%0 Journal Article
%T A Predictive Model for Identifying the Most Effective Anti-CCR5 Monoclonal Antibody
%A Tatiana Hillman
%J Archives of Pharmacy Practice
%@ 2320-5210
%D 2023
%V 14
%N 1
%R 10.51847/d9m2zUfqr4
%P 40-49
%X CCR5 (R5) inhibition is increasingly being studied for its potential to prevent, treat, and cure illnesses. R5 is a transmembrane protein that interacts with the CD4 receptor and CXCR4 (X4) of T cells, allowing the attachment of HIV viruses to lymphocytes. Consequently, because R5 inhibition has performed well as a medicinal drug, such as maraviroc, many researchers have speculated that R5 inhibition via binding antibodies may effectively treat HIV patients. However, currently, there is a lack of information about the structural interaction between monoclonal antibodies (mAbs) and R5. The understanding of the structural CCR5 blockade via mAbs is limited. As a consequence, in this study, a predictive model with a sample size of N=160 was performed using non-linear regressions, in which the predicted reaction rates of the target R5 to gp120 interaction based on Michaelis-Menten enzyme kinetics of the inhibitor types (no, inhibitor (Control), competitive (CI), non-competitive (NI), and uncompetitive (UI)) were analyzed for their level to reduce the Vmax and Km of the R5-to-gp120 interaction.At a significant p-value of P
%U https://archivepp.com/article/a-predictive-model-for-identifying-the-most-effective-anti-ccr5-monoclonal-antibody-jkgbvxcktfa3qsv