Leveraging Machine Learning Models for Peptide-Protein Interaction Prediction

Peptides play a pivotal role in a wide range of biological activities through participating in up to 40% protein-protein interactions in cellular processes. They also demonstrate remarkable specificity and efficacy, making them promising candidates for drug development. However, predicting peptide-protein complexes by traditional computational approaches, such as Docking and Molecular Dynamics simulations, still remains a challenge due to high computational cost, flexible nature of peptides, and limited structural information of peptide-protein complexes. In recent years, the surge of available biological data has given rise to the development of an increasing number of machine learning models for predicting peptide-protein interactions. These models offer efficient solutions to address the challenges associated with traditional computational approaches. Furthermore, they offer enhanced accuracy, robustness, and interpretability in their predictive outcomes. This review presents a comprehensive overview of machine learning and deep learning models that have emerged in recent years for the prediction of peptide-protein interactions.Comment: 46 pages, 10 figure

Functional Haplotypes of the hTERT Gene, Leukocyte Telomere Length Shortening, and the Risk of Peripheral Arterial Disease

Background: The development of peripheral arterial disease (PAD) is heterogeneous even in the presence of similar risk factors. Our aim was to determine whether inter-individual differences in leukocyte telomere length contribute to the susceptibility of PAD. Methods A total of 485 patients with PAD (defined by the ankle-brachial index) and 970 age- and gender-matched controls were recruited from seven rural communities in Henan Province in China. The relative leukocyte telomere length was determined by a quantitative PCR-based method. Two common promoter variants of the hTERT gene were genotyped to assess their effects on telomere length and the risk of PAD. In vivo luciferase assay was performed to study the transcriptional activity. Results: After adjustment for vascular risk factors and genetic variants in the hTERT gene, individuals in the lowest and middle tertiles of telomere length had a significantly higher risk of PAD than did those in the highest tertile (odds ratio [OR] 1.73, 95% confidence interval [CI] 1.29–2.49 in the middle tertile; 3.15, 95%CI 2.31–4.29 in the lowest tertile). Haplotype analysis using the 2 variants (rs2735940 and rs2853669) showed that subjects with the at-risk C-C haplotype had shorter telomere length than those individuals with the T-T haplotype and consistently had 1.30-fold (OR 1.30, 95%CI 1.06–1.58; P = 0.005) increased risk for PAD. The C-C haplotype had 43% lowered transcription activity of hTERT promoter (P<0.001). Conclusion: The associations between the functional haplotype of hTERT gene and telomere length and the risk of atherosclerotic PAD suggested that mean leukocyte telomere length may independently serve as a potential predictor of PAD

MicroRNA-216a Promotes Endothelial Inflammation by Smad7/IκBα Pathway in Atherosclerosis

Background. The endothelium is the first line of defence against harmful microenvironment risks, and microRNAs (miRNAs) involved in vascular inflammation may be promising therapeutic targets to modulate atherosclerosis progression. In this study, we aimed to investigate the mechanism by which microRNA-216a (miR-216a) modulated inflammation activation of endothelial cells. Methods. A replicative senescence model of human umbilical vein endothelial cells (HUVECs) was established, and population-doubling levels (PDLs) were defined during passages. PDL8 HUVECs were transfected with miR-216a mimics/inhibitor or small interfering RNA (siRNA) of SMAD family member 7 (Smad7). Real-time PCR and Western blot assays were performed to detect the regulatory role of miR-216a on Smad7 and NF-κB inhibitor alpha (IκBα) expression. The effect of miR-216a on adhesive capability of HUVECs to THP-1 cells was examined. MiR-216a and Smad7 expression in vivo were measured using human carotid atherosclerotic plaques of the patients who underwent carotid endarterectomy (n=41). Results. Luciferase assays showed that Smad7 was a direct target of miR-216a. Smad7 mRNA expression, negatively correlated with miR-216a during endothelial aging, was downregulated in senescent PDL44 cells, compared with young PDL8 HUVECs. MiR-216a markedly increased endothelial inflammation and adhesive capability to monocytes in PDL8 cells by promoting the phosphorylation and degradation of IκBα and then activating NF-κB signalling pathway. The effect of miR-216a on endothelial cells was consistent with that blocked Smad7 by siRNAs. When inhibiting endogenous miR-216a, the Smad7/IκBα expression was rescued, which led to decreased endothelial inflammation and monocytes recruitment. In human carotid atherosclerotic plaques, Smad7 level was remarkably decreased in high miR-216a group compared with low miR-216a group. Moreover, miR-216a was negatively correlated with Smad7 and IκBα levels and positively correlated with interleukin 1 beta (IL1β) expression in vivo. Conclusion. In summary, our findings suggest a new mechanism of vascular endothelial inflammation involving Smad7/IκBα signalling pathway in atherosclerosis

Risk of peripheral arterial disease in different tertiles of leukocyte mean telomere length.

<p>PAD indicates peripheral arterial disease; CI, confidence interval.</p>*<p>Odds ratio and 95%CI were obtained with multivariate conditional logistic regression analysis.</p>†<p>Model I: Adjustment for body mass index, systolic and diastolic blood pressure, smoking, alcohol intake, fasting glucose, triglycerides, total cholesterol, HDL cholesterol, and LDL cholesterol.</p>‡<p>Model II: Adjustment for the covariates mentioned above plus diabetes, history of hypertension, previous cardiovascular disease, and medication treatment.</p>§<p>Model III: Adjustment for individual genetic variants rs2735940 and rs2853669 of the <i>hTERT</i> gene, except for the covariates mentioned in Model II.</p

Haplotype effect of variants rs2735940 and rs2853669 on the promoter transcription activity of <i>hTERT</i> gene.

<p>The luciferase reporter plasmids containing the <i>hTERT</i> gene promoter region with haplotype T-T, T-C, C-T, or C-C (rs2735940 and rs2853669) were constructed and then transfected into Hek293S cells. (A) Without co-transfection of transcription factors Ets2 and c-Myc; (B) With co-transfection of Ets2; (C) With co-transfection of c-Myc; (D) With co-transfection of both Ets2 and c-Myc. Data shown are the means ± SD, n = 3. **<i>P</i><0.001, compared with the relative luciferase activity of the wild-type haplotype T-T.</p

Characteristics of peripheral arterial disease patients and control subjects.^*

<p>PAD indicates peripheral arterial disease; HDL, high-density lipoprotein cholesterol; LDL, low-density lipoprotein cholesterol; T, telomere repeat copy; S, single-copy gene <i>globin</i> copy.</p>*<p>Data are given as mean ± SD, numbers (percentage) or medians (interquartile range). Telomere length is expressed as a relative telomere/single-copy gene (T/S) ratio.</p>†<p><i>P</i> value was calculated between PAD patients and control subjects by the two-sample <i>t</i>-test for comparison of continuous variables, the χ² test for categorical variables, and the Mann-Whitney U test for triglycerides and telomere length.</p

Novel serum metabolites associate with cognition phenotypes among Bogalusa Heart Study participants.

BackgroundMetabolomics study provides an opportunity to identify novel molecular determinants of altered cognitive function.MethodsDuring 2013 to 2016 Bogalusa Heart Study (BHS) visit, 1,177 participants underwent untargeted, ultrahigh performance liquid chromatography-tandem mass spectroscopy metabolomics profiling. Global cognition and five cognition domains were also assessed. The cross-sectional associations of single metabolites with cognition were tested using multiple linear regression models. Weighted correlation network analysis was used to examine the covariable-adjusted correlations of modules of co-abundant metabolites with cognition. Analyses were conducted in the overall sample and according to both ethnicity and sex.ResultsFive known metabolites and two metabolite modules robustly associated with cognition across overall and stratified analyses. Two metabolites were from lipid sub-pathways including fatty acid metabolism [9-hydroxystearate; minimum P-value (min-P)=1.11×10-5], and primary bile acid metabolism (glyco-alpha-muricholate; min-P=4.10×10-5). One metabolite from the glycogen metabolism sub-pathway (maltose; min-P=9.77×10-6), one from the polyamine metabolism sub-pathway (N-acetyl-isoputreanine; min-P=1.03×10-5), and one from the purine metabolism sub-pathway (7-methylguanine; min-P=1.19×10-5) were also identified. Two metabolite modules reflecting bile acid metabolism and androgenic steroids correlated with cognition (min-P=5.00×10-4 and 3.00×10-3, respectively).ConclusionThe novel associations of 5 known metabolites and 2 metabolite modules with cognition provide insights into the physiological mechanisms regulating cognitive function

Haplotype analysis of variants rs2735940 and rs2853669 and the risk of peripheral arterial disease.

*<p>Haplotype analysis was conducted on the basis of the Stochastic-EM algorithm using THESIAS program. Haplotypes possess 2 loci rs2735940 and rs2853669 from left to right.</p>†<p>Multivariable model I: Adjustment for conventional risk factors, including body mass index, triglycerides, total cholesterol, HDL cholesterol, blood glucose, blood pressure, smoking, alcohol intake, diabetes, history of hypertension, and medication treatment.</p>‡<p>Multivariable model II: Adjustment for telomere lengths, except for those covariates mentioned in model I.</p

Correlations between telomere length and <i>hTERT</i> gene variants.

<p>Data shown were the means ± S.E.M. S.E.M. denotes standard error of the mean. Multiple linear regression analysis was used to compare the mean leukocyte telomere lengths by genotypes of rs2853669 (Panel A) or by haplotypes containing rs2735940 and rs2853669 (Panel B) in the <i>hTERT</i> gene promoter region among PAD patients and control subjects, respectively, after adjustment for age, gender, and conventional vascular risk factors. Haplotype analysis was conducted on the basis of the Stochastic-EM algorithm using THESIAS program, and possesses 2 loci rs2735940 and rs2853669 from left to right. **<i>P</i> = 0.005, compared with wild-type TT genotype; <i>P</i> = 0.002 and <i>P</i> = 0.08, compared with wild-type T-T haplotype.</p

Novel serum metabolites associate with cognition phenotypes among Bogalusa Heart Study participants.

BackgroundMetabolomics study provides an opportunity to identify novel molecular determinants of altered cognitive function.MethodsDuring 2013 to 2016 Bogalusa Heart Study (BHS) visit, 1,177 participants underwent untargeted, ultrahigh performance liquid chromatography-tandem mass spectroscopy metabolomics profiling. Global cognition and five cognition domains were also assessed. The cross-sectional associations of single metabolites with cognition were tested using multiple linear regression models. Weighted correlation network analysis was used to examine the covariable-adjusted correlations of modules of co-abundant metabolites with cognition. Analyses were conducted in the overall sample and according to both ethnicity and sex.ResultsFive known metabolites and two metabolite modules robustly associated with cognition across overall and stratified analyses. Two metabolites were from lipid sub-pathways including fatty acid metabolism [9-hydroxystearate; minimum P-value (min-P)=1.11×10-5], and primary bile acid metabolism (glyco-alpha-muricholate; min-P=4.10×10-5). One metabolite from the glycogen metabolism sub-pathway (maltose; min-P=9.77×10-6), one from the polyamine metabolism sub-pathway (N-acetyl-isoputreanine; min-P=1.03×10-5), and one from the purine metabolism sub-pathway (7-methylguanine; min-P=1.19×10-5) were also identified. Two metabolite modules reflecting bile acid metabolism and androgenic steroids correlated with cognition (min-P=5.00×10-4 and 3.00×10-3, respectively).ConclusionThe novel associations of 5 known metabolites and 2 metabolite modules with cognition provide insights into the physiological mechanisms regulating cognitive function