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Online Journal of Bioinformatics ©
Volume 8 (1):45-55, 2007
Analysis of MMFF94x and AMBER99 force fields
using aspartic, serine
metallo-proteases and sugar-binding protein data sets.
Singh H1, Marla SS2, Verma D3
1,2,3 Biotechnology and Bioinformatics
Singh H, Marla SS, Verma D, Analysis of MMFF94x and AMBER99 force fields using aspartic, serine, metallo-proteases and sugar-binding protein data sets, Online J Bioinformatics, 8 (1) 45-55, 2007. Force fields vary in that they are developed to be applied to different aspects of bio-organic chemistry. They are all developed differently and with specific sets of data. It has been found that although there are significant differences in modern day force fields, they all perform at the same magnitude of precision. Although there are differences but each one has its own strength due to the intended application during development and the data sets used to derive and parameterize them. In this work MMFF94x & AMBER99 force fields were applied for energy minimization on proteins belonging to different classes e.g. Aspartic Proteases, Serine Proteases, Metallo-proteases, Sugar-binding proteins. Since both the force fields are successful in their respective terms, a question remains unanswered; Out of the two, MMFF94 & AMBER, which force field should we use for energy minimization of proteins? In this study we have tried to evaluate this question by dividing the proteins in their respective classes, finding their initial and final energies and finally applying statistical techniques (paired test). This was done by using MOE (Molecular Operating Environment) software Package from Chemical Computing Group. It was observed that the selection of force field should be on the basis of class of protein to which that protein belongs.