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Littérature scientifique sur le sujet « Computer-based drug design »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 10 mars 2023

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Articles de revues sur le sujet "Computer-based drug design"

ISHIGURO, Masaji. "Computer-Aided Structure Based Drug Design." Journal of the agricultural chemical society of Japan 67, no. 9 (1993): 1295–98. http://dx.doi.org/10.1271/nogeikagaku1924.67.1295.

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Barrawaz, Aateka Y. "COMPUTER AIDED DRUG DESIGN: A MINI-REVIEW." Journal of Medical Pharmaceutical And Allied Sciences 9, no. 5 (2020): 2584–91. http://dx.doi.org/10.22270/jmpas.v9i5.971.

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New drug discovery and development process is considered much complex process which is time consuming and resources accommodating too. So computer aided drug design are being broadly used to enhance the effectiveness of the drug discovery and development process which ultimately saves time and resources. Various approaches to Computer aided drug design are evaluated to shows potential techniques in accordance with their needs. Two approaches are considered to designing of drug first one is structure-based and second one is Ligand based drug designs. In this review, we are discussing about highly effective and powerful techniques for drug discovery and development as well as various methods of Computer aided drug design like molecular docking at virtual screening for lead identification, QSAR, molecular homology, de-novo design, molecular modeling and optimization. It also elaborate about different software used in Computer aided drug design, different application of Computer aided drug design etc. Major objectives of Computer aided drug design are to commence collaborative foundation of research activities and to discover new chemical entities for novel therapeutics drugs

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Prathipati, Philip, Anshuman Dixit, and Anil Saxena. "Computer-Aided Drug Design: Integration of Structure-Based and Ligand-Based Approaches in Drug Design." Current Computer Aided-Drug Design 3, no. 2 (2007): 133–48. http://dx.doi.org/10.2174/157340907780809516.

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Zeng, Huahui, and Xiangxiang Wu. "Alzheimer's disease drug development based on Computer-Aided Drug Design." European Journal of Medicinal Chemistry 121 (October 2016): 851–63. http://dx.doi.org/10.1016/j.ejmech.2015.08.039.

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Sharma, Anu, Lalubhai Jangid, Nusrat Shaikh, and Jitendra Bhangale. "Computer-Aided Drug Design Boon in Drug Discovery." Asian Journal of Organic & Medicinal Chemistry 7, no. 1 (2022): 55–64. http://dx.doi.org/10.14233/ajomc.2022.ajomc-p361.

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An innovative sequential step of detecting new medicines or drugs dependent on the information of a target is called drug design. The drug is a small molecule that alters the capacity of a bimolecular, example, protein, receptor or catalyst that leads to restorative incentive for patients. Designing of drug by computational method helped steady use of computational science to find, improve and study drugs as well as biologically related active molecules. The displaying examines like the structure-based plan; ligand-based drugs structure; database looking and restricting partiality dependent on the information of a biological target. In this article, we present the zones where CADD (computer aided drug design) devices uphold the medication disclosure measure.

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Suzuki, E., T. Akutsu, and S. Ohsuga. "Knowledge-based system for computer-aided drug design." Knowledge-Based Systems 6, no. 2 (1993): 114–26. http://dx.doi.org/10.1016/0950-7051(93)90026-p.

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Ejalonibu, Murtala A., Segun A. Ogundare, Ahmed A. Elrashedy, et al. "Drug Discovery for Mycobacterium tuberculosis Using Structure-Based Computer-Aided Drug Design Approach." International Journal of Molecular Sciences 22, no. 24 (2021): 13259. http://dx.doi.org/10.3390/ijms222413259.

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Developing new, more effective antibiotics against resistant Mycobacterium tuberculosis that inhibit its essential proteins is an appealing strategy for combating the global tuberculosis (TB) epidemic. Finding a compound that can target a particular cavity in a protein and interrupt its enzymatic activity is the crucial objective of drug design and discovery. Such a compound is then subjected to different tests, including clinical trials, to study its effectiveness against the pathogen in the host. In recent times, new techniques, which involve computational and analytical methods, enhanced the chances of drug development, as opposed to traditional drug design methods, which are laborious and time-consuming. The computational techniques in drug design have been improved with a new generation of software used to develop and optimize active compounds that can be used in future chemotherapeutic development to combat global tuberculosis resistance. This review provides an overview of the evolution of tuberculosis resistance, existing drug management, and the design of new anti-tuberculosis drugs developed based on the contributions of computational techniques. Also, we show an appraisal of available software and databases on computational drug design with an insight into the application of this software and databases in the development of anti-tubercular drugs. The review features a perspective involving machine learning, artificial intelligence, quantum computing, and CRISPR combination with available computational techniques as a prospective pathway to design new anti-tubercular drugs to combat resistant tuberculosis.

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Ugariogu, Sylvester Nnaemeka. "Natural Product Chemistry and Computer Aided Drug Design an Approach to Drug Discovery: A Review Article." International Journal of Pharmacognosy & Chinese Medicine 4, no. 3 (2020): 1–8. http://dx.doi.org/10.23880/ipcm-16000207.

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Natural products have been an inherent part of sustaining acculturation because of their medicinal properties. Past discoveries of bioactive natural products have relied on serendipity and accidental experience, and these compounds serve as inspiration for the generation of analogs with desired physicochemical properties. Bioactive natural products with therapeutic potential are abundantly available in nature and some of them are beyond exploration by conventional methods. However there has been a great breakthrough in the study of computer aided drug design (CADD) as many unfruitful lab researches have been averted and money, time and energies saved through CADD. Computer-aided drug design is a stimulating, arousing and manifold discipline where various aspects of applied and basic research integrate and induce each other. The empirical basis of CADD involves quantum mechanics and molecular modeling studies like structure based drug design; ligand-based drug design; database searching and binding affinity based on the knowledge of a biological target. In this present review we present the areas where natural product chemistry and CADD tools support drug discovery processes.

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Douguet, Dominique, Hélène Munier-Lehmann, Gilles Labesse, and Sylvie Pochet. "LEA3D: A Computer-Aided Ligand Design for Structure-Based Drug Design." Journal of Medicinal Chemistry 48, no. 7 (2005): 2457–68. http://dx.doi.org/10.1021/jm0492296.

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Yu, Wenye, and Zhenyu Chen. "Computer Aided Drug Design Based on Artificial Intelligence Algorithm." Journal of Physics: Conference Series 2066, no. 1 (2021): 012012. http://dx.doi.org/10.1088/1742-6596/2066/1/012012.

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Abstract The problems such as high cost and long development time in drug design and development have an important impact on its development, which makes many scholars devote themselves to looking for the auxiliary model of drug design. With the rapid development of computer technology, computer-aided drug molecular research model is more and more mature. This paper aims to study the computer-aided drug system based on artificial intelligence algorithm, so that researchers can speed up the process and reduce the cost when searching for specific protein molecules. In this paper, the principle of complementary matching in the docking process of target molecules and ligands, which is commonly used in drug design, is described, and the functional expression mode and various docking methods of molecular docking are studied. Finally, the research hotspots of molecular docking technology are analyzed, including scoring function, search strategy and flexible protein docking. Ant colony algorithm is introduced into molecular docking platform as a variant of conformation search algorithm, and a new plants algorithm is developed. Finally, the implementation of plants algorithm is analyzed in detail, and the optimized plants system and gold system based on genetic algorithm are simulated, and the relevant experimental data are counted. The simulation results show that the new drug design method based on ant colony algorithm has advantages in docking success rate, docking speed and docking accuracy. The success rate of plants is higher than that of gold, and the docking time is only 1/6 of that of gold.

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Thèses sur le sujet "Computer-based drug design"

Nomkoko, Thembelani Edmund. "Computer-aided chemical speciation in metal-based drug design." Doctoral thesis, University of Cape Town, 2002. http://hdl.handle.net/11427/21347.

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Formation constants of Cu²⁺, Ni²⁺, Zn²⁺, Ca²⁺ and Gd³⁺ with the polyamine(amide) ligands N,N' -bis(2-hydroxyiminopropionyl) propane-1,3-diamine (L² ) and (1, 15)- bis(N,N-dimethyl)-5, 11-dioxo-8-(N-benzyl)-l ,4,8, 12, 15-pentaazapentadecane (L³ ) as well as those of Gd³⁺ with 3,3,9,9-tetramethyl-4,8-diazaundecane-2,10-dione dioxime (L 1 ) were investigated by glass electrode potentiometry at 25°C and an ionic strength (I) of 0.15 mol dm-³.

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Kumari, Vandana. "Structure-Based Computer Aided Drug Design and Analysis for Different Disease Targets." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1311612599.

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Mahasenan, Kiran V. "Discovery of novel small molecule enzyme inhibitors and receptor modulators through structure-based computational design." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1332367560.

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Shi, Guqin. "Structure-based Computer-aided Drug Design and Analyses against Disease Target: Cytokine IL-6/IL-6R/GP130 Complex." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu151197172881965.

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ORSATO, ALEXANDRE. "Studies on tumor drug targeting." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19200.

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Tumor drug targeting is one of the most promising therapeutic strategies in oncology. The aim of this PhD work was the study of the essential features required for the assembly of tumor targeting conjugates.This work was focused on the deveploment of ligands for the GRP receptor that should function as carrier molecules for the targeting of tumor cells overexpressing this receptor. For this purpose, non-peptide GRP mimetics were designed, using a computer-based drug design technique, synthesized and tested. Two analogue compounds based on a bicyclic scaffold exerted an antagonist behaviour on the GRP receptor. Synthetic studies have been performed to optimize their production as well as biological tests to determine their potential as carrier molecules. Apart from the targeting moiety, we also studied the antineoplastic part of tumor targeting conjugates. Akt is a proto-oncogenic kinase that has been associated to cancer development. Therefore, the Akt inhibitory activity of phosphatidylinositol phosphate analogues was exploited. A small library of iminosugar-based phosphatidylinositol phosphate analogues was designed and synthesized. During the biological evaluation, target compounds displayed low to moderate inhibitory activity for Akt, which suggests their feasibility for the development of new and more potent Akt inhibitors.

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Lundborg, Magnus. "Computer-Assisted Carbohydrate Structural Studies and Drug Discovery." Doctoral thesis, Stockholms universitet, Institutionen för organisk kemi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-56411.

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Carbohydrates are abundant in nature and have functions ranging from energy storage to acting as structural components. Analysis of carbohydrate structures is important and can be used for, for instance, clinical diagnosis of diseases as well as in bacterial studies. The complexity of glycans makes it difficult to determine their structures. NMR spectroscopy is an advanced method that can be used to examine carbohydrates at the atomic level, but full assignments of the signals require much work. Reliable automation of this process would be of great help. Herein studies of Escherichia coli O-antigen polysaccharides are presented, both a structure determination by NMR and also research on glycosyltransferases which assemble the polysaccharides. The computer program CASPER has been improved to assist in carbohydrate studies and in the long run make it possible to automatically determine structures based only on NMR data. Detailed computer studies of glycans can shed light on their interactions with proteins and help find inhibitors to prevent unwanted binding. The WaaG glycosyltransferase is important for the formation of E. coli lipopolysaccharides. Molecular docking analyses of structures confirmed to bind this enzyme have provided information on how inhibitors could be composed. Noroviruses cause gastroenteritis, such as the winter vomiting disease, after binding human histo-blood group antigens. In one of the projects, fragment-based docking, followed by molecular dynamics simulations and binding free energy calculations, was used to find competitive binders to the P domain of the capsid of the norovirus VA387. These novel structures have high affinity and are a very good starting point for developing drugs against noroviruses. The protein targets in these two projects are carbohydrate binding, but the techniques are general and can be applied to other research projects.<br>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Submitted. Paper 5: Manuscript. Paper 6. Manuscript.

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Craan, Tobias Friedrich [Verfasser], and Gerhard [Akademischer Betreuer] Klebe. "Fragment based Drug Discovery : Design and Validation of a Fragment Library ; Computer-based Fragment Screening and Fragment-to-Lead Expansion / Tobias Friedrich Craan. Betreuer: Gerhard Klebe." Marburg : Philipps-Universität Marburg, 2011. http://d-nb.info/1013288807/34.

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Ward, D. J. "Further development of methods for the computer-aided design of neuropeptide-based drugs." Thesis, University of Manchester, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280534.

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Vankayala, Sai Lakshmana Kumar. "Computational Approaches for Structure Based Drug Design and Protein Structure-Function Prediction." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4601.

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This dissertation thesis consists of a series of chapters that are interwoven by solving interesting biological problems, employing various computational methodologies. These techniques provide meaningful physical insights to promote the scientific fields of interest. Focus of chapter 1 concerns, the importance of computational tools like docking studies in advancing structure based drug design processes. This chapter also addresses the prime concerns like scoring functions, sampling algorithms and flexible docking studies that hamper the docking successes. Information about the different kinds of flexible dockings in terms of accuracy, time limitations and success studies are presented. Later the importance of Induced fit docking studies was explained in comparison to traditional MD simulations to predict the absolute binding modes. Chapter 2 and 3 focuses on understanding, how sickle cell disease progresses through the production of sickled hemoglobin and its effects on sickle cell patients. And how, hydroxyurea, the only FDA approved treatment of sickle cell disease acts to subside sickle cell effects. It is believed the primary mechanism of action is associated with the pharmacological elevation of nitric oxide in the blood, however, the exact details of this mechanism is still unclear. HU interacts with oxy and deoxyHb resulting in slow NO production rates. However, this did not correlate with the observed increase of NO concentrations in patients undergoing HU therapy. The discrepancy can be attributed to the interaction of HU competing with other heme based enzymes such as catalase and peroxidases. In these two chapters, we investigate the atomic level details of this process using a combination of flexible-ligand / flexible-receptor virtual screening (i.e. induced fit docking, IFD) coupled with energetic analysis that decomposes interaction energies at the atomic level. Using these tools we were able to elucidate the previously unknown substrate binding modes of a series of hydroxyurea analogs to human hemoglobin, catalase and the concomitant structural changes of the enzymes. Our results are consistent with kinetic and EPR measurements of hydroxyurea-hemoglobin reactions and a full mechanism is proposed that offers new insights into possibly improving substrate binding and/or reactivity. Finally in chapter 4, we have developed a 3D bioactive structure of O6-alkylguanine-DNA alkyltransferase (AGT), a DNA repair protein using Monte Carlo conformational search process. It is known that AGT prevents DNA damage, mutations and apoptosis arising from alkylated guanines. Various Benzyl guanine analouges of O6- methylguanine were tested for activity as potential inhibitors. The nature and position of the substitutions methyl and aminomethyl profoundly affected their activity. Molecular modeling of their interactions with alkyltransferase provided a molecular explanation for these results. The square of the correlation coefﬁcient (R2 ) obtained between E-model scores (obtained from GLIDE XP/QPLD docking calculations) vs log(ED)values via a linear regression analysis was 0.96. The models indicate that the ortho-substitution causes a steric clash interfering with binding, whereas the meta-aminomethyl substitution allows an interaction of the amino group to generate an additional hydrogen bond with the protein. Using this model for virtually screening studies resulted in identification of seven lead compounds with novel scaffolds from National Cancer Institute Diversity Set2.

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Tripathi, Ashutosh. "DEVELOPMENT OF HINT BASED COMPUTATIONAL TOOLS FOR DRUG DESIGN: APPLICATIONS IN THE DESIGN AND DEVELOPMENT OF NOVEL ANTI-CANCER AGENTS." VCU Scholars Compass, 2009. http://scholarscompass.vcu.edu/etd/1866.

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The overall aim of the research is to develop a computational platform based on HINT paradigm for manipulating, predicting and analyzing biomacromolecular-ligand structure. A second synergistic goal is to apply the above methodology to design novel and potent anti-cancer agents. The crucial role of the microtubule in cell division has identified tubulin as an interesting target for the development of therapeutics for cancer. Pyrrole-containing molecules derived from nature have proven to be particularly useful as lead compounds for drug development. We have designed and developed a series of substituted pyrroles that inhibit growth and promote death of breast tumor cells at nM and μM concentrations in human breast tumor cell lines. In another project, stilbene analogs were designed and developed as microtubule depolymerizing agents that showed anti-leukemic activity. A molecular modeling study was carried out to accurately represent the complex structure and the binding mode of a new class of tubulin inhibitors that bind at the αβ-tubulin colchicine site. These studies coupled with HINT interaction analyses were able to describe the complex structure and the binding modes of inhibitors. Qualitative analyses of the results showed general agreement with the experimental in vitro biological activity for these derivatives. Consequently, we have been designing new analogs that can be synthesized and tested; we believe that these molecules will be highly selective against cancer cells with minimal toxicity to the host tissue. Another goal of our research is to develop computational tools for drug design. The development and implementation of a novel cavity detection algorithm is also reported and discussed. The algorithm named VICE (Vectorial Identification of Cavity Extents) utilizes HINT toolkit functions to identify and delineate a binding pocket in a protein. The program is based on geometric criteria and applies simple integer grid maps to delineate binding sites. The algorithm was extensively tested on a diverse set of proteins and detects binding pockets of different shapes and sizes. The study also implemented the computational titration algorithm to understand the complexity of ligand binding and protonation state in the active site of HIV-1 protease. The Computational titration algorithm is a powerful tool for understanding ligand binding in a complex biochemical environment and allows generating hypothesis on the best model for binding.

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Livres sur le sujet "Computer-based drug design"

Du, Qishi. Developments in structure-based theoretical modeling of hydrophobicity for computer-aided drug design. Laurentian University Press, 1995.

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W, Codding Penelope, North Atlantic Treaty Organization. Scientific Affairs Division., and NATO Advanced Study Institute on Experimental and Computational Approaches to Structure-Based Drug Design (1996 : Erice, Italy), eds. Structure-based drug design: Experimental and computational approaches. Kluwer Academic Publishers, 1998.

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Harren, Jhoti, and Leach Andrew R, eds. Structure-based drug discovery. Springer, 2007.

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Computer Aided Drug Design (CADD): From Ligand-Based Methods to Structure-Based Approaches. Elsevier, 2022. http://dx.doi.org/10.1016/c2020-0-04039-9.

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Poroikov, Vladimir, and Roman Efremov, eds. PROCEEDINGS BOOK OF THE XXVIII SYMPOSIUM "BIOINFORMATICS AND COMPUTER-AIDED DRUG DISCOVERY", MOSCOW, 2022. Institute of Biomedical Chemistry, Moscow, Russia, 2022. http://dx.doi.org/10.18097/bcadd2022.

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The materials of the XXVIII Symposium "Bioinformatics and Computer-Aided Drug Discovery" are presented. This Symposium is dedicated to the emerging challenges and opportunities for in silico drug discovery.The Symposium's main topics: development and practical application of computational methods for finding and validation of new pharmacological targets, in silico design of potent and safe pharmaceutical agents, optimization of the structure and properties of drug-like compounds, rational approaches to the utilization of pharmacotherapeutic remedies in medical practice. This information will be useful for researchers whose investigations are dedicated to creating computational methods and their application to drug research and development using bio- and chemoinformatics methods based on post-genomic technologies. It can also be useful for undergraduate, graduate, and postgraduate students specializing in the relevant fields.

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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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(Editor), Harren Jhoti, and Andrew R. Leach (Editor), eds. Structure-based Drug Discovery. Springer, 2007.

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R, Leach· Andrew, and Harren Jhoti. Structure-based Drug Discovery. Springer, 2010.

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Chapitres de livres sur le sujet "Computer-based drug design"

Loftus, Philip, Marvin Waldman, and Robert F. Hout. "Computer-Based Approaches to Drug Design." In Drug Discovery and Development. Humana Press, 1987. http://dx.doi.org/10.1007/978-1-4612-4828-6_3.

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Hawkins, Paul C. D., and Gunther Stahl. "Ligand-Based Methods in GPCR Computer-Aided Drug Design." In Methods in Molecular Biology. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7465-8_18.

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Andrianov, A. M., I. A. Kashyn, and A. V. Tuzikov. "Computer-Based Technologies for Virtual Screening and Analysis of Chemical Compounds Promising for Anti-HIV-1 Drug Design." In Communications in Computer and Information Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54220-1_2.

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Agnihotry, Shikha, Rajesh Kumar Pathak, Ajeet Srivastav, Pradeep Kumar Shukla, and Budhayash Gautam. "Molecular Docking and Structure-Based Drug Design." In Computer-Aided Drug Design. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6815-2_6.

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Gubernator, K., C. Broger, D. Bur, et al. "Structure-Based Ligand Design." In Computer Aided Drug Design in Industrial Research. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03141-4_4.

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Droschinsky, Andre, Lina Humbeck, Oliver Koch, Nils M. Kriege, Petra Mutzel, and Till Schäfer. "Graph-Based Methods for Rational Drug Design." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-21534-6_5.

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AbstractRational drug design deals with computational methods to accelerate the development of new drugs. Among other tasks, it is necessary to analyze huge databases of small molecules. Since a direct relationship between the structure of these molecules and their effect (e.g., toxicity) can be assumed in many cases, a wide set of methods is based on the modeling of the molecules as graphs with attributes.Here, we discuss our results concerning structural molecular similarity searches and molecular clustering and put them into the wider context of graph similarity search. In particular, we discuss algorithms for computing graph similarity w.r.t. maximum common subgraphs and their extension to domain specific requirements.

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Sessa, Lucia, Luigi Di Biasi, Simona Concilio, and Stefano Piotto. "Fragment Based Molecular Dynamics for Drug Design." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78658-2_4.

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Tollenaere, J. P. "The Role of Structure-Based Ligand Design in Industrial Pharmaceutical Research." In Computer Aided Drug Design in Industrial Research. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03141-4_10.

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Bodor, Nicholas, and Ming-Ju Huang. "Computer-Aided Design of New Drugs Based on Retrometabolic Concepts." In ACS Symposium Series. American Chemical Society, 1995. http://dx.doi.org/10.1021/bk-1995-0589.ch007.

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Raina, Neha, Amit Kumar Singh, and Asimul Islam. "Biological Implications of Polyethylene Glycol and PEGylation: Therapeutic Approaches Based on Biophysical Studies and Protein Structure-Based Drug Design Tools." In Innovations and Implementations of Computer Aided Drug Discovery Strategies in Rational Drug Design. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8936-2_11.

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Actes de conférences sur le sujet "Computer-based drug design"

Recio, Rocío, Elena Benito, Victoria Valdivia, et al. "COMPUTER ASSISTED DRUG DESIGN BY USING PROBLEM BASED LEARNING METHODOLOGIES." In 10th annual International Conference of Education, Research and Innovation. IATED, 2017. http://dx.doi.org/10.21125/iceri.2017.1444.

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Santos, Beatriz P., Maryam Abbasi, Tiago Pereira, Bernardete Ribeiro, and Joel P. Arrais. "Optimizing Recurrent Neural Network Architectures for De Novo Drug Design." In 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2021. http://dx.doi.org/10.1109/cbms52027.2021.00067.

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Scheiner, Stefan, Peter Pivonka, David W. Smith, and Colin R. Dunstan. "Computer Simulation-Based Modeling of the Pharmaceutical Intervention of Postmenopausal Osteoporosis by Denosumab." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82990.

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Postmenopausal osteoporosis (PMO), leading to a higher bone fracture risk, is characterized by a significantly increasing bone porosity. Recently, denosumab, which is able to efficiently interfere with bone resorption, has been approved for the treatment of PMO. In order to optimize the design of drug administration regimes, we propose a computational methodology, based on mechanistic mathematical modeling of bone remodeling, considering the governing biochemical and biomechanical regulation mechanisms, and the targeted action of denosumab. The time-dependent serum concentration of denosumab, obtained from a pharmacokinetics model, is fed into a bone cell population model, allowing for prediction of porosity evolution in PMO patients. In order to account for the mechanobiology of bone remodeling, we utilize the concept of continuum micromechanics, which accurately provides the actual (microscopic) strain state of the investigated bone. Finally, different drug administration regimes are simulated, and their effect on the bone microarchitecture is discussed.

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Gu, Chunyu, Kiran V. Mahasenan, Tyler Auvil, et al. "Abstract 3298: Structure-based computer-aided drug design to discover novel small molecules that target brain tumor stem cells." In Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/1538-7445.am2011-3298.

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Hsu, Yung Chang, Hui-Yi Shiao, Yi-Yu Ke, et al. "Abstract 2530: Optimization of 5,6-fused pyrimidine-based kinase inhibitors by computer-aided drug design for the treatment of AML." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-2530.

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Zha, Xuan F., Ram D. Sriram, and Satyandra K. Gupta. "Information and Knowledge Modeling for Computer Supported Micro Electro-Mechanical Systems Design and Development." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85607.

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In this paper, we present a preliminary research effort towards an effective computer support environment for the design and development of micro-electro-mechanical systems (MEMS). We first identify the characteristics of MEMS product design and development processes and examine the state-of-the-art of MEMS CAD and simulation systems. We then propose a function-(environment-effect)-behavior-(principle-state)-form (FEEBPSF) framework based on the NIST core product model and its extensions for modeling MEMS products, and apply the OESM (open embedded system model) developed to model information and knowledge for embedded MEMS design and development. Moreover, in order to tackle the knowledge-intensive tasks of design and development for MEMS products, we develop a general and flexible knowledge repository, called KR-MEMS, based on the FEEBPSF framework and the UML/XML model, and integrate KR-MEMS into a web-based MEMS design support system. Throughout the paper, a micro fluidic dispensing device (a biomedical device for drug-delivery) is used as an example to illustrate the concepts, models, and knowledge bases necessary to support the MEMS product design and development.

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Chou, Ting-Chao. "Abstract CT155: General pharmacodynamics algorithm-based clinical protocol design with two to three dose-data points for single-drug, and ten data points for two-drug-combination synergy quantification, using computer simulation for digitalized data analysis and conclusions." In Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-ct155.

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Iqbal, Liaquat U., Gautam S. Naik, Daniel Pothala, Phani Kiran Surapaneni, Fu Zhao, and John P. Sullivan. "Environmentally Conscious Wing Design for the Medium Altitude Long Endurance Unmanned Aerial Vehicle." In ASME 2009 International Manufacturing Science and Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/msec2009-84292.

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The use of Unmanned Aerial Vehicles (UAVs) has become widespread and is ever increasing. There are plans for utilizing the UAVs for the military as well as the humanitarian and law enforcement missions such as flood and hurricane relief, firefighting, drug trafficking control, and so on. The number of UAVs is likely to continue to grow exponentially in the near future and there is a great need for the environmentally conscious design and manufacturing efforts in the UAV market. The authors are developing an integrated approach to bring the high fidelity Computer Aided Design and Engineering (CAD/E) tools to the preliminary design phase for designing new aircraft. In this paper, this approach is extended to include the environmentally conscious material selection when designing a UAV wing for the medium altitude long endurance mission. Finite Element Analysis is used to determine the material needed for the wing and the computed weights are supplied to the spreadsheet for calculating environmental impacts of different materials selected for the wing design. This spreadsheet has been developed based on the data in the Lifecycle Assessment software package SimaPro/Ecoinvent. The study demonstrates how to integrate environmental considerations into the preliminary UAV design using high fidelity models.

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"Deep Belief Networks for Ligand-Based Virtual Screening of Drug Design." In 2016 the 6th International Workshop on Computer Science and Engineering. WCSE, 2016. http://dx.doi.org/10.18178/wcse.2016.06.115.

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Hossain, A. T. M. Mosharof, Nazia Hasan Tuktuki, Hasibul Kabir, and Rajesh Palit. "Design and Development of a Mobile Application Based Drug Requisition System." In 2016 IEEE International Conference on Computer and Information Technology (CIT). IEEE, 2016. http://dx.doi.org/10.1109/cit.2016.113.

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