme Research Centre for Functional Materials Design, University of Liverpool Oxford Street Liverpool L7 3NY UK
| | - Peter A Wood
- Cambridge Crystallographic Data Centre 12 Union Road Cambridge CB2 1EZ UK
| | - Vitaliy Kurlin
- Materials Innovation Factory, Computer Science Department, University of Liverpool Liverpool L69 3BX UK
| | - Neil Berry
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK
| | - Matthew S Dyer
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK .,Leverhulme Research Centre for Functional Materials Design, University of Liverpool Oxford Street Liverpool L7 3NY UK
| | - Matthew J Rosseinsky
- Department of Chemistry and Materials Innovation Factory, University of Liverpool 51 Oxford Street Liverpool L7 3NY UK .,Leverhulme Research Centre for Functional Materials Design, University of Liverpool Oxford Street Liverpool L7 3NY UK
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12
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Schenck L, Erdemir D, Saunders Gorka L, Merritt JM, Marziano I, Ho R, Lee M, Bullard J, Boukerche M, Ferguson S, Florence AJ, Khan SA, Sun CC. Recent Advances in Co-processed APIs and Proposals for Enabling Commercialization of These Transformative Technologies. Mol Pharm 2020; 17:2232-2244. [DOI: 10.1021/acs.molpharmaceut.0c00198] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Luke Schenck
- Process Research and Development, Merck & Co. Inc., 126 East Lincoln Avenue, Rahway, New Jersey 07065, United States
| | - Deniz Erdemir
- Drug Product Development, Bristol-Myers Squibb, 1 Squibb Drive, New Brunswick New Jersey 08903, United States
| | | | - Jeremy M. Merritt
- Small Molecule Design and Development, Lilly Research Laboratories, Eli Lilly and Company, Indianapolis, Indiana 46221, United States
| | - Ivan Marziano
- Pfizer R&D UK Limited, Discovery Park, Ramsgate Road, Sandwich CT13 9NJ, United Kingdom
| | - Raimundo Ho
- Solid State Chemistry, AbbVie Inc., 1 North Waukegan Road, Chicago, Illinois 60064, United States
| | - Mei Lee
- Chemical Development, Product Development and Supply, GlaxoSmithKline, Gunnelswood Road, Stevenage SG1 2NY, United Kingdom
| | - Joseph Bullard
- Vertex Pharmaceuticals Incorporated, 50 Northern Avenue, Boston, Massachusetts 02210, United States
| | - Moussa Boukerche
- Center of Excellence for Isolation and Separation Technologies, AbbVie Inc., 1 North Waukegan Road, Chicago, Illinois 60064, United States
| | - Steven Ferguson
- SSPC, The SFI Centre for Pharmaceuticals, School of Chemical and Bioprocess Engineering, University College Dublin, Belifield, Dublin 4, Ireland
| | - Alastair J. Florence
- EPSRC Future Continuous Manufacturing and Advanced Crystallization Hub, CMAC, University of Strathclyde Glasgow, Glasgow, United Kingdom
| | - Saif A. Khan
- Department of Chemical and Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, Singapore 117576, Singapore
| | - Changquan Calvin Sun
- Pharmaceutical Materials Science and Engineering Laboratory, Department of Pharmaceutics, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota 55455, United States
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13
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Caron G, Digiesi V, Solaro S, Ermondi G. Flexibility in early drug discovery: focus on the beyond-Rule-of-5 chemical space. Drug Discov Today 2020; 25:621-627. [PMID: 31991117 DOI: 10.1016/j.drudis.2020.01.012] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 01/09/2020] [Accepted: 01/16/2020] [Indexed: 01/02/2023]
Abstract
Large and flexible compounds are of interest in pharmaceutical programs aimed at challenging protein targets that cannot be modulated by Rule of Five (Ro5)-compliant small molecules. Given their particular structural features, early drug discovery is now in charge of identifying which molecular descriptors should be used in the often called beyond-Rule-of-5 (bRo5) chemical space. Here, we focus on flexibility descriptors. First, we discuss the concept of flexibility and then focus on the number of rotatable bonds (NRot), the most common in silico descriptor. After identifying the pros and cons of NRot, we discuss how Kier's index Φ can replace NRot, and the limits of 3D descriptors. Finally, we show how a misuse of NRot and Φ can result in incorrect interpretations of the impact of flexibility in the bRo5 space and how flexibility has potential in the prospective design of orally bioavailable bRo5 drug candidates.
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Affiliation(s)
- Giulia Caron
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Quarello 15, 10135, Torino, Italy
| | - Vito Digiesi
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Quarello 15, 10135, Torino, Italy
| | - Sara Solaro
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Quarello 15, 10135, Torino, Italy
| | - Giuseppe Ermondi
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Quarello 15, 10135, Torino, Italy.
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14
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Nantasenamat C. Best Practices for Constructing Reproducible QSAR Models. METHODS IN PHARMACOLOGY AND TOXICOLOGY 2020. [DOI: 10.1007/978-1-0716-0150-1_3] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
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15
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Marchese Robinson RL, Geatches D, Morris C, Mackenzie R, Maloney AGP, Roberts KJ, Moldovan A, Chow E, Pencheva K, Vatvani DRM. Evaluation of Force-Field Calculations of Lattice Energies on a Large Public Dataset, Assessment of Pharmaceutical Relevance, and Comparison to Density Functional Theory. J Chem Inf Model 2019; 59:4778-4792. [DOI: 10.1021/acs.jcim.9b00601] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Richard L. Marchese Robinson
- Centre for Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Dawn Geatches
- Science and Technology Facilities Council, Daresbury Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, United Kingdom
| | - Chris Morris
- Science and Technology Facilities Council, Daresbury Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, United Kingdom
| | - Rebecca Mackenzie
- Science and Technology Facilities Council, Daresbury Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, United Kingdom
| | - Andrew G. P. Maloney
- Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, United Kingdom
| | - Kevin J. Roberts
- Centre for Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Alexandru Moldovan
- Centre for Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Ernest Chow
- Pfizer Worldwide R&D, Ramsgate Road, Sandwich CT13 9NJ, United Kingdom
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16
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Lai T, Pencheva K, Chow E, Docherty R. De-Risking Early-Stage Drug Development With a Bespoke Lattice Energy Predictive Model: A Materials Science Informatics Approach to Address Challenges Associated With a Diverse Chemical Space. J Pharm Sci 2019; 108:3176-3186. [DOI: 10.1016/j.xphs.2019.06.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Revised: 05/24/2019] [Accepted: 06/12/2019] [Indexed: 01/11/2023]
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17
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Abstract
In this paper, theories on anisotropic crystal growth and crystallization of atropisomers are reviewed and a model for anisotropic crystal growth from solution containing slow inter-converting conformers is presented. The model applies to systems with growth-dominated crystallization from solutions and assumes that only one conformation participates in the solute integration step and is present in the crystal lattice. Other conformers, defined as the wrong conformers, must convert to the right conformer before they can assemble to the crystal lattice. The model presents a simple implicit method for evaluating the growth inhibition effect by the wrong conformers. The crystal growth model applies to anisotropic growth in two main directions, namely a slow-growing face and a fast-growing face and requires the knowledge of solute crystal face integration coefficients in both directions. A parameter estimation algorithm was derived to extract those coefficients from data about temporal concentration and crystal size during crystallization and was designed to have a short run time, while providing a high-resolution estimation. The model predicts a size-dependent growth rate and simulations indicated that for a given seed size and solvent system and for an isothermal anti-solvent addition crystallization, the seed loading and the supersaturation at seeding are the main factors impacting the final aspect ratio. The model predicts a decrease of the growth inhibition effect by the wrong conformer with increasing temperature, likely due to faster equilibration between conformers and/or a decrease of the population of the wrong conformer, if of low energy, at elevated temperatures. Finally, the model predicts that solute surface integration becomes the rate-limiting mechanism for high solute integration activation energies, resulting in no impact of the WC on the overall crystal growth process.
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18
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Taylor R, Wood PA. A Million Crystal Structures: The Whole Is Greater than the Sum of Its Parts. Chem Rev 2019; 119:9427-9477. [PMID: 31244003 DOI: 10.1021/acs.chemrev.9b00155] [Citation(s) in RCA: 127] [Impact Index Per Article: 25.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The founding in 1965 of what is now called the Cambridge Structural Database (CSD) has reaped dividends in numerous and diverse areas of chemical research. Each of the million or so crystal structures in the database was solved for its own particular reason, but collected together, the structures can be reused to address a multitude of new problems. In this Review, which is focused mainly on the last 10 years, we chronicle the contribution of the CSD to research into molecular geometries, molecular interactions, and molecular assemblies and demonstrate its value in the design of biologically active molecules and the solid forms in which they are delivered. Its potential in other commercially relevant areas is described, including gas storage and delivery, thin films, and (opto)electronics. The CSD also aids the solution of new crystal structures. Because no scientific instrument is without shortcomings, the limitations of CSD research are assessed. We emphasize the importance of maintaining database quality: notwithstanding the arrival of big data and machine learning, it remains perilous to ignore the principle of garbage in, garbage out. Finally, we explain why the CSD must evolve with the world around it to ensure it remains fit for purpose in the years ahead.
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Affiliation(s)
- Robin Taylor
- Cambridge Crystallographic Data Centre , 12 Union Road , Cambridge CB2 1EZ , United Kingdom
| | - Peter A Wood
- Cambridge Crystallographic Data Centre , 12 Union Road , Cambridge CB2 1EZ , United Kingdom
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19
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Study of Conformational and Supramolecular Structural Stability of Propylene-Bridged 2-Pyridone Dimers. ChemistrySelect 2018. [DOI: 10.1002/slct.201702565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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20
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Phanus-umporn C, Shoombuatong W, Prachayasittikul V, Anuwongcharoen N, Nantasenamat C. Privileged substructures for anti-sickling activity via cheminformatic analysis. RSC Adv 2018; 8:5920-5935. [PMID: 35539618 PMCID: PMC9078244 DOI: 10.1039/c7ra12079f] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Revised: 02/21/2018] [Accepted: 01/12/2018] [Indexed: 11/21/2022] Open
Abstract
Sickle cell disease (SCD), an autosomal recessive genetic disorder, has been recognized by the World Health Organization (WHO) as a major public health problem as it affects 300 000 individuals worldwide. Complications arising from SCD include anemia, microvascular occlusion, severe pain, stokes, renal dysfunction and infections. A lucrative therapeutic strategy is to employ anti-sickling agents that can disrupt the formation of the HbS polymer. This study therefore employed cheminformatic approaches, encompassing classification structure–activity relationship (CSAR) modeling, to deduce the privileged substructures giving rise to the anti-sickling activity of an investigated set of 115 compounds, followed by substructure analysis. Briefly, the compiled compounds were described by fingerprint descriptors and used in the construction of CSAR models via several machine learning algorithms. The modelability of the data set, as exemplified by the MODI index, was determined to be in the range of 0.70–0.84. The predictive performance was deduced by the accuracy, sensitivity, specificity and Matthews correlation coefficient, which was found to be statistically robust, whereby the former three parameters afforded values in excess of 0.7 while the latter statistical parameter provided a value greater than 0.5. An analysis of the top 20 important substructure descriptors for anti-sickling activity revealed that 10 important features were significant in the differentiation of actives from inactives, as illustrated by aromaticity/conjugation (e.g. SubFPC287, SubFPC171 and SubFPC5), carbonyl groups (e.g. SubFPC137, SubFPC139, SubFPC49 and SubFPC135) and miscellaneous groups (e.g. SubFPC303, SubFPC302 and SubFPC275). Furthermore, an analysis of the structure–activity relationship revealed that the length of alkyl chains, choice of functional moiety and position of substitution on the benzene ring may affect the anti-sickling activity of these compounds. Thus, this knowledge is anticipated to be useful for guiding the design of robust compounds against the gelling activity of HbS, as preliminarily demonstrated in the data-driven compound design presented herein. Cheminformatic approaches (classification structure–activity relationship models based on 12 fingerprint classes) were employed for deducing privileged substructures giving rise to the anti-sickling activity of an investigated set of 115 compounds.![]()
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Affiliation(s)
- Chuleeporn Phanus-umporn
- Center of Data Mining and Biomedical Informatics
- Faculty of Medical Technology
- Mahidol University
- Bangkok 10700
- Thailand
| | - Watshara Shoombuatong
- Center of Data Mining and Biomedical Informatics
- Faculty of Medical Technology
- Mahidol University
- Bangkok 10700
- Thailand
| | - Veda Prachayasittikul
- Center of Data Mining and Biomedical Informatics
- Faculty of Medical Technology
- Mahidol University
- Bangkok 10700
- Thailand
| | - Nuttapat Anuwongcharoen
- Center of Data Mining and Biomedical Informatics
- Faculty of Medical Technology
- Mahidol University
- Bangkok 10700
- Thailand
| | - Chanin Nantasenamat
- Center of Data Mining and Biomedical Informatics
- Faculty of Medical Technology
- Mahidol University
- Bangkok 10700
- Thailand
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21
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Muddukrishna BS, Pai V, Lobo R, Pai A. Application of two-dimensional binary fingerprinting methods for the design of selective Tankyrase I inhibitors. Mol Divers 2017; 22:359-381. [PMID: 29168093 DOI: 10.1007/s11030-017-9793-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Accepted: 10/24/2017] [Indexed: 12/11/2022]
Abstract
In the present study, five important binary fingerprinting techniques were used to model novel flavones for the selective inhibition of Tankyrase I. From the fingerprints used: the fingerprint atom pairs resulted in a statistically significant 2D QSAR model using a kernel-based partial least square regression method. This model indicates that the presence of electron-donating groups positively contributes to activity, whereas the presence of electron withdrawing groups negatively contributes to activity. This model could be used to develop more potent as well as selective analogues for the inhibition of Tankyrase I. Schematic representation of 2D QSAR work flow.
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Affiliation(s)
- B S Muddukrishna
- Department of Pharmaceutical Quality Assurance, Manipal College of Pharmaceutical Sciences (MCOPS), Manipal University, Manipal, Karnataka, India
| | - Vasudev Pai
- Department of Pharmacognosy, Manipal College of Pharmaceutical Sciences (MCOPS), Manipal University, Manipal, Karnataka, India
| | - Richard Lobo
- Department of Pharmacognosy, Manipal College of Pharmaceutical Sciences (MCOPS), Manipal University, Manipal, Karnataka, India
| | - Aravinda Pai
- Department of Pharmaceutical Chemistry, Manipal College of Pharmaceutical Sciences (MCOPS), Manipal University, Manipal, Karnataka, 576 104, India.
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22
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Polishchuk P. Interpretation of Quantitative Structure–Activity Relationship Models: Past, Present, and Future. J Chem Inf Model 2017; 57:2618-2639. [DOI: 10.1021/acs.jcim.7b00274] [Citation(s) in RCA: 120] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Affiliation(s)
- Pavel Polishchuk
- Institute of Molecular and
Translational Medicine, Faculty of Medicine and Dentistry, Palacký University and University Hospital in Olomouc, Hněvotínská
1333/5, 779 00 Olomouc, Czech Republic
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