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Journal articles on the topic 'Protein-molecule interactions'

Author: Grafiati

Published: 26 October 2024

Last updated: 31 July 2025

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1

Kuusk, Ave, Helen Boyd, Hongming Chen, and Christian Ottmann. "Small-molecule modulation of p53 protein-protein interactions." Biological Chemistry 401, no. 8 (2020): 921–31. http://dx.doi.org/10.1515/hsz-2019-0405.

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AbstractSmall-molecule modulation of protein-protein interactions (PPIs) is a very promising but also challenging area in drug discovery. The tumor suppressor protein p53 is one of the most frequently altered proteins in human cancers, making it an attractive target in oncology. 14-3-3 proteins have been shown to bind to and positively regulate p53 activity by protecting it from MDM2-dependent degradation or activating its DNA binding affinity. PPIs can be modulated by inhibiting or stabilizing specific interactions by small molecules. Whereas inhibition has been widely explored by the pharmac

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2

Ottmann, Christian. "Small-molecule modulation of protein–protein interactions." Drug Discovery Today: Technologies 10, no. 4 (2013): e499-e500. http://dx.doi.org/10.1016/j.ddtec.2013.08.001.

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3

Pollock, Julie A., Courtney L. Labrecque, Cassidy N. Hilton, et al. "Small Molecule Modulation of MEMO1 Protein-Protein Interactions." Journal of the Endocrine Society 5, Supplement_1 (2021): A1031. http://dx.doi.org/10.1210/jendso/bvab048.2110.

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Abstract MEMO1 (mediator of ErbB2-driven cell motility) is upregulated in breast tumors and has been correlated with poor prognosis in patients. As a scaffolding protein that binds to phosphorylated-tyrosine residues on receptors such as estrogen receptor and ErbB2, MEMO1 levels can influence phosphorylation cascades. Using our previously developed fluorescence polarization assay, we have identified small molecules with the ability to disrupt the interactions of MEMO1. We have performed limited structure-activity-relationship studies and computational analyses to investigate the molecular requ

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4

Guo, Z. "Designing Small-Molecule Switches for Protein-Protein Interactions." Science 288, no. 5473 (2000): 2042–45. http://dx.doi.org/10.1126/science.288.5473.2042.

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5

SAHA, MIRABEAU, and TIMOLÉON C. KOFANÉ. "NONLINEAR DYNAMICS OF LONG-RANGE PROTEIN-HELICOIDAL DNA INTERACTIONS." International Journal of Modern Physics B 26, no. 19 (2012): 1250101. http://dx.doi.org/10.1142/s0217979212501019.

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The effects of long-range interactions between peptides on the protein–DNA dynamics in the long-wave limit are studied. The investigation, done at the physiological temperature, is based on a coupled spin system of DNA molecule which includes the helicoidal geometry of DNA molecule and the Kac–Baker long-range interaction between the peptides of the protein molecule. By using the Holstein–Primakoff bosonic representation of the spin operators, we show that the original discrete equations for the protein–DNA interaction dynamics can be reduced to the nonlinear Schrödinger (NLS) equation of whic

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6

Nemashkalo, A., M. E. Phipps, S. P. Hennelly, and P. M. Goodwin. "Real-time, single-molecule observation of biomolecular interactions inside nanophotonic zero mode waveguides." Nanotechnology 33, no. 16 (2022): 165101. http://dx.doi.org/10.1088/1361-6528/ac467c.

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Abstract Living cells rely on numerous protein-protein, RNA-protein and DNA-protein interactions for processes such as gene expression, biomolecular assembly, protein and RNA degradation. Single-molecule microscopy and spectroscopy are ideal tools for real-time observation and quantification of nucleic acids-protein and protein-protein interactions. One of the major drawbacks of conventional single-molecule imaging methods is low throughput. Methods such as sequencing by synthesis utilizing nanofabrication and single-molecule spectroscopy have brought high throughput into the realm of single-m

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7

D’Abramo, C. M. "Small Molecule Inhibitors of Human Papillomavirus Protein - Protein Interactions." Open Virology Journal 5, no. 1 (2011): 80–95. http://dx.doi.org/10.2174/1874357901105010080.

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8

Linhares, Brian M., Jolanta Grembecka, and Tomasz Cierpicki. "Targeting epigenetic protein–protein interactions with small-molecule inhibitors." Future Medicinal Chemistry 12, no. 14 (2020): 1305–26. http://dx.doi.org/10.4155/fmc-2020-0082.

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Epigenetic protein–protein interactions (PPIs) play essential roles in regulating gene expression, and their dysregulations have been implicated in many diseases. These PPIs are comprised of reader domains recognizing post-translational modifications on histone proteins, and of scaffolding proteins that maintain integrities of epigenetic complexes. Targeting PPIs have become focuses for development of small-molecule inhibitors and anticancer therapeutics. Here we summarize efforts to develop small-molecule inhibitors targeting common epigenetic PPI domains. Potent small molecules have been rep

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9

Li, Xiyan, Xin Wang, and Michael Snyder. "Systematic investigation of protein-small molecule interactions." IUBMB Life 65, no. 1 (2012): 2–8. http://dx.doi.org/10.1002/iub.1111.

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10

Luo, Fang, Gege Qin, Tie Xia, and Xiaohong Fang. "Single-Molecule Imaging of Protein Interactions and Dynamics." Annual Review of Analytical Chemistry 13, no. 1 (2020): 337–61. http://dx.doi.org/10.1146/annurev-anchem-091619-094308.

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Live-cell single-molecule fluorescence imaging has become a powerful analytical tool to investigate cellular processes that are not accessible to conventional biochemical approaches. This has greatly enriched our understanding of the behaviors of single biomolecules in their native environments and their roles in cellular events. Here, we review recent advances in fluorescence-based single-molecule bioimaging of proteins in living cells. We begin with practical considerations of the design of single-molecule fluorescence imaging experiments such as the choice of imaging modalities, fluorescent

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11

Balci, Hamza, Sujay Ray, Jagat Budhathoki, and Parastoo Maleki. "Single Molecule Studies on G-Quadruplex, Protein, and Small Molecule Interactions." Biophysical Journal 112, no. 3 (2017): 170a. http://dx.doi.org/10.1016/j.bpj.2016.11.940.

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12

Song, Yun, and Peter Buchwald. "TNF Superfamily Protein-Protein Interactions: Feasibility of Small- Molecule Modulation." Current Drug Targets 16, no. 4 (2015): 393–408. http://dx.doi.org/10.2174/1389450116666150223115628.

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13

de Vink, Pim J., Sebastian A. Andrei, Yusuke Higuchi, Christian Ottmann, Lech-Gustav Milroy, and Luc Brunsveld. "Cooperativity basis for small-molecule stabilization of protein–protein interactions." Chemical Science 10, no. 10 (2019): 2869–74. http://dx.doi.org/10.1039/c8sc05242e.

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A cooperativity framework to describe and interpret small-molecule stabilization of protein–protein interactions (PPI) is presented, which allows elucidating structure–activity relationships regarding cooperativity and intrinsic affinity.

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14

Lee, Hong-Won, Ji Young Ryu, Janghyun Yoo, Byungsan Choi, Kipom Kim, and Tae-Young Yoon. "Real-time single-molecule coimmunoprecipitation of weak protein-protein interactions." Nature Protocols 8, no. 10 (2013): 2045–60. http://dx.doi.org/10.1038/nprot.2013.116.

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15

Aeluri, Madhu, Srinivas Chamakuri, Bhanudas Dasari, et al. "Small Molecule Modulators of Protein–Protein Interactions: Selected Case Studies." Chemical Reviews 114, no. 9 (2014): 4640–94. http://dx.doi.org/10.1021/cr4004049.

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16

Ottmann, Christian. "Small-molecule modulators of 14-3-3 protein–protein interactions." Bioorganic & Medicinal Chemistry 21, no. 14 (2013): 4058–62. http://dx.doi.org/10.1016/j.bmc.2012.11.028.

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17

Fry, David C. "Protein–protein interactions as targets for small molecule drug discovery." Biopolymers 84, no. 6 (2006): 535–52. http://dx.doi.org/10.1002/bip.20608.

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18

Vargas, Carolyn, Gerald Radziwill, Gerd Krause, et al. "Small-Molecule Inhibitors of AF6 PDZ-Mediated Protein-Protein Interactions." ChemMedChem 9, no. 7 (2014): 1458–62. http://dx.doi.org/10.1002/cmdc.201300553.

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19

Sierecki, E., N. Giles, M. Polinkovsky, M. Moustaqil, K. Alexandrov, and Y. Gambin. "A cell-free approach to accelerate the study of protein–protein interactions in vitro." Interface Focus 3, no. 5 (2013): 20130018. http://dx.doi.org/10.1098/rsfs.2013.0018.

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Protein–protein interactions are highly desirable targets in drug discovery, yet only a fraction of drugs act as binding inhibitors. Here, we review the different technologies used to find and validate protein–protein interactions. We then discuss how the novel combination of cell-free protein expression, AlphaScreen and single-molecule fluorescence spectroscopy can be used to rapidly map protein interaction networks, determine the architecture of protein complexes, and find new targets for drug discovery.

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20

Jain, Ankur, Ruijie Liu, Yang K. Xiang, and Taekjip Ha. "Single-molecule pull-down for studying protein interactions." Nature Protocols 7, no. 3 (2012): 445–52. http://dx.doi.org/10.1038/nprot.2011.452.

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21

Jeong, Min Gyu, Kai Zhou, Soyeon Park, et al. "Analysis of transient membrane protein interactions by single-molecule diffusional mobility shift assay." Experimental & Molecular Medicine 53, no. 2 (2021): 291–99. http://dx.doi.org/10.1038/s12276-021-00567-1.

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AbstractVarious repertoires of membrane protein interactions determine cellular responses to diverse environments around cells dynamically in space and time. Current assays, however, have limitations in unraveling these interactions in the physiological states in a living cell due to the lack of capability to probe the transient nature of these interactions on the crowded membrane. Here, we present a simple and robust assay that enables the investigation of transient protein interactions in living cells by using the single-molecule diffusional mobility shift assay (smDIMSA). Utilizing smDIMSA,

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22

Bai, Bing, Rongfeng Zou, H. C. Stephen Chan, Hongchun Li, and Shuguang Yuan. "MolADI: A Web Server for Automatic Analysis of Protein–Small Molecule Dynamic Interactions." Molecules 26, no. 15 (2021): 4625. http://dx.doi.org/10.3390/molecules26154625.

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Protein–ligand interaction analysis is important for drug discovery and rational protein design. The existing online tools adopt only a single conformation of the complex structure for calculating and displaying the interactions, whereas both protein residues and ligand molecules are flexible to some extent. The interactions evolved with time in the trajectories are of greater interest. MolADI is a user-friendly online tool which analyzes the protein–ligand interactions in detail for either a single structure or a trajectory. Interactions can be viewed easily with both 2D graphs and 3D represe

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23

Berwanger, Anja, Susanne Eyrisch, Inge Schuster, Volkhard Helms, and Rita Bernhardt. "Polyamines: Naturally occurring small molecule modulators of electrostatic protein–protein interactions." Journal of Inorganic Biochemistry 104, no. 2 (2010): 118–25. http://dx.doi.org/10.1016/j.jinorgbio.2009.10.007.

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24

Arkin, Michelle R., and James A. Wells. "Small-molecule inhibitors of protein–protein interactions: progressing towards the dream." Nature Reviews Drug Discovery 3, no. 4 (2004): 301–17. http://dx.doi.org/10.1038/nrd1343.

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25

Taguchi, Hideki, Taro Ueno, Hisashi Tadakuma, Masasuke Yoshida, and Takashi Funatsu. "Single-molecule observation of protein–protein interactions in the chaperonin system." Nature Biotechnology 19, no. 9 (2001): 861–65. http://dx.doi.org/10.1038/nbt0901-861.

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26

Arkin, Michelle R., Yinyan Tang, and James A. Wells. "Small-Molecule Inhibitors of Protein-Protein Interactions: Progressing toward the Reality." Chemistry & Biology 21, no. 9 (2014): 1102–14. http://dx.doi.org/10.1016/j.chembiol.2014.09.001.

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27

Vera, Andrés M., and Mariano Carrión-Vázquez. "Direct Identification of Protein-Protein Interactions by Single-Molecule Force Spectroscopy." Angewandte Chemie International Edition 55, no. 45 (2016): 13970–73. http://dx.doi.org/10.1002/anie.201605284.

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28

Vera, Andrés M., and Mariano Carrión-Vázquez. "Direct Identification of Protein-Protein Interactions by Single-Molecule Force Spectroscopy." Angewandte Chemie 128, no. 45 (2016): 14176–79. http://dx.doi.org/10.1002/ange.201605284.

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29

Hashimoto, Chie, and Jutta Eichler. "Turning Peptide Ligands into Small-Molecule Inhibitors of Protein-Protein Interactions." ChemBioChem 16, no. 13 (2015): 1855–56. http://dx.doi.org/10.1002/cbic.201500298.

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30

Ferreira de Freitas, Renato, and Matthieu Schapira. "A systematic analysis of atomic protein–ligand interactions in the PDB." MedChemComm 8, no. 10 (2017): 1970–81. http://dx.doi.org/10.1039/c7md00381a.

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We compiled a list of 11 016 unique structures of small-molecule ligands bound to proteins representing 750 873 protein–ligand atomic interactions, and analyzed the frequency, geometry and the impact of each interaction type. The most frequent ligand–protein atom pairs can be clustered into seven interaction types.

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31

C. Fry, David. "Small-Molecule Inhibitors of Protein-Protein Interactions: How to Mimic a Protein Partner." Current Pharmaceutical Design 18, no. 30 (2012): 4679–84. http://dx.doi.org/10.2174/138161212802651634.

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32

Guan, Yan, Xiaonan Shan, Fenni Zhang, Shaopeng Wang, Hong-Yuan Chen, and Nongjian Tao. "Kinetics of small molecule interactions with membrane proteins in single cells measured with mechanical amplification." Science Advances 1, no. 9 (2015): e1500633. http://dx.doi.org/10.1126/sciadv.1500633.

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Measuring small molecule interactions with membrane proteins in single cells is critical for understanding many cellular processes and for screening drugs. However, developing such a capability has been a difficult challenge. We show that molecular interactions with membrane proteins induce a mechanical deformation in the cellular membrane, and real-time monitoring of the deformation with subnanometer resolution allows quantitative analysis of small molecule–membrane protein interaction kinetics in single cells. This new strategy provides mechanical amplification of small binding signals, maki

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33

Zhao, Yujun, Denzil Bernard, and Shaomeng Wang. "Small Molecule Inhibitors of MDM2-p53 and MDMX-p53 Interactions as New Cancer Therapeutics." BioDiscovery 8 (July 8, 2013): e8950. https://doi.org/10.7750/BioDiscovery.2013.8.4.

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Inactivation of the function of tumor suppressor p53 is common in human cancers. In approximately half of human cancers, the tumor suppressor function of p53 is inactivated by deletion or mutation of TP53, the gene encoding p53 protein. In the remaining 50% of human cancers, p53 tumor suppressor function can be effectively inhibited by oncoprotein MDM2 or its homolog MDMX. Since inhibition of p53 by MDM2 or MDMX protein is mediated by their direct interaction with p53, small-molecule inhibitors designed to block the MDM2-p53 or MDMX-p53 protein-protein interaction (MDM2 or MDMX inhibitors) can

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34

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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35

Stringer, Bas, Hans de Ferrante, Sanne Abeln, Jaap Heringa, K. Anton Feenstra, and Reza Haydarlou. "PIPENN: protein interface prediction from sequence with an ensemble of neural nets." Bioinformatics 38, no. 8 (2022): 2111–18. http://dx.doi.org/10.1093/bioinformatics/btac071.

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Abstract Motivation The interactions between proteins and other molecules are essential to many biological and cellular processes. Experimental identification of interface residues is a time-consuming, costly and challenging task, while protein sequence data are ubiquitous. Consequently, many computational and machine learning approaches have been developed over the years to predict such interface residues from sequence. However, the effectiveness of different Deep Learning (DL) architectures and learning strategies for protein–protein, protein–nucleotide and protein–small molecule interface p

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36

Li, Fengzhi, Ieman A. M. Aljahdali, and Xiang Ling. "Molecular Glues: Capable Protein-Binding Small Molecules That Can Change Protein–Protein Interactions and Interactomes for the Potential Treatment of Human Cancer and Neurodegenerative Diseases." International Journal of Molecular Sciences 23, no. 11 (2022): 6206. http://dx.doi.org/10.3390/ijms23116206.

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Molecular glue (MG) compounds are a type of unique small molecule that can change the protein–protein interactions (PPIs) and interactomes by degrading, stabilizing, or activating the target protein after their binging. These small-molecule MGs are gradually being recognized for their potential application in treating human diseases, including cancer. Evidence suggests that small-molecule MG compounds could essentially target any proteins, which play critical roles in human disease etiology, where many of these protein targets were previously considered undruggable. Intriguingly, most MG compo

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37

Dyrda-Terniuk, Tetiana, Mateusz Sugajski, Oleksandra Pryshchepa, et al. "The Study of Protein–Cyclitol Interactions." International Journal of Molecular Sciences 23, no. 6 (2022): 2940. http://dx.doi.org/10.3390/ijms23062940.

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Investigation of interactions between the target protein molecule and ligand allows for an understanding of the nature of the molecular recognition, functions, and biological activity of protein–ligand complexation. In the present work, non-specific interactions between a model protein (Bovine Serum Albumin) and four cyclitols were investigated. D-sorbitol and adonitol represent the group of linear-structure cyclitols, while shikimic acid and D-(–)-quinic acid have cyclic-structure molecules. Various analytical methods, including chromatographic analysis (HPLC-MS/MS), electrophoretic analysis

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38

Jin, Jianshi, Tengfei Lian, Chan Gu, et al. "Probing protein - DNA interaction by single molecule and structural analysis." Acta Crystallographica Section A Foundations and Advances 70, a1 (2014): C198. http://dx.doi.org/10.1107/s2053273314098015.

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In proteins, conformational change impacting their function has been well investigated in the past decades, and was named `allosteric effect'. However, in DNA-protein interaction, the concept of DNA conformational change caused by DNA-protein binding will affect another nearby DNA-binding protein has not been well investigated and understood. Combined with structural biology and Single Molecule Assays, we can now probe and study allosteric propagation through DNA which exists as a fundamental property in DNA-protein interaction, and this allosteric effect through DNA can fine tune gene express

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39

Wilson, Hugh, Miles Lee, and Quan Wang. "Probing DNA-protein interactions using single-molecule diffusivity contrast." Biophysical Reports 1, no. 1 (2021): 100009. http://dx.doi.org/10.1016/j.bpr.2021.100009.

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40

Liu, W., Vedrana Montana, Jihong Bai, Edwin R. Chapman, U. Mohideen, and Vladimir Parpura. "Single Molecule Mechanical Probing of the SNARE Protein Interactions." Biophysical Journal 91, no. 2 (2006): 744–58. http://dx.doi.org/10.1529/biophysj.105.073312.

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41

Shapshak, Paul. "Molecule of the month: Synaptic plasticity – Protein miRNA interactions." Bioinformation 8, no. 21 (2012): 1003–4. http://dx.doi.org/10.6026/97320630081003.

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42

Huang, Da, Aaron D. Robison, Yiquan Liu, and Paul S. Cremer. "Monitoring protein–small molecule interactions by local pH modulation." Biosensors and Bioelectronics 38, no. 1 (2012): 74–78. http://dx.doi.org/10.1016/j.bios.2012.05.023.

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43

Feingold, Mario. "Single-molecule studies of DNA and DNA–protein interactions." Physica E: Low-dimensional Systems and Nanostructures 9, no. 3 (2001): 616–20. http://dx.doi.org/10.1016/s1386-9477(00)00270-8.

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44

Hilario, Jovencio, and Stephen C. Kowalczykowski. "Visualizing protein–DNA interactions at the single-molecule level." Current Opinion in Chemical Biology 14, no. 1 (2010): 15–22. http://dx.doi.org/10.1016/j.cbpa.2009.10.035.

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45

Froberg, James. "Monitoring Protein-Ligands Interactions by Single-Molecule Lysozyme Nanocircuits." Biophysical Journal 114, no. 3 (2018): 419a. http://dx.doi.org/10.1016/j.bpj.2017.11.2321.

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46

McFedries, Amanda, Adam Schwaid, and Alan Saghatelian. "Methods for the Elucidation of Protein-Small Molecule Interactions." Chemistry & Biology 20, no. 5 (2013): 667–73. http://dx.doi.org/10.1016/j.chembiol.2013.04.008.

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47

Matin, Tina R., Krishna P. Sigdel, Linda L. Randall, and Gavin M. King. "Probing Protein-Lipid Interactions at the Single Molecule Level." Biophysical Journal 108, no. 2 (2015): 559a. http://dx.doi.org/10.1016/j.bpj.2014.11.3066.

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48

Hillger, Frank, Dominik Hänni, Daniel Nettels, et al. "Probing Protein-Chaperone Interactions with Single-Molecule Fluorescence Spectroscopy." Angewandte Chemie International Edition 47, no. 33 (2008): 6184–88. http://dx.doi.org/10.1002/anie.200800298.

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49

Robison, Aaron D., and Ilya J. Finkelstein. "High-throughput single-molecule studies of protein-DNA interactions." FEBS Letters 588, no. 19 (2014): 3539–46. http://dx.doi.org/10.1016/j.febslet.2014.05.021.

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50

Benes, Madeleine, and Nathan T. Wright. "BPS2025 - Characterizing small-molecule/desmoplakin interactions preventing protein degradation." Biophysical Journal 124, no. 3 (2025): 221a—222a. https://doi.org/10.1016/j.bpj.2024.11.1221.

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