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Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity.

ABSTRACT: While reverse genetics and functional genomics have long affirmed the role of individual mutations in determining protein function, there have been fewer studies addressing how large-scale changes in protein sequences, such as in entire modular segments, influence protein function and evolution. Given how recombination can reassort protein sequences, these types of changes may play an underappreciated role in how novel protein functions evolve in nature. Such studies could aid our understanding of whether certain organismal phenotypes related to protein function-such as growth in the presence or absence of an antibiotic-are robust with respect to the identity of certain modular segments. In this study, we combine molecular genetics with biochemical and biophysical methods to gain a better understanding of protein modularity in dihydrofolate reductase (DHFR), an enzyme target of antibiotics also widely used as a model for protein evolution. We replace an integral ?-helical segment of Escherichia coli DHFR with segments from a number of different organisms (many nonmicrobial) and examine how these chimeric enzymes affect organismal phenotypes (e.g., resistance to an antibiotic) as well as biophysical properties of the enzyme (e.g., thermostability). We find that organismal phenotypes and enzyme properties are highly sensitive to the identity of DHFR modules, and that this chimeric approach can create enzymes with diverse biophysical characteristics.

SUBMITTER: Rodrigues JV

PROVIDER: S-EPMC7663999 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity.

Rodrigues João V JV Ogbunugafor C Brandon CB Hartl Daniel L DL Shakhnovich Eugene I EI

Protein science : a publication of the Protein Society 20190530 7

While reverse genetics and functional genomics have long affirmed the role of individual mutations in determining protein function, there have been fewer studies addressing how large-scale changes in protein sequences, such as in entire modular segments, influence protein function and evolution. Given how recombination can reassort protein sequences, these types of changes may play an underappreciated role in how novel protein functions evolve in nature. Such studies could aid our understanding ...[more]

PMID: 31095809

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Project description:BACKGROUND:Plasmodium falciparum readily develops resistance to the anti-folates pyrimethamine and proguanil via a characteristic set of mutations in the dihydrofolate reductase (PfDHFR) gene that leads to reduced competitive drug binding at the enzyme's active site. Analogous mutations can be found in the DHFR gene in isolates of Plasmodium vivax (PvDHFR) although anti-folates have not been widely used for the treatment of this infection. Here the interactions between DHFR inhibitors and modelled structures of the DHFR enzymes of Plasmodium malariae (PmDHFR) and Plasmodium ovale (PoDHFR) are described, along with an investigation of the effect of recently reported mutations within PmDHFR. METHODS:DHFR models for PmDHFR and PoDHFR were constructed using the solved PfDHFR-TS and PvDHFR structures respectively as templates. The modelled structures were docked with three DHFR inhibitors as ligands and more detailed interactions were explored via simulation of molecular dynamics. RESULTS:Highly accurate models were obtained containing sets of residues that mediate ligand binding which are highly comparable to those mediating binding in known crystal structures. Within this set, there were differences in the relative contribution of individual residues to inhibitor binding. Modelling of PmDHFR mutant sequences revealed that PmDHFR I170M was associated with a significant reduction in binding energy to all DHFR inhibitors studied, while the other predicted resistance mutations had lesser or no effects on ligand binding. CONCLUSIONS:Binding of DHFR inhibitors to the active sites of all four Plasmodium enzymes is broadly similar, being determined by an analogous set of seven residues. PmDHFR mutations found in field isolates influenced inhibitor interactions to a varying extent. In the case of the isolated I170M mutation, the loss of interaction with pyrimethamine suggests that DHFR-inhibitor interactions in P. malariae are different to those seen for DHFRs from P. falciparum and P. vivax.

Project description:Chimeric virus-like particles (cVLPs) are protein-based nanostructures applied as investigational vaccines against infectious diseases, cancer, and immunological disorders. Low solubility of cVLP vaccine candidates is a challenge that can prevent development of these very substances. Solubility of cVLPs is typically assessed empirically, leading to high time and material requirements. Prediction of cVLP solubility in silico can aid in reducing this effort. Protein aggregation by hydrophobic interaction is an important factor driving protein insolubility. In this article, a recently developed soft ensemble vote classifier (sEVC) for the prediction of cVLP solubility was used based on 91 literature amino acid hydrophobicity scales. Optimization algorithms were developed to boost model performance, and the model was redesigned as a regression tool for ammonium sulfate concentration required for cVLP precipitation. The present dataset consists of 568 cVLPs, created by insertion of 71 different peptide sequences using eight different insertion strategies. Two optimization algorithms were developed that (I) modified the sEVC with regard to systematic misclassification based on the different insertion strategies, and (II) modified the amino acid hydrophobicity scale tables to improve classification. The second algorithm was additionally used to synthesize scales from random vectors. Compared to the unmodified model, Matthew's Correlation Coefficient (MCC), and accuracy of the test set predictions could be elevated from 0.63 and 0.81 to 0.77 and 0.88, respectively, for the best models. This improved performance compared to literature scales was suggested to be due to a decreased correlation between synthesized scales. In these, tryptophan was identified as the most hydrophobic amino acid, i.e., the amino acid most problematic for cVLP solubility, supported by previous literature findings. As a case study, the sEVC was redesigned as a regression tool and applied to determine ammonium sulfate concentrations for the precipitation of cVLPs. This was evaluated with a small dataset of ten cVLPs resulting in an R 2 of 0.69. In summary, we propose optimization algorithms that improve sEVC model performance for the prediction of cVLP solubility, allow for the synthesis of amino acid scale tables, and further evaluate the sEVC as regression tool to predict cVLP-precipitating ammonium sulfate concentrations.

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Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity.

Publications

Chimeric dihydrofolate reductases display properties of modularity and biophysical diversity.

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