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Journal articles on the topic 'Structure drug design'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

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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2

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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3

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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4

HENRY, CELIA M. "STRUCTURE-BASED DRUG DESIGN." Chemical & Engineering News 79, no. 23 (2001): 69–78. http://dx.doi.org/10.1021/cen-v079n023.p069.

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5

Colman, Peter M. "Structure-based drug design." Current Opinion in Structural Biology 4, no. 6 (1994): 868–74. http://dx.doi.org/10.1016/0959-440x(94)90268-2.

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6

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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7

Nishigaya, Yuki, Tadashi Satoh, Yoshiki Tanaka, and Simon Miller. "Agrochemical structure-based drug design." Japanese Journal of Pesticide Science 48, no. 2 (2023): 159–64. http://dx.doi.org/10.1584/jpestics.w23-36.

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8

Whittle, P. J., and T. L. Blundell. "Protein Structure-Based Drug Design." Annual Review of Biophysics and Biomolecular Structure 23, no. 1 (1994): 349–75. http://dx.doi.org/10.1146/annurev.bb.23.060194.002025.

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9

Blundell, T. L. "Protein structure and drug design." Journal of Molecular Graphics 11, no. 4 (1993): 265. http://dx.doi.org/10.1016/0263-7855(93)80024-l.

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10

Flight, Monica Hoyos. "Drug Discovery: Structure-led design." Nature 502, no. 7471 (2013): S50—S52. http://dx.doi.org/10.1038/502s50a.

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11

Fesik, StephenW. "NMR structure-based drug design." Journal of Biomolecular NMR 3, no. 3 (1993): 261–69. http://dx.doi.org/10.1007/bf00212513.

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12

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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13

Cheng, Yuexuan, Chunhong Zhong, Shujing Yan, Chunli Chen, and Xiaoli Gao. "Structure modification: a successful tool for prodrug design." Future Medicinal Chemistry 15, no. 4 (2023): 379–93. http://dx.doi.org/10.4155/fmc-2022-0309.

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Prodrug strategy is critical for innovative drug development. Structural modification is the most straightforward and effective method to develop prodrugs. Improving drug defects and optimizing the physical and chemical properties of a drug, such as lipophilicity and water solubility, changing the way of administration can be achieved through specific structural modification. Designing prodrugs by linking microenvironment-responsive groups to the prototype drugs is of great help in enhancing drug targeting. In the meantime, making connections between prodrugs and suitable drug delivery systems

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14

Sun, Hao, and Dennis O. Scott. "Structure-based Drug Metabolism Predictions for Drug Design." Chemical Biology & Drug Design 75, no. 1 (2010): 3–17. http://dx.doi.org/10.1111/j.1747-0285.2009.00899.x.

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15

Takeda-Shitaka, Mayuko, Daisuke Takaya, Chieko Chiba, Hirokazu Tanaka, and Hideaki Umeyama. "Protein Structure Prediction in Structure Based Drug Design." Current Medicinal Chemistry 11, no. 5 (2004): 551–58. http://dx.doi.org/10.2174/0929867043455837.

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16

Jadhav, Anita. "Drug Design - A Review." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 7582–89. https://doi.org/10.22214/ijraset.2025.71942.

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Pharmaceutical drug discovery is an expensive and time consuming process.The development of a drug from an initial idea to its entry into the market is a very complex process which can take around 5-10 yrs. and cost is very high upto billion. It is an development process involves use of variety of computational techniques ,such as structure activity relationship ,quantitative structure activity relationship ,molecular mechanics ,quantam mechanics, molecular dynamics and drug protein docking. The idea for a new development can come from a variety of sources which include the current necessities

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17

&NA;. "NOS structure will guide drug design." Inpharma Weekly &NA;, no. 1115 (1997): 9. http://dx.doi.org/10.2165/00128413-199711150-00016.

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18

Liang, Zhongjie, and Guang Hu. "Protein Structure Network-based Drug Design." Mini-Reviews in Medicinal Chemistry 16, no. 16 (2016): 1330–43. http://dx.doi.org/10.2174/1389557516999160612163350.

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19

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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20

Carneiro, Marta G., Eiso AB, Stephan Theisgen, and Gregg Siegal. "NMR in structure-based drug design." Essays in Biochemistry 61, no. 5 (2017): 485–93. http://dx.doi.org/10.1042/ebc20170037.

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NMR spectroscopy is a powerful technique that can provide valuable structural information for drug discovery endeavors. Here, we discuss the strengths (and limitations) of NMR applications to structure-based drug discovery, highlighting the different levels of resolution and throughput obtainable. Additionally, the emerging field of paramagnetic NMR in drug discovery and recent developments in approaches to speed up and automate protein-observed NMR data collection and analysis are discussed.

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21

Schaffhausen, Joanna. "Advances in structure-based drug design." Trends in Pharmacological Sciences 33, no. 5 (2012): 223. http://dx.doi.org/10.1016/j.tips.2012.03.011.

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22

Guida, Wayne C. "Software for structure-based drug design." Current Opinion in Structural Biology 4, no. 5 (1994): 777–81. http://dx.doi.org/10.1016/s0959-440x(94)90179-1.

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23

Wade, Rebecca C. "‘Flu’ and structure-based drug design." Structure 5, no. 9 (1997): 1139–45. http://dx.doi.org/10.1016/s0969-2126(97)00265-7.

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24

MONTGOMERY, J. A., and S. NIWAS. "ChemInform Abstract: Structure-Based Drug Design." ChemInform 25, no. 8 (2010): no. http://dx.doi.org/10.1002/chin.199408333.

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25

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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26

Wang, Xin, Ke Song, Li Li, and Lijiang Chen. "Structure-Based Drug Design Strategies and Challenges." Current Topics in Medicinal Chemistry 18, no. 12 (2018): 998–1006. http://dx.doi.org/10.2174/1568026618666180813152921.

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Over the past ten years, the number of three-dimensional protein structures identified by advanced science and technology increases, and the gene information becomes more available than ever before as well. The development of computing science becomes another driving force which makes it possible to use computational methods effectively in various phases of the drug design and research. Now Structure-Based Drug Design (SBDD) tools are widely used to help researchers to predict the position of small molecules within a three-dimensional representation of the protein structure and estimate the af

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27

Gemma, Sandra. "Structure-Based Design of Biologically Active Compounds." Molecules 25, no. 14 (2020): 3115. http://dx.doi.org/10.3390/molecules25143115.

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The past decades have witnessed tremendous progress in the detailed structural knowledge of proteins as potential or validated drug targets and the discovery of new drugs based on this wealth of knowledge progressed in parallel [...]

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Mano, Erica Candido Costa, Ana Ligia Scott, and Kathia M. Honorio. "UDP-glucuronosyltransferases: Structure, Function and Drug Design Studies." Current Medicinal Chemistry 25, no. 27 (2018): 3247–55. http://dx.doi.org/10.2174/0929867325666180226111311.

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UDP-glucuronosyltransferases (UGTs) are important phase II metabolic enzymes responsible for approximately 40-70% of endo and xenobiotic reactions. It catalyzes the transfer of glucuronic acid to lipophilic substrates, converting them into hydrophilic compounds that are excreted. There are 22 active human UGTs that belong to 4 families. This review focuses on human UGTs, highlighting the most current issues in order to connect all information available and allowing a discussion on the challenges already solved and those in which we need to move forward. Although, several UGTs studies have been

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29

Dutta, Shubhankar, and Kakoli Bose. "Remodelling structure-based drug design using machine learning." Emerging Topics in Life Sciences 5, no. 1 (2021): 13–27. http://dx.doi.org/10.1042/etls20200253.

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To keep up with the pace of rapid discoveries in biomedicine, a plethora of research endeavors had been directed toward Rational Drug Development that slowly gave way to Structure-Based Drug Design (SBDD). In the past few decades, SBDD played a stupendous role in identification of novel drug-like molecules that are capable of altering the structures and/or functions of the target macromolecules involved in different disease pathways and networks. Unfortunately, post-delivery drug failures due to adverse drug interactions have constrained the use of SBDD in biomedical applications. However, rec

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30

Pliushcheuskaya, Palina, and Georg Künze. "Recent Advances in Computer-Aided Structure-Based Drug Design on Ion Channels." International Journal of Molecular Sciences 24, no. 11 (2023): 9226. http://dx.doi.org/10.3390/ijms24119226.

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Ion channels play important roles in fundamental biological processes, such as electric signaling in cells, muscle contraction, hormone secretion, and regulation of the immune response. Targeting ion channels with drugs represents a treatment option for neurological and cardiovascular diseases, muscular degradation disorders, and pathologies related to disturbed pain sensation. While there are more than 300 different ion channels in the human organism, drugs have been developed only for some of them and currently available drugs lack selectivity. Computational approaches are an indispensable t

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31

Yadav, Khushi Joshi Ankur* Khemani Purva Malviya Sapna Kharia Anil. "A Short Review Docking: Structure Based Drug Design." International Journal of Pharmaceutical Sciences 2, no. 9 (2024): 1013–27. https://doi.org/10.5281/zenodo.13820440.

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Molecular docking plays a vital role in advancing scientific research, particularly in drug development and understanding biomolecular interactions. This computational approach simulates the binding of small molecules, such as potential drugs, to specific biological targets like proteins or DNA. By predicting the optimal binding configuration and energy, molecular docking helps identify promising drug candidates and sheds light on the underlying mechanisms of biological processes. The accuracy of this method relies heavily on a robust scoring function, which distinguishes between strong and we

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32

Dorahy, Georgia, Jake Zheng Chen, and Thomas Balle. "Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs." Molecules 28, no. 3 (2023): 1324. http://dx.doi.org/10.3390/molecules28031324.

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Central nervous system (CNS) disorders are a therapeutic area in drug discovery where demand for new treatments greatly exceeds approved treatment options. This is complicated by the high failure rate in late-stage clinical trials, resulting in exorbitant costs associated with bringing new CNS drugs to market. Computer-aided drug design (CADD) techniques minimise the time and cost burdens associated with drug research and development by ensuring an advantageous starting point for pre-clinical and clinical assessments. The key elements of CADD are divided into ligand-based and structure-based m

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Das, K., A. D. Clark Jr, P. J. Lewi, S. H. Hughes, P. A. J. Janssen, and E. Arnold. "Structure-based design of new AIDS drugs: overcoming drug resistance." Acta Crystallographica Section A Foundations of Crystallography 61, a1 (2005): c119. http://dx.doi.org/10.1107/s0108767305094973.

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34

Klupt, Kody A., and Zongchao Jia. "eEF2K Inhibitor Design: The Progression of Exemplary Structure-Based Drug Design." Molecules 28, no. 3 (2023): 1095. http://dx.doi.org/10.3390/molecules28031095.

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The α-kinase, eEF2K, phosphorylates the threonine 56 residue of eEF2 to inhibit global peptide elongation (protein translation). As a master regulator of protein synthesis, in combination with its unique atypical kinase active site, investigations into the targeting of eEF2K represents a case of intense structure-based drug design that includes the use of modern computational techniques. The role of eEF2K is incredibly diverse and has been scrutinized in several different diseases including cancer and neurological disorders—with numerous studies inhibiting eEF2K as a potential treatment option

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35

Arnold, Eddy. "Triumphs of Crystallography in Tackling HIV/AIDS: Drugs by Design." Acta Crystallographica Section A Foundations and Advances 70, a1 (2014): C7. http://dx.doi.org/10.1107/s2053273314099926.

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Crystallography has made extraordinary contributions to our understanding of the biology and chemistry of HIV. Judicious applications of structure-based drug design against HIV-1 protease and reverse transcriptase (RT) has led to the discovery of key drugs that are used in combinations to treat HIV infection. Extensive research and development efforts by pharma, academia, and government have made it possible for an HIV-infected person to live a nearly normal life. I will summarize the elegant structures that have been determined of components of HIV, with an emphasis on the enzyme RT, which my

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36

Gurung, Arun Bahadur, Mohammad Ajmal Ali, Joongku Lee, Mohammad Abul Farah, and Khalid Mashay Al-Anazi. "An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19." BioMed Research International 2021 (June 24, 2021): 1–18. http://dx.doi.org/10.1155/2021/8853056.

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The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health concerns around the world. The lack of approved drugs or vaccines continues to be a challenge and further necessitates the discovery of new therapeutic molecules. Computer-aided drug design has helped to expedite the drug discovery and development process by minimizing the cost and time. In this review article, we highlight two important categories of computer-aided drug design (CADD), viz., the ligand-based as well as structured-based drug discovery. Various molecular modeling techniques involved

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37

Oli, Bharti. "Revolutionizing Drug Discovery: A Comprehensive Review of Computer-Aided Drug Design Approaches." International Journal for Research in Applied Science and Engineering Technology 12, no. 7 (2024): 308–17. http://dx.doi.org/10.22214/ijraset.2024.63563.

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Abstract: Computer-Aided Drug Design (CADD) has significantly advanced the drug discovery process, offering tools to enhance efficiency and reduce costs. This review explores essential CADD methodologies, including molecular docking, virtual screening, ADMET profiling, homology modeling, and Quantitative Structure-Activity Relationship (QSAR) models. Molecular docking predicts interactions between drugs and targets, while virtual screening evaluates large compound libraries to identify promising candidates. ADMET profiling assesses pharmacokinetic and toxicological properties early in developm

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38

Bruch, Eduardo M., Stéphanie Petrella, and Marco Bellinzoni. "Structure-Based Drug Design for Tuberculosis: Challenges Still Ahead." Applied Sciences 10, no. 12 (2020): 4248. http://dx.doi.org/10.3390/app10124248.

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Structure-based and computer-aided drug design approaches are commonly considered to have been successful in the fields of cancer and antiviral drug discovery but not as much for antibacterial drug development. The search for novel anti-tuberculosis agents is indeed an emblematic example of this trend. Although huge efforts, by consortiums and groups worldwide, dramatically increased the structural coverage of the Mycobacterium tuberculosis proteome, the vast majority of candidate drugs included in clinical trials during the last decade were issued from phenotypic screenings on whole mycobacte

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39

Szarecka, Agnieszka, and Christopher Dobson. "Protein Structure Analysis: Introducing Students to Rational Drug Design." American Biology Teacher 81, no. 6 (2019): 423–29. http://dx.doi.org/10.1525/abt.2019.81.6.423.

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We describe a series of engaging exercises in which students emulate the process that researchers use to efficiently develop new pharmaceutical drugs, that of rational drug design. The activities are taken from a three- to four-hour workshop regularly conducted with first-year college students and presented here to take place over three to four class periods. Although targeted at college students, these activities may be appropriate at the high school level as well, particularly in an AP Biology course. The exercises introduce students to the topics of bioinformatics and computer modeling, in

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40

van Montfort, Rob L. M., and Paul Workman. "Structure-based drug design: aiming for a perfect fit." Essays in Biochemistry 61, no. 5 (2017): 431–37. http://dx.doi.org/10.1042/ebc20170052.

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Knowledge of the three-dimensional structure of therapeutically relevant targets has informed drug discovery since the first protein structures were determined using X-ray crystallography in the 1950s and 1960s. In this editorial we provide a brief overview of the powerful impact of structure-based drug design (SBDD), which has its roots in computational and structural biology, with major contributions from both academia and industry. We describe advances in the application of SBDD for integral membrane protein targets that have traditionally proved very challenging. We emphasize the major pro

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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 th

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42

Bino, Athira, and Murugan . "Topological Indices of Molecular Graph and Drug Design." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (2022): 1470–72. http://dx.doi.org/10.22214/ijraset.2022.47629.

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Abstracts: The application of topology in molecular graph and drug design is covered in this article. On the basis of the most recent developments in this area, an overview of the use of topological indices (TIs) in the process of drug design and development is provided. The introduction of concepts used in drug design and discovery, graph theory, and topological indices is the primary goal of the first section of this book. Researchers can learn more about the physical characteristics, chemical reactivity, and biological activity of these chemical molecular structures by using topological ind

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Vijayakrishnan, R. "Structure-based drug design and modern medicine." Journal of Postgraduate Medicine 55, no. 4 (2009): 301. http://dx.doi.org/10.4103/0022-3859.58943.

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Zhong, Haizhen Andrew. "Structure-based Design on Anticancer Drug Discovery." Current Topics in Medicinal Chemistry 20, no. 10 (2020): 813–14. http://dx.doi.org/10.2174/156802662010200331100200.

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Romano T. Kroemer. "Structure-Based Drug Design: Docking and Scoring." Current Protein & Peptide Science 8, no. 4 (2007): 312–28. http://dx.doi.org/10.2174/138920307781369382.

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Liang, Zhongjie, and Guang Hu. "Drug Design based on Protein Structure Network." Mini-Reviews in Medicinal Chemistry 16, no. 999 (2016): 1. http://dx.doi.org/10.2174/1389557516666160524145517.

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Torres, Felix, and Julien Orts. "Nuclear magnetic resonance structure-based drug design." Future Medicinal Chemistry 10, no. 20 (2018): 2373–76. http://dx.doi.org/10.4155/fmc-2018-0160.

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48

FUJITA, Toshio. "Quantitative structure-activity relationship and drug design." Journal of the agricultural chemical society of Japan 64, no. 1 (1990): 1–11. http://dx.doi.org/10.1271/nogeikagaku1924.64.1.

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Greenwald, J., O. Vix, C. Farnet, F. Bushman, and S. Choe. "Structure-based drug design with HIV integrase." Acta Crystallographica Section A Foundations of Crystallography 52, a1 (1996): C204. http://dx.doi.org/10.1107/s0108767396091192.

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50

Li, Rui, Xinheng He, Chengwei Wu, Mingyu Li, and Jian Zhang. "Advances in structure-based allosteric drug design." Current Opinion in Structural Biology 90 (February 2025): 102974. https://doi.org/10.1016/j.sbi.2024.102974.

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