Quantification of Soluble or Insoluble Fractions of Leishmania Parasite Proteins in Microvolume Applications: A Simplification to Standard Lowry Assay.

Protein quantification is often an important step in the field of research involving protein. Although the standard Lowry assay and the most abundant modifications used in quantifying protein, the method that is rigid or often exhibit non-linear between protein concentration and color intensity.

 A fast and accurate method for qualitative Porcine Recombinant Proteins and / or quantitative determination of the amount of protein that is soluble / insoluble or micro-well plate immobilized protein isolated from the parasite Leishmania in microvolumes described in this study. Improvements in cost-effective techniques necessary to enhance the research output in resource-limited settings. 

This method is a modification to the Lowry assay was established for quantification of the protein. The concentration of unknown samples is calculated using a standard curve prepared using a standard series of bovine serum albumin (BSA). optimized reagent is 2 N NaOH (sodium hydroxide), 2% Na2CO3 (sodium carbonate), 1% CuSO4 (copper sulfate), 2% KNaC4H4O6 (potassium sodium tartrate), and 2 N Folin and Ciocalteu's phenol. 

These modified proteins sensitive test to measure the Leishmania protein in the crude extract totally or partially dissolve in the estimated range of 10-500 mg / ml (1-50 mg / test) and showed linearity between the color intensity and the protein concentration. It is easier, faster method, and accurate way to measure proteins with microvolumes with cost-effective way for routine use in research laboratories in resource-limited settings.

ISP-RAAC: identification of secretory proteins of the malaria parasite uses reduced amino acid composition.

As the malaria pathogen, parasite malaria secrete a variety of proteins for growth and reproduction.The identification of secretory proteins of the malaria parasite has important reference significance for anti-malaria vaccine development and medicine.In this study, computational classification method developed to identify proteins secreted from Plasmodium. 

Amino acid composition, the composition of the dipeptide and tripeptide composition and reduce amino acid alphabet proposed to illuminate protein sequences, we are more used SVM to train and predict each and optimized features.74 type Rabbit Recombinant Proteins of amino acid decreases the alphabet are used to predict the secretory proteins, the research results indicates that the enhanced accuracy of 91.67% with a correlation coefficient of 0.84 this Mathew (PKS) with a dipeptide composition, and the highest reaching 92.26% prediction accuracy of selection feature, which shows that our method is reputable and reliable in the field of malaria parasite proteins prediction secreted