The expanding role of mass spectrometry in the field of vaccine development.

Biological mass spectrometry has evolved as a core analytical technology in the last decade mainly because of its unparalleled ability to perform qualitative as well as quantitative profiling of enormously complex biological samples with high mass accuracy, sensitivity, selectivity and specificity. Mass spectrometry-based techniques are also routinely used to assess glycosylation and other post-translational modifications, disulfide bond linkage, and scrambling as well as for the detection of host cell protein contaminants in the field of biopharmaceuticals. The role of mass spectrometry in vaccine development has been very limited but is now expanding as the landscape of global vaccine development is shifting towards the development of recombinant vaccines. In this review, the role of mass spectrometry in vaccine development is presented, some of the ongoing efforts to develop vaccines for diseases with global unmet medical need are discussed and the regulatory challenges of implementing mass spectrometry techniques in a quality control laboratory setting are highlighted.

Using polarizable POSSIM force field and fuzzy-border continuum solvent model to calculate pK(a) shifts of protein residues.

Our Fuzzy-Border (FB) continuum solvent model has been extended and modified to produce hydration parameters for small molecules using POlarizable Simulations Second-order Interaction Model (POSSIM) framework with an average error of 0.136 kcal/mol. It was then used to compute pKa shifts for carboxylic and basic residues of the turkey ovomucoid third domain (OMTKY3) protein. The average unsigned errors in the acid and base pKa values were 0.37 and 0.4 pH units, respectively, versus 0.58 and 0.7 pH units as calculated with a previous version of polarizable protein force field and Poisson Boltzmann continuum solvent. This POSSIM/FB result is produced with explicit refitting of the hydration parameters to the pKa values of the carboxylic and basic residues of the OMTKY3 protein; thus, the values of the acidity constants can be viewed as additional fitting target data. In addition to calculating pKa shifts for the OMTKY3 residues, we have studied aspartic acid residues of Rnase Sa. This was done without any further refitting of the parameters and agreement with the experimental pKa values is within an average unsigned error of 0.65 pH units. This result included the Asp79 residue that is buried and thus has a high experimental pKa value of 7.37 units. Thus, the presented model is capable or reproducing pKa results for residues in an environment that is significantly different from the solvated protein surface used in the fitting. Therefore, the POSSIM force field and the FB continuum solvent parameters have been demonstrated to be sufficiently robust and transferable. © 2016 Wiley Periodicals, Inc.

Calculating pKa values for substituted phenols and hydration energies for other compounds with the first-order Fuzzy-Border continuum solvation model.

We have computed pK(a) values for 11 substituted phenol compounds using the continuum Fuzzy-Border (FB) solvation model. Hydration energies for 40 other compounds, including alkanes, alkenes, alkynes, ketones, amines, alcohols, ethers, aromatics, amides, heterocycles, thiols, sulfides, and acids have been calculated. The overall average unsigned error in the calculated acidity constant values was equal to 0.41 pH units and the average error in the solvation energies was 0.076 kcal/mol. We have also reproduced pK(a) values of propanoic and butanoic acids within about 0.1 pH units from the experimental values by fitting the solvation parameters for carboxylate ion carbon and oxygen atoms. The FB model combines two distinguishing features. First, it limits the amount of noise which is common in numerical treatment of continuum solvation models by using fixed-position grid points. Second, it uses either second- or first-order approximation for the solvent polarization, depending on a particular implementation. These approximations are similar to those used for solute and explicit solvent fast polarization treatment which we developed previously. This article describes results of using the first-order technique. This approximation places the presented methodology between the Generalized Born and Poisson-Boltzmann continuum solvation models with respect to their accuracy of reproducing the many-body effects in modeling a continuum solvent.

Selection of carbon nanotubes with specific chiralities using helical assemblies of flavin mononucleotide.

The chirality of single-walled carbon nanotubes affects many of their physical and electronic properties. Current production methods result in nanotubes of mixed chiralities, so facile extraction of specific chiralities of single-walled carbon nanotubes is an important step in their effective utilization. Here we show that the flavin mononucleotide, a common redox cofactor, wraps around single-walled carbon nanotubes in a helical pattern that imparts efficient individualization and chirality selection. The cooperative hydrogen bonding between adjacent flavin moieties results in the formation of a helical ribbon, which organizes around single-walled carbon nanotubes through concentric pi-pi interactions between the flavin mononucleotide and the underlying graphene wall. The strength of the helical flavin mononucleotide assembly is strongly dependent on nanotube chirality. In the presence of a surfactant, the flavin mononucleotide assembly is disrupted and replaced without precipitation by a surfactant micelle. The significantly higher affinity of the flavin mononucleotide assembly for (8,6)-single-walled carbon nanotubes results in an 85% chirality enrichment from a nanotube sample with broad diameter distribution.