iHyd-LysSite (EPSV): Identifying Hydroxylysine Sites in Protein Using Statistical Formulation by Extracting Enhanced Position and Sequence Variant Feature Technique.

INTRODUCTION: Hydroxylation is one of the most important post-translational modifications (PTM) in cellular functions and is linked to various diseases. The addition of one of the hydroxyl groups (OH) to the lysine sites produces hydroxylysine when undergoes chemical modification. METHODS: The method which is used in this study for identifying hydroxylysine sites based on powerful mathematical and statistical methodology incorporating the sequence-order effect and composition of each object within protein sequences. This predictor is called "iHyd-LysSite (EPSV)" (identifying hydroxylysine sites by extracting enhanced position and sequence variant technique). The prediction of hydroxylysine sites by experimental methods is difficult, laborious and highly expensive. In silico technique is an alternative approach to identify hydroxylysine sites in proteins. RESULTS: The experimental results require that the predictive model should have high sensitivity and specificity values and must be more accurate. The self-consistency, independent, 10-fold cross-validation and jackknife tests are performed for validation purposes. These tests are resulted by using three renowned classifiers, Neural Networks (NN), Random Forest (RF) and Support Vector Machine (SVM) with the demanding prediction rate. The overall predictive outcomes are extraordinarily superior to the results obtained by previous predictors. The proposed model contributed an excellent prediction rate in the system for NN, RF, and SVM classifiers. The sensitivity and specificity results using all these classifiers for jackknife test are 96.08%, 94.99%, 98.16% and 97.52%, 98.52%, 80.95%. CONCLUSION: The results obtained by the proposed tool show that this method may meet the future demand of hydroxylysine sites with a better prediction rate over the existing methods.

iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition.

BACKGROUND: In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests. METHODS: With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effect within polypeptide chains, an innovative in-silico> predictor via a mathematical model is proposed. RESULTS: Later, it was stringently verified using self-consistency, cross-validation and jackknife tests on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values are superior to the values predicted by previous methodologies. CONCLUSION: This new mathematical technique is the most appropriate and encouraging as compared with the existing models.

A Novel Modeling in Mathematical Biology for Classification of Signal Peptides.

The molecular structure of macromolecules in living cells is ambiguous unless we classify them in a scientific manner. Signal peptides are of vital importance in determining the behavior of newly formed proteins towards their destined path in cellular and extracellular location in both eukaryotes and prokaryotes. In the present research work, a novel method is offered to foreknow the behavior of signal peptides and determine their cleavage site. The proposed model employs neural networks using isolated sets of prokaryote and eukaryote primary sequences. Protein sequences are classified as secretory or non-secretory in order to investigate secretory proteins and their signal peptides. In comparison with the previous prediction tools, the proposed algorithm is more rigorous, well-organized, significantly appropriate and highly accurate for the examination of signal peptides even in extensive collection of protein sequences.

Native, acidic pre-treated and composite clay efficiency for the adsorption of dicationic dye in aqueous medium.

Environmental applications of composites have attracted the interests of researchers due to their excellent adsorption efficiency for pollutants. Native, HCl pre-treated clay and MnFe2O4/clay composite were investigated as an adsorbent for removal of methyl green from aqueous solution. The adsorption behaviors of dye onto native, HCl pre-treated and composite clays were studied as a function of contact time, adsorbent dose, pH, initial dye concentration and temperature. Maximum dye adsorption of 44 mg/g was achieved at pH of 8, contact time 40 min, adsorbent dose 0.20 g/L and initial dye concentration of 125 mg/L using clay composite. The Langmuir isotherm and pseudo-second-order kinetic model best explained the methyl green dye adsorption onto clay adsorbents. Thermodynamic parameters revealed the endothermic and spontaneous adsorption nature of dye. From results, it is concluded that clay has potential for adsorbing methyl green and can be used for the removal of dyes from industrial effluents.

Usefulness of ST segment depression limited to the recovery phase of exercise stress test.

OBJECTIVE: To determine the diagnostic value of ST segment depression limited to recovery phase of Exercise Tolerance Test (ETT). STUDY DESIGN: An observational cross-sectional study. PLACE AND DURATION OF STUDY: The study was carried out at Punjab Institute of Cardiology, Lahore, from March to August 2007 for a period of 6 months. METHODOLOGY: In this study, 100 patients were selected with purposive non-probability sampling technique and were divided into two groups, group A having ST segment depression during exercise phase of ETT, and group B having ST segment depression only in recovery phase after undergoing ETT according to Bruce protocol. The patients were subjected to coronary angiography later on. The chi-square or Fischer's exact test of significance was applied at 0.05 level of significance to compare the coronary angiographic finding between two groups. Diagnostic value of ST segment depression was computed keeping angiographic finding as Gold standard. RESULTS: There were no major differences between the two groups regarding angiographic finding. Significant coronary artery stenosis (> 50% narrowing) was found in 68 (93%) patients of group A and 23 (85%) patients of group B (p=0.18). Three vessel disease was found in 30 (41%) patients in group A and 7 (26%) patients in group B (p=0.08). Left main stem disease was found in 5 (6.8%) patients of group A and 1 (3.7%) patient of group B. Normal coronaries were found in 6% of patients among group A and 14% of patients among group B (p=0.12). Specificity, sensitivity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV) of ST segment depression in recovery phase was 55, 25, 85 and 6 percent respectively (95% CI; 1.16 - 2.25). CONCLUSION: In patients undergoing exercise stress test, ST segment depression occurring only in recovery phase of ETT has a diagnostic value largely comparable with that of ST segment depression induced during exercise phase of ETT. Thus careful evaluation of ST segment depression occurring only in recovery phase may add significantly to the clinical information derived from the results of ETT.