Biocomputing has moved into central position in molecular biology research. Enormous improvements in genetic engineering have led to the accumulation of a vast amount of biological information. With the advent of this extensive repertoire of raw sequence information, the next major challenge for a modern researcher is to interpret this biological information. Molecular Evolutionary Genetic Analysis (MEGA) is bio-computational software to fill the vacuum between data development and analysis. In this paper, an attempt to review the evolution of MEGA software, working and application has been made. Moreover, data analysis, implementation and advantages over other bioinformatics software have been discussed systematically.

The direction of evolution can estimate based on the variation among nonsynonymous to synonymous substitution. The simulative study investigated the nucleotide sequence of closely related strains of respiratory syndrome viruses, codon-by-codon with maximum likelihood analysis, z selection, and the divergence time. The simulated results, dN/dS > 1 signify that an entire substitution model tends towards the hypothesis's positive evolution. The effect of transition/transversion proportion, Z-test of selection, and the evolution associated with these respiratory syndromes, are also analyzed. Z-test of selection for neutral and positive evolution indicates lower to positive values of dN-dS (0.012, 0.019) due to multiple substitutions in a short span. Modified Nei-Gojobori (P) statistical technique results also favor multiple substitutions with the transition/transversion rate from 1 to 7. The divergence time analysis also supports the result of dN/dS and imparts substantiating proof of evolution. Results conclude that a positive evolution model, higher dN-dS, and transition/transversion ratio significantly analyzes the evolution trend of severe acute respiratory syndrome coronavirus 2, severe acute respiratory syndrome coronavirus, and Middle East respiratory syndrome coronavirus.

Biodiesel is an alternative source of fuel that can be synthesized from edible, non-edible and waste oils through transesterification. Firstly Transesterification reaction of Jatropha Curcas oil with butanol in the ratio of 1:25 investigated by using of sodium hydroxide catalyst with mixing intensity of 250 rpm in isothermal batch reactor. Secondly the fuzzy model of the temperature is developed. Performance was evaluated by comparing fuzzy model with the batch kinetic data. Fuzzy models were developed using adaptive neurofuzzy inference system (ANFIS). © 2011 BCREC UNDIP. All rights reserved

(Received: 27th January 2011, Revised: 13rd February 2011; Accepted: 16th February 2011)

[How to Cite: V.K. Sohpal, A. Singh, A. Dey. (2011). Fuzzy Modeling to Evaluate the Effect of Temperature on Batch Transesterification of Jatropha Curcas for Biodiesel Production. Bulletin of Chemical Reaction Engineering and Catalysis, 6(1): 31-38. doi:10.9767/bcrec.6.1.816.31-38]

[How to Link / DOI: http://dx.doi.org/10.9767/bcrec.6.1.816.31-38 ]

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Plasmodium malariae is one of the causative agents of the deadly disease, malaria. From past few years, investigators have been vigorously involved in searching for an effective cure for this disease. However, the available drugs have not yet proven to be quite effi cient in its eradication primarily because of the advanced rate of mutation of the parasite. The present study is directed towards fi nding an inhibitor against plasmepsin II, one of the aspartic protease encoded by the malarial parasite, which is essential in degrading the host hemoglobin. The structure of the biological target was used to predict candidate drugs that could bind with high affi nity and selectivity to the target. The docking behaviour of target protein (2BJU) was studied in order to fi nd out the binding sites for the inhibitor on the protein molecule. The binding pocket that was selected had Phe84 and Thr341 as their active residues, depending upon which few ligand molecules were examined. Subsequently one of the ligand exhibited the best binding properties and the drug likeliness studies were carried out. Based on these studies, it could be inferred that the selected ligand could act as a potential drug candidate and thus, could also be considered for further studies.

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