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Добірка наукової літератури з теми "PHARMACOPHORE MODELING"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Статті в журналах з теми "PHARMACOPHORE MODELING"

Kutlushina, Alina, Aigul Khakimova, Timur Madzhidov, and Pavel Polishchuk. "Ligand-Based Pharmacophore Modeling Using Novel 3D Pharmacophore Signatures." Molecules 23, no. 12 (November 27, 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 pharmacophore ligand-based modeling approach to search for pharmacophores which preferably match active compounds and do not match inactive ones was developed. The approach searches for 3D pharmacophore models starting from 2D structures of available active and inactive compounds. The implemented approach was successfully applied for several retrospective studies. The results were compared to a 2D similarity search, demonstrating some of the advantages of the developed 3D pharmacophore models. Also, the generated 3D pharmacophore models were able to match the 3D poses of known ligands from their protein-ligand complexes, confirming the validity of the models. The developed approach is available as an open-source software tool: http://www.qsar4u.com/pages/pmapper.php and https://github.com/meddwl/psearch.

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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 (August 6, 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 energy functions. The most relevant points are selected by a newly developed filtering cascade and clustered to pharmacophore features with a density-based algorithm. Using five different protein classes, the ability of this method to identify essential pharmacophore features was compared to structure-based pharmacophores derived from ligand-target interactions. This method represents an extremely valuable instrument for drug design in a situation of scarce ligand information available, but also in the case of underexplored therapeutic targets, as well as to investigate protein allosteric pockets and protein-protein interactions.

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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 (January 17, 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 pharmacophore models were proposed. Both approaches to some extent correspond to commonly used consensus approaches like the common hit approach or the one based on a logical OR operation uniting hit lists of individual models. Unlike some known approaches, the proposed ones can rank compounds retrieved by multiple models. These approaches were benchmarked on multiple ChEMBL datasets used for ligand-based pharmacophore modeling and externally validated on corresponding DUD-E datasets. The influence of complexity of pharmacophores and their performance on a calibration set on results of virtual screening was analyzed. It was shown that Max and Mean approaches have superior early enrichment to the commonly used approaches. Thus, a well-performing, easy-to-implement, and probabilistic alternative to existing approaches for pharmacophore-based virtual screening was proposed.

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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 (October 18, 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, and consider only the physiochemical properties of ligands. However, these ligand-based methods have their own limitations and sometimes fail to predict the BBB permeation of xenobiotics. The objective of this work was to investigate the influence of the pharmacophoric features of protein–ligand interactions on BBB permeation. For these purposes, receptor-based pharmacophore and ligand-based pharmacophore fingerprints were developed using docking and Rdkit, respectively. Then, these fingerprints were trained on classical machine-learning models and compared with classical fingerprints. Among the tested footprints, the ligand-based pharmacophore fingerprint achieved slightly better (77% accuracy) performance compared to the classical fingerprint method. In contrast, receptor-based pharmacophores did not lead to much improvement compared to classical descriptors. The performance can be further improved by considering efflux proteins such as BCRP (breast cancer resistance protein), as well as P-gp (P-glycoprotein). However, the limited data availability for other proteins regarding their pharmacophoric interactions is a bottleneck to its improvement. Nonetheless, the developed models and exploratory analysis provide a path to extend the same framework for environmental chemicals, which, like drugs, are also xenobiotics. This research can help in human health risk assessment by a priori screening for neurotoxicity-causing agents.

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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 HDAC7 enzyme. Analysis of the binding characteristics of all the compounds collected and tested in the model resulted in the characteristics produced by the 3D pharmacophore of the selected hypothesis. This led to note that the efficiency of any HDAC enzyme inhibitor was related to the characteristics of the designed pharmacophore. At the end, the pharmacophore hypothesis used here was presented as a useful basis for the development of anticancer compounds. Keywords: Pharmacophore, 3c0z, HDAC7, QSAR

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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 (November 6, 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 collected and studied. Every single receptorligand interaction was validated and the significant ones were converted into their corresponding pharmacophoric features. The generated pharmacophores were scored by the Receiver Operating Characteristic (ROC) curve analysis. Results: Consequently, 169 pharmacophores were generated and sorted, 11 pharmacophores acquired good ROC-AUC results of 0.8 and a selectivity value above 8. Pharmacophore 1UU3_2_01 was used in particular as a searching filter to screen NCI database because of its acceptable validity criteria and its distinctive positive ionizable feature. Several low micromolar PDK1 inhibitors were revealed. The most potent hit illustrated anti-PDK1 IC50 values of 200 nM with 70% inhibition against SW480 cell lines. Conclusion: Eventually, the active hits were docked inside the PDK1 binding pocket and the recognition points between the active hits and the receptor were analyzed that led to the discovery of new scaffolds as potential PDK1 inhibitors.

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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 (July 1, 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 derivatives as an inhibitor. This study has been undertaken to realize intuitions into molecular mechanisms and structural necessities crucial for potential inhibition of betulonic acid derivatives. The standard procedure was adapted to develop the pharmacophoric models. It is found that the pharmacophore model of active betulonic acid derivative (compound 5h) unveils the importance of five- and six-member aliphatic cyclic hydrocarbon moiety, aromatic ring, –OH group of carboxylic acid, five-member heterocyclic rings (triazolo) and aliphatic alkene group and their correlation with the biological activity. It may be helpful within the design of novel betulonic acid derivatives inhibitors for human coronavirus-229E replication. Keywords: Pharmacophore Model, Antiviral activity, HCoV-229E replication, Betulonic acid derivatives, nsp15.

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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 (June 6, 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 features responsible for anti-lung cancer activities.Method:A robust pharmacophore developed for the receptor have been analyzed to identify potential areas of selectivity in the hyperspace of 3D pharmacophores that may lead to the discovery of anti-lung cancer drug or such compounds which could serve as templates for the design of new molecules as potential anti lung cancer agents.Results:The generated best pharmacophore hypothesis yielded a statistically significant 3D-QSAR model, with a correlation coefficient of R2= 0.86 for training set and R2= 0.76 for the test set molecules. The Cross validation regression coefficient is Q2= 0.84 for training set and Q2= 0.5 for test set molecules.Conclusion:The R2and Q2reveals that pharmacophore model provide insights into the structural and chemical features of the EGFR inhibitors of Quercetin derivatives that can be used as lead compound for further synthesis as well as for screening other similar novel inhibitors of EGFR.

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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 (May 1, 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 (June 1, 2013): 1327–42. http://dx.doi.org/10.2174/15680266113139990037.

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Дисертації з теми "PHARMACOPHORE MODELING"

Vendruscolo, Maria Helena. "Obtenção de iridoides de espécies nativas da flora do Rio Grande do Sul, modificações estruturais, determinação da atividade anti-Leishmania amazonensis in vitro e modelagem molecular." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/166272.

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Iridoides são metabólitos secundários provenientes de angiospermas eudicotiledôneas, presentes principalmente em espécies das ordens Gentianales e Lamiales. Os iridoides dividem-se em carbocíclicos e seco-iridoides, ocorrendo comumente na forma glicosilada. Estes compostos são marcadores taxonômicos em algumas famílias vegetais e apresentam diversas atividades biológicas tais como cardiovascular, neuroprotetora e anti-Leishmania. Diante da importância dos iridoides, este trabalho teve como finalidade a prospecção química destes metabólitos em espécies nativas do Rio Grande Grande dos Sul, bem como a semissíntese de análogos e a investigação da atividade anti-Leishmania através de ensaios in vitro e modelagem molecular. Os compostos isolados foram identificados através de métodos espectroscópicos e os resultados comparados aos descritos na literatura. A partir de Escallonia bifida e Escallonia megapotamica (Escalloniaceae) foram isolados asperulosídeo, desacetilasperulosídeo, geniposídeo, ácido geniposídico e dafilosídeo, sendo que o asperulosídeo foi convertido em asperulosídeo tetraacetilado por meio de semissíntese. De Angelonia integerrima (Scrophulariaceae) foram obtidos galiridosídeo e antirrídeo. Nos experimentos in vitro para atividade anti-Leishmania, asperulosídeo, galiridosídeo, geniposídeo, ipolamida e teveridosídeo, nas concentrações 5-100 μM, não demonstraram inibição frente às formas promastigotas de Leishmania amazonensis. O estudo de modelagem molecular destes iridoides e daqueles descritos na literatura com atividade anti-Leishmania propôs um modelo farmacofórico que demonstrou que as diferenças estruturais não são responsáveis pela inatividade das moléculas isoladas neste trabalho. A perspectiva é realizar ensaios enzimáticos de tripanotiona redutase, bem com docking molecular e estudos de dinâmica molecular para investigar as interações entre grupamentos farmacofóricos das moléculas isoladas e o sítio de ligação de tripanotiona redutase.
Iridoids are secondary metabolites of eudicotyledonous angiosperms, present mainly in species of the orders Gentianales and Lamiales. The iridoids are divided into carbocyclic and seco-iridoids, occurring commonly in the glycosylated form. These compounds are taxonomic markers in same families of plants and have shown cardiovascular, neuroprotective and anti-Leishmania activities. In view of the importance of iridoids, this work aimed to the chemical prospection of these metabolites of native species of Rio Grande do Sul, as well as semi-synthesis of analogues and to investigate the anti-Leishmania activity through in vitro assays and molecular modeling. The isolated compounds were identified by spectroscopic methods and the results compared to those described in literature. From Escallonia bifida and Escallonia megapotamica (Escalloniaceae) asperuloside, deacetylasperuloside, geniposide, geniposidic acid and daphyloside were isolated, being asperuloside developed in asperuloside tetraacetylated by means of semi- synthesis. From Angelonia integerrima (Scrophulariaceae) galiridoside and antirride were obtained. In the in vitro experiments for anti-Leishmania activity, asperuloside, galiridoside, geniposideo, ipolamiide and theveridoside in concentrations 5-100 μM, did not demonstrate inhibition in promastigote form of Leishmania amazonensis. The molecular modeling study of these iridoids and those described in the literature with anti-Leishmania activity proposed a pharmacophoric model that demonstrated that the structures are not responsible by the inactivity of the molecules isolated in this work. The prospect is to carry out enzymatic assays of trypanothione redutase as well as molecular docking and molecular dynamics studies to investigate the interactions between pharmacophoric grouping of the isolated molecules and the trypanothione reductase binding site.

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Argade, Malaika. "Galantamine's Deconstruction in the Quest of a PAM Pharmacophore." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5461.

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Alzheimer’s disease is a progressive neurodegenerative disorder generally affecting people above the age of 65 years. Even though the pathophysiological hallmarks of AD were established more than a hundred years ago, there is yet to be a drug that can stop its characteristic neuronal damage. Of the five currently FDA-approved drugs, galantamine has a unique mechanism of action. Apart from being an AChE inhibitor, galantamine can effectively potentiate (positive allosteric modulator) the effect of agonists at nAChRs at concentrations lower than those required for its action as an AChE inhibitor. Perhaps the clinical benefits observed with galantamine are associated mainly with its nAChRs-PAM action and not its AChE inhibitory effect. Inhibiting AChE causes a delay in the degradation of ACh and a prolonged presence of ACh might act at either nAChRs or mAChRs. By indirectly targeting mAChRs as well, AChE inhibitors may lead to potential side effects. Hence there is a need for specific nAChR agents. The aim of this study was to identify the structural features of galantamine that contribute solely towards its a7 nAChR-PAM effect. In doing so, we wish to divorce the structural features that might be important for interacting with AChE. Using the deconstruction approach, we have synthesized structurally abbreviated analogs of galantamine. To study the probable interactions, we docked these molecules in human a7 nAChR homology models. Ultimately, it is of interest to determine which analogs retain the PAM activity of galantamine and to address that, a preliminary screening was performed with a select few analogs using the two-electrode voltage clamp technique

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Aldhumani, Ali Hamed. "Pharmacophore Model Development: Targeting Noncoding RNA for Antibacterial/Antiviral Drug Discovery." Ohio University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1610705872573225.

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Varela, Rial Alejandro 1993. "In silico modeling of protein-ligand binding." Doctoral thesis, TDX (Tesis Doctorals en Xarxa), 2022. http://hdl.handle.net/10803/673579.

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The affinity of a drug to its target protein is one of the key properties of a drug. Although there are experimental methods to measure the binding affinity, they are expensive and relatively slow. Hence, accurately predicting this property with software tools would be very beneficial to drug discovery. In this thesis, several applications have been developed to model and predict the binding mode of a ligand to a protein, to evaluate the feasibility of that prediction and to perform model interpretability in deep neural networks trained on protein-ligand complexes.
La afinidad de un fármaco a su proteína diana es una de las propiedades clave de un fármaco. Actualmente, existen métodos experimentales para medir la afinidad, pero son muy costosos y relativamente lentos. Así, predecir esta propiedad con precisión empleando herramientas de software sería muy beneficioso para el descubrimiento de fármacos. En esta tesis se han desarrollado aplicaciones de software para modelar y predecir el modo de unión de ligando a proteína, para evaluar cómo de factible es tal predicción y para interpretar redes neuronales profundas entrenadas en complejos proteína-ligando.

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Chang, Cheng. "In silico approaches for studying transporter and receptor structure-activity relationships." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1117553995.

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Thesis (Ph. D.)--Ohio State University, 2005.
Title from first page of PDF file. Document formatted into pages; contains xvii, 271 p.; also includes graphics. Includes bibliographical references (p. 245-269). Available online via OhioLINK's ETD Center

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Shah, Urjita H. "A Roadmap for Development of Novel Antipsychotic Agents Based on a Risperidone Scaffold." VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/4804.

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Schizophrenia is a chronic psychotic illness affecting ~21 million people globally. Currently available antipsychotic agents act through a dopamine D2 receptor mechanism, and produce extrapyramidal or metabolic side effects. Hence, there is a need for novel targets and agents. The mGlu2/5-HT2A receptor heteromer has been implicated in the action of antipsychotic agents, and represents a novel and attractive therapeutic target for the treatment of schizophrenia. A long-term goal of this project is to synthesize bivalent ligands where a 5-HT2A receptor antagonist is tethered to an mGlu2 PAM via a linker. The goals of the investigation were to study the SAR of risperidone (an atypical antipsychotic agent) at 5-HT2A receptors using a “deconstruction-reconstruction-elaboration” approach to determine the minimal structural features of risperidone that contribute to its 5-HT2A receptor affinity and antagonism, and to determine where on the “minimized risperidone” structure an mGlu2 PAM can be introduced. Additional goals included studying the binding modes of various mGlu2 PAMs and identifying where on an mGlu2 PAM a risperidone “partial” structure could be introduced. Biological studies of deconstructed/elaborated analogs of risperidone suggest that the entire structure of risperidone is not necessary for 5-HT2A receptor affinity and antagonism, and that a fluoro group contributes to 5-HT2A binding. 6-Fluoro-3-(4-piperidinyl)-1,2-benz[d]isoxazole that has only half the structural features of risperidone retains 5-HT2A receptor affinity and antagonist activity, and represents the “minimized risperidone” structure with the piperidine nitrogen atom representing a potential linker site for eventual construction of bivalent ligands. Molecular modeling studies at 5-HT2A receptors suggest that risperidone and its analogs have more than one binding mode. Modeling studies to evaluate binding modes of various PAMs at mGlu2 receptors, coupled with known SAR information, were used to identify a PAM (JNJ-40411813), and the pyridone nitrogen atom of JNJ-40411813 as a potential linker site. Additionally, potential synthetic routes for JNJ-40411813 were explored that might be of value in the synthesis of bivalent ligands. Based on the structural features of 6-fluoro-3-(4-piperidinyl)-1,2-benz[d]isoxazole, a new pharmacophore for 5-HT2A receptor antagonists, consisting of one aromatic region, a basic protonated amine and hydrogen bond acceptors, has been proposed.

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Klenc, Jeffrey D. "Design and Synthesis of Novel Serotonin Receptor Ligands." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/chemistry_diss/50.

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Novel and potent ligands to the serotonin7 (5-HT7) receptor have been synthesized. The synthesized compounds include a set of substituted pyrimidines which show high affinity to the 5-HT7 receptor, synthesized by previously described methods [1,2] in high yield. Comparing the affinities of substituted pyrimidines to previously calculated models [3,4] yielded new hypotheses about the nature of interaction between the pyrimidine ligands and the 5-HT7 binding site. Several new series of compounds were synthesized by various methods to validate these hypotheses, including a conjugate addition to vinylpyrimidines [5]. These compounds include benzofurans, oximes, hydrazones, as well as a group of substituted piperazines. All series of compounds show affinity to the 5-HT7 receptor comparable to previously synthesized 5-HT7 ligands. Several of the synthesized ligands show affinity which exceeds that of currently available ligands. The synthesized compounds were evaluated quantitatively by calculating a three-dimensional quantitative structure-affinity relationship (3D-QSAR) for the 5-HT7 receptor. Evaluation of the calculated model validated qualitative assumptions about the data set as well as described regions of interaction in greater detail than previously available. These observations give further insight on the nature of ligand-binding site interactions with highly potent ligands such as 4-(3-furyl)-2-(N-methylpiperazino)pyrimidine which will lead to more potent 5-HT7 receptor ligands. Additionally, a model was calculated for affinity to the 5-HT2a receptor. Comparing this model to that calculated for affinity to the 5-HT7 receptor identified two regions which may be exploited in future sets of ligands to increase selectivity to the 5HT7 receptor.

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Wong, Carmen Ka-Wing. "Unlocking mechanisms implicated in drug-induced bizarre idiosyncratic behaviours - learning from people and molecules." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16263.

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Zolpidem, an imidazopyridine hypnotic, which acts on GABA‐A receptors has been associated with the development of a number of disturbing neuropsychiatric adverse drug reactions (ADRs) including parasomnias, amnesia and hallucinations. Although other non-hypnotic medications are also implicated in the induction of such adverse events; the mechanism behind these ADRs remains elusive and have been postulated to arise from off-target receptor or pathway activation resulting in the disruption and dysregulation of keyneurotransmitters including GABA, acetylcholine, noradrenaline and dopamine. Using a novel multidisciplinary approach, we aim to investigate relationships between these rare idiosyncratic ADRs (parasomnia, movement-based parasomnia, non-movement based parasomnia, amnesia and hallucination) by identifying similarities in the chemical structure amongst drugs that share these reactions. These shared structural features or motifs may enable diverse drugs to participate in a pharmacological reaction with a mutual target receptor or pathway. By combining human population pharmacovigilance data with in silico computational techniques, insights into mechanisms underlying idiosyncratic reactions or toxicities can be elucidated.

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Afzelius, Lovisa. "Computational Modelling of Structures and Ligands of CYP2C9." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4016.

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Junior, Nilson Nicolau. "Diferenças Estruturais e \"Docking\" Receptor-Ligante da Proteína E7 do Vírus do Papiloma Humano (HPV) de Alto e Baixo Riscos para o Câncer Cervical." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/17/17135/tde-13062013-092311/.

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O câncer cervical afeta milhões de mulheres em todo o mundo a cada ano. A maioria dos casos de câncer cervical é causada pelo vírus do papiloma humano (HPV) que é sexualmente transmissível. Cerca de 40 tipos de HPV infectam o colo do útero e estes são designados como sendo de alto ou de baixo risco com base no seu potencial para provocar lesões de alto grau e câncer. A oncoproteína E7 do HPV está diretamente envolvida no aparecimento de câncer de colo do útero. Esta se associada com a proteína pRb e outros alvos celulares que promovem a imortalização celular e carcinogênese. Apesar de muito progresso nos estudos sobre os HPVs de alto risco, ainda não existe uma terapêutica adequada para o tratamento das lesões e câncer causados por este vírus. Este trabalho teve como objetivo entender as diferenças estruturais entre E7 de alto e baixo risco e sugerir, através de análises de bioinformática, possíveis sítios de ligação e inibidores para a E7. Esta é a primeira descrição da modelagem e análise de dinâmica molecular de quatro estruturas tridimensionais completas da E7 dos tipos de alto risco (HPV tipos 16 e 18), de baixo risco (HPV tipo 11) e não relacionadas ao câncer cervical (HPV tipo 1A). Os modelos foram construídos por uma abordagem híbrida usando modelagem por homologia e ab initio. Os modelos foram usados em simulações de dinâmica molecular por 50 ns, sob condições normais de temperatura e pressão. A desordem intrínseca da sequência da proteína E7 foi avaliada com o uso de ferramentas in silico. Os domínios N-terminal de todas as E7 estudadas, mesmo as de alto risco, exibiram estruturas secundárias depois da modelagem. Nas análises da trajetória da dinâmica molecular, as E7s dos HPVs dos tipos 16 e 18 apresentaram maior instabilidade nos seus domínios N-terminais em relação aos do HPV dos tipos 11 e 01. No entanto, esta variação não afetou a conformação das estruturas secundárias durante a simulação. A análise com ANCHOR indicou que as regiões CR1 e CR2 regiões dos tipos de HPV 16 e 18 contêm possíveis alvos para a descoberta da droga. Já a região CR3 do domínio C-terminal indicou estabilidade nas análises in silico e, por isso, foi usada como alvo de busca de modelos farmacofóricos e docking macromolecular. A proteína usada como modelo foi a E7 do HPV tipo 45 resultante de análises de ressonância magnética nuclear (RMN) e depositada no banco de dados de proteína (ID: 2F8B). Foram selecionados por análises sequenciais de busca farmacofórica, docking e re-docking, 19 compostos (extraídos de amplas bibliotecas de pequenos ligantes) com potencial para candidatos a inibidores da E7. Eles foram avaliados quanto a sua função de pontuação, mapas de interação receptor-ligante e toxicidade e os melhores foram indicados para estudos futuros.
Cervical cancer affects millions of women around the world each year. Most cases of cervical cancer are caused by human papilloma virus (HPV) which is sexually transmitted. About 40 types of HPV infect the cervix and these are designated as being at high or low risk based on their potential to cause high-grade lesions and cancer. The E7 oncoprotein from HPV is directly involved in the onset of cervical cancer. It associates with the pRb protein and other cellular targets that promote cell immortalization and carcinogenesis. Although the progress in studies with high-risk HPVs there is still no adequate therapy for the treatment of lesions and cancers caused by this virus. This study aimed to understand the structural differences between E7 of high and low risk and suggest, with the aid of bioinformatics analyzes, possible binding sites and inhibitors for the E7. This is the first description of the modeling and molecular dynamics analysis of four complete three-dimensional structures of E7 from high-risk types (HPV types 16 and 18), low risk (HPV type 11) and that not related to cervical cancer (HPV 01). The models were constructed by a hybrid approach using homology modeling and ab initio. The models were used in molecular dynamics simulations for 50 ns, under normal temperature and pressure. The intrinsic disorder of the E7 protein sequence was assessed using in silico tools. The N-terminal domains of all E7s, even the high-risks, showed secondary structures after modeling. In the trajectory analyzes of molecular dynamics, the E7s of HPV types 16 and 18 showed high instability in their N-terminal domains than those of HPV types 11 and 01, however, this variation did not affect the conformation of secondary structures during the simulation. The analysis with ANCHOR indicated that regions CR1 and CR2 regions of types of HPV 16 and 18 contain possible targets for drug discovery. The CR3 region of the C-terminal domain indicated stability by in silico analyzes and was therefore used as target to search for pharmacophoric models and \"docking\". The protein used as a model was the E7, from HPV type 45, constructed by analysis of nuclear magnetic resonance (NMR) and deposited in the protein data bank (ID: 2F8B). It was selected 19 compounds as potential candidates for E7 inhibitors (extracted from large libraries of small ligands) using sequential pharmacophore search, docking and re-docking analyzes. They were evaluated for their scoring function, maps of receptor-ligand interactions and toxicity and the best suited were indicated for future studies.

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Книги з теми "PHARMACOPHORE MODELING"

Beneditti, P. G. De. Theoretical Approaches to Quantitative Pharmacophore Modeling Biological Activity Relationships (Tcc , Vol 7). Elsevier Science Ltd, 1998.

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Zaheer Ul-Haq and Angela K. Wilson, eds. Frontiers in Computational Chemistry: Volume 6. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/97898150368481220601.

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Frontiers in Computational Chemistry presents contemporary research on molecular modeling techniques used in drug discovery and the drug development process: computer aided molecular design, drug discovery and development, lead generation, lead optimization, database management, computer and molecular graphics, and the development of new computational methods or efficient algorithms for the simulation of chemical phenomena including analyses of biological activity. The sixth volume of this series features these six different perspectives on the application of computational chemistry in rational drug design: 1. Computer-aided molecular design in computational chemistry 2. The role of ensemble conformational sampling using molecular docking & dynamics in drug discovery 3. Molecular dynamics applied to discover antiviral agents 4. Pharmacophore modeling approach in drug discovery against the tropical infectious disease malaria 5. Advances in computational network pharmacology for Traditional Chinese Medicine (TCM) research 6. Progress in electronic-structure based computational methods: from small molecules to large molecular systems of biological significance

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Частини книг з теми "PHARMACOPHORE MODELING"

Koes, David Ryan. "Pharmacophore Modeling: Methods and Applications." In Methods in Pharmacology and Toxicology, 167–88. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/7653_2015_46.

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Takahashi, Mitsuo, Kuniya Sakurai, Seji Niwa, and Seiji Oono. "Pharmacophore Model of Endothelin Antagonists." In Molecular Modeling and Prediction of Bioactivity, 416–17. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4141-7_103.

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Bhattacharjee, Apurba K. "Pharmacophore Modeling Applied to Mosquito-Borne Diseases." In Computational Design of Chemicals for the Control of Mosquitoes and Their Diseases, 139–70. Boca Raton : CRC Press, [2018]: CRC Press, 2017. http://dx.doi.org/10.4324/9781315151656-5.

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Froloff, Nicolas. "Pharmacophore Modeling of Sweet and Bitter Tasting Molecules." In Sweetness and Sweeteners, 133–46. Washington, DC: American Chemical Society, 2008. http://dx.doi.org/10.1021/bk-2008-0979.ch009.

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Boström, Jonas, Klaus Gundertofte, and Tommy Liljefors. "A 3D-Pharmacophore Model for Dopamine D4 Receptor Antagonists." In Molecular Modeling and Prediction of Bioactivity, 382–83. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4141-7_87.

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Høst, Jan, Inge Thøger Christensen, and Flemming Steen Jørgensen. "Conformational Analysis and Pharmacophore Identification of Potential Drugs for Osteoporosis." In Molecular Modeling and Prediction of Bioactivity, 373–74. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4141-7_83.

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Swaminathan, Priya. "Advances in Pharmacophore Modeling and Its Role in Drug Designing." In Computer-Aided Drug Design, 223–43. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6815-2_10.

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Seidel, Thomas, Sharon D. Bryant, Gökhan Ibis, Giulio Poli, and Thierry Langer. "3D Pharmacophore Modeling Techniques in Computer-Aided Molecular Design Using LigandScout." In Tutorials in Chemoinformatics, 279–309. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119161110.ch20.

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Kumar, Pawan, and Indira Ghosh. "Probing with Pharmacophore Modeling the Chloroquine Resistance and Designing Novel Antimalarials." In Biophysical and Computational Tools in Drug Discovery, 369–402. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/7355_2021_131.

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López-de-Briñas, Elena, Juan J. Lozano, Nuría B. Centeno, Jordi Segura, Marisa González, Rafael de la Torre, and Ferran Sanz. "Pharmacophore Development for the Interaction of Cytochrome P450 1A2 with Its Substrates and Inhibitors." In Molecular Modeling and Prediction of Bioactivity, 141–46. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4141-7_16.

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Тези доповідей конференцій з теми "PHARMACOPHORE MODELING"

Djokovic, Nemanja, Ana Postolovic, and Katarina Nikolic. "MOLECULAR MODELING OF 5‐[(AMIDOBENZYL)OXY]‐ NICOTINAMIDES AS SIRTUIN 2 INHIBITORS USING ALIGNMENT- (IN)DEPENDENT 3D-QSAR ANALYSIS AND MOLECULAR DOCKING." In 1st INTERNATIONAL Conference on Chemo and BioInformatics. Institute for Information Technologies, University of Kragujevac, 2021. http://dx.doi.org/10.46793/iccbi21.410dj.

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The group of 5‐[(amidobenzyl)oxy]‐nicotinamides represents promising group of sirtuin 2 (SIRT2) inhibitors. Despite structural similarity, representatives of this group of inhibitors displayed versatile mechanisms of inhibition which hamper rational drug design. The aim of this research was to form a 3D-QSAR (3D-Quantitative Structure-Activity Relationship) model, define the pharmacophore of this subgroup of SIRT2 inhibitors, define the mode of protein-ligand interactions and design new compounds with improved predicted activity and pharmacokinetics. For the 3D-QSAR study, data set was generated using structures and activities of 166 5‐[(amidobenzyl)oxy]‐nicotinamides. 3D-conformations of compounds were optimized, alignment-independent GRIND2 descriptors were calculated and 3D-QSAR PLS models were generated using 70% of data set. To investigate bioactive conformations of inhibitors, molecular docking was used. Molecular docking analysis identified two clusters of predicted bioactive conformations which is in alignment with experimental observations. The defined pharmacophoric features were used to design novel inhibitors with improved predicted potency and ADMET profiles.

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Shih, Kuei-Chung, Chun-Yuan Lin, Jiayi Zhou, Shih-Han Huang, and Chuan-Yi Tang. "Develop integration modeling approach for discovery neuraminidase inhibitors in silico based on pharmacophore and CoMSIA models." In 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2010. http://dx.doi.org/10.1109/bibmw.2010.5703855.

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Huo, Xiaoqian, Ludi Jiang, Xi Chen, Yusu He, Yongqiang Yang, and Yanling Zhang. "A combination of pharmacophore modeling, molecular docking and virtual screening for NPC1L1 receptor inhibitors from Chinese herbs." In 2014 8th International Conference on Systems Biology (ISB). IEEE, 2014. http://dx.doi.org/10.1109/isb.2014.6990429.

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Johari, Surabhi, Panchamita Basumatary, Kanwar Narain, Pratap Parida, and N. C. Barua. "Ligand-Based Pharmacophore Modeling, Virtual Screening and Molecular Docking Studies for Discovery of Novel Inhibitors against Staphylococcal Infections." In 2013 International Conference on Machine Intelligence and Research Advancement (ICMIRA). IEEE, 2013. http://dx.doi.org/10.1109/icmira.2013.131.

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Lengers, Isabelle, Fabian Herrmann, Samer Haidar, and Joachim Jose. "Human Hyal‑1 – from in silico Pharmacophore Modeling to in vitro Inhibitor Screening." In 3rd International Electronic Conference on Medicinal Chemistry. Basel, Switzerland: MDPI, 2017. http://dx.doi.org/10.3390/ecmc-3-04708.

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Cvijetić, Ilija, Miljan Bigović, Petar Ristivojević, Maja Vitorović-Todorović, Mire Zloh, and Dušanka Milojković-Opsenica. "THERMODYNAMICS OF THE ANTIOXIDANT ACTIVITY OF HUMULONES AND OTHER ANTIOXIDANTS FROM BEER – A MOLECULAR MODELING APPROACH." In 1st INTERNATIONAL Conference on Chemo and BioInformatics. Institute for Information Technologies, University of Kragujevac, 2021. http://dx.doi.org/10.46793/iccbi21.408c.

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Recent experimental study identified eight potent antioxidants in German beers, including isoxanthohumol, (R)- and (S)-adhumulone, cis– and trans-iso-adhumulone, cis– and trans-iso- n-humulone, and desdimetyhyl-octahydro-iso-cohumulone. To provide insights into the structural basis of their radical scavenging activity, we calculated the thermodynamic feasibility of two common antioxidant mechanisms, hydrogen atom transfer (HAT) and single electron transfer followed by proton transfer (SET-PT), using the density functional theory (DFT) with B3LYP/6-311g++(2d,2p) method in the gas phase and implicit solvation model of water. The calculated bond dissociation enthalpies (BDEs) and ionization potential (IP) of all compounds were compared with the corresponding values for resveratrol, a highly potent antioxidant found in red wine. The fully reduced humulone isomer, desdimetyhyl-octahydro-iso-cohumulone, could scavenge free radicals via HAT as revealed by BDEs 5.1 and 23.9 kJ/mol lower than the values for resveratrol in gas phase and water, respectively. Furthermore, the enolic –OH group was identified as the pharmacophoric hotspot for the interaction of humulones with the reactive free radicals. The HAT potency of this group is significantly reduced through the formation of strong intramolecular hydrogen bond (IHB) with the β-keto group. Moreover, the SET-PT mechanism was thermodynamically favorable for isoxanthohumol. These results strongly suggest higher antioxidant activity of beers with the increased content of the reduced forms of humulones and their isomers.

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