Design of a basigin-mimicking inhibitor targeting the malaria invasion protein RH5
File(s)Warszawski et al accepted version.pdf (1.14 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
Many human pathogens use host cell-surface receptors to attach and invade cells. Often, the
host-pathogen interaction affinity is low, presenting opportunities to block invasion using a
soluble, high-affinity mimic of the host protein. The Plasmodium falciparum reticulocyte-binding
protein homolog 5 (RH5) provides an exciting candidate for mimicry: it is highly conserved and
its moderate affinity binding to the human receptor basigin (KD≥1 μM) is an essential step in
erythrocyte invasion by this malaria parasite. We used deep mutational scanning of a soluble
fragment of human basigin to systematically characterize point mutations that enhance basigin
affinity for RH5 and then used Rosetta to design a variant within the sequence space of
affinity-enhancing mutations. The resulting seven-mutation design exhibited 2,500-fold higher
affinity (KD<1 nM) for RH5 with a very slow binding off rate (0.23 h-1) and reduced the effective
Plasmodium growth-inhibitory concentration by at least tenfold compared to human basigin. The
design provides a favorable starting point for engineering on-rate improvements that are likely
to be essential to reach therapeutically effective growth inhibition. Designed mimics may provide
therapeutic advantages over antibodies, since the mimics bind to essential surfaces on the target
pathogen proteins, reducing the likelihood for the emergence of escape mutants
host-pathogen interaction affinity is low, presenting opportunities to block invasion using a
soluble, high-affinity mimic of the host protein. The Plasmodium falciparum reticulocyte-binding
protein homolog 5 (RH5) provides an exciting candidate for mimicry: it is highly conserved and
its moderate affinity binding to the human receptor basigin (KD≥1 μM) is an essential step in
erythrocyte invasion by this malaria parasite. We used deep mutational scanning of a soluble
fragment of human basigin to systematically characterize point mutations that enhance basigin
affinity for RH5 and then used Rosetta to design a variant within the sequence space of
affinity-enhancing mutations. The resulting seven-mutation design exhibited 2,500-fold higher
affinity (KD<1 nM) for RH5 with a very slow binding off rate (0.23 h-1) and reduced the effective
Plasmodium growth-inhibitory concentration by at least tenfold compared to human basigin. The
design provides a favorable starting point for engineering on-rate improvements that are likely
to be essential to reach therapeutically effective growth inhibition. Designed mimics may provide
therapeutic advantages over antibodies, since the mimics bind to essential surfaces on the target
pathogen proteins, reducing the likelihood for the emergence of escape mutants
Date Issued
2020-01
Date Acceptance
2019-07-12
Citation
Proteins: Structure, Function, and Bioinformatics, 2020, 88 (1), pp.187-195
ISSN
0887-3585
Publisher
Wiley
Start Page
187
End Page
195
Journal / Book Title
Proteins: Structure, Function, and Bioinformatics
Volume
88
Issue
1
Copyright Statement
© 2019 Wiley Periodicals, Inc. This is the accepted version of the following article: Warszawski, S, Dekel, E, Campeotto, I, et al. Design of a basigin‐mimicking inhibitor targeting the malaria invasion protein RH5. Proteins. 2020; 88: 187– 195, which has been published in final form at https://doi.org/10.1002/prot.25786
Sponsor
Wellcome Trust
Wellcome Trust
Wellcome Trust
Identifier
https://onlinelibrary.wiley.com/doi/full/10.1002/prot.25786
Grant Number
100993/Z/13/Z
100993/Z/13/Z
107366/Z/15/Z
Subjects
Science & Technology
Life Sciences & Biomedicine
Biochemistry & Molecular Biology
Biophysics
deep sequencing
high-affinity design
host-pathogen interactions
Plasmodium falciparum
Rosetta
PLASMODIUM-FALCIPARUM MEROZOITES
COMPUTATIONAL DESIGN
ERYTHROCYTE INVASION
ANTIBODIES
VACCINE
SPECIFICITY
AFFINITY
BINDING
Plasmodium falciparum
Rosetta
deep sequencing
high-affinity design
host-pathogen interactions
06 Biological Sciences
08 Information and Computing Sciences
01 Mathematical Sciences
Bioinformatics
Publication Status
Published
Date Publish Online
2019-07-20