Artificial intelligence-based inspection of contact shock of a functional protein on a silicon substrate
Source abstract
Abstract
For the development of next-generation biomedical devices, it is necessary to understand the precise interactions between proteins and solid surfaces. However, current approaches only allow these interactions to be roughly estimated. Here, using artificial intelligence-based targeting and computer simulations, we assessed the binding behavior of approximately 80 tetrapeptides in the active site of papain adsorbed on a semiconductor surface. The contact shock of papain resulted in different peptides becoming compatible (i.e. fitting into the active site) and others losing this compatibility. Therefore, we propose contact shock as a potentially powerful approach to modify protein function. Moreover, the structural information for tetrapeptides that were insensitive to structural changes of papain could be valuable for drug design. From our decision trees, we found that the shock changed the main factors that determined compatibility.
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Research context
OpenAlex topics: Advanced Biosensing Techniques and Applications · Nanofabrication and Lithography Techniques · Force Microscopy Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
National Institute of Technology, Tsuruoka College , 104 Sawada, Inooka, Tsuruoka, Yamagata 997-8511, Japan
Funding
the National Institute of Technology
References (28)
Show source-provided references
1. Nature · 2004 · 427 · 46510.1038/nature02212 ↗
2. Jpn. J. Appl. Phys. · 2001 · 40 · L113510.1143/jjap.40.l1135 ↗
3. Trends. Biotechnol. · 2002 · 20 · s1410.1016/s0167-7799(02)02035-8 ↗
4. Curr. Opin. Chem. Biol. · 2003 · 7 · 5510.1016/S1367-5931(02)00005-4 ↗
5. Nanoscale Res. Lett. · 2012 · 7 · 28810.1186/1556-276x-7-288 ↗
6. Jpn. J. Appl. Phys. · 2000 · 39 · 218610.1143/jjap.39.2186 ↗
7. Jpn. J. Appl. Phys. · 2000 · 39 · 535210.1143/jjap.39.5352 ↗
8. J. Biomater. Nanobiotechnol. · 2013 · 4 · 19410.4236/jbnb.2013.42024 ↗
9. Langmuir · 1996 · 12 · 160510.1021/la950665s ↗
10. J. Colloid Interface Sci. · 2006 · 299 · 5610.1016/j.jcis.2006.01.065 ↗
11. Anal. Biochem. · 2006 · 351 · 28210.1016/j.ab.2006.01.008 ↗
12. J. Med. Chem. · 1998 · 41 · 456710.1021/jm980249f ↗
13. J. Enzyme Inhibition · 1992 · 6 · 11310.3109/14756369209040742 ↗
14. 2002
15. ACS Chem. Biol. · 2012 · 7 · 55210.1021/cb200332k ↗
16. Bioorg. Med. Chem. · 2012 · 20 · 77510.1016/j.bmc.2011.12.004 ↗
17. J. Phys. Chem. B · 2010 · 114 · 52110.1021/jp908314f ↗
18. J. Am. Chem. Soc. · 2006 · 128 · 788710.1021/ja060682b ↗
19. Chem. Phys. Lett. · 2016 · 647 · 4210.1016/j.cplett.2016.01.035 ↗
20. AIP Advances · 2018 · 8 · 05513310.1063/1.5033471 ↗
21. 1992
22. 2012
23. Jpn. J. Appl. Phys. · 2005 · 44 · 821010.1143/jjap.44.8210 ↗
24. J. Comput. Chem. · 2010 · 31 · 45510.1002/jcc.21334 ↗
25. Journal of the Operational Research Society · 1981 · 32 · 81510.1057/jors.1981.159 ↗
26. 2008
27. 1999
28. Research · 2018 · 971283210.1155/2018/9712832 ↗