Sustained performance of knowledge-based potentials in fold recognition

Domingues, Francisco S.; Koppensteiner, Walter A.; Jaritz, Markus; Prlić, Andreas; Weichenberger, Christian X.; Wiederstein, Markus; Floeckner, Hannes; Lackner, Peter; Sippl, Manfred J.

doi:10.1002/(sici)1097-0134(1999)37:3+<112::aid-prot15>3.0.co;2-r

Cited by 46 publications

(26 citation statements)

References 18 publications

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“…Sequence-structure alignments were generated with the Smith-Waterman algorithm (9). Two mean force potentials describing the energetic forces between the residues of a fold and between residues and the surrounding solvent were used to calculate the sequencestructure fitness (10,11). Default ProHit values for gap restrictions were used to control the number, size, and placement of gaps in the query sequence and the fold library entries.…”

Section: Generating Structure-based Protein Function Hypothesismentioning

confidence: 99%

Cutting Edge: Novel Human Dendritic Cell- and Monocyte-Attracting Chemokine-Like Protein Identified by Fold Recognition Methods

Pisabarro

Leung²,

Kwong³

et al. 2006

The Journal of Immunology

171

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Chemokines play an important role in the immune system by regulating cell trafficking in homeostasis and inflammation. In this study, we report the identification and characterization of a novel cytokine-like protein, DMC (dendritic cell and monocyte chemokine-like protein), which attracts dendritic cells and monocytes. The key to the identification of this putative new chemokine was the application of threading techniques to its uncharacterized sequence. Based on our studies, DMC is predicted to have an IL-8-like chemokine fold and to be structurally and functionally related to CXCL8 and CXCL14. Consistent with our predictions, DMC induces migration of monocytes and immature dendritic cells. Expression studies show that DMC is constitutively expressed in lung, suggesting a potential role for DMC in recruiting monocytes and dendritic cells from blood into lung parenchyma.

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Section: Generating Structure-based Protein Function Hypothesismentioning

confidence: 99%

Cutting Edge: Novel Human Dendritic Cell- and Monocyte-Attracting Chemokine-Like Protein Identified by Fold Recognition Methods

Pisabarro

Leung²,

Kwong³

et al. 2006

The Journal of Immunology

171

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“…The ProCeryon program package was used as the main prediction tool for molecular modeling (ProHit package ProCeryon Biosciences GmbH, Salzburg, Austria). It uses knowledge-based potentials for atom pair and protein solvent interactions that were derived from a database of known structures (Domingues et al, 1999). The resulting models were evaluated using different ProSA II (King's Beech Biosoftware) type z-scores based on pair interactions and surface terms.…”

Section: Sequence Analysis and Molecular Modelingmentioning

confidence: 99%

PARP-10, a novel Myc-interacting protein with poly(ADP-ribose) polymerase activity, inhibits transformation

et al. 2005

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“…Distributions of atomic distances have been used successfully in structure comparison [26,27]. In protein structure prediction, distributions of distances have been applied as knowledgebased potentials to evaluate the fit of a sequence to a specific structure [28,29].…”

Section: Novel Structural Descriptor and Related Methodsmentioning

confidence: 99%

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

Sander¹,

Sing²,

Sommer³

et al. 2005

PLoS Comput Biol

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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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Sustained performance of knowledge-based potentials in fold recognition

Cited by 46 publications

References 18 publications

Cutting Edge: Novel Human Dendritic Cell- and Monocyte-Attracting Chemokine-Like Protein Identified by Fold Recognition Methods

Cutting Edge: Novel Human Dendritic Cell- and Monocyte-Attracting Chemokine-Like Protein Identified by Fold Recognition Methods

PARP-10, a novel Myc-interacting protein with poly(ADP-ribose) polymerase activity, inhibits transformation

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

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