Development and assessment of scoring functions for protein identification using PMF data

PMF is one of the major methods for protein identification using the MS technology. It is faster and cheaper than MS/MS. Although PMF does not differentiate trypsin-digested peptides of identical mass, which makes it less informative than MS/MS, current computational methods for PMF have the potential to improve its detection accuracy by better use of the information content in PMF spectra. We developed a number of new probability-based scoring functions for PMF protein identification based on the MOWSE algorithm. We considered a detailed distribution of matching masses in a protein database and peak intensity, as well as the likelihood of peptide matches to be close to each other in a protein sequence. Our computational methods are assessed and compared with other methods using PMF data of 52 gel spots of known protein standards. The comparison shows that our new scoring schemes have higher or comparable accuracies for protein identification in comparison to the existing methods. Our software is freely available upon request. The scoring functions can be easily incorporated into other proteomics software packages.     

Explicit treatment of force contribution from alignment tensor using overdetermined linear equations and its application in NMR structure determination

Residual dipolar coupling (RDC) provides valuable information about the orientation of each internuclear vector in a macromolecule with respect to the static magnetic field. However, structure determination utilizing RDC still remains challenging without additional restraints such as NOE. In this context, a novel approach has been developed to efficiently extract structural information from RDC by successive application of singular value decomposition (SVD) method in the course of NMR structure determination. Force contribution from the alignment tensor is rigorously formulated in the context of SVD, and assessments have been made to verify its numerical accuracy. The efficacy of this approach is illustrated by showing that RDC restraints alone can restore a distorted beta-hairpin to native-like structure using the replica-exchange molecular dynamics simulations.     

Implementation of pi-pi interactions in molecular dynamics simulation

No explicit pi-pi interaction term has been incorporated in the conventional molecular dynamics (MD) simulation programs in spite of its significant role in the folding of biomolecules and the clustering of organic chemicals. In this article, we propose a technique to emphasize the effect of pi-pi interactions using a function of energy and implement it into an MD simulation program. Several trial calculations show that the pi-pi incorporated program gives improved results consistent with experimental data on atom geometry and has no unfavorable interference with the conventional computational framework. This indicates an importance of the explicit consideration of pi-pi interactions in MD simulation.     

Common system setup for the entire catalytic cycle of cytochrome P450(cam) in quantum mechanical/molecular mechanical studies

We describe a system setup that is applicable to all species in the catalytic cycle of cytochrome P450(cam). The chosen procedure starts from the X-ray coordinates of the ferrous dioxygen complex and follows a protocol that includes the careful assignment of protonation states, comparison between different conceivable hydration schemes, and system preparation through a series of classical minimizations and molecular dynamics (MD) simulations. The resulting setup was validated by quantum mechanical/molecular mechanical (QM/MM) calculations on the resting state, the pentacoordinated ferric and ferrous complexes, Compound I, the transition state and hydroxo intermediate of the C--H hydroxylation reaction, and the product complex. The present QM/MM results are generally consistent with those obtained previously with individual setups. Concerning hydration, we find that saturating the protein interior with water is detrimental and leads to higher structural flexibility and catalytically inefficient active-site geometries. The MD simulations favor a low water density around Asp251 that facilitates side chain rotation of protonated Asp251 during the conversion of Compound 0 to Compound I. The QM/MM results for the two preferred hydration schemes (labeled SE-1 and SE-4) are similar, indicating that slight differences in the solvation close to the active site are not critical as long as camphor and the crystallographic water molecules preserve their positions in the experimental X-ray structures.     

All-atom de novo protein folding with a scalable evolutionary algorithm

The search for efficient and predictive methods to describe the protein folding process at the all-atom level remains an important grand-computational challenge. The development of multi-teraflop architectures, such as the IBM BlueGene used in this study, has been motivated in part by the large computational requirements of such studies. Here we report the predictive all-atom folding of the forty-amino acid HIV accessory protein using an evolutionary stochastic optimization technique. We implemented the optimization method as a master-client model on an IBM BlueGene, where the algorithm scales near perfectly from 64 to 4096 processors in virtual processor mode. Starting from a completely extended conformation, we optimize a population of 64 conformations of the protein in our all-atom free-energy model PFF01. Using 2048 processors the algorithm predictively folds the protein to a near-native conformation with an RMS deviation of 3.43 A in < 24 h.     

Dead-end elimination for multistate protein design

Multistate protein design is the task of predicting the amino acid sequence that is best suited to selectively and stably fold to one state out of a set of competing structures. Computationally, it entails solving a challenging optimization problem. Therefore, notwithstanding the increased interest in multistate design, the only implementations reported are based on either genetic algorithms or Monte Carlo methods. The dead-end elimination (DEE) theorem cannot be readily transfered to multistate design problems despite its successful application to single-state protein design. In this article we propose a variant of the standard DEE, called type-dependent DEE. Our method reduces the size of the conformational space of the multistate design problem, while provably preserving the minimal energy conformational assignment for any choice of amino acid sequence. Type-dependent DEE can therefore be used as a preprocessing step in any computational multistate design scheme. We demonstrate the applicability of type-dependent DEE on a set of multistate design problems and discuss its strength and limitations.     

Renaturation with simultaneous purification of rhG-CSF from Escherichia coli by ion exchange chromatography

Protein refolding is a key step for the production of recombinant proteins, especially at large scales, and usually their yields are very low. Application of liquid chromatography to protein refolding is an exciting step forward for this field. In this work, recombinant human granulocyte colony-stimulating factor (rhG-CSF) expressed in Escherichia coli was renatured with simultaneous purification by ion exchange chromatography (IEC) with a Q Sepharose FF column. Several chromatographic parameters affecting the refolding yield of the denatured/reduced rhG-CSF, such as the urea concentration, pH value, concentration and ratio of reduced/oxidized glutathione in the mobile phase, as well as the flow rate of the mobile phase, were investigated in detail and indicated that the urea concentration and the pH value were of great importance. At the optimal conditions, the renatured and purified rhG-CSF was found to have a specific bioactivity of 3.0 x 10(8) IU/mg, a purity of 96%, and a mass recovery of 49%. Compared with the usual dilution method, the IEC method developed here is more effective for rhG-CSF refolding in terms of specific bioactivity and mass recovery.     

Surface plasmon resonance imaging for affinity analysis of aptamer–protein interactions with PDMS microfluidic chips

We report on the use of PDMS multichannels for affinity studies of DNA aptamer–human Immunoglobulin E (IgE) interactions by surface plasmon resonance imaging (SPRi). The sensing surface was prepared with thiol-terminated aptamers through a self-assembling process in the PDMS channels defined on a gold substrate. Cysteamine was codeposited with the thiol aptamers to promote proper spatial arrangement of the aptamers and thus maintain their optimal binding efficiencies. Four aptamers with different nucleic acid sequences were studied to test their interaction affinity toward IgE, and the results confirmed that aptamer I (5′-SH-GGG GCA CGT TTA TCC GTC CCT CCT AGT GGC GTG CCC C-3′) has the strongest binding affinity. Control experiments were conducted with a PEG-functionalized surface and IgG was used to replace IgE in order to verify the selective binding of aptamer I to the IgE molecules. A linear concentration-dependent relationship between IgE and aptamer I was obtained, and a 2-nM detection limit was achieved. SPRi data were further analyzed by global fitting, and the dissociation constant of aptamer I–IgE complex was found to be 2.7 × 10⁻⁷ M, which agrees relatively well with the values reported in the literature. Aptamer affinity screening by SPR imaging demonstrates marked advantages over competing methods because it does not require labeling, can be used in real-time, and is potentially high-throughput. The ability to provide both qualitative and quantitative results on a multichannel chip further establishes SPRi as a powerful tool for the study of biological interactions in a multiplexed format. Figure The SPRi sensograms and thier global fits for aptamer I and IgE interactions. Insert in the difference image obtained with the PDMS microchannel flow cell for aptamer IV, III, and I (from left to right