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Journal articles on the topic 'PHARMACOPHORE MODELING'

Author: Grafiati

Published: 11 September 2023

Last updated: 25 July 2025

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1

Kutlushina, Alina, Aigul Khakimova, Timur Madzhidov, and Pavel Polishchuk. "Ligand-Based Pharmacophore Modeling Using Novel 3D Pharmacophore Signatures." Molecules 23, no. 12 (2018): 3094. http://dx.doi.org/10.3390/molecules23123094.

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Pharmacophore modeling is a widely used strategy for finding new hit molecules. Since not all protein targets have available 3D structures, ligand-based approaches are still useful. Currently, there are just a few free ligand-based pharmacophore modeling tools, and these have a lot of restrictions, e.g., using a template molecule for alignment. We developed a new approach to 3D pharmacophore representation and matching which does not require pharmacophore alignment. This representation can be used to quickly find identical pharmacophores in a given set. Based on this representation, a 3D pharm

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Mortier, Jérémie, Pratik Dhakal, and Andrea Volkamer. "Truly Target-Focused Pharmacophore Modeling: A Novel Tool for Mapping Intermolecular Surfaces." Molecules 23, no. 8 (2018): 1959. http://dx.doi.org/10.3390/molecules23081959.

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Pharmacophore models are an accurate and minimal tridimensional abstraction of intermolecular interactions between chemical structures, usually derived from a group of molecules or from a ligand-target complex. Only a limited amount of solutions exists to model comprehensive pharmacophores using the information of a particular target structure without knowledge of any binding ligand. In this work, an automated and customable tool for truly target-focused (T²F) pharmacophore modeling is introduced. Key molecular interaction fields of a macromolecular structure are calculated using the AutoGRID

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Madzhidov, Timur I., Assima Rakhimbekova, Alina Kutlushuna, and Pavel Polishchuk. "Probabilistic Approach for Virtual Screening Based on Multiple Pharmacophores." Molecules 25, no. 2 (2020): 385. http://dx.doi.org/10.3390/molecules25020385.

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Pharmacophore modeling is usually considered as a special type of virtual screening without probabilistic nature. Correspondence of at least one conformation of a molecule to pharmacophore is considered as evidence of its bioactivity. We show that pharmacophores can be treated as one-class machine learning models, and the probability the reflecting model’s confidence can be assigned to a pharmacophore on the basis of their precision of active compounds identification on a calibration set. Two schemes (Max and Mean) of probability calculation for consensus prediction based on individual pharmac

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Kumar, Saurav, Deepika Deepika, and Vikas Kumar. "Pharmacophore Modeling Using Machine Learning for Screening the Blood–Brain Barrier Permeation of Xenobiotics." International Journal of Environmental Research and Public Health 19, no. 20 (2022): 13471. http://dx.doi.org/10.3390/ijerph192013471.

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Daily exposure to xenobiotics affects human health, especially the nervous system, causing neurodegenerative diseases. The nervous system is protected by tight junctions present at the blood–brain barrier (BBB), but only molecules with desirable physicochemical properties can permeate it. This is why permeation is a decisive step in avoiding unwanted brain toxicity and also in developing neuronal drugs. In silico methods are being implemented as an initial step to reduce animal testing and the time complexity of the in vitro screening process. However, most in silico methods are ligand based,

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Mansi, Iman A., Mahmoud A. Al-Sha'er, Nizar M. Mhaidat, Mutasem O. Taha, and Rand Shahin. "Investigation of Binding Characteristics of Phosphoinositide-dependent Kinase-1 (PDK1) Co-crystallized Ligands Through Virtual Pharmacophore Modeling Leading to Novel Anti-PDK1 Hits." Medicinal Chemistry 16, no. 7 (2020): 860–80. http://dx.doi.org/10.2174/1573406415666190724131048.

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Background: 3-Phosphoinositide Dependent Protein Kinase-1 (PDK1) is being lately considered as an attractive and forthcoming anticancer target. A Protein Data Bank (PDB) cocrystallized crystal provides not only rigid theoretical data but also a realistic molecular recognition data that can be explored and used to discover new hits. Objective: This incited us to investigate the co-crystallized ligands' contacts inside the PDK1 binding pocket via a structure-based receptor-ligand pharmacophore generation technique in Discovery Studio 4.5 (DS 4.5). Methods: Accordingly, 35 crystals for PDK1 were

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AFFI, Sopi Thomas, Doh SORO, Souleymane COULIBALY, Bibata KONATE, and Nahossé ZIAO. "Modeling anticancer pharmacophore based on inhibition of HDAC7." SDRP Journal of Computational Chemistry & Molecular Modeling 5, no. 3 (2021): 657–63. http://dx.doi.org/10.25177/jccmm.5.3.ra.10776.

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Histone deacetylases (HDACs) are the target inhibition enzymes in cancer treatment via chemotherapy. Application of this therapeutic technique requires the use of drugs whose side effects are reduced and tiny with necessary safety. In this study, the methods and tools of pharmacophore modeling were used to investigate ten molecules known for their anticancer properties. Particular attention has been given to pinpoint a promising anti-cancer pharmacophore in order to lead new effective inhibitors. Using Discovery Studio 2.5 software, the ten compounds were docked within the active site of the H

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Kadu, Nilesh S., and Atul V. Ingle. "Three-Dimensional Pharmacophore Modeling of Betulonic Acid Derivatives as a Strong Inhibitor of Human Coronavirus-229E Replication." International Journal of Science and Healthcare Research 6, no. 2 (2021): 356–61. http://dx.doi.org/10.52403/ijshr.20210462.

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These-days, pharmacophore approaches have become one of the foremost tools in drug discovery after the past century’s development. Numerous ligand-based and structure-based strategies are developed for improved pharmacophore modeling with success and extensively applied in virtual screening, de novo design and lead improvement. Till now, there is little information on 3D-pharmacophore studies of 1,2,3-triazolo-fused betulonic acid derivatives as a strong inhibitor for human coronavirus-229E replication. Here, we tend to report the appliance of pharmacophore modeling for betulonic acid derivati

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Mendez, Nixon, and Md Afroz Alam. "Structural Features of Quercetin Derivatives by Using Pharmaco-phore Modeling Approach." Open Pharmaceutical Sciences Journal 3, no. 1 (2016): 79–98. http://dx.doi.org/10.2174/1874844901603010079.

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Background:Quercetin which is a natural occurring flavonoid, exert a direct pro-apoptotic effect on tumor cells by blocking the growth of several cancer cell lines at different phases of the cell cycle. Quercetin derivatives have attracted considerable attention for their cytotoxity against human cancer cell lines. In this study the derivatives of Quercetin were used for docking followed by pharmacophore modeling for studying the 3D features and configurations responsible for biological activity of structurally diverse compounds.Objective:To develop a model which depicts the crucial structural

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Vaddavalli, Radha, Bagyanaryana Gaddam, and Pradeep Kumar Maddikara. "Discovery of Novel Inhibitors Against Resistant Streptococcus pneumoniae MurF Enzyme using Phamracophore Modeling and QSAR Analysis." International Journal of Drug Design and Discovery 2, no. 1 (2024): 403–12. https://doi.org/10.37285/ijddd.2.1.7.

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Main aim of the current study was to discover novel inhibitors against Streptococcus pneumoniae MurF enzyme using analogue based drug design. Pharmacophore mapping and 3D-QSAR analysis was performed on some previously synthesized and evaluated sulfonamide derivatives which are known to be potent inhibitors of penicillin resistant Streptococcus pneumoniae MurF receptor. 3D-QSAR study based on the principle of alignment of pharmacophoric features was performed on the same set of inhibitors using the PHASE module of Schrodinger suite. A five point pharmacophore, ADHRR, with one hydrogen bond acce

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Thai, Khac-Minh, Trieu-Du Ngo, Thanh-Dao Tran, and Minh-Tri Le. "Pharmacophore Modeling for Antitargets." Current Topics in Medicinal Chemistry 13, no. 9 (2013): 1002–14. http://dx.doi.org/10.2174/1568026611313090004.

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Guner, Osman, and J. Bowen. "Pharmacophore Modeling for ADME." Current Topics in Medicinal Chemistry 13, no. 11 (2013): 1327–42. http://dx.doi.org/10.2174/15680266113139990037.

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Engels, Maida, Se Balaji B, Divakar S., and Geetha G. "LIGAND BASED PHARMACOPHORE MODELING, VIRTUAL SCREENING AND MOLECULAR DOCKING STUDIES TO DESIGN NOVEL PANCREATIC LIPASE INHIBITORS." International Journal of Pharmacy and Pharmaceutical Sciences 9, no. 4 (2017): 48. http://dx.doi.org/10.22159/ijpps.2017v9i4.16392.

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Objective: To understand the essential structural features required for pancreatic lipase (PL) inhibitory activity and to design novel chemical entities, ligand-based pharmacophore modeling, virtual screening and docking studies were carried out.Methods: The pharmacophore model was generated based on 133 compounds with PL inhibitory activity using PHASE. An external test set and decoy dataset methods were applied to validate the hypothesis and to retrieve potential PL inhibitors. The generated hypothesis model was further subjected to virtual screening and molecular docking studies.Results: A

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de Groot, Marcel J., and Sean Ekins. "Pharmacophore modeling of cytochromes P450." Advanced Drug Delivery Reviews 54, no. 3 (2002): 367–83. http://dx.doi.org/10.1016/s0169-409x(02)00009-1.

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Lu, Xin, Hongyu Yang, Yao Chen, et al. "The Development of Pharmacophore Modeling: Generation and Recent Applications in Drug Discovery." Current Pharmaceutical Design 24, no. 29 (2018): 3424–39. http://dx.doi.org/10.2174/1381612824666180810162944.

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Background: The pharmacophore concept in modern drug research is of great importance and promotes the development of drug industry as indicated by the number of publications available. Methods: : In this article, we reviewed and highlighted some successful examples of pharmacophore modeling, which was applied either in virtual screening for efficient hit discovery or in the optimization of the lead compounds. Meanwhile, the analysis of some important aspects of pharmacophore modeling such as a database, the software was listed as well. <p> Results: Based on the analysis of these examples

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Shirbhate E., Divya, V. K. Patel, P. Patel, et al. "LEAD IDENTIFICATION OF HYDROXAMATE DERIVATIVE AS SELECTIVE HDAC2 INHIBITOR USING COMPUTATIONAL APPROACHES." INDIAN DRUGS 57, no. 07 (2020): 26–39. http://dx.doi.org/10.53879/id.57.07.12042.

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Histone deacetylase (HDAC) inhibitors have been established as a novel class of anticancer agents. The HDAC enzyme plays a vital role in gene transcription for regulation of cell proliferation, migration and apoptosis, immune pathways and angiogenesis. In this work, a series of 49 hydroxamate derivatives with available IC50 data were analyzed by computational method for the identification of leads. 3D-QSAR and pharmacophore modeling investigation were accomplished to identify the crucial pharmacophoric features and correlate 3D-chemical structure with HDAC inhibitory activity. The e-pharmacoph

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Kumar, Sivakumar Prasanth, and Prakash Chandra Jha. "Multi-Pharmacophore Modeling of Caspase-3 Inhibitors using Crystal, Dock and Flexible Conformation Schemes." Combinatorial Chemistry & High Throughput Screening 21, no. 1 (2018): 26–40. http://dx.doi.org/10.2174/1386207321666180102114917.

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Aim and Objective: Numerous caspase-3 drug discovery projects were found to have relied on single receptor as the template to recognize most promising small molecule candidates using docking approach. Alternatively, some researchers were contingent upon ligand-based alignment to build up an empirical relationship between ligand functional groups and caspase-3 inhibitory activity quantitatively. To connect both caspase-3 receptor details and its inhibitors chemical functionalities, this study was undertaken to develop receptor- and ligand-pharmacophore models based on different conformational s

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Hariono, Maywan, and Habibah A. Wahab. "Pharmacophore Modeling of N1-alkyltheobromine as Histamine-H1 Receptor Antagonist." International Journal of Modeling and Optimization 5, no. 2 (2015): 98–103. http://dx.doi.org/10.7763/ijmo.2015.v5.443.

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Noonan, Theresa, Katrin Denzinger, Valerij Talagayev, et al. "Mind the Gap—Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence." Pharmaceuticals 15, no. 11 (2022): 1304. http://dx.doi.org/10.3390/ph15111304.

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G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. Three-dimensional pharmacophore models are powerful computational tools in in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, the discovery of biased and allosteric ligands,

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Yamakawa, Yuko, Kazuharu Furutani, Atsushi Inanobe, Yuko Ohno, and Yoshihisa Kurachi. "Pharmacophore modeling for hERG channel facilitation." Biochemical and Biophysical Research Communications 418, no. 1 (2012): 161–66. http://dx.doi.org/10.1016/j.bbrc.2011.12.153.

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20

Chidambaram, Kumarappan. "Identification of BACE-1 Inhibitors against Alzheimer’s Disease through E-Pharmacophore-Based Virtual Screening and Molecular Dynamics Simulation Studies: An Insilco Approach." Life 13, no. 4 (2023): 952. http://dx.doi.org/10.3390/life13040952.

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Alzheimer is a severe memory and cognitive impairment neurodegenerative disease that is the most common cause of dementia worldwide and characterized by the pathological accumulation of tau protein and amyloid-beta peptides. In this study, we have developed E-pharmacophore modeling to screen the eMolecules database with the help of a reported co-crystal structure bound with Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1 (BACE-1). Flumemetamol, florbetaben, and florbetapir are currently approved drugs for use in the clinical diagnosis of Alzheimer’s disease. Despite the benefits of comme

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21

Sugumar, Shobana. "VIRTUAL SCREENING, PHARMACOPHORE MODELING, AND QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP STUDIES ON HISTAMINE 4 RECEPTOR." Asian Journal of Pharmaceutical and Clinical Research 10, no. 12 (2017): 150. http://dx.doi.org/10.22159/ajpcr.2017.v10i12.19991.

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Objective: To find out novel inhibitors for histamine 4 receptor (H4R), the target for various allergic and inflammatory pathophysiological conditions.Methods: Homology modeling of H4R was performed using easy modeler and validated using structure analysis and verification server, and with the modeled structure, virtual screening, pharmacophore modeling, and quantitative structure activity relationship (QSAR) studies were performed using the Schrodinger 9.3 software.Results: Among all the synthetic and natural ligands, hesperidin, vitexin, and diosmin were found to have the highest dock score,

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Jb, Sheema, and Waheeta Hopper. "ENERGY-BASED PHARMACOPHORE MODELING, VIRTUAL SCREENING, AND MOLECULAR DYNAMICS TO IDENTIFY POTENTIAL INHIBITORS FOR GLYCOGEN SYNTHASE KINASE 3 BETA." Asian Journal of Pharmaceutical and Clinical Research 11, no. 2 (2018): 181. http://dx.doi.org/10.22159/ajpcr.2018.v11i2.22962.

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Objective: Glycogen synthase kinase 3 beta (GSK3β) is one of the main targets for wound healing activity. Our objective is to identify novel inhibitors for GSK3β using in silico approach.Methods: Grid-based molecular docking, energy-based pharmacophore (e-pharmacophore) modeling, and molecular dynamics (MD) studies were performed for phytocompounds with GSK3β and compared with standard drugs using Schrodinger software.Results: The glide scores and the molecular interactions of the phytocompounds were well comparable to the standard drugs. The MD was performed for the target bound to the best s

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S, Janardhan, та Padmanabha Reddy Y. "Molecular Modeling Studies of β-aminoacyl containing Homopiperazine derivatives as DPP4 Inhibitors". International Journal of Drug Design and Discovery 2, № 3 (2024): 533–47. https://doi.org/10.37285/ijddd.2.3.4.

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Dipeptidyl peptidase IV (DPP4) is a promising target for developing novel anti-diabetic and anti-obesity drugs. Pharmacophore based three dimensional quantitative structure activity relationship studies (3D-QSAR) and molecular docking were performed on a series of 56 β-aminoacyl-containing homopiperazine derivatives of DPP4 inhibitors to find out the structural relationship with the activity. The best predictive 3D-QSAR model with pharmacophore based alignment resulted in R2 (training set) value of 0.9407, Q2 (internal test set) value of 0.9053, Pearson-R value of 0.9517 and root mean square e

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Zou, Jun, Huan-Zhang Xie, Sheng-Yong Yang, Jin-Juan Chen, Ji-Xia Ren, and Yu-Quan Wei. "Towards more accurate pharmacophore modeling: Multicomplex-based comprehensive pharmacophore map and most-frequent-feature pharmacophore model of CDK2." Journal of Molecular Graphics and Modelling 27, no. 4 (2008): 430–38. http://dx.doi.org/10.1016/j.jmgm.2008.07.004.

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Dong, Xialan, Jerry O. Ebalunode, Sheng-Yong Yang, and Weifan Zheng. "Receptor-Based Pharmacophore and Pharmacophore Key Descriptors for Virtual Screening and QSAR Modeling." Current Computer Aided-Drug Design 7, no. 3 (2011): 181–89. http://dx.doi.org/10.2174/157340911796504332.

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Katlaria, Sanjana, Ashish Singh Chauhan, Krishna Kumar, Mohit Kumar, Bhumika Chauhan, and Vikash Jakhmola. "Pharmacophore insights and molecular docking of ciprofloxacin analogues against 2XE1: strategies for reduced antibiotic resistance." Journal of Applied Pharmaceutical Research 12, no. 6 (2024): 100–121. https://doi.org/10.69857/joapr.v12i6.660.

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Background: Antibiotic resistance is a silent pandemic disease that is growing and causing a global threat. Existing antibiotics are less effective against infectious diseases, so we must discover more potent and effective drugs. The latest report from the World Health Organization (WHO) underscores the global nature of the situation, revealing that high levels of antibiotic resistance in bacteria worldwide lead to life-threatening bloodstream infections and resistance to treatment. Methods: This study focuses on the Molecular Docking and Pharmacophore Modeling of Ciprofloxacin and its analogs

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Todkar, S. S., and A. H. Hoshmani. "DESIGN OF POTENTIAL CYCLOOXYGENASE INHIBITORS USING PHARMACOPHORE OPTIMIZATION BY MOLECULAR MODELING STUDIES." INDIAN DRUGS 52, no. 12 (2015): 16–22. http://dx.doi.org/10.53879/id.52.12.10154.

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Recently discovery of relation between cyclooxygenase–2 (COX–2) inhibition and prevention of growth of cansar cells is a major area for research in medicinal chemistry, as it is free from side effects which are genetically shown by developed anticancer agents. In an attempt to develop potent and nontoxic COX–2 inhibitors, we have optimized the 1,5- diaryl pyrazole pharmacophore by using molecular modeling studies. In this paper we present results of 2D and 3D QSAR studies of a series of 22 molecules containing 1,5- diaryl pyrazole pharmacophore as selective COX–2 inhibitors. The 3D QSAR studie

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Vadlakonda, Rajashekar, Sreenivas Enaganti, and Raghunandan Nerella. "INSILICO DISCOVERY OF HUMAN AURORA B KINASE INHIBITORS BY MOLECULAR DOCKING, PHARMACOPHORE VALIDATION AND ADMET STUDIES." Asian Journal of Pharmaceutical and Clinical Research 10, no. 2 (2017): 165. http://dx.doi.org/10.22159/ajpcr.2017.v10i2.14974.

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Objectives: To predict the anticancer potentiality of some newly designed azaindole derivatives gainst human Aurora B kinase and to identify the critical features important for their activity.Methods: Initially, the derivatives of azaindoles, (Z)-2-(oxo-1 H-pyrrolo [2,3-b] pyridine-3 (2H)-ylidene)-N-(p-substituted) hydrazine carbothioamide (scaffold A), (E)-3-((E)-substituted benzylidene hydrazono)-1H-pyrrolo[2,3-b]pyridine-2(3H)-one (scaffold B), and 1-(2-substituted acetyl)-1H- pyrrolo [2,3-b]pyridine-2,3-dione are synthesized and sketched using ACD/ChemSketch (12.0). With the 3D converted c

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Mansi, Iman, Mahmoud A. Al-Sha'er, Nizar Mhaidat, and Mutasem Taha. "Ligand Based Pharmacophore Modeling Followed by Biological Screening Lead to Discovery of Novel PDK1 Inhibitors as Anticancer Agents." Anti-Cancer Agents in Medicinal Chemistry 20, no. 4 (2020): 476–85. http://dx.doi.org/10.2174/1871520620666191224110600.

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Background: Phosphoinositide-Dependent Kinase-1 (PDK1) is a serine/threonine kinase, which belongs to AGC kinase family required by cancer cells. Methods: harmacophoric space of 86 PDK1 inhibitors using six diverse sets of inhibitors was explored to identify high-quality pharmacophores. The best combination of pharmacophoric models and physicochemical descriptors was selected by genetic algorithm-based QSAR analysis that can elucidate the variation of bioactivity within the training inhibitors. Two successful orthogonal pharmacophores emerged in the optimum QSAR equation (r2 69 = 0.90, r2 LOO=

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Pu, Yinglan, Shuqun Zhang, Zhe Chang, et al. "Discovery of new dual binding TNKS inhibitors of Wnt signaling inhibition by pharmacophore modeling, molecular docking and bioassay." Molecular BioSystems 13, no. 2 (2017): 363–70. http://dx.doi.org/10.1039/c6mb00712k.

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AbdElmoniem, Nihal, Marwa H. Abdallah, Rua M. Mukhtar, et al. "Identification of Novel Natural Dual HDAC and Hsp90 Inhibitors for Metastatic TNBC Using e-Pharmacophore Modeling, Molecular Docking, and Molecular Dynamics Studies." Molecules 28, no. 4 (2023): 1771. http://dx.doi.org/10.3390/molecules28041771.

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Breast cancer (BC) is one of the main types of cancer that endangers women’s lives. The characteristics of triple-negative breast cancer (TNBC) include a high rate of recurrence and the capacity for metastasis; therefore, new therapies are urgently needed to combat TNBC. Dual targeting HDAC6 and Hsp90 has shown good synergistic effects in treating metastatic TNBC. The goal of this study was to find potential HDAC6 and Hsp90 dual inhibitors. Therefore, several in silico approaches have been used. An e-pharmacophore model generation based on the HDAC6-ligand complex and subsequently a pharmacoph

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Agrawal, Nikhil, Balakumar Chandrasekaran, and Amal Al-Aboudi. "Recent Advances in the In-silico Structure-based and Ligand-based Approaches for the Design and Discovery of Agonists and Antagonists of A2A Adenosine Receptor." Current Pharmaceutical Design 25, no. 7 (2019): 774–82. http://dx.doi.org/10.2174/1381612825666190306162006.

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A2A receptor belongs to the family of GPCRs, which are the most abundant membrane protein family. Studies in the last few decades have shown the therapeutic applications of A2A receptor in various diseases. In the present mini-review, we have discussed the recent progress in the in-silico studies of the A2A receptor. Herein, we described the different structures of A2A receptor, the discovery of new agonists and antagonists using virtualscreening/ docking, pharmacophore modeling, and QSAR based pharmacophore modeling. We have also discussed various molecular dynamics (MD) simulations studies o

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Damale, Manoj G., Shahebaaz K. Pathan, Rajesh B. Patil, and Jaiprakash N. Sangshetti. "Pharmacoinformatics approaches to identify potential hits against tetraacyldisaccharide 4′-kinase (LpxK) of Pseudomonas aeruginosa." RSC Advances 10, no. 54 (2020): 32856–74. http://dx.doi.org/10.1039/d0ra06675c.

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Zhang, Chao, Junjie Xiang, Qian Xie, et al. "Identification of Influenza PAN Endonuclease Inhibitors via 3D-QSAR Modeling and Docking-Based Virtual Screening." Molecules 26, no. 23 (2021): 7129. http://dx.doi.org/10.3390/molecules26237129.

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Structural and biochemical studies elucidate that PAN may contribute to the host protein shutdown observed during influenza A infection. Thus, inhibition of the endonuclease activity of viral RdRP is an attractive approach for novel antiviral therapy. In order to envisage structurally diverse novel compounds with better efficacy as PAN endonuclease inhibitors, a ligand-based-pharmacophore model was developed using 3D-QSAR pharmacophore generation (HypoGen algorithm) methodology in Discovery Studio. As the training set, 25 compounds were taken to generate a significant pharmacophore model. The

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Santos, Kelton L. B. dos, Jorddy N. Cruz, Luciane B. Silva, et al. "Identification of Novel Chemical Entities for Adenosine Receptor Type 2A Using Molecular Modeling Approaches." Molecules 25, no. 5 (2020): 1245. http://dx.doi.org/10.3390/molecules25051245.

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Adenosine Receptor Type 2A (A2AAR) plays a role in important processes, such as anti-inflammatory ones. In this way, the present work aimed to search for compounds by pharmacophore-based virtual screening. The pharmacokinetic/toxicological profiles of the compounds, as well as a robust QSAR, predicted the binding modes via molecular docking. Finally, we used molecular dynamics to investigate the stability of interactions from ligand-A2AAR. For the search for A2AAR agonists, the UK-432097 and a set of 20 compounds available in the BindingDB database were studied. These compounds were used to ge

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Peng, Xiu Xiu, Kai Rui Feng та Yu Jie Ren. "Molecular modeling studies of quinazolinone derivatives as novel PI3Kδ selective inhibitors". RSC Advances 7, № 89 (2017): 56344–58. http://dx.doi.org/10.1039/c7ra10870b.

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Derz, Wiebke, Melita Fleischmann, and Paul W. Elsinghorst. "Guiding Molecularly Imprinted Polymer Design by Pharmacophore Modeling." Molecules 26, no. 16 (2021): 5101. http://dx.doi.org/10.3390/molecules26165101.

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Molecularly imprinted polymers (MIP) combine the selectivity of immunoaffinity chromatography with the robustness of common solid-phase extraction in what is referred to as molecularly imprinted solid-phase extraction (MISPE). This contribution shows how MIP design may be guided by pharmacophore modeling for the example of citrinin, which is an emerging mycotoxin from cereals. The obtained pharmacophore model allowed searching public databases for a set of citrinin-mimicking molecular surrogates. Imprinted and non-imprinted polymers were subsequently obtained through bulk and core-shell polyme

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Mathpal, Deepti, Tahani M. Almeleebia, Kholoud M. Alshahrani, et al. "Identification of 3-((1-(Benzyl(2-hydroxy-2-phenylethyl)amino)-1-oxo-3-phenylpropan-2-yl)carbamoyl)pyrazine-2-carboxylic Acid as a Potential Inhibitor of Non-Nucleosidase Reverse Transcriptase Inhibitors through InSilico Ligand- and Structure-Based Approaches." Molecules 26, no. 17 (2021): 5262. http://dx.doi.org/10.3390/molecules26175262.

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Non-nucleosidase reverse transcriptase inhibitors (NNRTIs) are highly promising agents for use in highly effective antiretroviral therapy. We implemented a rational approach for the identification of promising NNRTIs based on the validated ligand- and structure-based approaches. In view of our state-of-the-art techniques in drug design and discovery utilizing multiple modeling approaches, we report here, for the first time, quantitative pharmacophore modeling (HypoGen), docking, and in-house database screening approaches in the identification of potential NNRTIs. The validated pharmacophore mo

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Kaushik, Pawan, Sukhbir Lal Khokra, A. C. Rana, and Dhirender Kaushik. "Pharmacophore Modeling and Molecular Docking Studies on Pinus roxburghii as a Target for Diabetes Mellitus." Advances in Bioinformatics 2014 (July 10, 2014): 1–8. http://dx.doi.org/10.1155/2014/903246.

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The present study attempts to establish a relationship between ethnopharmacological claims and bioactive constituents present in Pinus roxburghii against all possible targets for diabetes through molecular docking and to develop a pharmacophore model for the active target. The process of molecular docking involves study of different bonding modes of one ligand with active cavities of target receptors protein tyrosine phosphatase 1-beta (PTP-1β), dipeptidyl peptidase-IV (DPP-IV), aldose reductase (AR), and insulin receptor (IR) with help of docking software Molegro virtual docker (MVD). From th

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Brogi, Simone, Maria Kladi, Constantinos Vagias, Panagiota Papazafiri, Vassilios Roussis, and Andrea Tafi. "Pharmacophore Modeling for Qualitative Prediction of Antiestrogenic Activity." Journal of Chemical Information and Modeling 49, no. 11 (2009): 2489–97. http://dx.doi.org/10.1021/ci900254b.

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Xu, Zhejun, Feixiong Cheng, Chenxiao Da, Guixia Liu, and Yun Tang. "Pharmacophore modeling of human adenosine receptor A2A antagonists." Journal of Molecular Modeling 16, no. 12 (2010): 1867–76. http://dx.doi.org/10.1007/s00894-010-0690-z.

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Ghose, Arup K., Vellarkad N. Viswanadhan, and John J. Wendoloski. "THE FUNDAMENTALS OF PHARMACOPHORE MODELING IN COMBINATORIAL CHEMISTRY*." Journal of Receptors and Signal Transduction 21, no. 4 (2001): 357–75. http://dx.doi.org/10.1081/rrs-100107923.

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Markt, Patrick, Daniela Schuster, Johannes Kirchmair, Christian Laggner, and Thierry Langer. "Pharmacophore modeling and parallel screening for PPAR ligands." Journal of Computer-Aided Molecular Design 21, no. 10-11 (2007): 575–90. http://dx.doi.org/10.1007/s10822-007-9140-0.

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Bharatham, Kavitha, Nagakumar Bharatham, and Keun Woo Lee. "Pharmacophore modeling for protein tyrosine phosphatase 1B inhibitors." Archives of Pharmacal Research 30, no. 5 (2007): 533–42. http://dx.doi.org/10.1007/bf02977644.

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Faden, Alan I, Vilen A Movsesyan, Xueliang Fang, and Shaomeng Wang. "Identification of Novel Neuroprotective Agents Using Pharmacophore Modeling." Chemistry & Biodiversity 2, no. 11 (2005): 1564–70. http://dx.doi.org/10.1002/cbdv.200590127.

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Singh, Karanveer, Manish Sinha, Shruti Kuletha, et al. "Synthesis, Antitubercular Activity, Molecular Modeling and Docking Studies of Novel Thiazolidin-4-One Linked Dinitrobenzamide Derivatives." Current Bioactive Compounds 16, no. 1 (2020): 64–71. http://dx.doi.org/10.2174/1573407214666180720150009.

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Background: Tuberculosis is a catastrophe sprawled across the world. The World Health Organization Global Tuberculosis Report 2017 inferred that there were an estimated 10.4 million people suffered from tuberculosis including 490000 Multidrug-Resistant TB (MDR-TB) cases. Several new lead molecules like dinitrobenzamide derivatives were found to be highly active against multidrugresistant strains of M. tuberculosis. To further explore the pharmacophoric space around the dinitobenzamide moiety, a series of compounds have been synthesized by linking it with the thiazolidin- 4-one. The presented w

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Kandakatla, Naresh, and Geetha Ramakrishnan. "Ligand Based Pharmacophore Modeling and Virtual Screening Studies to Design Novel HDAC2 Inhibitors." Advances in Bioinformatics 2014 (November 26, 2014): 1–11. http://dx.doi.org/10.1155/2014/812148.

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Histone deacetylases 2 (HDAC2), Class I histone deacetylase (HDAC) family, emerged as an important therapeutic target for the treatment of various cancers. A total of 48 inhibitors of two different chemotypes were used to generate pharmacophore model using 3D QSAR pharmacophore generation (HypoGen algorithm) module in Discovery Studio. The best HypoGen model consists of four pharmacophore features namely, one hydrogen bond acceptor (HBA), and one hydrogen donor (HBD), one hydrophobic (HYP) and one aromatic centres, (RA). This model was validated against 20 test set compounds and this model was

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Munir, Anum, Shaukat I. Malik, and Khalid A. Malik. "De-Novo Ligand Design against Mutated Huntington Gene by Ligand-based Pharmacophore Modeling Approach." Current Computer-Aided Drug Design 16, no. 2 (2020): 134–44. http://dx.doi.org/10.2174/1573409915666181207104437.

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Background: Huntington's disease is characterized by three side effects, including motor disturbances, psychiatric elements, and intellectual weakness. The onset for HD has nonlinear converse associations with the number of repeat sequences of the polyglutamine mutations, so that younger patients have a tendency for longer repeats length. This HD variation is because of the development of a polyglutamine (CAG) repeats in the exon 1 of the Huntingtin protein. Methods: In the present study, a few derivatives utilized as a part of the treatment of HD, are used to create the pharmacophore model an

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Kalva, Sukesh, Nikhil Agrawal, Adam A. Skelton, and Lilly M. Saleena. "Identification of novel selective MMP-9 inhibitors as potential anti-metastatic lead using structure-based hierarchical virtual screening and molecular dynamics simulation." Molecular BioSystems 12, no. 8 (2016): 2519–31. http://dx.doi.org/10.1039/c6mb00066e.

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Crisan, Luminita, Daniela Varga, and Liliana Pacureanu. "Pharmacophore Modeling and Docking Study of Pyrazolylaminoquinazoline Derivatives as Highly Potent Fibroblast Growth Factor Receptor Inhibitors2 (FGFR2)." Revista de Chimie 70, no. 3 (2019): 790–96. http://dx.doi.org/10.37358/rc.19.3.7008.

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In this study pharmacophore modeling and molecular docking investigations have been performed on pyrazolylaminoquinazoline derivatives, highly potent fibroblast growth factor receptor2 (FGFR2) inhibitors. The best pharmacophore hypotheses displaying five features (ADHRR.2051 and AADHR.798) were generated using a set of 28 compounds. The associated 3D atom-based quantitative structure � activity relationships (QSAR) models were statistically robust showing high correlation coefficients (R-squared = 0.981 / 0.982), and cross validation coefficients (Q-squared = 0.645 / 0.671). The R-Pearson valu

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