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Journal articles on the topic 'Drug design'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

James, Keith. "Drug design." Nature 359, no. 6394 (1992): 458. http://dx.doi.org/10.1038/359458a0.

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2

Garepally, Prasad, Swathi Goli, and Vijay Kumar Bontha. "Design, Development and Characterizations of Acyclovir Osmotic Tablets." Pharmaceutics and Pharmacology Research 1, no. 1 (2018): 01–14. http://dx.doi.org/10.31579/2693-7247/005.

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Oral drug delivery is the most widely utilized route of administration, among all the routes of administration. That has been explored for the systemic delivery drug through different pharmaceutical dosage forms. It can be said that at least 90%of all drugs used to produce systemic effect is by oral route. Conventional oral drug delivery systems are known to provide an immediate release of drug, in which one cannot control the release of the drug and effective concentration at the target site.

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3

Takayanagl, Issei. "Drug receptors and drug design." Japanese Journal of Pharmacology 67 (1995): 45. http://dx.doi.org/10.1016/s0021-5198(19)46150-7.

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4

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

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5

Buchwald, Peter. "Computer-aided retrometabolic drug design: soft drugs." Expert Opinion on Drug Discovery 2, no. 7 (2007): 923–33. http://dx.doi.org/10.1517/17460441.2.7.923.

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6

Walsh, John S., and Gerald T. Miwa. "Bioactivation of Drugs: Risk and Drug Design." Annual Review of Pharmacology and Toxicology 51, no. 1 (2011): 145–67. http://dx.doi.org/10.1146/annurev-pharmtox-010510-100514.

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7

Takayanagi, Issei. "Drug receptor mechanisms and drug design." Japanese Journal of Pharmacology 73 (1997): 4. http://dx.doi.org/10.1016/s0021-5198(19)33785-0.

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8

Cooper, Kelvin. "Drug-receptor interactions and drug design." Trends in Pharmacological Sciences 9, no. 2 (1988): 51. http://dx.doi.org/10.1016/0165-6147(88)90115-0.

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9

Barakat, Khaled H., Michael Houghton, D. Lorne Tyrrel, and Jack A. Tuszynski. "Rational Drug Design." International Journal of Computational Models and Algorithms in Medicine 4, no. 1 (2014): 59–85. http://dx.doi.org/10.4018/ijcmam.2014010104.

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For the past three decades rationale drug design (RDD) has been developing as an innovative, rapid and successful way to discover new drug candidates. Many strategies have been followed and several targets with diverse structures and different biological roles have been investigated. Despite the variety of computational tools available, one can broadly divide them into two major classes that can be adopted either separately or in combination. The first class involves structure-based drug design, when the target's 3-dimensional structure is available or it can be computationally generated using

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10

Cohen, F. E. "Structural Drug Design." Science 261, no. 5122 (1993): 773. http://dx.doi.org/10.1126/science.261.5122.773.

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11

Lorber, David M. "Computational drug design." Chemistry & Biology 6, no. 8 (1999): R227—R228. http://dx.doi.org/10.1016/s1074-5521(99)80093-3.

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12

Häyry, Pekka. "Rational drug design." Transplant Immunology 9, no. 2-4 (2002): 201. http://dx.doi.org/10.1016/s0966-3274(02)00018-7.

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13

J. Wilson, Lon, Dawson W. Cagle, Thomas P. Thrash, et al. "Metallofullerene drug design." Coordination Chemistry Reviews 190-192 (September 1999): 199–207. http://dx.doi.org/10.1016/s0010-8545(99)00080-6.

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14

Häyry, P., D. du Toit, M. Sarwal, E. Aavik, A. Hoffrén, and J. Vamvakopoulos. "Rational drug design:." Transplantation Proceedings 34, no. 6 (2002): 2000–2002. http://dx.doi.org/10.1016/s0041-1345(02)02829-4.

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15

Hart, D., A. Langridge, D. Barlow, and B. Sutton. "Antiparasitic drug design." Parasitology Today 5, no. 4 (1989): 117–20. http://dx.doi.org/10.1016/0169-4758(89)90054-9.

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16

Mandal, Soma, Mee'nal Moudgil, and Sanat K. Mandal. "Rational drug design." European Journal of Pharmacology 625, no. 1-3 (2009): 90–100. http://dx.doi.org/10.1016/j.ejphar.2009.06.065.

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17

陈, 米佳. "Research on Interactive Drug Packaging Design for the Elderly." Design 08, no. 03 (2023): 1735–42. http://dx.doi.org/10.12677/design.2023.83209.

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18

Gupta, Satya Prakash. "Roles of Fluorine in Drug Design and Drug Action." Letters in Drug Design & Discovery 16, no. 10 (2019): 1089–109. http://dx.doi.org/10.2174/1570180816666190130154726.

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The article discusses the basic properties of fluorine atom that have made it so useful in drug development. It presents several examples of therapeutically useful drugs acting against many life-threatening diseases along with the mechanism as to how fluorine influences the drug activity. It has been pointed out that fluorine, due to its ability to increase the lipophilicity of the molecule, greatly affects the hydrophobic interaction between the drug molecule and the receptor. Because of its small size, it hardly produces any steric effect, rather due to electronic properties enters into elec

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19

Prasad, G., K. Devika, P. Varshith, B. Shravani, E. Pavithra, and Ch Swathi. "Design and Optimizations of Aceclofenac Bioadhesive Extended Release Microspheres." Pharmaceutics and Pharmacology Research 4, no. 4 (2021): 01–15. http://dx.doi.org/10.31579/2693-7247/055.

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The oral route for drug delivery is the most popular, desirable, and most preferred method for administrating therapeutically agents for systemic effects because it is a natural, convenient, and cost effective to manufacturing process. Oral route is the most commonly used route for drug administration. Although different route of administration are used for the delivery of drugs, oral route remain the preferred mode. Even for sustained release systems the oral route of administration has been investigated the most because of flexibility in designing dosage forms. Present controlled release dru

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20

K., Rekha Rani* R. Mohana Priya G. Bhagya Buela. "DESIGN AND CHARACTERIZATION OF VORICONAZOLE MICROSPHERES." IAJPS,CSK PUBLICATIONS 03, no. 10 (2016): 1172–81. https://doi.org/10.5281/zenodo.164928.

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The objective of the presentreserach work was to formulate bioadhesive microspheres of Voriconazole using different polymers Eudragit RS 100, Ethyl Celulose, Sodium alginate were formulated to deliver Voriconazole via oral route.Increase in the polymer concentration led to increase in % Yield, % Drug entrapment efficiency, Particle size. The invitro drug release decreased with increase in the polymer.Analysis of drug release mechanism showed that the drug release from the formulations followed diffusion and the best fit model was found to be Korsmeyer-Peppas.FT-IR studies were carried out to f

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21

Doytchinova, Irini. "Drug Design—Past, Present, Future." Molecules 27, no. 5 (2022): 1496. http://dx.doi.org/10.3390/molecules27051496.

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Drug design is a complex pharmaceutical science with a long history. Many achievements have been made in the field of drug design since the end of 19th century, when Emil Fisher suggested that the drug–receptor interaction resembles the key and lock interplay. Gradually, drug design has been transformed into a coherent and well-organized science with a solid theoretical background and practical applications. Now, drug design is the most advanced approach for drug discovery. It utilizes the innovations in science and technology and includes them in its wide-ranging arsenal of methods and tools

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22

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 high

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23

Borisov, D. V., and A. V. Veselovsky. "Ligand-receptor binding kinetics in drug design." Biomeditsinskaya Khimiya 66, no. 1 (2020): 42–53. http://dx.doi.org/10.18097/pbmc20206601042.

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Traditionally, the thermodynamic values of affinity are considered as the main criterion for the development of new drugs. Usually, these values for drugs are measured in vitro at steady concentrations of the receptor and ligand, which are differed from in vivo environment. Recent studies have shown that the kinetics of the process of drug binding to its receptor make significant contribution in the drug effectiveness. This has increased attention in characterizing and predicting the rate constants of association and dissociation of the receptor ligand at the stage of preclinical studies of dr

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24

Pareek, Varun, Lakshya Tuteja, Lokendra Sharma, Susheel Kumar, and Noopur Verma. "Revolutionizing Drug Design with Artificial Intelligence: A Comprehensive Review of Techniques, Applications, and Case Studies." Journal of Pharmaceutical Research 22, no. 3 (2023): 103–12. http://dx.doi.org/10.18579/jopcr/v22.3.23.54.

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Introduction: Artificial intelligence (AI) has the potential to revolutionize drug design and discovery by significantly reducing the time and costs involved in developing new drugs. This literature review aims to explore the use of AI in drug design, focusing on virtual screening, de novo drug design, and prediction of ADME properties. Objective: The objective of this review is to provide an overview of the AI techniques used in drug design and their applications in virtual screening, de novo drug design, and prediction of ADME properties. The review also aims to summarize the advantages and

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25

Narkhede, Jagruti. "Artificial Intelligence in Drug Discovery and Drug Design." International Journal of Pharmaceutical Research and Applications 09, no. 05 (2024): 640–55. https://doi.org/10.35629/4494-0905640655.

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Overthepasttenyears,artificialintelligencehasrevolut ionisedthefieldofdrugresearch. The process for discovering new drugs could be completelytransformed by artificial intelligence, which could provide increased speed, accuracy, and efficiency. The process for discovering new drugs could be completely transformed by artificial intelligence, which could provide increased speed, accuracy, and efficiency. Numerous uses of artificial intelligence, including virtual screening and drug design, have been employed in drug development. AI methods are brokendown into learning paradigms and modelarchitect

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26

Gibson, D. "Drug–DNA interactions and novel drug design." Pharmacogenomics Journal 2, no. 5 (2002): 275–76. http://dx.doi.org/10.1038/sj.tpj.6500133.

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27

Ranade, Vasant V. "Drug Metabolism in Drug Design and Development." American Journal of Therapeutics 16, no. 5 (2009): 467. http://dx.doi.org/10.1097/mjt.0b013e3181728805.

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28

Prokai, Laszlo, and Katalin Prokai-Tatrai. "Metabolism-based drug design and drug targeting." Pharmaceutical Science & Technology Today 2, no. 11 (1999): 457–62. http://dx.doi.org/10.1016/s1461-5347(99)00208-4.

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29

Mihai, Dragos Paul, and George Mihai Nitulescu. "Computer-Aided Drug Design and Drug Discovery." Pharmaceuticals 18, no. 3 (2025): 436. https://doi.org/10.3390/ph18030436.

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30

Xu, Zishuo. "Research on targeted drug design based on computer technology." E3S Web of Conferences 553 (2024): 04013. http://dx.doi.org/10.1051/e3sconf/202455304013.

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This paper provides an insight into the importance and application of computer-aided drug design in today’s drug discovery and development. With the development of medicinal chemistry, molecular biology and proteomics, the synthesis and extraction pathways of many common drugs have been computer-assisted, which helps to optimize the reaction conditions, reduce the generation of waste and hazardous substances, and promote green synthesis and sustainable development. Scientists have conducted in-depth research on the pathogenesis of various diseases, especially in the field of oncology, where si

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31

Zishan Ibrahim, Mohammad. "Review on Design of liposome’s as drug delivery system." Pharmacy and Drug Development 1, no. 2 (2022): 01–04. http://dx.doi.org/10.58489/2836-2322/010.

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Liposomes wasinitially described by the British haematologist Dr. Alec D. Bangham and collaborators at the University of Cambridge in the 1960s and the first report was publicized in 1964.Liposomes are a form of vesicles that consist of many, few or just one phospholipid bilayer. The polar character of the liposomal core allow polar drug molecules to be capsulize. Amphiphilic (both hydrophilic and hydrophobic) and lipophilic molecules are solubilised within the phospholipid bilayer according to their affinity towards phospholipids.

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32

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 resea

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33

Rother, Kristian, Mathias Dunkel, Elke Michalsky, et al. "A structural keystone for drug design." Journal of Integrative Bioinformatics 3, no. 1 (2006): 21–31. http://dx.doi.org/10.1515/jib-2006-19.

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Abstract 3D-structures of proteins and potential ligands are the cornerstones of rational drug design. The first brick to build upon is selecting a protein target and finding out whether biologically active compounds are known. Both tasks require more information than the structures themselves provide. For this purpose we have built a web resource bridging protein and ligand databases. It consists of three parts: i) A data warehouse on annotation of protein structures that integrates many well-known databases such as Swiss-Prot, SCOP, ENZYME and others. ii) A conformational library of structur

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34

De, Baishakhi, Koushik Bhandari, Francisco J. B. Mendonça, Marcus T. Scotti, and Luciana Scotti. "Computational Studies in Drug Design Against Cancer." Anti-Cancer Agents in Medicinal Chemistry 19, no. 5 (2019): 587–91. http://dx.doi.org/10.2174/1871520618666180911125700.

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Background: The application of in silico tools in the development of anti cancer drugs. Objective: The summing of different computer aided drug design approaches that have been applied in the development of anti cancer drugs. Methods: Structure based, ligand based, hybrid protein-ligand pharmacophore methods, Homology modeling, molecular docking aids in different steps of drug discovery pipeline with considerable saving in time and expenditure. In silico tools also find applications in the domain of cancer drug development. Results: Structure-based pharmacophore modeling aided in the identific

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35

Zhang, Changsheng, and Luhua Lai. "Towards structure-based protein drug design." Biochemical Society Transactions 39, no. 5 (2011): 1382–86. http://dx.doi.org/10.1042/bst0391382.

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Structure-based drug design for chemical molecules has been widely used in drug discovery in the last 30 years. Many successful applications have been reported, especially in the field of virtual screening based on molecular docking. Recently, there has been much progress in fragment-based as well as de novo drug discovery. As many protein–protein interactions can be used as key targets for drug design, one of the solutions is to design protein drugs based directly on the protein complexes or the target structure. Compared with protein–ligand interactions, protein–protein interactions are more

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36

Sharma, Vikas. "Kinase Inhibitors In Drug-design, Drug-discovery, and Drug-delivery." Current Medicinal Chemistry 30, no. 13 (2023): 1463. http://dx.doi.org/10.2174/092986733013230112163412.

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37

Gozes, Illana, and Sharon Furman. "VIP and Drug Design." Current Pharmaceutical Design 9, no. 6 (2003): 483–94. http://dx.doi.org/10.2174/1381612033391667.

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38

Schiavone, N., M. Donnini, A. Nicolin, and S. Capaccioli. "Antisense Oligonucleotide Drug Design." Current Pharmaceutical Design 10, no. 7 (2004): 769–84. http://dx.doi.org/10.2174/1381612043452956.

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39

Kamiya, Kotaro, and Daitaro Misawa. "AI-based drug design." Japanese Journal of Pesticide Science 47, no. 2 (2022): 109–12. http://dx.doi.org/10.1584/jpestics.w22-33.

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40

SAITO, Isao. "DNA-Targeting Drug Design." Journal of Pesticide Science 25, no. 3 (2000): 270–74. http://dx.doi.org/10.1584/jpestics.25.270.

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41

Marshall, G. R. "Computer-Aided Drug Design." Annual Review of Pharmacology and Toxicology 27, no. 1 (1987): 193–213. http://dx.doi.org/10.1146/annurev.pa.27.040187.001205.

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42

Jain, A. "Computer aided drug design." Journal of Physics: Conference Series 884 (August 2017): 012072. http://dx.doi.org/10.1088/1742-6596/884/1/012072.

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43

Watson, Dr K. A. "COMPUTERS IN DRUG DESIGN." Biochemical Society Transactions 27, no. 3 (1999): A90. http://dx.doi.org/10.1042/bst027a090c.

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44

Hodgson, John. "Data-Directed Drug Design." Nature Biotechnology 9, no. 1 (1991): 19–21. http://dx.doi.org/10.1038/nbt0191-19.

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45

Chin, G. "BIOCHEMISTRY: Bacterial Drug Design." Science 316, no. 5832 (2007): 1670c. http://dx.doi.org/10.1126/science.316.5832.1670c.

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46

Dowty, Martin E., George Hu, Fengmei Hua, F. Barclay Shilliday, and Heather V. Dowty. "Drug Design Structural Alert." International Journal of Toxicology 30, no. 5 (2011): 546–50. http://dx.doi.org/10.1177/1091581811413833.

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In the process of drug design, it is important to consider potential structural alerts that may lead to toxicosis. This work illustrates how using trifluoroethane as a part of a novel chemical entity led to cytochrome P450 – mediated N-dealkylation and the formation of trifluoroacetaldehyde, a known testicular toxicant, in exploratory safety studies in rats. Testicular toxicosis was noted microscopically in a dose-dependent manner as measured by testicular spermatocytic degeneration and necrosis and excessive intratubular cellular debris in the epididymis. This apparent toxic effect correlated

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47

Amzel, L. Mario. "Structure-based drug design." Current Opinion in Biotechnology 9, no. 4 (1998): 366–69. http://dx.doi.org/10.1016/s0958-1669(98)80009-8.

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48

Stepan, Antonia F., Vincent Mascitti, Kevin Beaumont, and Amit S. Kalgutkar. "Metabolism-guided drug design." MedChemComm 4, no. 4 (2013): 631. http://dx.doi.org/10.1039/c2md20317k.

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49

Johnson, L. N. "Structure based drug design." Acta Crystallographica Section A Foundations of Crystallography 49, s1 (1993): c4. http://dx.doi.org/10.1107/s0108767378099882.

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Zhang, Weilin, Jianfeng Pei, and Luhua Lai. "Computational Multitarget Drug Design." Journal of Chemical Information and Modeling 57, no. 3 (2017): 403–12. http://dx.doi.org/10.1021/acs.jcim.6b00491.

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