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Journal articles on the topic 'Pharmacophore models'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 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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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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Polishchuk, Pavel, Alina Kutlushina, Dayana Bashirova, Olena Mokshyna, and Timur Madzhidov. "Virtual Screening Using Pharmacophore Models Retrieved from Molecular Dynamic Simulations." International Journal of Molecular Sciences 20, no. 23 (2019): 5834. http://dx.doi.org/10.3390/ijms20235834.

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Pharmacophore models are widely used for the identification of promising primary hits in compound large libraries. Recent studies have demonstrated that pharmacophores retrieved from protein-ligand molecular dynamic trajectories outperform pharmacophores retrieved from a single crystal complex structure. However, the number of retrieved pharmacophores can be enormous, thus, making it computationally inefficient to use all of them for virtual screening. In this study, we proposed selection of distinct representative pharmacophores by the removal of pharmacophores with identical three-dimensiona

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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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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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Gajjar, Krishna A., and Anuradha K. Gajjar. "Combiphore (Structure and Ligand Based Pharmacophore) - Approach for the Design of GPR40 Modulators in the Management of Diabetes." Current Drug Discovery Technologies 17, no. 2 (2020): 233–47. http://dx.doi.org/10.2174/1570163815666181008165822.

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Background: Pharmacophore mapping and molecular docking can be synergistically integrated to improve the drug design and discovery process. A rational strategy, combiphore approach, derived from the combined study of Structure and Ligand based pharmacophore has been described to identify novel GPR40 modulators. Methods: DISCOtech module from Discovery studio was used for the generation of the Structure and Ligand based pharmacophore models which gave hydrophobic aromatic, ring aromatic and negative ionizable as essential pharmacophoric features. The generated models were validated by screening

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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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Wieder, Marcus, Ugo Perricone, Thomas Seidel, and Thierry Langer. "Pharmacophore Models Derived from Molecular Dynamics Simulations of Protein-Ligand Complexes: A Case Study." Natural Product Communications 11, no. 10 (2016): 1934578X1601101. http://dx.doi.org/10.1177/1934578x1601101019.

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A single, merged pharmacophore hypothesis is derived combining 2000 pharmacophore models obtained during a 20 ns molecular dynamics simulation of a protein-ligand complex with one pharmacophore model derived from the initial PDB structure. This merged pharmacophore model contains all features that are present during the simulation and statistical information about the dynamics of the pharmacophore features. Based on the dynamics of the pharmacophore features we derive two distinctive feature patterns resulting in two different pharmacophore models for the analyzed system – the first model cons

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Weng, Chia-Wei, Chi-Hsuan Wei, Jeng-Yuan Tsai, Yi-Hua Lai, Gee-Chen Chang, and Jeremy J. W. Chen. "Hybrid Pharmacophore- and Structure-Based Virtual Screening Pipeline to Identify Novel EGFR Inhibitors That Suppress Non-Small Cell Lung Cancer Cell Growth." International Journal of Molecular Sciences 23, no. 7 (2022): 3487. http://dx.doi.org/10.3390/ijms23073487.

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Dysregulated epidermal growth factor receptor (EGFR) expression is frequently observed in non-small cell lung cancer (NSCLC) growth and metastasis. Despite recent successes in the development of tyrosine kinase inhibitors (TKIs), inevitable resistance to TKIs has led to urgent calls for novel EGFR inhibitors. Herein, we report a rational workflow used to identify novel EGFR-TKIs by combining hybrid ligand- and structure-based pharmacophore models. Three types of models were developed in this workflow, including 3D QSAR-, common feature-, and structure-based EGFR-TK domain-containing pharmacoph

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Al-Sha'er, Mahmoud A., Rua'a A. Al-Aqtash та Mutasem O. Taha. "Discovery of New Phosphoinositide 3-kinase Delta (PI3Kδ) Inhibitors via Virtual Screening using Crystallography-derived Pharmacophore Modelling and QSAR Analysis". Medicinal Chemistry 15, № 6 (2019): 588–601. http://dx.doi.org/10.2174/1573406415666190222125333.

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<P>Background: PI3K&#948; is predominantly expressed in hematopoietic cells and participates in the activation of leukocytes. PI3K&#948; inhibition is a promising approach for treating inflammatory diseases and leukocyte malignancies. Accordingly, we decided to model PI3K&#948; binding. </P><P> Methods: Seventeen PI3K&#948; crystallographic complexes were used to extract 94 pharmacophore models. QSAR modelling was subsequently used to select the superior pharmacophore(s) that best explain bioactivity variation within a list of 79 diverse inhibitors (i.e., upon

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Glennon, Richard A., та Małgorzata Dukat. "α4β2 nACh Receptor pharmacophore models". Bioorganic & Medicinal Chemistry Letters 14, № 8 (2004): 1841–44. http://dx.doi.org/10.1016/j.bmcl.2003.07.035.

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Zhang, Yan Ling, Yuan Ming Wang, and Yan Jiang Qiao. "Sub-Pharmacophore Generation of JNK3 Inhibitors." Applied Mechanics and Materials 444-445 (October 2013): 1756–60. http://dx.doi.org/10.4028/www.scientific.net/amm.444-445.1756.

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The structure-based pharmacophore (SBP) model is consisted by the complementarity of the chemical features and space of the interaction between the ligand and receptor. The SBP models always have a high specificity which can only represent the specific class of the ligand. To simplify the models, sub-pharmacophore was then proposed in present study, and was expected to have and only have the most important or the common chemical features which play the major role in the interaction of ligand and receptor. Sub-pharmacophore should contain 4-6 features, the higher specificity with more features,

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Permann, Christian, Thomas Seidel, and Thierry Langer. "Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment." Molecules 26, no. 23 (2021): 7201. http://dx.doi.org/10.3390/molecules26237201.

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Chemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilitates the virtual screening of even large compound databases. Existing alignment methods, used in computational drug discovery and bio-activity prediction, are often not suitable for finding matches between pharmacophores accurately as they purely aim to minimize RMSD or maximize volume overlap, when

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Zhang, Yan Ling, Yuan Ming Wang, and Yan Jiang Qiao. "Structure-Based Pharmacophore Models Generation and Combinatorial Screening of ICE Inhibitors." Applied Mechanics and Materials 347-350 (August 2013): 1216–20. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.1216.

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Eight structure-based pharmacophore models of Interleukin-1β converting enzyme (ICE) inhibitors were generated by LigandScout based on ICE inhibitor complexes from the Protein Data Bank (PDB). A combinatorial screening method based on multiple pharmacophore models were proposed in present study, since the binding pockets of different complexes were different, the structure-based pharmacophore models have a high specificity and cannot cover all the active molecules. Based on the screening results of MDDR and the metrics of E and A%, a new metric CAI (comprehensive appraisal index) was defined a

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Van Drie, John H. "Generation of three-dimensional pharmacophore models." Wiley Interdisciplinary Reviews: Computational Molecular Science 3, no. 5 (2012): 449–64. http://dx.doi.org/10.1002/wcms.1129.

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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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Ekins, Sean, Joel S. Freundlich, and Megan Coffee. "A common feature pharmacophore for FDA-approved drugs inhibiting the Ebola virus." F1000Research 3 (November 14, 2014): 277. http://dx.doi.org/10.12688/f1000research.5741.1.

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We are currently faced with a global infectious disease crisis which has been anticipated for decades. While many promising biotherapeutics are being tested, the search for a small molecule has yet to deliver an approved drug or therapeutic for the Ebola or similar filoviruses that cause haemorrhagic fever. Two recent high throughput screens published in 2013 did however identify several hits that progressed to animal studies that are FDA approved drugs used for other indications. The current computational analysis uses these molecules from two different structural classes to construct a commo

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Zhang, Yan Ling, Yuan Ming Wang, and Yan Jiang Qiao. "Virtual Screening in Chinese Herbs with Multi-Target Effect on Alzheimer's Disease." Advanced Materials Research 765-767 (September 2013): 256–60. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.256.

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Multiple targets which closely related to Alzheimer's disease (AD) pathogenesis were selected for pharmacophore models generation and virtual screening in Chinese herbs. The targets comprised Acetylcholinesterase (AchE), muscarinic receptor 1 (M1), γ-secretase and glycogen synthase kinase 3β (GSK-3β). The pharmacophore models, which of AchE inhibitors, M1 agonists, γ-secretase inhibitors and GSK-3β inhibitors, were constructed by distance comparison method. Four testing databases for the evaluation of pharmacophore models were constructed with the active compounds with clearly marked activity

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Wang, Kate, Eden L. Romm, Valentina L. Kouznetsova, and Igor F. Tsigelny. "Prediction of Premature Termination Codon Suppressing Compounds for Treatment of Duchenne Muscular Dystrophy Using Machine Learning." Molecules 25, no. 17 (2020): 3886. http://dx.doi.org/10.3390/molecules25173886.

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A significant percentage of Duchenne muscular dystrophy (DMD) cases are caused by premature termination codon (PTC) mutations in the dystrophin gene, leading to the production of a truncated, non-functional dystrophin polypeptide. PTC-suppressing compounds (PTCSC) have been developed in order to restore protein translation by allowing the incorporation of an amino acid in place of a stop codon. However, limitations exist in terms of efficacy and toxicity. To identify new compounds that have PTC-suppressing ability, we selected and clustered existing PTCSC, allowing for the construction of a co

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Dai, Shao-Xing, Gong-Hua Li, Yue-Dong Gao, and Jing-Fei Huang. "Pharmacophore-Map-Pick: A Method to Generate Pharmacophore Models for All Human GPCRs." Molecular Informatics 35, no. 2 (2015): 81–91. http://dx.doi.org/10.1002/minf.201500075.

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Malo, Marcus, Lars Brive, Kristina Luthman, and Peder Svensson. "Selective Pharmacophore Models of Dopamine D1and D2Full Agonists Based on Extended Pharmacophore Features." ChemMedChem 5, no. 2 (2010): 232–46. http://dx.doi.org/10.1002/cmdc.200900398.

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Witkowska, Ewa, Magda Godlewska, Jowita Osiejuk, et al. "Bifunctional Opioid/Melanocortin Peptidomimetics for Use in Neuropathic Pain: Variation in the Type and Length of the Linker Connecting the Two Pharmacophores." International Journal of Molecular Sciences 23, no. 2 (2022): 674. http://dx.doi.org/10.3390/ijms23020674.

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Based on the mechanism of neuropathic pain induction, a new type of bifunctional hybrid peptidomimetics was obtained for potential use in this type of pain. Hybrids consist of two types of pharmacophores that are connected by different types of linkers. The first pharmacophore is an opioid agonist, and the second pharmacophore is an antagonist of the pronociceptive system, i.e., an antagonist of the melanocortin-4 receptor. The results of tests in acute and neuropathic pain models of the obtained compounds have shown that the type of linker used to connect pharmacophores had an effect on antin

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Sabitha, Kesavan. "Nilotinib based pharmacophore models for BCR-ABL." Bioinformation 8, no. 14 (2012): 658–63. http://dx.doi.org/10.6026/97320630008658.

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Poulsen, Anders, Berith Bjørnholm, Klaus Gundertofte, Irina D. Pogozheva, and Tommy Liljefors. "Pharmacophore and receptor models for neurokinin receptors." Journal of Computer-Aided Molecular Design 17, no. 11 (2003): 765–83. http://dx.doi.org/10.1023/b:jcam.0000017497.58165.d8.

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Srinivasan, Ashwin, David Page, Rui Camacho, and Ross King. "Quantitative pharmacophore models with inductive logic programming." Machine Learning 64, no. 1-3 (2006): 65–90. http://dx.doi.org/10.1007/s10994-006-8262-2.

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Kohlbacher, Stefan Michael, Matthias Schmid, Thomas Seidel, and Thierry Langer. "Applications of the Novel Quantitative Pharmacophore Activity Relationship Method QPhAR in Virtual Screening and Lead-Optimisation." Pharmaceuticals 15, no. 9 (2022): 1122. http://dx.doi.org/10.3390/ph15091122.

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Pharmacophores are an established concept for the modelling of ligand–receptor interactions based on the abstract representations of stereoelectronic molecular features. They became widely popular as filters for the fast virtual screening of large compound libraries. A lot of effort has been put into the development of sophisticated algorithms and strategies to increase the computational efficiency of the screening process. However, hardly any focus has been put on the development of automated procedures that optimise pharmacophores towards higher discriminatory power, which still has to be do

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Kaserer, Teresa, Katharina Beck, Muhammad Akram, Alex Odermatt, and Daniela Schuster. "Pharmacophore Models and Pharmacophore-Based Virtual Screening: Concepts and Applications Exemplified on Hydroxysteroid Dehydrogenases." Molecules 20, no. 12 (2015): 22799–832. http://dx.doi.org/10.3390/molecules201219880.

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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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Febrina, Ellin, and Aiyi Asnawi. "Lead compound discovery using pharmacophore-based models of small-molecule metabolites from human blood as inhibitor cellular entry of SARS-CoV-2." Journal of Pharmacy & Pharmacognosy Research 11, no. 5 (2023): 810–22. http://dx.doi.org/10.56499/jppres23.1688_11.5.810.

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Context: The development of emerging viral diseases like SARS-CoV-2 has underlined the critical need for new antiviral medicines. Many of the discovered inhibitors have off-target effects or toxicity issues, but no single lead chemical has been found as a powerful SARS-CoV-2 inhibitor. Small-molecule metabolites from human blood, for example, have been demonstrated to exhibit biological action, such as anti-inflammatory or antiviral properties, but have not been reported as pharmacophore-based drug discovery models. Aims: To evaluate the feasibility of employing pharmacophore models of small-m

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Haseeb, Muhammad, Sana Vaqar, Sahar Fazal, and Aftab Khalil. "LIGAND BASED PHARMACOPHORE DEVELOPMENT FOR COLORECTAL CANCER DRUGS." Professional Medical Journal 21, no. 05 (2018): 856–63. http://dx.doi.org/10.29309/tpmj/2014.21.05.2548.

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….Objective: Focusing on the drugs used for chemotherapy and their associatedside effects, there is a need to design and develop new anti-colon cancer drugs with lesser sideeffects and improved efficacy. Pharmacophore model proves to be a very helpful tool servingin the designing and development of new lead compounds. Place and Duration: Departmentof Bioinformatics, Mohammad Ali Jinnah University, Islamabad from January 2014 to May2014. Results: In this paper, pharmacophore of 4 novel anti-colon cancer compounds hasbeen identified and validated for the first time. Using LigandScout the pharmac

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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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Gupta, Shikhar, and C. Gopi Mohan. "Dual Binding Site and Selective Acetylcholinesterase Inhibitors Derived from Integrated Pharmacophore Models and Sequential Virtual Screening." BioMed Research International 2014 (2014): 1–21. http://dx.doi.org/10.1155/2014/291214.

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In this study, we have employedin silicomethodology combining double pharmacophore based screening, molecular docking, and ADME/T filtering to identify dual binding site acetylcholinesterase inhibitors that can preferentially inhibit acetylcholinesterase and simultaneously inhibit the butyrylcholinesterase also but in the lesser extent than acetylcholinesterase. 3D-pharmacophore models of AChE and BuChE enzyme inhibitors have been developed from xanthostigmine derivatives through HypoGen and validated using test set, Fischer’s randomization technique. The best acetylcholinesterase and butyrylc

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Hariyanti, Hariyanti, Kusmadi Kurmardi, Arry Yanuar та Hayun Hayun. "Ligand Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies of Asymmetrical Hexahydro-2H-Indazole Analogs of Curcumin (AIACs) to Discover Novel Estrogen Receptors Alpha (ERα) Inhibitor". Indonesian Journal of Chemistry 21, № 1 (2020): 137. http://dx.doi.org/10.22146/ijc.54745.

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The estrogen receptor alpha (ERα) plays an important role in breast development and pro-proliferation signal activation in the normal and cancerous breast. The ERα inhibitors were potentially active as cytotoxic agents against breast cancer. This study was conducted in order to find Asymmetrical Hexahydro-2H-Indazole Analogs of Curcumin (AIACs) as hits of ERα inhibitor. A training set of 17 selected ERα inhibitors was used to create 10 pharmacophore models using LigandScout 4.2. The pharmacophore models were validated using 383 active compounds as positive data and 20674 decoys as negative dat

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V, Sharma, Sharma PC, and Kumar V. "INDOLIZINE DERIVATIVES AS PHOSPHODIESTERASE IV INHIBITORS: DEVELOPMENT AND VALIDATION OF PHARMACOPHORE MODELS." Bulletin of Pharmaceutical Research 6, no. 2 (2016): 68–73. http://dx.doi.org/10.21276/bpr.2016.6.2.5.

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Tutone, Marco, Giulia Culletta, Luca Livecchi, and Anna M. Almerico. "A Definitive Pharmacophore Modelling Study on CDK2 ATP Pocket Binders: Tracing the Path of New Virtual High-Throughput Screenings." Current Drug Discovery Technologies 17, no. 5 (2020): 740–47. http://dx.doi.org/10.2174/1570163816666190620113944.

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Cyclin Dependent Kinases-2 (CDK2) are members of serine/threonine protein kinases family. They play an important role in the regulation events of the eukaryotic cell division cycle, especially during the G1 to S phase transition. Experimental evidence indicate that excessive expression of CDK2s should cause abnormal cell cycle regulation. Therefore, since a long time, CDK2s have been considered potential therapeutic targets for cancer therapy. In this work, onehundred and forty-nine complexes of inhibitors bound in the CDK2-ATP pocket were submitted to short MD simulations (10ns) and free ener

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Bojarski, Andrzej. "Pharmacophore Models for Metabotropic 5-HT Receptor Ligands." Current Topics in Medicinal Chemistry 6, no. 18 (2006): 2005–26. http://dx.doi.org/10.2174/156802606778522186.

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Cinel, Bruno, Michel Roberge, Hans Behrisch, Leen van Ofwegen, Clovis B. Castro, and Raymond J. Andersen. "Antimitotic Diterpenes fromErythropodiumcaribaeorumTest Pharmacophore Models for Microtubule Stabilization." Organic Letters 2, no. 3 (2000): 257–60. http://dx.doi.org/10.1021/ol9912027.

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Wei, Jing, Yixi Liu, and Songqing Wang. "3D pharmacophore models for thromboxane A2 receptor antagonists." Journal of Molecular Modeling 15, no. 10 (2009): 1185–91. http://dx.doi.org/10.1007/s00894-009-0475-4.

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Mosberg, Henry I. "Complementarity of ? opioid ligand pharmacophore and receptor models." Biopolymers 51, no. 6 (1999): 426–39. http://dx.doi.org/10.1002/(sici)1097-0282(1999)51:6<426::aid-bip5>3.0.co;2-g.

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Langer, Thierry, and G. Wolber. "Virtual combinatorial chemistry and in silico screening: Efficient tools for lead structure discovery?" Pure and Applied Chemistry 76, no. 5 (2004): 991–96. http://dx.doi.org/10.1351/pac200476050991.

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In this article, an overview of the most common ligand-based in silico screening techniques is given together with an example on the recent successful application of combined use of pharmacophore modeling, database mining, and biological assays. Additionally, a new approach for structure-based high-throughput pharmacophore model generation is presented. The LigandScout program contains an automated method for creating pharmacophore models from experimentally determined structure data, e.g., publicly available from the Brookhaven Protein Databank (PDB). In a first step, known algorithms were im

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Lee, June, Sung Cho, and Mi-hyun Kim. "Discovery of CNS-Like D3R-Selective Antagonists Using 3D Pharmacophore Guided Virtual Screening." Molecules 23, no. 10 (2018): 2452. http://dx.doi.org/10.3390/molecules23102452.

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The dopamine D3 receptor is an important CNS target for the treatment of a variety of neurological diseases. Selective dopamine D3 receptor antagonists modulate the improvement of psychostimulant addiction and relapse. In this study, five and six featured pharmacophore models of D3R antagonists were generated and evaluated with the post-hoc score combining two survival scores of active and inactive. Among the Top 10 models, APRRR215 and AHPRRR104 were chosen based on the coefficient of determination (APRRR215: R2training = 0.80; AHPRRR104: R2training = 0.82) and predictability (APRRR215: Q2tes

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Kumar, Vinay, and Achintya Saha. "Chemometric Modeling of Structurally Diverse Carbamates for the Inhibition of Acetylcholinesterase (AChE) Enzyme in Alzheimer's Disease." International Journal of Quantitative Structure-Property Relationships 5, no. 3 (2020): 6–60. http://dx.doi.org/10.4018/ijqspr.2020070102.

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In this research, we have developed two-dimensional quantitative structure-activity relationship (2D-QSAR) and group-based QSAR (GQSAR) models employing a dataset of 78 carbamate derivatives (acetylcholinesterase enzyme inhibitors). The developed models were validated using various stringent validation parameters. From the insights obtained from the developed 2D-QSAR and GQSAR models, we have found that the structural features appearing in the models are responsible for the enhancement of the inhibitory activity against the AChE enzyme. Furthermore, we have performed the pharmacophore modeling

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Zhang, Yan Ling, Yuan Ming Wang, and Yan Jiang Qiao. "Combinatorial Screening of COX-2 Inhibitors from Chinese Herbs Based on Multiple Structure-Based Pharmacophores." Advanced Materials Research 791-793 (September 2013): 269–73. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.269.

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Ten structure-based pharmacophore models of Cyclooxygenase 2 (COX-2) inhibitors were generated by LigandScout based on COX-2 inhibitor complexes from the Protein Data Bank (PDB). The potential COX-2 inhibitors were identified from traditional Chinese medicine with the method of combinatorial screening with ten models. Based on the screening results of MDDR and the metrics of E, A% and comprehensive appraisal index (CAI), the threshold of hit frequency of molecules was defined and used to identify the active molecules from Chinese herbs. The molecules hit by not less than six pharmacophore mode

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Mitra, Indrani, Achintya Saha, and Kunal Roy. "Quantification of contributions of different molecular fragments for antioxidant activity of coumarin derivatives based on QSAR analyses." Canadian Journal of Chemistry 91, no. 6 (2013): 428–41. http://dx.doi.org/10.1139/cjc-2012-0527.

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Attempts have been made in the present work using in silico techniques for identification of essential structural features imparting antioxidant potential to naturally available coumarin molecules and their synthetic derivatives. Four different types of modeling tools have been employed for the qualitative and quantitative assessment of the molecular fragments constituting the biological pharmacophore. The descriptor-based quantitative structure–activity relationship (QSAR) and group-based QSAR (G-QSAR) models provide a quantitative estimation of the substituent requirements and the chemical n

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Rai, Amit, Mohamed H. Aboumanei, Suraj P. Verma, Sachidanand Kumar, and Vinit Raj. "Molecular Docking, Pharmacophore, and 3D-QSAR Approach: Can Adenine Derivatives Exhibit Significant Inhibitor Towards Ebola Virus?" Open Medicinal Chemistry Journal 11, no. 1 (2017): 127–37. http://dx.doi.org/10.2174/1874104501711010127.

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Introduction: Ebola Virus Disease (EVD) is caused by Ebola virus, which is often accompanied by fatal hemorrhagic fever upon infection in humans. This virus has caused the majority of deaths in human. There are no proper vaccinations and medications available for EVD. It is pivoting the attraction of scientist to develop the potent vaccination or novel lead to inhibit Ebola virus. Methods & Materials: In the present study, we developed 3D-QSAR and the pharmacophoric model from the previous reported potent compounds for the Ebola virus. Results & Discussion: Results & Discussion: Th

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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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Klenina, Olena. "In Silico Exploration of Molecular Mechanisms for Inhibiting Inflammatory Responses by 3Н-Thiazolo[4,5-b]pyridin-2-one Derivatives". Acta Chimica Slovenica 71, № 2 (2024): 264–87. http://dx.doi.org/10.17344/acsi.2024.8726.

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Combined in silico strategy for molecular mechanisms exploration of a series 3H-thiazolo[4,5-b]pyridin-2-ones exhibiting strong anti-exudative action through QSAR analysis, molecular docking and pharmacophore modelling is reported. GA-ML technique was used for QSAR models generation with 2D autocorrelation descriptors. One- and two-parameter regressions revealed that certain structural patterns or heteroatoms contribute mutually to the anti-exudative activity potentiation. Possible action mechanisms were discovered through flexible docking simulations with cyclooxygenase pathway enzymes (COX-1

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Agrawal, Neetu. "Pharmacophore modeling and 3D-QSAR studies of 2,4-disubstituted pyrimidine derivatives as Janus kinase 3 inhibitors." Journal of Theoretical and Computational Chemistry 19, no. 01 (2020): 2050001. http://dx.doi.org/10.1142/s0219633620500017.

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A robust pharmacophore model was developed and the structure-activity relationship was analyzed using 71 pyrimidine derivatives reported for covalent Janus Kinase 3 (JAK3) inhibition. Pharmacophore modeling developed a five featured pharmacophore: one H-bond acceptor, two H-bond donors, one hydrophobic, and one aromatic ring features. The atom-based three-dimensional QSAR models with statistical significance were generated using the training set of 52 compounds. The excellent predictive correlation coefficients were obtained for 3D models determined using a test set of 19 molecules. The genera

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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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Ghoshal, Nanda, and R. Suyambu Kesava Vijayan. "Pharmacophore models for GABAAmodulators: implications in CNS drug discovery." Expert Opinion on Drug Discovery 5, no. 5 (2010): 441–60. http://dx.doi.org/10.1517/17460441003789363.

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