Arrangement of Hydrogen Bonds in Aqueous Solutions of Different Globular Proteins.

This work presents the first evidence that dissolved globular proteins change the arrangement of hydrogen bonds in water, with different proteins showing quantitatively different effects. Using ATR-FTIR (attenuated total reflection-Fourier transform infrared) spectroscopic analysis of OH-stretch bands, we obtain quantitative estimates of the relative amounts of the previously reported four subpopulations of water structures coexisting in a variety of aqueous solutions. Where solvatochromic dyes can measure the properties of solutions of non-ionic polymers, the results correlate well with ATR-FTIR measurements. In protein solutions to which solvatochromic dye probes cannot be applied, NMR (nuclear magnetic resonance) spectroscopy was used for the first time to estimate the hydrogen bond donor acidity of water. We found strong correlations between the solvent acidity and arrangement of hydrogen bonds in aqueous solutions for several globular proteins. Even quite similar proteins are found to change water properties in dramatically different ways.

Interfacial tension and mechanism of liquid-liquid phase separation in aqueous media.

The organization of multiple subcellular compartments is controlled by liquid-liquid phase separation. Phase separation of this type occurs with the emergence of interfacial tension. Aqueous two-phase systems formed by two non-ionic polymers can be used to separate and analyze biological macromolecules, cells and viruses. Phase separation in these systems may serve as the simple model of phase separation in cells also occurring in aqueous media. To better understand liquid-liquid phase separation mechanisms, interfacial tension was measured in aqueous two-phase systems formed by dextran and polyethylene glycol and by polyethylene glycol and sodium sulfate in the presence of different additives. Interfacial tension values depend on differences between the solvent properties of the coexisting phases, estimated experimentally by parameters representing dipole-dipole, ion-dipole, ion-ion, and hydrogen bonding interactions. Based on both current and literature data, we propose a mechanism for phase separation in aqueous two-phase systems. This mechanism is based on the fundamental role of intermolecular forces. Although it remains to be confirmed, it is possible that these may underlie all liquid-liquid phase separation processes in biology.

Hydrogen Bond Arrangement Is Shown to Differ in Coexisting Phases of Aqueous Two-Phase Systems.

Analysis by attenuated total reflection-Fourier transform infrared spectroscopy shows that each coexisting phase in aqueous two-phase systems has a different arrangement of hydrogen bonds. Specific arrangements vary for systems formed by different solutes. The hydrogen bond arrangement is shown to correlate with differences in hydrophobic and electrostatic properties of the different phases of five specific systems, four formed by two polymers and one by a single polymer and salt. The results presented here suggest that the arrangement of hydrogen bonds may be an important factor in phase separation.

Protein crystallization: virtual screening and optimization.

Advances in genomics have yielded entire genetic sequences for a variety of prokaryotic and eukaryotic organisms. This accumulating information has escalated the demands for three-dimensional protein structure determinations. As a result, high-throughput structural genomics has become a major international research focus. This effort has already led to several significant improvements in X-ray crystallographic and nuclear magnetic resonance methodologies. Crystallography is currently the major contributor to three-dimensional protein structure information. However, the production of soluble, purified protein and diffraction-quality crystals are clearly the major roadblocks preventing the realization of high-throughput structure determination. This paper discusses a novel approach that may improve the efficiency and success rate for protein crystallization. An automated nanodispensing system is used to rapidly prepare crystallization conditions using minimal sample. Proteins are subjected to an incomplete factorial screen (balanced parameter screen), thereby efficiently searching the entire "crystallization space" for suitable conditions. The screen conditions and scored experimental results are subsequently analyzed using a neural network algorithm to predict new conditions likely to yield improved crystals. Results based on a small number of proteins suggest that the combination of a balanced incomplete factorial screen and neural network analysis may provide an efficient method for producing diffraction-quality protein crystals.

Efficient protein crystallization.

High-throughput molecular biology and crystallography advances have placed an increasing demand on crystallization, the one remaining bottleneck in macromolecular crystallography. This paper describes three experimental approaches, an incomplete factorial crystallization screen, a high-throughput nanoliter crystallization system, and the use of a neural net to predict crystallization conditions via a small sample (approximately 0.1%) of screening results. The use of these technologies has the potential to reduce time and sample requirements. Initial experimental results indicate that the incomplete factorial design detects initial crystallization conditions not previously discovered using commercial screens. This may be due to the ability of the incomplete factorial screen to sample a broader portion of "crystallization space," using a multidimensional set of components, concentrations, and physical conditions. The incomplete factorial screen is complemented by a neural network program used to model crystallization. This capability is used to help predict new crystallization conditions. An automated, nanoliter crystallization system, with a throughput of up to 400 conditions/h in 40-nl droplets (total volume), accommodates microbatch or traditional "sitting-drop" vapor diffusion experiments. The goal of this research is to develop a fully-automated high-throughput crystallization system that integrates incomplete factorial screen and neural net capabilities.