Abstract
COMPUTATIONAL DESIGN OF NANOPARTICLES FOR DETECTION OF CLINICALLY RELEVANT PEPTIDES FOR THE ULTRA-RARE LIVER DISEASE CREIGLER-NAJJAR SYNDROME

Anthony E. Soroh*, Berezi E. P., Kal Karim, Mirrin E. and Berezi P. K.

ABSTRACT

The present study focused on the selection of a suitable monomer that can be used for the development of a molecular imprinted polymer (MIP) for the identification of the rare liver disease Creigler-Najjar Syndrome (CNS). The computational approach was used to screen eight (8) selected monomers which were initially minimized along with 6 clinically relevant peptides of different sequences using the Sybyl 7.3 software. The Leapfrog results showed that 3-methacrylamido-1-aminium gave the highest value and was the preferred functional monomer amongst the selected monomers. It exhibited the highest binding scores with all the six peptides. Recorded values were -72.56 kcal/mol, -64.77 kcal/mol, -68.68 kcal/mol, -77.38 kcal/mol, -108.45 kcal/mol and -88.14 kcal/mol. This functional monomer showed promising properties as it exhibited strong hydrogen bonding with the six peptides.

Keywords: Nanoparticles, Creigler-Najjar Syndrome, Functional Monomers, Leapfrog, Binding Scores, Peptides.


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