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Yunjun Wang

Publications and source records attributed to Yunjun Wang.

9 recordsLinked to original sources
PubMed2006

Highly luminescent, stable, and water-soluble CdSe/CdS core-shell dendron nanocrystals with carboxylate anchoring groups.

A dendron ligand with two carboxylate anchoring groups at its focal point and eight hydroxyl groups as its terminal groups was found to efficiently convert as-synthesized CdSe/CdS core-shell nanocrystals in toluene to water-soluble dendron-ligand stabilized nanocrystals (dendron nanocrystals). The resulting dendron nanocrystals retained 60% of the photoluminescence value of the original CdSe/CdS core-shell nanocrystals in toluene and were significantly brighter than the similar dendron nanocrystals with thiolate (deprotonated thiol group) as the anchoring group which retained just 10% of the photoluminescence value of the original CdSe/CdS core-shell nanocrystals in toluene. The carboxylate-based dendron nanocrystals survived UV irradiation in air for at least 13 days, about 9 times better than the thiolate-based dendron nanocrystals (35 h) and similar to that of the thiolate-based dendron-box stabilized CdSe/CdS core-shell nanocrystals (box nanocrystals). Upon UV irradiation, the dendron nanocrystals became even 2 times brighter than the original CdSe/CdS core-shell nanocrystals in toluene, and the UV-brightened PL can retain the brightness for at least several months. These stable and bright dendron nanocrystals were soluble in various aqueous media, including all common biological buffer solutions tested, for at least 1.5 years. In addition to their superior performance, the synthetic chemistry of carboxylate dendron ligands and the corresponding dendron nanocrystals is relatively simple and with high yield.

Cadmium Compounds↗
PubMed2005

Size-dependent dissociation pH of thiolate ligands from cadmium chalcogenide nanocrystals.

A method, pseudo steady-state titration, is introduced for determining the precipitation pH of nanocrystals coated by electron-donating ligands. CdSe nanocrystals coated with hydrophilic deprotonated thiol (thiolate) ligands were studied systematically. For comparison, CdTe and CdS nanocrystals coated with the same types of ligands were also examined. The results show that the precipitation of the nanocrystals is caused by the dissociation of the nanocrystal-ligand coordinating bonds from the nanocrystal surface. The ligands are removed from the surface due to protonation in a relatively low pH range, between 2 and 7 depending on the size, approximately within the quantum confinement size regime, and chemical composition (band gap) of the nanocrystals. In contrast, the redispersion of the nanocrystals was found to be solely determined by the deprotonation of the ligands. The size-dependent dissociation pH of the ligands was tentatively used as a means for determining the size-dependent free energy associated with the formation of a nanocrystal-ligand coordinating bond.

Cadmium↗
PubMed2005

A simple method to adjust inconsistently referenced 13C and 15N chemical shift assignments of proteins.

Inconsistent 13C and 15N chemical shift referencing is a continuing problem associated with protein chemical shift assignments deposited in BioMagResBank (BMRB). Here we describe a simple and robust approach that can quantitatively determine the 13C and 15N referencing offsets solely from chemical shift assignment data and independently of 3D coordinate data. This novel structure-independent approach permitted the assessment and determination of 13C and 15N reference offsets for all protein entries deposited in the BMRB. Tests on 452 proteins with known 3D structures show that this structure-independent approach yields 13C and 15N referencing offsets that exhibit excellent agreement with those calculated on the basis of 3D structures. Furthermore, this protocol appears to improve the accuracy of chemical shift-derived secondary structural identification, and has been formally incorporated into a computer program called PSSI (http//www.pronmr.com).

Amino Acid Sequence↗
PubMed2004

Secondary structural effects on protein NMR chemical shifts.

For an amino acid in protein, its chemical shift, delta(phi, psi)(s), is expressed as a function of its backbone torsion angles (phi and psi) and secondary state (s): delta(phi, psi)(s=deltaphi, psi)_coil+Deltadelta(phi, psi)_s), where delta(phi, psi)(coil) represents its chemical shift at coil state (s=coil); Delta delta(phi, psi)(s) (s=sheet or helix) is herein defined as secondary structural effect correction factor, which are quantitatively determined from Residue-specific Secondary Structure Shielding Surface (RSS) for (13)CO, (13)Calpha, (13)Cbeta,(1)Halpha, (15)N, and (1)HN nuclei. The secondary structural effect correction factors defined in this study differ from those in earlier investigations by separating out the backbone conformational effects. As a consequence, their magnitudes are significantly smaller than those earlier reported. The present Delta delta(phi, psi)(sheet) and Delta delta(phi, psi)(helix) were found varying little with backbone conformation and the 20 amino acids, specifically for (13)CO, (13)Calpha, and (1)Halpha nuclei. This study also carries out some useful investigations on other chemical shift prediction approaches - the traditional shielding surfaces, SHIFTS, SHIFTX, PROSHIFT, and identifies some unexpected shortcomings with these methods. It provides some useful insights into understanding protein chemical shifts and suggests a new route to improving chemical shifts prediction. The RSS surfaces were incorporated into the program PRSI.

Amino Acids↗
PubMed2004

Predicting 15N chemical shifts in proteins using the preceding residue-specific individual shielding surfaces from phi, psi i-1, and chi 1 torsion angles.

Empirical shielding surfaces are most commonly used to predict chemical shifts in proteins from known backbone torsion angles, phi and psi. However, the prediction of (15)N chemical shifts using this technique is significantly poorer, compared to that for the other nuclei such as (1)H(alpha), (13)C(alpha), and (13)C(beta). In this study, we investigated the effects from the preceding residue and the side-chain geometry, chi(1), on (15)N chemical shifts by statistical methods. For an amino acid sequence XY, the (15)N chemical shift of Y is expressed as a function of the amino acid types of X and Y, as well as the backbone torsion angles, phi and psi(i-1). Accordingly, 380 empirical 'Preceding Residue Specific Individual (PRSI)' (15)N chemical shift shielding surfaces, representing all the combinations of X and Y (except for Y=Pro), were built and used to predict (15)N chemical shift from phi and psi(i-1). We further investigated the chi(1) effects, which were found to account for differences in (15)N chemical shifts by approximately 5 ppm for amino acids Val, Ile, Thr, Phe, His, Tyr, and Trp. Taking the chi(1) effects into account, the chi(1)-calibrated PRSI shielding surfaces (XPRSI) were built and used to predict (15)N chemical shifts for these amino acids. We demonstrated that (15)N chemical shift predictions are significantly improved by incorporating the preceding residue and chi(1) effects. The present PRSI and XPRSI shielding surfaces were extensively compared with three recently published programs, SHIFTX (Neal et al., 2003), SHIFTS (Xu and Case, 2001 and 2002), and PROSHIFT (Meiler, 2003) on a set of ten randomly selected proteins. A set of Java programs using XPRSI shielding surfaces to predict (15)N chemical shifts in proteins were developed and are freely available for academic users at http://www.pronmr.com or by sending email to one of the authors Yunjun Wang (yunjunwang@yahoo.com).

Internet↗
PubMed2002

Investigation of the neighboring residue effects on protein chemical shifts.

In this study, we report nearest neighbor residue effects statistically determined from a chemical shift database. For an amino acid sequence XYZ, we define two correction factors, Delta((X)Y)n,s and Delta(Y(Z))n,s, representing the effects on Y's chemical shifts from the preceding residue (X) and the following residue (Z), respectively, where X, Y, and Z are any of the 20 naturally occurring amino acids, n stands for (1)H(N), (15)N, (1)H(alpha), (13)C(alpha), (13)C(beta), and (13)C' nuclei, and s represents the three secondary structural types beta-strand, random coil, and alpha-helix. A total of approximately 14400 Delta((X)Y)n,s and Delta(Y(Z))n,s, representing nearly all combinations of X, Y, Z, n, and s, have been quantitatively determined. Our approach overcomes the limits of earlier experimental methods using short model peptides, and the resulting correction factors have important applications such as chemical shift prediction for the folded proteins. More importantly, we have found, for the first time, a linear correlation between the Delta((X)Y)n,s (n = (15)N) and the (13)C(alpha) chemical shifts of the preceding residue X. Since (13)C(alpha) chemical shifts of the 20 amino acids, which span a wide range of 40-70 ppm, are largely dominated by one property, the electron density of the side chain, the correlation indicates that the same property is responsible for the effect on the following residue. The influence of the secondary structure on both the chemical shifts and the nearest neighbor residue effect are also investigated.

Amino Acids↗
PubMed2002

Probability-based protein secondary structure identification using combined NMR chemical-shift data.

For a long time, NMR chemical shifts have been used to identify protein secondary structures. Currently, this is accomplished through comparing the observed (1)H(alpha), (13)C(alpha), (13)C(beta), or (13)C' chemical shifts with the random coil values. Here, we present a new protocol, which is based on the joint probability of each of the three secondary structural types (beta-strand, alpha-helix, and random coil) derived from chemical-shift data, to identify the secondary structure. In combination with empirical smooth filters/functions, this protocol shows significant improvements in the accuracy and the confidence of identification. Updated chemical-shift statistics are reported, on the basis of which the reliability of using chemical shift to identify protein secondary structure is evaluated for each nucleus. The reliability varies greatly among the 20 amino acids, but, on average, is in the order of: (13)C(alpha)>(13)C'>(1)H(alpha)>(13)C(beta)>(15)N>(1)H(N) to distinguish an alpha-helix from a random coil; and (1)H(alpha)>(13)C(beta) >(1)H(N) approximately (13)C(alpha) approximately (13)C' approximately (15)N for a beta-strand from a random coil. Amide (15)N and (1)H(N) chemical shifts, which are generally excluded from the application, in fact, were found to be helpful in distinguishing a beta-strand from a random coil. In addition, the chemical-shift statistical data are compared with those reported previously, and the results are discussed. A JAVA User Interface program has been developed to make the entire procedure fully automated and is available via http://ccsr3150-p3.stanford.edu.

Amino Acids↗