Evolutionary Medicine is the application of evolutionary thinking to problems in medicine and medical research. This approach has exceptional merit in infectious diseases, in which evolution is critically important in understanding virulence, immune evasion, drug resistance, and other features critical in public health and clinical intervention. This proposal takes an evolutionary approach to the evaluation of lead compounds for the development of third-generation triazine inhibitors of the enzyme dihydrofolate reductase (DHFR). DHFR is one of the most effective drug targets used for the prevention and treatment of malaria. The goal of this project is twofold: (1) To apply evolutionary thinking to make informed choices of the best lead compounds to select for further development into clinically effective drugs with a long therapeutic lifetime; and (2) To perform the studies in such a way as to explore how adaptive landscapes of drug resistance change as a function of drug concentration and in response to differing perturbagens.
In Specific Aim 1 we will examine the wildtype allele and all known naturally occurring polymorphisms in DHFR of P. falciparum and P. vivax for their resistance to five potential lead compounds for third-generation antifolates These tests will use both the yeast and bacterial transgenic DHFR expression systems. The use of experimental models is essential, as P. vivax cannot be cultured in the laboratory, and the production of the isogenic strains needed for the tests in P. falciparum is not feasible in regard to time or cost.
In Specific Aim 2, we will augment the studies in Specific Aim 1 by creating the missing intermediate alleles to allow a complete combinatorial analysis of the adaptive landscape with respect to each of the novel triazine antifolates as perturbagens.
In Specific Aim 3 we will carry out mutagenesis and selection experiments in the P. falciparum and P. vivax transgenic systems to determine whether the wildtype allele or any of the polymorphisms are easily converted via new mutations to resistance against any of the novel antifolates. This is a critical issue in evaluating the potential therapeutic lifetime of new drugs. The lead compounds to be tested are the five triazine antifolates WR99210, JPC-2067, JPC-2122, JPC-1058, and JPC-1054. The research will be carried out in collaboration with the Jacobus Pharmaceutical Company, a small company that is nevertheless a world leader in developing and producing antifolates against malaria and toxoplasmosis. Our collaborator, David P. Jacobus, MD has a distinguished track record of collaboration with academic researchers and open dissemination of research resources and information. The research is a unique combination of drug development and evolutionary biology with the potential to contribute to the development of new life-saving drugs while at the same time revealing new principles of protein evolution.

Public Health Relevance

This project uses the approach of Evolutionary Medicine to help choose the most promising lead compounds for new antimalarial antifolates and to explore how adaptive landscapes of drug resistance change as a function of drug concentration and in response to differing drugs. The research will be carried out in collaboration with one of the world's leading companies in developing and supplying antifolates for malaria. Future development of the lead compounds will result in new clinically effective antimalarial drugs with a long therapeutic lifetime.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI106734-03
Application #
9001901
Study Section
Genetic Variation and Evolution Study Section (GVE)
Program Officer
O'Neil, Michael T
Project Start
2014-03-15
Project End
2018-02-28
Budget Start
2016-03-01
Budget End
2017-02-28
Support Year
3
Fiscal Year
2016
Total Cost
$449,538
Indirect Cost
$183,539
Name
Harvard University
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
082359691
City
Cambridge
State
MA
Country
United States
Zip Code
02138
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Ogbunugafor, C Brandon; Wylie, C Scott; Diakite, Ibrahim et al. (2016) Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance. PLoS Comput Biol 12:e1004710
Liénard, Marjorie A; Araripe, Luciana O; Hartl, Daniel L (2016) Neighboring genes for DNA-binding proteins rescue male sterility in Drosophila hybrids. Proc Natl Acad Sci U S A 113:E4200-7
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