A Comprehensive Study on Interactions Between Protein Molecules and Their Importance in Drug Discovery

Author: Taneesha Gupta, Pankaj Malhotra Research & Reviews: A Journal of Drug Formulation, Development and Production-STM Journals Issn: 2394-1944 Date: 2024-07-04 10:43 Volume: 10 Issue: 3 Keyworde: In vitro and in vivo methodologies, protein-protein interaction, databases on protein- protein interaction, experimental and computational methods, therapeutic targets Full Text PDF Submit Manuscript Journals


Keyworde: In vitro and in vivo methodologies, protein-protein interaction, databases on protein- protein interaction, experimental and computational methods, therapeutic targets

Full Text PDF


1. Braun P, Gingras AC. History of protein-protein interactions: from egg-white to complex
networks. Proteomics. 2012; 12 (10): 1478–1498.
2. Ofran Y, Rost B. Analysing six types of protein-protein interfaces. J Mol Biol. 2003; 325 (2):
3. Nooren IMA, Thornton JM. Diversity of protein-protein interactions. EMBO J. 2003; 22 (14):
4. Zhang A. Protein Interaction Networks – Computational Analysis. New York, NY, USA:
Cambridge University Press; 2009.
5. Othman S, Richaud P, Verméglio A, Desbois A. Evidence for a proximal histidine interaction in
the structure of cytochromes c’ in solution: a resonance Raman study. Biochemistry. 1996; 35
(28): 9224–9234.
6. Tsunogae Y, Tanaka I, Yamane T, Kikkawa JI, Ashida T, Ishikawa C, Watanabe K, NakamuraS,
Takahashi K. Structure of the trypsin-binding domain of Bowman-Birk type protease inhibitor
and its interaction with trypsin. J Biochem. 1986; 100: 1637–1646.
7. Berggård T, Linse S, James P. Methods for the detection and analysis of protein-protein
interactions. Proteomics. 2007; 7: 2833–2842.
8. Gonzalez MW, Kann MG. Chapter 4: Protein interactions and disease. PLoS Comput Biol. 2012;
8: e1002819.
9. De Las Rivas J, Fontanillo C. Protein-protein interactions essentials: key concepts to building and
analyzing interactome networks. PLoS Comput Biol. 2010; 6: e1000807.
10. Pedamallu CS, Posfai J. Open source tool for prediction of genome wide protein-protein
interaction network based on ortholog information. Source Code Biol Med. 2010; 5: 1–6.
11. Skrabanek L, Saini HK, Bader GD, Enright AJ. Computational prediction of protein-protein
interactions. Mol Biotechnol. 2008; 38: 1–17.
12. Hanukoglu I. Electron transfer proteins of cytochrome P450 systems. In: Bittar EE, Jefcoate CR,
editors. Physiological Functions of Cytochrome P450 in Relation to Structure and Regulation.
Advances in Molecular and Cell Biology. Vol. 14. Leeds UK: JAI Press; 1996. pp. 29–55.
13. Brandt ME, Vickery LE. Charge pair interactions stabilizing ferredoxin-ferredoxin reductase
complexes. Identification by complementary site-specific mutations. J Biol Chem. 1993; 268 (23):
14. Hanukoglu I. Conservation of the enzyme-coenzyme interfaces in FAD and NADP binding
adrenodoxin reductase – a ubiquitous enzyme. J Mol Evol. 2017; 85 (5): 205–218.
15. Ooper G. The Cell: A Molecular Approach. 2nd edition. Washington, DC, USA: ASM Press; 2000.
16. Rigaut G, Shevchenko A, Rutz B, Wilm M, Mann M, Seraphin B. A generic protein purification
method for protein complex characterization and proteome exploration. Nat Biotechnol. 1999; 17
(10): 1030–1032.
17. Uetz P, Glot L, Cagney G, et al. A comprehensive analysis of protein-protein interactions in
Saccharomyces cerevisiae. Nature. 2000; 403 (6770): 623–627.
18. Ito T, Chiba T, Ozawa R, Yoshida M, Hattori M, Sakaki Y. A comprehensive two-hybrid analysis
to explore the yeast protein interactome. Proc Natl Acad Sci U S A. 2001; 98 (8): 4569–4574.
19. Gavin A-C, Bösche M, Krause R, et al. Functional organization of the yeast proteome by
systematic analysis of protein complexes. Nature. 2002; 415 (6868): 141–147.
20. Rohila JS, Chen M, Cerny R, Fromm ME. Improved tandem affinity purification tag and methods
for isolation of protein heterocomplexes from plants. Plant J. 2004; 38 (1): S172–S181.
21. Pitre S, Alamgir M, Green JR, Dumontier M, Dehne F, Golshani A. Computational methods for
predicting protein-protein interactions. Adv Biochem Eng Biotechnol. 2008; 110: 247–267.
22. MacBeath G, Schreiber SL. Printing proteins as microarrays for high-throughput function
determination. Science. 2000; 289 (5485): 1760–1763.
23. Tong AHY, Evangelista M, Parsons AB, et al. Systematic genetic analysis with ordered arrays of
yeast deletion mutants. Science. 2001; 294 (5550): 2364–2368.
24. O’Connell MR, Gamsjaeger R, Mackay JP. The structural analysis of protein-protein interactions
by NMR spectroscopy. Proteomics. 2009; 9 (23): 5224–5232.
25. Gao G, Williams JG, Campbell SL. Protein-protein interaction analysis by nuclear magnetic
resonance spectroscopy. Methods Mol Biol. 2004; 261: 79–92.
26. Semple JI, Sanderson CM, Campbell RD. The jury is out on “guilt by association” trials. Brief
Funct Genomic Proteomic. 2002; 1 (1): 40–52.
27. James P, Halladay J, Craig EA. Genomic libraries and a host strain designed for highly efficient
two-hybrid selection in yeast. Genetics. 1996; 144 (4): 1425–1436.
28. Llères D, Swift S, Lamond AI. Detecting protein-protein interactions in vivo with FRET using
multiphoton fluorescence lifetime imaging microscopy (FLIM). Curr Protocols Cytometry. 2007;
12: Unit 12.10.
29. Rutherford SL. From genotype to phenotype: buffering mechanisms and the storage of genetic
information. BioEssays. 2000; 22 (12): 1095–1105.
30. Hartman JL, IV, Garvik B, Hartwell L. Cell biology: principles for the buffering of genetic
variation. Science. 2001; 291 (5506): 1001–1004.
31. Bender A, Pringle JR. Use of a screen for synthetic lethal and multicopy suppressee mutants to
identify two new genes involved in morphogenesis in Saccharomyces cerevisiae. Mol Cell Biol.
32. Ooi SL, Pan X, Peyser BD, et al. Global synthetic-lethality analysis and yeast functional profiling.
Trends Genet. 2006; 22 (1): 56–63.
33. Brown JA, Sherlock G, Myers CL, et al. Global analysis of gene function in yeast by quantitative
phenotypic profiling. Mol Syst Biol. 2006; 2: 2006.0001.
34. Jones S, Thornton JM. Principles of protein–protein interactions. Proc Natl Acad Sci U S A.
1996; 93 (1): 13–20.
35. Qin K, Dong C, Wu G, Lambert NA. Inactive-state preassembly of G(q)-coupled receptors and
G(q) heterotrimers. Nat Chem Biol. 2011; 7 (10): 740–747.
36. Qin K, Sethi PR, Lambert NA. Abundance and stability of complexes containing inactive G
protein-coupled receptors and G proteins. FASEB J. 2008; 22 (8): 2920–2927.
37. Malhis N, Gsponer J. Computational identification of MoRFs in protein sequences.
Bioinformatics. 2015; 31 (11): 1738–1744.
38. Westermarck J, Ivaska J, Corthals GL. Identification of protein interactions involved in cellular
signaling. Mol Cell Proteomics. 2013; 12 (7): 1752–1763.
39. Pei D, Xu J, Zhuang Q, Tse HF, Esteban MA. Induced pluripotent stem cell technology in
regenerative medicine and biology. In: Kasper C, van Griensven M, Pörtner R, editors. Bioreactor
Systems for Tissue Engineering II: Strategies for the Expansion and Directed Differentiation of
Stem Cells. Berlin, Germany: Springer; 2010. pp. 127–141.
40. Orchard S, Kerrien S, Abbani S, et al. Protein interaction data curation: the International
Molecular Exchange (IMEx) consortium. Nat Methods. 2012; 9: 345–350.
41. Chatr-Aryamontri A, Breitkreutz BJ, Oughtred R, et al. The BioGRID interaction database: 2015
update. Nucleic Acids Res. 2015; 43: D470–D478.
42. Oughtred R, Stark C, Breitkreutz BJ, et al. The BioGRID interaction database: 2019 update.
Nucleic Acids Res. 2019; 47: D529–D541.
43. Szklarczyk D, Franceschini A, Kuhn M, et al. The STRING database in 2011: functional
interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 2011; 39:
44. Szklarczyk D, Franceschini A, Wyder S, et al. STRING v10: protein-protein interaction networks,
integrated over the tree of life. Nucleic Acids Res. 2015; 43: D447–D452.
45. Szklarczyk D, Gable AL, Lyon D, et al STRING v11: protein-protein association networks with
increased coverage, supporting functional discovery in genome-wide experimental datasets.
Nucleic Acids Res. 2019; 47: D607–D613.

46. Ammari MG, Gresham CR, McCarthy FM, Nanduri B. HPIDB 2.0: a curated database for host-
pathogen interactions. Database (Oxford) 2016; 2016: baw103.

47. Orchard S, Ammari M, Aranda B, et al. The MIntAct project–IntAct as a common curation
platform for 11 molecular interaction databases. Nucleic Acids Res. 2014; 42: D358–D363.
48. IMEx Consortium Curators. Del-Toro N, Duesbury M, Koch M, et al. Capturing variation impact on
molecular interactions in the IMEx Consortium mutations data set. Nat Commun. 2019; 10: 10.
49. Goodacre N, Devkota P, Bae E, Wuchty S, Uetz P. Protein-protein interactions of human viruses.
Semin Cell Dev Biol. 2020; 99: 31–39.
50. Kwofie SK, Schaefer U, Sundararajan VS, Bajic VB, Christoffels A. HCVpro: hepatitis C virus
protein interaction database. Infect Genet Evol. 2011; 11: 1971–1977.
51. Guirimand T, Delmotte S, Navratil V. VirHostNet 2.0: surfing on the web of virus/host molecular
interactions data. Nucleic Acids Res. 2015; 43: D583–D587.
52. Titeca K, Lemmens I, Tavernier J, Eyckerman S. Discovering cellular protein‐protein interactions:
technological strategies and opportunities. Mass Spectrometry Rev. 2018; 38 (1): 79–111.
53. Pagel P, Kovac S, Oesterheld M, et al. The MIPS mammalian protein–protein interaction
database. Bioinformatics. 2005; 21 (6): 832–834.
54. Terentiev AA, Moldogazieva NT, Shaitan KV. Dynamic proteomics in modeling of the living
cell. protein–protein interactions. Biochemistry. Biokhimiia. 2009; 74 (13): 1586–607.
55. Wodak SJ, Vlasblom J, Turinsky AL, Pu S. Protein–protein interaction networks: the puzzling
riches. Curr Opin Struct Biol. 2013; 23 (6): 941–953.
56. Banerjee S, Velásquez-Zapata V, Fuerst G, Elmore JM, Wise RP. NGPINT: a next-generation
protein–protein interaction software. Brief Bioinformatics. 2020; 22 (4).

57. Velásquez-Zapata V, Elmore JM, Banerjee S, Dorman K, Wise RP. Next-generation yeast-two-
hybrid analysis with Y2H-SCORES identifies novel interactors of the MLA immune receptor.

PLoS Comput Biol. 2021; 23 (4): e1008890.
58. Rajagopala SV, Sikorski P, Caufield JH, Tovchigrechko A, Uetz P. Studying protein complexes
by the yeast two-hybrid system. Methods. 2012; 58 (4): 392–399.
59. Stelzl U, Wanker EE. The value of high quality protein–protein interaction networks for systems
biology. Curr Opin Chem Biol. 2006; 10 (6): 551–558.
60. Petschnigg J, Snider J, Stagljar I. Interactive proteomics research technologies: recent applications
and advances. Curr Opin Biotechnol. 2011; 22 (1): 50–58.
61. Venkatesan K, Rual JF, Vazquez A, et al. An empirical framework for binary interactome
mapping. Nat Methods. 2009; 6 (1): 83–90.
62. Battesti A, Bouveret E. The bacterial two-hybrid system based on adenylate cyclase reconstitution
in Escherichia coli. Methods. 2012; 58 (4): 325–334.
63. Ramachandran N, Hainsworth E, Bhullar B, Eisenstein S, Rosen B, Lau AY, Walter JC, LaBaer J.
Self-assembling protein microarrays. Science. 2004; 305 (5680): 86–90.
64. Ramachandran N, Raphael JV, Hainsworth E, Demirkan G, Fuentes MG, Rolfs A, Hu Y, LaBaer
J. Next-generation high-density self-assembling functional protein arrays. Nat Methods. 2008; 5
(6): 535–538.
65. Laraia L, McKenzie G, Spring DR, Venkitaraman AR, Huggins DJ. Overcoming chemical,
biological, and computational challenges in the development of inhibitors targeting protein–
protein interactions. Chem Biol. 2015; 22 (6): 689–703.
66. Arkin MR, Wells JA. Small-molecule inhibitors of protein–protein interactions: progressing
towards the dream. Nat Rev Drug Discov. 2004; 3 (4): 301–317.
67. Chen J, Sawyer N, Regan L. Protein–protein interactions: general trends in the relationship
between binding affinity and interfacial buried surface area. Protein Sci. 2013; 22 (4): 510–515.
68. Jaiswal A, Lakshmi PT. Molecular inhibition of telomerase recruitment using designer peptides:
an in silico approach. J Biomol Struct Dynam. 2014; 33 (7): 1442–1459.
69. Jaiswal A. AtTRB1–3 mediates structural changes in AtPOT1b to hold ssDNA. Int Scholar Res
Notices Struct Biol. 2014; 2014: Article 827201.
70. Ivanov AA, Khuri FR, Fu H. Targeting protein–protein interactions as an anticancer strategy.
Trends Pharmacol Sci. 2013; 34 (7): 393–400.
71. Hargreaves D, Carbajo RJ, Bodnarchuk MS, et al. Design of rigid protein–protein interaction
inhibitors enables targeting of undruggable Mcl-1. Proc Natl Acad Sci U S A. 2023; 120 (21):

If-Else Example