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Journal articles on the topic 'Structure- and fragment-based drug design'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Bancet, Alexandre, Claire Raingeval, Thierry Lomberget, Marc Le Borgne, Jean-François Guichou, and Isabelle Krimm. "Fragment Linking Strategies for Structure-Based Drug Design." Journal of Medicinal Chemistry 63, no. 20 (2020): 11420–35. http://dx.doi.org/10.1021/acs.jmedchem.0c00242.

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Du, Qi-Shi, Ri-Bo Huang, Yu-Tuo Wei, Zong-Wen Pang, Li-Qin Du, and Kuo-Chen Chou. "Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design." Journal of Computational Chemistry 30, no. 2 (2009): 295–304. http://dx.doi.org/10.1002/jcc.21056.

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3

Mendes, Vitor, and Tom L. Blundell. "Targeting tuberculosis using structure-guided fragment-based drug design." Drug Discovery Today 22, no. 3 (2017): 546–54. http://dx.doi.org/10.1016/j.drudis.2016.10.003.

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4

Kashyap, Aanchal, Pankaj Kumar Singh, and Om Silakari. "Counting on Fragment Based Drug Design Approach for Drug Discovery." Current Topics in Medicinal Chemistry 18, no. 27 (2019): 2284–93. http://dx.doi.org/10.2174/1568026619666181130134250.

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Fragment based drug design (FBDD) is a structure guided ligand design approach used in the process of drug discovery. It involves identification of low molecular weight fragments as hits followed by determination of their binding mode using X-ray crystallography and/or NMR spectroscopy. X-ray protein crystallography is one of the most sensitive biophysical methods used for screening and is least prone to false positives. It also provides detailed structural information of the protein–fragment complex at the atomic level. The retrieved binding information facilitates the optimization of fragmen

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5

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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6

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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7

Murray, Christopher W., and Tom L. Blundell. "Structural biology in fragment-based drug design." Current Opinion in Structural Biology 20, no. 4 (2010): 497–507. http://dx.doi.org/10.1016/j.sbi.2010.04.003.

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8

Shulga, Dmitry A., Nikita N. Ivanov, and Vladimir A. Palyulin. "In Silico Structure-Based Approach for Group Efficiency Estimation in Fragment-Based Drug Design Using Evaluation of Fragment Contributions." Molecules 27, no. 6 (2022): 1985. http://dx.doi.org/10.3390/molecules27061985.

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The notion of a contribution of a specific group in an organic molecule’s property and/or activity is both common in our thinking and is still not strictly correct due to the inherent non-additivity of free energy with respect to molecular fragments composing a molecule. The fragment- based drug discovery (FBDD) approach has proven to be fruitful in addressing the above notions. The main difficulty of the FBDD, however, is in its reliance on the low throughput and expensive experimental means of determining the fragment-sized molecules binding. In this article we propose a way to enhance the t

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9

Pihan, Emilie, Lionel Colliandre, Jean-François Guichou, and Dominique Douguet. "e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design." Bioinformatics 28, no. 11 (2012): 1540–41. http://dx.doi.org/10.1093/bioinformatics/bts186.

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10

Malhotra, Sony, Sherine E. Thomas, Bernardo Ochoa Montano, and Tom L. Blundell. "Structure-guided, target-based drug discovery – exploiting genome information from HIV to mycobacterial infections." Postępy Biochemii 62, no. 3 (2016): 262–72. http://dx.doi.org/10.18388/pb.2016_25.

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The use of protein crystallography in structure-guided drug discovery allows identification of potential inhibitor-binding sites and optimisation of interactions of hits and lead compounds with a target protein. An early example of this approach was the use of the structure of HIV protease in designing AIDS antivirals. More recently, use of structure-guided design with fragment-based drug discovery, which reduces the size of screening libraries by decreasing complexity, has improved ligand efficiency in drug design. Here, we discuss the use of structure-guided target identification and lead op

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11

Shan, Jinwen, Xiaolin Pan, Xingyu Wang, Xudong Xiao, and Changge Ji. "FragRep: A Web Server for Structure-Based Drug Design by Fragment Replacement." Journal of Chemical Information and Modeling 60, no. 12 (2020): 5900–5906. http://dx.doi.org/10.1021/acs.jcim.0c00767.

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12

Knehans, Tim, Andreas Schüller, Danny N. Doan, et al. "Structure-guided fragment-based in silico drug design of dengue protease inhibitors." Journal of Computer-Aided Molecular Design 25, no. 3 (2011): 263–74. http://dx.doi.org/10.1007/s10822-011-9418-0.

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13

Togre, Namdev S., Ana M. Vargas, Gunapati Bhargavi, Mohan Krishna Mallakuntla, and Sangeeta Tiwari. "Fragment-Based Drug Discovery against Mycobacteria: The Success and Challenges." International Journal of Molecular Sciences 23, no. 18 (2022): 10669. http://dx.doi.org/10.3390/ijms231810669.

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The emergence of drug-resistant mycobacteria, including Mycobacterium tuberculosis (Mtb) and non-tuberculous mycobacteria (NTM), poses an increasing global threat that urgently demands the development of new potent anti-mycobacterial drugs. One of the approaches toward the identification of new drugs is fragment-based drug discovery (FBDD), which is the most ingenious among other drug discovery models, such as structure-based drug design (SBDD) and high-throughput screening. Specialized techniques, such as X-ray crystallography, nuclear magnetic resonance spectroscopy, and many others, are par

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14

Nath Pandeya, Surendra. "Semicarbazone – a versatile therapeutic pharmacophore for fragment based anticonvulsant drug design." Acta Pharmaceutica 62, no. 3 (2012): 263–86. http://dx.doi.org/10.2478/v10007-012-0030-1.

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During the last fifteen years, semicarbazones have been extensively investigated for their anticonvulsant properties. 4-(4-Flurophenoxy) benzaldehyde semicarbazone (C0102862, V102862) was discovered as a lead molecule and is being developed as a potent antiepileptic drug, with maximal electroshock (MES) ED50 of i.p. 12.9 mg kg-1. In MES (oral screen), this compound has a protective index (PI = TD50/ED50 > 315) higher than carbamazepine (PI 101), phenytoin (PI > 21.6) and valproate (PI 2.17). The compound is a potent sodium channel blocker. Other semicarbazones have demonstrated activity

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15

Patne, Akshata Yashwant, Sai Madhav Dhulipala, William Lawless, Satya Prakash, Shyam S. Mohapatra, and Subhra Mohapatra. "Drug Discovery in the Age of Artificial Intelligence: Transformative Target-Based Approaches." International Journal of Molecular Sciences 25, no. 22 (2024): 12233. http://dx.doi.org/10.3390/ijms252212233.

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The complexities inherent in drug development are multi-faceted and often hamper accuracy, speed and efficiency, thereby limiting success. This review explores how recent developments in machine learning (ML) are significantly impacting target-based drug discovery, particularly in small-molecule approaches. The Simplified Molecular Input Line Entry System (SMILES), which translates a chemical compound’s three-dimensional structure into a string of symbols, is now widely used in drug design, mining, and repurposing. Utilizing ML and natural language processing techniques, SMILES has revolutioni

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16

Niazi, Sarfaraz K. "Quantum Mechanics in Drug Discovery: A Comprehensive Review of Methods, Applications, and Future Directions." International Journal of Molecular Sciences 26, no. 13 (2025): 6325. https://doi.org/10.3390/ijms26136325.

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Quantum mechanics (QM) revolutionizes drug discovery by providing precise molecular insights unattainable with classical methods. This review explores QM’s role in computational drug design, detailing key methods like density functional theory (DFT), Hartree–Fock (HF), quantum mechanics/molecular mechanics (QM/MM), and fragment molecular orbital (FMO). These methods model electronic structures, binding affinities, and reaction mechanisms, enhancing structure-based and fragment-based drug design. This article highlights the applicability of QM to various drug classes, including small-molecule k

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17

Alexeev, Yuri, Michael P. Mazanetz, Osamu Ichihara, and Dmitri G. Fedorov. "GAMESS As a Free Quantum-Mechanical Platform for Drug Research." Current Topics in Medicinal Chemistry 12, no. 18 (2013): 2013–33. http://dx.doi.org/10.2174/1568026611212180008.

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Driven by a steady improvement of computational hardware and significant progress in ab initio method development, quantum-mechanical approaches can now be applied to large biochemical systems and drug design. We review the methods implemented in GAMESS, which are suitable to calculate large biochemical systems. An emphasis is put on the fragment molecular orbital method (FMO) and quantum mechanics interfaced with molecular mechanics (QM/MM). The use of FMO in the protein-ligand binding, structure-activity relationship (SAR) studies, fragment- and structure-based drug design (FBDD/SBDD) is dis

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18

Tang, Bowen, Fengming He, Dongpeng Liu, et al. "AI-Aided Design of Novel Targeted Covalent Inhibitors against SARS-CoV-2." Biomolecules 12, no. 6 (2022): 746. http://dx.doi.org/10.3390/biom12060746.

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The drug repurposing of known approved drugs (e.g., lopinavir/ritonavir) has failed to treat SARS-CoV-2-infected patients. Therefore, it is important to generate new chemical entities against this virus. As a critical enzyme in the lifecycle of the coronavirus, the 3C-like main protease (3CLpro or Mpro) is the most attractive target for antiviral drug design. Based on a recently solved structure (PDB ID: 6LU7), we developed a novel advanced deep Q-learning network with a fragment-based drug design (ADQN–FBDD) for generating potential lead compounds targeting SARS-CoV-2 3CLpro. We obtained a se

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19

McBride, Christopher, Zacharia Cheruvallath, Mallareddy Komandla, et al. "Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design—Part 2." Bioorganic & Medicinal Chemistry Letters 26, no. 12 (2016): 2779–83. http://dx.doi.org/10.1016/j.bmcl.2016.04.072.

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20

Cheruvallath, Zacharia, Mingnam Tang, Christopher McBride, et al. "Discovery of potent, reversible MetAP2 inhibitors via fragment based drug discovery and structure based drug design—Part 1." Bioorganic & Medicinal Chemistry Letters 26, no. 12 (2016): 2774–78. http://dx.doi.org/10.1016/j.bmcl.2016.04.073.

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21

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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22

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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23

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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24

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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25

Sommer, Kai, Florian Flachsenberg, and Matthias Rarey. "NAOMInext – Synthetically feasible fragment growing in a structure-based design context." European Journal of Medicinal Chemistry 163 (February 2019): 747–62. http://dx.doi.org/10.1016/j.ejmech.2018.11.075.

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26

Caro, Engelo John Gabriel V., Marineil C. Gomez, Po-Wei Tsai, and Lemmuel L. Tayo. "Overcoming Clusterin-Induced Chemoresistance in Cancer: A Computational Study Using a Fragment-Based Drug Discovery Approach." Biology 14, no. 6 (2025): 639. https://doi.org/10.3390/biology14060639.

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Clusterin is one of the many known proteins implicated in cancer chemoresistance, which hinders the effectiveness of chemotherapy. This study aimed to design novel inhibitors targeting clusterin using fragment-based drug discovery (FBDD). This approach aims to develop new medicines by identifying small, simple molecules known as “fragments” that can bind to a specific target, such as a disease-causing protein. In this study, a primary ligand-binding site and an allosteric site on the clusterin molecule were identified through hotspot analysis. We screened commercially available fragment librar

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27

Thomas, Sherine E., Andrew J. Whitehouse, Karen Brown, et al. "Fragment-based discovery of a new class of inhibitors targeting mycobacterial tRNA modification." Nucleic Acids Research 48, no. 14 (2020): 8099–112. http://dx.doi.org/10.1093/nar/gkaa539.

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Abstract Translational frameshift errors are often deleterious to the synthesis of functional proteins and could therefore be promoted therapeutically to kill bacteria. TrmD (tRNA-(N(1)G37) methyltransferase) is an essential tRNA modification enzyme in bacteria that prevents +1 errors in the reading frame during protein translation and represents an attractive potential target for the development of new antibiotics. Here, we describe the application of a structure-guided fragment-based drug discovery approach to the design of a new class of inhibitors against TrmD in Mycobacterium abscessus. F

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28

Phusi, Naruedon, Yuta Hashimoto, Naoki Otsubo, et al. "Structure-based drug design of novel M. tuberculosis InhA inhibitors based on fragment molecular orbital calculations." Computers in Biology and Medicine 152 (January 2023): 106434. http://dx.doi.org/10.1016/j.compbiomed.2022.106434.

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29

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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30

Apostolakist, J., and A. Caflisch. "Computational Ligand Design." Combinatorial Chemistry & High Throughput Screening 2, no. 2 (1999): 91–104. http://dx.doi.org/10.2174/1386207302666220203193501.

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Abstract: A variety of computational tools that are used to assist drug design are reviewed. Particular emphasis is given to the limitations and merits of different methodologies. Recently, a number of general methods have been proposed for clustering compounds in classes of drug like and non-drug-like molecules. The usefulness of this classification for drug design is discussed. The estimation of (relative) binding affinities is from a theoretical point of view the most challenging part of ligand design. We review three methods for the estimation of binding energies. Firstly, quantitative st

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31

Nurizzo, Didier. "Massif-1 at MASSIF-1 and fragment-based drug design." Acta Crystallographica Section A Foundations and Advances 78, a1 (2022): a207. http://dx.doi.org/10.1107/s2053273322097923.

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32

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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33

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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34

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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35

Winter, Anja, Alicia P. Higueruelo, May Marsh, Anna Sigurdardottir, Will R. Pitt, and Tom L. Blundell. "Biophysical and computational fragment-based approaches to targeting protein–protein interactions: applications in structure-guided drug discovery." Quarterly Reviews of Biophysics 45, no. 4 (2012): 383–426. http://dx.doi.org/10.1017/s0033583512000108.

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AbstractDrug discovery has classically targeted the active sites of enzymes or ligand-binding sites of receptors and ion channels. In an attempt to improve selectivity of drug candidates, modulation of protein–protein interfaces (PPIs) of multiprotein complexes that mediate conformation or colocation of components of cell-regulatory pathways has become a focus of interest. However, PPIs in multiprotein systems continue to pose significant challenges, as they are generally large, flat and poor in distinguishing features, making the design of small molecule antagonists a difficult task. Neverthe

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36

Duong, Men Thi Hoai, and Hee-Chul Ahn. "Fragment-Based and Structural Investigation for Discovery of JNK3 Inhibitors." Pharmaceutics 14, no. 9 (2022): 1900. http://dx.doi.org/10.3390/pharmaceutics14091900.

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The c-Jun N-terminal kinases (JNKs) are members of the mitogen-activated protein kinase (MAPK) family and are related to cell proliferation, gene expression, and cell death. JNK isoform 3 (JNK3) is an important therapeutic target in varieties of pathological conditions including cancers and neuronal death. There is no approved drug targeting JNKs. To discover chemical inhibitors of JNK3, virtual fragment screening, the saturation transfer difference (STD) NMR, in vitro kinase assay, and X-ray crystallography were employed. A total of 27 fragments from the virtually selected 494 compounds were

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37

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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38

Fjellström, Ola, Sibel Akkaya, Hans-Georg Beisel, et al. "Creating Novel Activated Factor XI Inhibitors through Fragment Based Lead Generation and Structure Aided Drug Design." PLOS ONE 10, no. 1 (2015): e0113705. http://dx.doi.org/10.1371/journal.pone.0113705.

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39

Du, Xiaochen, Ran Zhang, and Matthew R. Groves. "Fragment Screening in the Development of a Novel Anti-Malarial." Crystals 13, no. 12 (2023): 1610. http://dx.doi.org/10.3390/cryst13121610.

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Fragment-based approaches offer rapid screening of chemical space and have become a mainstay in drug discovery. This manuscript provides a recent example that highlights the initial and intermediate stages involved in the fragment-based discovery of an allosteric inhibitor of the malarial aspartate transcarbamoylase (ATCase), subsequently shown to be a potential novel anti-malarial. The initial availability of high-resolution diffracting crystals allowed the collection of a number of protein fragment complexes, which were then assessed for inhibitory activity in an in vitro assay, and binding

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40

Li, Xiao-Ping, Rajesh K. Harijan, Bin Cao, et al. "Synthesis and Structural Characterization of Ricin Inhibitors Targeting Ribosome Binding Using Fragment-Based Methods and Structure-Based Design." Journal of Medicinal Chemistry 64, no. 20 (2021): 15334–48. http://dx.doi.org/10.1021/acs.jmedchem.1c01370.

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41

Chacón Simon, Selena, Feng Wang, Lance R. Thomas, et al. "Discovery of WD Repeat-Containing Protein 5 (WDR5)–MYC Inhibitors Using Fragment-Based Methods and Structure-Based Design." Journal of Medicinal Chemistry 63, no. 8 (2020): 4315–33. http://dx.doi.org/10.1021/acs.jmedchem.0c00224.

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42

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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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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44

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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45

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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46

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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47

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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48

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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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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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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