TY  - JOUR
T1  - A Predictive Model for Identifying the Most Effective Anti-CCR5 Monoclonal Antibody
A1  - Tatiana Hillman
JF  - Archives of Pharmacy Practice
JO  - Arch Pharm Pract
SN  - 2320-5210
Y1  - 2023
VL  - 14
IS  - 1
DO  - 10.51847/d9m2zUfqr4
SP  - 40
EP  - 49
N2  - 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
UR  - https://archivepp.com/article/a-predictive-model-for-identifying-the-most-effective-anti-ccr5-monoclonal-antibody-jkgbvxcktfa3qsv
ER  -