Elicit Broadly Neutralizing HIV Antibodies
It is well known that producing a vaccine for highly mutable viruses, like influenza or HIV, is a daunting, and yet unsolved, problem. The high mutability rates of these viruses allows them to elude the classical strategies employed by the immune system, making the produced antibodies inefficient.
Yet, in few infected patients it has been observed the formation of antibodies with a broad spectrum of activity, which are able to recognize different viral strains. Unfortunately, these Broadly Neutralizing Antibodies (bNAbs) take a long time to form naturally, if ever.
The goal of this research project is to give some insight into the modeling of the formation of these bNAbs, with the ultimate goal of developing vaccination strategies able to elicit their formation. In particular, my part of the project focuses on the in silico evaluation of the antibody-antigen binding affinity, which is a key step for a quantitative modeling of the maturation of the antibodies.
This project a collaboration between three research groups:
- Martin Karplus at Harvard University (where I am)
- Arup Chakraborty at the Massachusetts Institute of Technology (MIT)
- Felice Lightstone at the Lawrence Livermore National Laboratory (LLNL)
- Estimation of the breadth of CD4bs targeting HIV antibodies by molecular modeling and machine learning. S. Conti and M. Karplus. PLOS Computational Biology, 2019, 15(4). See details.