Fold Recognition of the Human Immunodeficiency Virus Type 1 V3 Loop and Flexibility of Its Crown Structure During the Course of Adaptation to a Host

Watabe, Teruaki; Kishino, Hirohisa; Okuhara, Yoshiyasu; Kitazoe, Yasuhiro

doi:10.1534/genetics.105.051508

“…Expecting that the fitness of an amino acid depends mostly on the local structure surrounding each of the amino acid residues, Simons et al (1999aSimons et al ( , 1999b categorized local environments and calculated amino acid frequencies in the proteins registered in PDB for each of the categories (see below for more detail). Watabe et al (2006) obtained evidence that implies that the structure of the crown region of the HIV V3 loop varies more in the patient where the viral population experienced larger sequence evolution. They traced the value of PðseqjstrÞ based on the information of the sequences and the structure of the templates in PDB.…”

Section: A Likelihood-based Index Of the Binding Ability Of Protein-pmentioning

confidence: 99%

“…Particularly in the arms race of the host-parasite system, binding affinity plays a crucial role. Watabe et al (2006) developed a likelihood-based index, named sequencestructure fitness (SSF), which quantifies the degree to which a sequence fits in the given structure. The SSF is calculated empirically based on amino acid preferences and pairwise interactions in the structural environment present in templates' structure.…”

Section: Introductionmentioning

confidence: 99%

A Likelihood-based Index of Protein Protein Binding Affinities with Application to Influenza HA Escape from Antibodies

Watabe

¹

,

Kishino

²

,

Martins

³

et al. 2007

Molecular Biology and Evolution

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In many biological systems, proteins interact with other organic molecules to produce indispensable functions, in which molecular recognition phenomena are essential. Proteins have kept or gained their functions during molecular evolution. Their functions seem to be flexible, and a few amino acid substitutions sometimes cause drastic changes in function. In order to monitor and predict such drastic changes in the early stages in target populations, we need to identify patterns of structural changes during molecular evolution causing decreases or increases in the binding affinity of protein complexes. In previous work, we developed a likelihood-based index to quantify the degree to which a sequence fits a given structure. This index was named the sequence-structure fitness (SSF) and is calculated empirically based on amino acid preferences and pairwise interactions in the structural environment present in template structures. In the present work, we used the SSF to develop an index to measure the binding affinity of protein-protein complexes defined as the log likelihood ratio, contrasting the fitness of the sequences to the structure of the complex and that of the uncomplexed proteins. We applied the developed index to the complexes formed between influenza A hemagglutinin (HA) and four antibodies. The antibody-antigen binding region of HA is under strong selection pressure by the host immune system. Hence, examination of the long-term adaptation of HA to the four antibodies could reveal the strategy of the molecular evolution of HA. Two antibodies cover the HA receptor-binding region, while the other two bind away from the receptor-binding region. By focusing on branches with a significant decline in binding ability, we could detect key amino acid replacements and investigate the mechanism via conditional probabilities. The contrast between the adaptations to the two types of antibodies suggests that the virus adapts to the immune system at the cost of structural change.

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“…In recent work, Watabe et al . [19] suggested empirical potentials to assess the fit of sequence variants to loop candidates generated by Monte Carlo variation of NMR peptide structures. So far, structural studies have been based on peptide structures, as no completely resolved structure of gp120 was available.…”

Section: Introductionmentioning

confidence: 99%

Structural Descriptors of gp120 V3 Loop for the Prediction of HIV-1 Coreceptor Usage

Sander

¹

,

Sing

²

,

Sommer

³

et al. 2007

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HIV-1 cell entry commonly uses, in addition to CD4, one of the chemokine receptors CCR5 or CXCR4 as coreceptor. Knowledge of coreceptor usage is critical for monitoring disease progression as well as for supporting therapy with the novel drug class of coreceptor antagonists. Predictive methods for inferring coreceptor usage based on the third hypervariable (V3) loop region of the viral gene coding for the envelope protein gp120 can provide us with these monitoring facilities while avoiding expensive phenotypic tests. All simple heuristics (such as the 11/25 rule) as well as statistical learning methods proposed to date predict coreceptor usage based on sequence features of the V3 loop exclusively. Here, we show, based on a recently resolved structure of gp120 with an untruncated V3 loop, that using structural information on the V3 loop in combination with sequence features of V3 variants improves prediction of coreceptor usage. In particular, we propose a distance-based descriptor of the spatial arrangement of physicochemical properties that increases discriminative performance. For a fixed specificity of 0.95, a sensitivity of 0.77 was achieved, improving further to 0.80 when combined with a sequence-based representation using amino acid indicators. This compares favorably with the sensitivities of 0.62 for the traditional 11/25 rule and 0.73 for a prediction based on sequence information as input to a support vector machine and constitutes a statistically significant improvement. A detailed analysis and interpretation of structural features important for classification shows the relevance of several specific hydrogen-bond donor sites and aliphatic side chains to coreceptor specificity towards CCR5 or CXCR4. Furthermore, an analysis of side chain orientation of the specificity-determining residues suggests a major role of one side of the V3 loop in the selection of the coreceptor. The proposed method constitutes the first approach to an improved prediction of coreceptor usage based on an original integration of structural bioinformatics methods with statistical learning.

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“…As Lusso [18] points out, structural understanding of coreceptor specificity is limited at the moment. In recent work, Watabe et al [19] suggested empirical potentials to assess the fit of sequence variants to loop candidates generated by Monte Carlo variation of NMR peptide structures. So far, structural studies have been based on peptide structures, as no completely resolved structure of gp120 was available.…”

Section: Structural Basis Of Coreceptor Usagementioning

confidence: 99%

Structural Descriptors of gp120 V3 Loop for the Prediction of HIV-1 Coreceptor Usage

Sander¹,

Sing²,

Sommer³

et al. 2005

View full text Add to dashboard Cite

HIV-1 cell entry commonly uses, in addition to CD4, one of the chemokine receptors CCR5 or CXCR4 as coreceptor. Knowledge of coreceptor usage is critical for monitoring disease progression as well as for supporting therapy with the novel drug class of coreceptor antagonists. Predictive methods for inferring coreceptor usage based on the third hypervariable (V3) loop region of the viral gene coding for the envelope protein gp120 can provide us with these monitoring facilities while avoiding expensive phenotypic tests. All simple heuristics (such as the 11/25 rule) as well as statistical learning methods proposed to date predict coreceptor usage based on sequence features of the V3 loop exclusively. Here, we show, based on a recently resolved structure of gp120 with an untruncated V3 loop, that using structural information on the V3 loop in combination with sequence features of V3 variants improves prediction of coreceptor usage. In particular, we propose a distance-based descriptor of the spatial arrangement of physicochemical properties that increases discriminative performance. For a fixed specificity of 0.95, a sensitivity of 0.77 was achieved, improving further to 0.80 when combined with a sequence-based representation using amino acid indicators. This compares favorably with the sensitivities of 0.62 for the traditional 11/25 rule and 0.73 for a prediction based on sequence information as input to a support vector machine and constitutes a statistically significant improvement. A detailed analysis and interpretation of structural features important for classification shows the relevance of several specific hydrogen-bond donor sites and aliphatic side chains to coreceptor specificity towards CCR5 or CXCR4. Furthermore, an analysis of side chain orientation of the specificity-determining residues suggests a major role of one side of the V3 loop in the selection of the coreceptor. The proposed method constitutes the first approach to an improved prediction of coreceptor usage based on an original integration of structural bioinformatics methods with statistical learning.

show abstract

Fold Recognition of the Human Immunodeficiency Virus Type 1 V3 Loop and Flexibility of Its Crown Structure During the Course of Adaptation to a Host

Cited by 11 publications

References 54 publications

A Likelihood-based Index of Protein Protein Binding Affinities with Application to Influenza HA Escape from Antibodies

A Likelihood-based Index of Protein Protein Binding Affinities with Application to Influenza HA Escape from Antibodies

Structural Descriptors of gp120 V3 Loop for the Prediction of HIV-1 Coreceptor Usage

Structural Descriptors of gp120 V3 Loop for the Prediction of HIV-1 Coreceptor Usage

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