Yunqi Li

REMO: A new protocol to refine full atomic protein models from C-alpha traces by optimizing hydrogen-bonding networks.

Protein structure prediction approaches usually perform modeling simulations based on reduced representation of protein structures. For biological utilizations, it is an important step to construct full atomic models from the reduced structure decoys. Most of the current full atomic model reconstruction procedures have defects which either could not completely remove the steric clashes among backbone atoms or generate final atomic models with worse topology similarity relative to the native structures than the reduced models. In this work, we develop a new protocol, called REMO, to generate full atomic protein models by optimizing the hydrogen‐bonding network with basic fragments matched from a newly constructed backbone isomer library of solved protein structures. The algorithm is benchmarked on 230 nonhomologous proteins with reduced structure decoys generated by I‐TASSER simulations. The results show that REMO has a significant ability to remove steric clashes, and meanwhile retains good topology of the reduced model. The hydrogen‐bonding network of the final models is dramatically improved during the procedure. The REMO algorithm has been exploited in the recent CASP8 experiment which demonstrated significant improvements of the I‐TASSER models in both atomic‐level structural refinement and hydrogen‐bonding network construction. Proteins 2009.

Predicting residue–residue contacts using random forest models

MOTIVATION Protein residue-residue contact prediction can be useful in predicting protein 3D structures. Current algorithms for such a purpose leave room for improvement. RESULTS We develop ProC_S3, a set of Random Forest algorithm-based models, for predicting residue-residue contact maps. The models are constructed based on a collection of 1490 non-redundant, high-resolution protein structures using >1280 sequence-based features. A new amino acid residue contact propensity matrix and a new set of seven amino acid groups based on contact preference are developed and used in ProC_S3. ProC_S3 delivers a 3-fold cross-validated accuracy of 26.9% with coverage of 4.7% for top L/5 predictions (L is the number of residues in a protein) of long-range contacts (sequence separation ≥24). Further benchmark tests deliver an accuracy of 29.7% and coverage of 5.6% for an independent set of 329 proteins. In the recently completed Ninth Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP9), ProC_S3 is ranked as No. 1, No. 3, and No. 2 accuracies in the top L/5, L/10 and best 5 predictions of long-range contacts, respectively, among 18 automatic prediction servers. AVAILABILITY http://www.abl.ku.edu/proc/proc_s3.html. CONTACT jwfang@ku.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Effects of pH on the Interactions and Conformation of Bovine Serum Albumin : Comparison between Chemical Force Microscopy and Small-Angle Neutron Scattering

The conformation of bovine serum albumin (BSA), as well as its interactions with negatively charged mica surfaces in saline solutions of different pH values, have been studied by small-angle neutron scattering (SANS) and chemical force microscopy (CFM), respectively. A new approach to extract the contribution of elementary interactions from the statistically averaged force-extension curves through self-consistent fitting was proposed and used to understand the effects of pH on the interactions and conformation of BSA in saline solutions. When pH increases, the SANS results reveal that the sizes of BSA molecules increase slightly, while the statistical analysis of the CFM results shows that the averaged pull-off force for the elongation monotonously decreases. The decrease of pull-off force with the increase of pH results from the decrease in the strength of hydrogen bonding and the number of interaction pairs, as well as the slight increase of the strength of van der Waals interaction. When pH approaches the isoelectric point (pI) of BSA, results from both SANS and CFM suggest a loss of long-range interactions in BSA molecules. Our results also suggest that the force-extension curve is mainly contributed by the van der Waals interaction. The combination of SANS and CFM provides new insight to understand the interactions and conformation of BSA molecules.

Investigate the Binding of Catechins to Trypsin Using Docking and Molecular Dynamics Simulation

To explore the inhibitory mechanism of catechins for digestive enzymes, we investigated the binding mode of catechins to a typical digestive enzyme-trypsin and analyzed the structure-activity relationship of catechins, using an integration of molecular docking, molecular dynamics simulation and binding free energy calculation. We found that catechins with different structures bound to a conservative pocket S1 of trypsin, which is comprised of residues 189–195, 214–220 and 225–228. In the trypsin-catechin complexes, Asp189 by forming strong hydrogen bonding, and Gln192, Trp215 and Gly216 through hydrophobic interactions, all significantly contribute to the binding of catechins. The number and the position of hydroxyl and aromatic groups, the structure of stereoisomers, and the orientation of catechins in the binding pocket S1 of trypsin all affect the binding affinity. The binding affinity is in the order of Epigallocatechin gallate (EGCG) > Epicatechin gallate (ECG) > Epicatechin (EC) > Epigallocatechin (EGC), and 2R-3R EGCG shows the strongest binding affinity out of other stereoisomers. Meanwhile, the synergic conformational changes of residues and catechins were also analyzed. These findings will be helpful in understanding the knowledge of interactions between catechins and trypsin and referable for the design of novel polyphenol based functional food and nutriceutical formulas.

A novel scoring function for discriminating hyperthermophilic and mesophilic proteins with application to predicting relative thermostability of protein mutants

BackgroundThe ability to design thermostable proteins is theoretically important and practically useful. Robust and accurate algorithms, however, remain elusive. One critical problem is the lack of reliable methods to estimate the relative thermostability of possible mutants.ResultsWe report a novel scoring function for discriminating hyperthermophilic and mesophilic proteins with application to predicting the relative thermostability of protein mutants. The scoring function was developed based on an elaborate analysis of a set of features calculated or predicted from 540 pairs of hyperthermophilic and mesophilic protein ortholog sequences. It was constructed by a linear combination of ten important features identified by a feature ranking procedure based on the random forest classification algorithm. The weights of these features in the scoring function were fitted by a hill-climbing algorithm. This scoring function has shown an excellent ability to discriminate hyperthermophilic from mesophilic sequences. The prediction accuracies reached 98.9% and 97.3% in discriminating orthologous pairs in training and the holdout testing datasets, respectively. Moreover, the scoring function can distinguish non-homologous sequences with an accuracy of 88.4%. Additional blind tests using two datasets of experimentally investigated mutations demonstrated that the scoring function can be used to predict the relative thermostability of proteins and their mutants at very high accuracies (92.9% and 94.4%). We also developed an amino acid substitution preference matrix between mesophilic and hyperthermophilic proteins, which may be useful in designing more thermostable proteins.ConclusionsWe have presented a novel scoring function which can distinguish not only HP/MP ortholog pairs, but also non-homologous pairs at high accuracies. Most importantly, it can be used to accurately predict the relative stability of proteins and their mutants, as demonstrated in two blind tests. In addition, the residue substitution preference matrix assembled in this study may reflect the thermal adaptation induced substitution biases. A web server implementing the scoring function and the dataset used in this study are freely available at http://www.abl.ku.edu/thermorank/.

Scaling Behaviors of α-Zein in Acetic Acid Solutions

Whether the concentration scaling behavior of a protein solution is similar to that of neutral polymer solutions, polyelectrolyte solutions, or neither still remains unclear. In this paper, the structure and rheological properties of α-zein in acetic acid solutions have been investigated by small-angle X-ray scattering (SAXS), rheology, and circular dichroism (CD) measurements. Through the investigation of the radii of gyration, the secondary structure, and the solution viscosities of α-zein in acetic acid solutions as a function of α-zein concentration, we observed two distinct scaling regions with an identical threshold. This critical concentration is close to the bulk density of the α-zein in very dilute solution. The scaling relationships are close to the theoretical predictions for polyelectrolyte solutions, but obvious discrepancies still exist. The phenomena presented here may be widely present in other protein solutions, which can stimulate more attentions on the understanding of the scaling behaviors of protein solutions.

Understanding complex coacervation in serum albumin and pectin mixtures using a combination of the Boltzmann equation and Monte Carlo simulation

A combination of turbidimetric titration, a sigmoidal Boltzmann equation approach and Monte Carlo simulation has been used to study the complex coacervation in serum albumin and pectin mixtures. The effects of the mass ratio of protein to polysaccharide on the critical pH values, the probability of complex coacervation and the electrostatic interaction from charge patches in serum albumin were investigated. Turbidimetric titration results showed an optimum pH for complex coacervation (pHm), which corresponded to the maximum turbidity in the protein/polysaccharide mixture. The pHm monotonically decreased as the ratio decreased, and could be fitted using the sigmoidal Boltzmann equation. It suggests that pHm could be a good ordering parameter to characterize the phase behavior associated with protein/polysaccharide complex coacervation. Qualitative understanding of pHm by taking into account the minimization of electrostatic interaction, as well as quantitative matching of pHm according to the concept of charge neutralization were both achieved. Our results suggest that the serum albumin/pectin complexes were ultimately neutralized by the partial charges originated from the titratable residues in protein and polysaccharide chains at pHm. The Monte Carlo simulation provided consistent phase boundaries for complex coacervation in the same system, and the intermolecular association strength was determined to be several kBT below the given ionic strength. The strongest binding site in the protein is convergent to the largest positive charge patch if pure electrostatic interaction was considered. Further inclusion of contribution from excluded volume resulted in the binding site distribution over five different positive charge patches at different protein/polysaccharide ratios and pH values.

HAAD: A Quick Algorithm for Accurate Prediction of Hydrogen Atoms in Protein Structures

Hydrogen constitutes nearly half of all atoms in proteins and their positions are essential for analyzing hydrogen-bonding interactions and refining atomic-level structures. However, most protein structures determined by experiments or computer prediction lack hydrogen coordinates. We present a new algorithm, HAAD, to predict the positions of hydrogen atoms based on the positions of heavy atoms. The algorithm is built on the basic rules of orbital hybridization followed by the optimization of steric repulsion and electrostatic interactions. We tested the algorithm using three independent data sets: ultra-high-resolution X-ray structures, structures determined by neutron diffraction, and NOE proton-proton distances. Compared with the widely used programs CHARMM and REDUCE, HAAD has a significantly higher accuracy, with the average RMSD of the predicted hydrogen atoms to the X-ray and neutron diffraction structures decreased by 26% and 11%, respectively. Furthermore, hydrogen atoms placed by HAAD have more matches with the NOE restraints and fewer clashes with heavy atoms. The average CPU cost by HAAD is 18 and 8 times lower than that of CHARMM and REDUCE, respectively. The significant advantage of HAAD in both the accuracy and the speed of the hydrogen additions should make HAAD a useful tool for the detailed study of protein structure and function. Both an executable and the source code of HAAD are freely available at http://zhang.bioinformatics.ku.edu/HAAD.

Probing Conformational Change of Bovine Serum Albumin–Dextran Conjugates under Controlled Dry Heating

The time-dependent conformational change of bovine serum album (BSA) during Maillard reaction with dextran under controlled dry heating has been studied by small-angle X-ray scattering, fluorescence spectroscopy, dynamic light scattering, and circular dichroism analysis. Through the research on the radii of gyration (Rg), intrinsic fluorescence, and secondary structure, conjugates with dextran coating were found to inhibit BSA aggregation and preserve the secondary structure of native BSA against long-time heat treatment during Maillard reaction. The results suggested that the hydrophilic dextran was conjugated to the compact protein surface and enclosed it and more dextran chains were attached to BSA with the increase of the heating time. The study presented here will be beneficial to the understanding of the conformational evolution of BSA molecules during the dry-heating Maillard reaction and to the control of the protein-polysaccharide conjugate structure.

PROTS-RF: A Robust Model for Predicting Mutation-Induced Protein Stability Changes

The ability to improve protein thermostability via protein engineering is of great scientific interest and also has significant practical value. In this report we present PROTS-RF, a robust model based on the Random Forest algorithm capable of predicting thermostability changes induced by not only single-, but also double- or multiple-point mutations. The model is built using 41 features including evolutionary information, secondary structure, solvent accessibility and a set of fragment-based features. It achieves accuracies of 0.799,0.782, 0.787, and areas under receiver operating characteristic (ROC) curves of 0.873, 0.868 and 0.862 for single-, double- and multiple- point mutation datasets, respectively. Contrary to previous suggestions, our results clearly demonstrate that a robust predictive model trained for predicting single point mutation induced thermostability changes can be capable of predicting double and multiple point mutations. It also shows high levels of robustness in the tests using hypothetical reverse mutations. We demonstrate that testing datasets created based on physical principles can be highly useful for testing the robustness of predictive models.