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Updated: Jun 27, 2026
Evaluating the Effectiveness of Cancer Drug Sensitization In Vitro and In Vivo
Published on: February 6, 2015
Comparative assessment of different anti-CD147/Basigin 2 antibodies as a potential therapeutic anticancer target by
Nail Besli1, Halil İbrahim Bulut2, İlhan Onaran3
1Department of Medical Biology, Hamidiye School of Medicine, University of Health Sciences, Istanbul, Turkey.
Abstract:
Cluster of differentiation 147 (CD147) is an attractive target for anticancer therapy since it is pivotal in developing and progressing several of malignant tumors in the context of its high expression levels. Although anti-CD147 antibodies by different laboratories are designed for the Ig-like domains of CD147, there is a demand to provide priority among these anti-CD147 antibodies for developing of therapeutic anti-CD147 antibody before experimental validations. This study uses molecular docking and dynamic simulation techniques to compare the binding modes and affinities of nine antibody models against the Ig-like domains of CD147. After obtaining the model antibodies by homology modeling via Robetta, we predicted the CDRs of nine antibodies and the epitopes of CD147 to reach more accurate results for antigen affinity in molecular docking. Next, from HADDOCK 2.4., we meticulously handpicked the most superior model clusters (Z-Score: - 2.5 to - 1.2) and identified that meplazumab had higher affinities according to the success rate as the percentage of a scoring scale. We achieved stable simulations of CD147-antibody interaction. Our outcomes hold hypothetical importance for further experimental cancer research on the design and development of the relevant model antibodies.
Insights
This study compared nine anti-CD147 antibody models using molecular docking. Meplazumab demonstrated higher binding affinities, suggesting its potential for developing targeted anticancer therapies.
Area of Science:
- Oncology
- Immunology
- Computational Biology
Background:
- Cluster of differentiation 147 (CD147) is highly expressed in many cancers, making it a promising target for anticancer therapies.
- Developing effective therapeutic anti-CD147 antibodies requires prioritizing candidates before extensive experimental validation.
Purpose of the Study:
- To compare the binding modes and affinities of nine antibody models against CD147's Ig-like domains.
- To identify superior antibody candidates for potential therapeutic development against CD147.
Main Methods:
- Homology modeling (Robetta) to generate antibody models.
- Prediction of antibody complementarity-determining regions (CDRs) and CD147 epitopes.
- Molecular docking (HADDOCK 2.4) and dynamic simulations to assess binding affinities and stability.
Main Results:
- Meplazumab exhibited higher binding affinities compared to other antibody models based on scoring metrics.
- Stable CD147-antibody interactions were achieved in simulations.
- Identification of superior antibody clusters with Z-scores between -2.5 and -1.2.
Conclusions:
- The study provides a computational framework for prioritizing anti-CD147 antibody candidates.
- Meplazumab shows significant potential for further investigation in experimental cancer research.
- Findings support the rational design and development of novel therapeutic antibodies targeting CD147.
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