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Online Journal of Bioinformaticsâ

Onl J Bioinform©

Established 1995

ISSN  1443-2250


Volume 25 (1): 19-25, 2024

In silico prediction for Ha-NMR chemical shifts in mouse epidermis growth factors.


Díaz HG1-2, De Armas RR2, Uriarte E3


1 Chemical Bio-actives Center, 2 Department of Chemistry, Central University of "Las Villas" 54830, Cuba. 3Department of Organic Chemistry, Faculty of Pharmacy, University of Santiago de Compostela 15706, Spain.




Díaz HG, De Armas RR, Uriarte E., In silico prediction for Ha-NMR chemical shifts in mouse epidermis growth factors.. Onl J Bioinform 25 (1):19-25, 2024.  A Markovian chemical In silico design (MARCH-INSIDE) method produced piecewise linear regression (r = 0.93) between protein backbone descriptors with (1Ha- NMR) values for mouse mEGF protein. The method extends preliminary findings on electron intra-molecular Markovian delocalization to polymer chains. Original results were supported by cross validation procedures excluding each fourth amino acid from processing resulting in r = Q1 = 0.93, Q2 = 0.94, Q3 = 0.94 and Q4 = 0.96 with a break-point value of 4.42 ppm characterizing 2 amino acid clusters.


KEYWORDS: Markov chains, Proteins, mouse Epidermis Growth Factor, NMR, piecewise regression, Bioinformatics.