Dataset Information

Using a Classifier Fusion Strategy to Identify Anti-angiogenic Peptides.

ABSTRACT: Anti-angiogenic peptides perform distinct physiological functions and potential therapies for angiogenesis-related diseases. Accurate identification of anti-angiogenic peptides may provide significant clues to understand the essential angiogenic homeostasis within tissues and develop antineoplastic therapies. In this study, an ensemble predictor is proposed for anti-angiogenic peptide prediction by fusing an individual classifier with the best sensitivity and another individual one with the best specificity. We investigate predictive capabilities of various feature spaces with respect to the corresponding optimal individual classifiers and ensemble classifiers. The accuracy and Matthew's Correlation Coefficient (MCC) of the ensemble classifier trained by Bi-profile Bayes (BpB) features are 0.822 and 0.649, respectively, which represents the highest prediction results among the investigated prediction models. Discriminative features are obtained from BpB using the Relief algorithm followed by the Incremental Feature Selection (IFS) method. The sensitivity, specificity, accuracy, and MCC of the ensemble classifier trained by the discriminative features reach up to 0.776, 0.888, 0.832, and 0.668, respectively. Experimental results indicate that the proposed method is far superior to the previous study for anti-angiogenic peptide prediction.

SUBMITTER: Zhang L

PROVIDER: S-EPMC6138733 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Using a Classifier Fusion Strategy to Identify Anti-angiogenic Peptides.

Zhang Lina L Yang Runtao R Zhang Chengjin C

Scientific reports 20180914 1

Anti-angiogenic peptides perform distinct physiological functions and potential therapies for angiogenesis-related diseases. Accurate identification of anti-angiogenic peptides may provide significant clues to understand the essential angiogenic homeostasis within tissues and develop antineoplastic therapies. In this study, an ensemble predictor is proposed for anti-angiogenic peptide prediction by fusing an individual classifier with the best sensitivity and another individual one with the best ...[more]

PMID: 30218091

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Project description:Abnormal migration and proliferation of endothelial cells (EC) drive neovascular retinopathies. While anti-VEGF treatment slows progression, pathology is often supported by decrease in intraocular pigment epithelium-derived factor (PEDF), an endogenous inhibitor of angiogenesis. A surface helical 34-mer peptide of PEDF, comprising this activity, is efficacious in animal models of neovascular retina disease but remains impractically large for therapeutic use. We sought smaller fragments within this sequence that mitigate choroidal neovascularization (CNV). Expecting rapid intravitreal (IVT) clearance, we also developed a method to reversibly attach peptides to nano-carriers for extended delivery. Synthetic fragments of 34-mer yielded smaller anti-angiogenic peptides, and N-terminal capping with dicarboxylic acids did not diminish activity. Charge restoration via substitution of an internal aspartate by asparagine improved potency, achieving low nM apoptotic response in VEGF-activated EC. Two optimized peptides (PEDF 335, 8-mer and PEDF 336, 9-mer) were tested in a mouse model of laser-induced CNV. IVT injection of either peptide, 2-5 days before laser treatment, gave significant CNV decrease at day +14 post laser treatment. The 8-mer also decreased CNV, when administered as eye drops. Also examined was a nanoparticle-conjugate (NPC) prodrug of the 9-mer, having positive zeta potential, expected to display longer intraocular residence. This NPC showed extended efficacy, even when injected 14 days before laser treatment. Neither inflammatory cells nor other histopathologic abnormalities were seen in rabbit eyes harvested 14 days following IVT injection of PEDF 336 (>200 ?g). No rabbit or mouse eye irritation was observed over 12-17 days of PEDF 335 eye drops (10 mM). Viability was unaffected in 3 retinal and 2 choroidal cell types by PEDF 335 up to 100 ?M, PEDF 336 (100 ?M) gave slight growth inhibition only in choroidal EC. A small anti-angiogenic PEDF epitope (G-Y-D-L-Y-R-V) was identified, variants (adipic-Sar-Y-N-L-Y-R-V) mitigate CNV, with clinical potential in treating neovascular retinopathy. Their shared active motif, Y - - - R, is found in laminin (Ln) peptide YIGSR, which binds Ln receptor 67LR, a known high-affinity ligand of PEDF 34-mer.

Dataset Information

Using a Classifier Fusion Strategy to Identify Anti-angiogenic Peptides.

Publications

Using a Classifier Fusion Strategy to Identify Anti-angiogenic Peptides.

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