Abstract
BackgroundMembrane proteins are important drug targets in many human diseases and gathering structural information regarding these proteins encourages the pharmaceutical industry to develop new molecules using structure-based drug design studies. Specifically, membrane-bound catechol-O-methyltransferase (MBCOMT) is an integral membrane protein that catalyzes the methylation of catechol substrates and has been linked to several diseases such as Parkinson’s disease and Schizophrenia. Thereby, improvements in the clinical outcome of the therapy to these diseases may come from structure-based drug design where reaching MBCOMT samples in milligram quantities are crucial for acquiring structural information regarding this target protein. Therefore, the main aim of this work was to optimize the temperature, dimethylsulfoxide (DMSO) concentration and the methanol flow-rate for the biosynthesis of recombinant MBCOMT by Pichia pastoris bioreactor methanol-induced cultures using artificial neural networks (ANN).ResultsThe optimization trials intended to evaluate MBCOMT expression by P. pastoris bioreactor cultures led to the development of a first standard strategy for MBCOMT bioreactor biosynthesis with a batch growth on glycerol until the dissolved oxygen spike, 3 h of glycerol feeding and 12 h of methanol induction. The ANN modeling of the aforementioned fermentation parameters predicted a maximum MBCOMT specific activity of 384.8 nmol/h/mg of protein at 30°C, 2.9 mL/L/H methanol constant flow-rate and with the addition of 6% (v/v) DMSO with almost 90% of healthy cells at the end of the induction phase. These results allowed an improvement of MBCOMT specific activity of 6.4-fold in comparison to that from the small-scale biosynthesis in baffled shake-flasks.ConclusionsThe ANN model was able to describe the effects of temperature, DMSO concentration and methanol flow-rate on MBCOMT specific activity, as shown by the good fitness between predicted and observed values. This experimental procedure highlights the potential role of chemical chaperones such as DMSO in improving yields of recombinant membrane proteins with a different topology than G-coupled receptors. Finally, the proposed ANN shows that the manipulation of classic fermentation parameters coupled with the addition of specific molecules can open and reinforce new perspectives in the optimization of P. pastoris bioprocesses for membrane proteins biosynthesis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12934-015-0304-7) contains supplementary material, which is available to authorized users.
Highlights
Membrane proteins are important drug targets in many human diseases and gathering structural information regarding these proteins encourages the pharmaceutical industry to develop new molecules using structure-based drug design studies
After selecting a set of independent variables associated with the methanol induction phase that greatly influence the levels of the membrane-bound catechol-O-methyltransferase (MBCOMT), artificial neural networks (ANN) modeling was carried out in order to maximize the biological activity of the target protein
Membrane-bound catechol-O-methyltransferase biosynthesis in a highly biological active form was successfully attained for the first time by P. pastoris bioreactor cultures under the control of the alcohol oxidase I gene (AOX) promoter
Summary
Membrane proteins are important drug targets in many human diseases and gathering structural information regarding these proteins encourages the pharmaceutical industry to develop new molecules using structure-based drug design studies. Membrane proteins (MP) are central to many cellular processes: they are involved in the uptake and export of diverse charged and uncharged molecules, as well as mediating the interaction of cells with their environment [1] As a consequence, they are of prime importance as drug targets to the pharmaceutical industry [1]. Over the past few years, many efforts have allowed relevant advances in the development of P. pastoris for the production of MP where significant achievements were made in order to improve yield and proper folding of these target proteins [10] Chemical chaperones such as dimethylsulfoxide (DMSO) have been shown to increase the expression of different G protein-coupled receptors such as the human neuromedin U subtype II receptor [11], the human adenosine A2A receptor or the human β2-adrenergic receptor [12], mostly due to the up-regulation of the expression of genes involved in membrane lipid components [10, 13]. ANNs coupled with design of experiments have been successfully applied in diverse areas such as the optimization of the culture conditions [16, 18], pharmaceutics [19] or chromatography [15, 20]
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