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Composite Sequence-Structure Stability Models as Screening Tools for Identifying Vulnerable Targets for HIV Drug and Vaccine Development.

Manocheewa S, Mittler JE, Samudrala R, Mullins JI - Viruses (2015)

Bottom Line: The destabilizing mutations predicted by these models were rarely found in a database of 5811 HIV-1 CA coding sequences, with none being present at a frequency greater than 2%.Furthermore, 90% of variants with the low predicted stability (from a set of 184 CA variants whose replication fitness or infectivity has been studied in vitro) had aberrant capsid structures and reduced viral infectivity.The CA regions enriched with these sites also overlap with peptides shown to induce cellular immune responses associated with lower viral loads in infected individuals.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, University ofWashington, Seattle,WA 98195-8070, USA. manocs@uw.edu.

ABSTRACT
Rapid evolution and high sequence diversity enable Human Immunodeficiency Virus (HIV) populations to acquire mutations to escape antiretroviral drugs and host immune responses, and thus are major obstacles for the control of the pandemic. One strategy to overcome this problem is to focus drugs and vaccines on regions of the viral genome in which mutations are likely to cripple function through destabilization of viral proteins. Studies relying on sequence conservation alone have had only limited success in determining critically important regions. We tested the ability of two structure-based computational models to assign sites in the HIV-1 capsid protein (CA) that would be refractory to mutational change. The destabilizing mutations predicted by these models were rarely found in a database of 5811 HIV-1 CA coding sequences, with none being present at a frequency greater than 2%. Furthermore, 90% of variants with the low predicted stability (from a set of 184 CA variants whose replication fitness or infectivity has been studied in vitro) had aberrant capsid structures and reduced viral infectivity. Based on the predicted stability, we identified 45 CA sites prone to destabilizing mutations. More than half of these sites are targets of one or more known CA inhibitors. The CA regions enriched with these sites also overlap with peptides shown to induce cellular immune responses associated with lower viral loads in infected individuals. Lastly, a joint scoring metric that takes into account both sequence conservation and protein structure stability performed better at identifying deleterious mutations than sequence conservation or structure stability information alone. The computational sequence-structure stability approach proposed here might therefore be useful for identifying immutable sites in a protein for experimental validation as potential targets for drug and vaccine development.

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Predicted stabilities of mutations with known phenotypes. Flexible-backbone models were predicted by DOPE (A,C) and FOLDEF (B,D) and compared to capsid structure (A,B) and virus infectivity (C,D).
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viruses-07-02901-f004: Predicted stabilities of mutations with known phenotypes. Flexible-backbone models were predicted by DOPE (A,C) and FOLDEF (B,D) and compared to capsid structure (A,B) and virus infectivity (C,D).

Mentions: The low percentage of observed mutations with different stabilities from the reference models hints at optimal protein stability being crucial for CA function. Two datasets were used to explore whether predicted stability was also predictive of capsid structure and virus infectivity. The first consisted of 56 single amino acid substitutions with known mature capsid morphology [35,36,37,38]. Twenty-three were reported to result in aberrant capsid shape, while the other 33 had no obvious impact on capsid morphology. Using flexible backbone models of the mature CA hexamer and CTD dimer, 88% of mutations resulting in a native conical shape were predicted to be as stable as the reference by FOLDEF. With DOPE, a majority of mutations resulting in a conical capsid shape were predicted to be more stable than the reference models, 76% (vs. 21% predicted to be as stable) (Figure 4A,B). Similar results were obtained using fixed-backbone models of the same template structures (data not shown).


Composite Sequence-Structure Stability Models as Screening Tools for Identifying Vulnerable Targets for HIV Drug and Vaccine Development.

Manocheewa S, Mittler JE, Samudrala R, Mullins JI - Viruses (2015)

Predicted stabilities of mutations with known phenotypes. Flexible-backbone models were predicted by DOPE (A,C) and FOLDEF (B,D) and compared to capsid structure (A,B) and virus infectivity (C,D).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664974&req=5

viruses-07-02901-f004: Predicted stabilities of mutations with known phenotypes. Flexible-backbone models were predicted by DOPE (A,C) and FOLDEF (B,D) and compared to capsid structure (A,B) and virus infectivity (C,D).
Mentions: The low percentage of observed mutations with different stabilities from the reference models hints at optimal protein stability being crucial for CA function. Two datasets were used to explore whether predicted stability was also predictive of capsid structure and virus infectivity. The first consisted of 56 single amino acid substitutions with known mature capsid morphology [35,36,37,38]. Twenty-three were reported to result in aberrant capsid shape, while the other 33 had no obvious impact on capsid morphology. Using flexible backbone models of the mature CA hexamer and CTD dimer, 88% of mutations resulting in a native conical shape were predicted to be as stable as the reference by FOLDEF. With DOPE, a majority of mutations resulting in a conical capsid shape were predicted to be more stable than the reference models, 76% (vs. 21% predicted to be as stable) (Figure 4A,B). Similar results were obtained using fixed-backbone models of the same template structures (data not shown).

Bottom Line: The destabilizing mutations predicted by these models were rarely found in a database of 5811 HIV-1 CA coding sequences, with none being present at a frequency greater than 2%.Furthermore, 90% of variants with the low predicted stability (from a set of 184 CA variants whose replication fitness or infectivity has been studied in vitro) had aberrant capsid structures and reduced viral infectivity.The CA regions enriched with these sites also overlap with peptides shown to induce cellular immune responses associated with lower viral loads in infected individuals.

View Article: PubMed Central - PubMed

Affiliation: Department of Microbiology, University ofWashington, Seattle,WA 98195-8070, USA. manocs@uw.edu.

ABSTRACT
Rapid evolution and high sequence diversity enable Human Immunodeficiency Virus (HIV) populations to acquire mutations to escape antiretroviral drugs and host immune responses, and thus are major obstacles for the control of the pandemic. One strategy to overcome this problem is to focus drugs and vaccines on regions of the viral genome in which mutations are likely to cripple function through destabilization of viral proteins. Studies relying on sequence conservation alone have had only limited success in determining critically important regions. We tested the ability of two structure-based computational models to assign sites in the HIV-1 capsid protein (CA) that would be refractory to mutational change. The destabilizing mutations predicted by these models were rarely found in a database of 5811 HIV-1 CA coding sequences, with none being present at a frequency greater than 2%. Furthermore, 90% of variants with the low predicted stability (from a set of 184 CA variants whose replication fitness or infectivity has been studied in vitro) had aberrant capsid structures and reduced viral infectivity. Based on the predicted stability, we identified 45 CA sites prone to destabilizing mutations. More than half of these sites are targets of one or more known CA inhibitors. The CA regions enriched with these sites also overlap with peptides shown to induce cellular immune responses associated with lower viral loads in infected individuals. Lastly, a joint scoring metric that takes into account both sequence conservation and protein structure stability performed better at identifying deleterious mutations than sequence conservation or structure stability information alone. The computational sequence-structure stability approach proposed here might therefore be useful for identifying immutable sites in a protein for experimental validation as potential targets for drug and vaccine development.

Show MeSH
Related in: MedlinePlus