CL6. Folding Mechanisms of Small Proteins GB1 and LB1

The B1 domains of protein G (GB1) and protein L (LB1) are two small proteins that bind to antibody immunoglobulin G (IgG). GB1 and LB1 are similar in size (about 60 residues), and also have an overall similar structure (β-hairpin--α-helix--β-hairpin). However their sequences are very different, possessing only 15% identity in a structure-based alignment [1,2]. Therefore, there are interesting comparisons in their folding mechanisms. Experimental evidence indicates that LB1 folds in a two-state manner; while GB1 folds in a more complex way -- an early stage intermediate may exist in the folding path. The folding mechanisms are still under extensive experimental and computational study. Here, we used a new all-atom structure-based method to investigate the folding mechanisms of GB1 and LB1. In this approach, folded structures of the two proteins were used to construct the restraints and they are stabilized by Lorentzian attractive term instead of conventional harmonic term [3]. We presume that our model will be able to identify two-state and non-two-state proteins, and give more insights on their folding pathways. Qianyi Cheng, University of Memphis InSuk Joung, Korea Institute for Advanced Study Kunihiro Kuwajima, University of Tokyo Jooyoung Lee, Korea Institute for Advanced Stud

Effects of Different Thawing Methods on the Quality of Micropterus salmoides at Room Temperature

In order to choose a suitable thawing method for Micropterus salmoides (room temperature thawing, running water thawing, saltwater thawing, ultrasonic static water thawing and ultrasonic running water thawing), this paper took Micropterus salmoides as the research subject. To investigate the effects of different thawing methods on water retention, total volatile base nitrogen (TVB-N), malondialdehyde content, peroxide value, total sulfhydryl content and Ca2+-ATPase activity of Micropterus salmoides. At the same time, the changes of texture properties such as hardness, elasticity and adhesion of fish were analyzed. The results showed that the normal temperature thaw 219 min, longest, fish water retention, lipid and protein oxidation was the most serious. Thawing water and salt water thawing time consuming 35 and 55 min, respectively, was the shorter of the normal temperature thaw, but fish water retention, protein oxidation, quality and structure characteristics of the various quality indexes such as the change was still serious. After ultrasonic static water thawing, the fish had better water retention and texture characteristics, and could effectively alleviate the oxidation of fish protein, but the lipid oxidation was more serious. Ultrasonic flow water thawing could complete the thawing of fish within 24 minutes, which was more efficient. Compared with other thawing methods, it could effectively maintain the water retention and texture characteristics of fish, and effectively delay the oxidation of fish protein and lipid. Ultrasonic thawing of frozen water, therefore, Micropterus salmoides had little effect on quality, was the most suitable thawing method

Desolvation and Dehydrogenation of Solvated Magnesium Salts of Dodecahydrododecaborate: Relationship between Structure and Thermal Decomposition

Attempts to synthesize solvent-free MgB_(12)H_(12) by heating various solvated forms (H_2O, NH_3, and CH_3OH) of the salt failed because of the competition between desolvation and dehydrogenation. This competition has been studied by thermogravimetric analysis (TGA) and temperature-programmed desorption (TPD). Products were characterized by IR, solution- and solid-state NMR spectroscopy, elemental analysis, and single-crystal or powder X-ray diffraction analysis. For hydrated salts, thermal decomposition proceeded in three stages, loss of water to form first hexahydrated then trihydrated, and finally loss of water and hydrogen to form polyhydroxylated complexes. For partially ammoniated salts, two stages of thermal decomposition were observed as ammonia and hydrogen were released with weight loss first of 14 % and then 5.5 %. Thermal decomposition of methanolated salts proceeded through a single step with a total weight loss of 32 % with the release of methanol, methane, and hydrogen. All the gaseous products of thermal decomposition were characterized by using mass spectrometry. Residual solid materials were characterized by solid-state 11B magic-angle spinning (MAS) NMR spectroscopy and X-ray powder diffraction analysis by which the molecular structures of hexahydrated and trihydrated complexes were solved. Both hydrogen and dihydrogen bonds were observed in structures of [Mg(H_2O_6B_(12)H_(12)]⋅6 H_2O and [Mg(CH_3OH)_(6)B_(12)H_(12)]⋅6 CH_3OH, which were determined by single-crystal X-ray diffraction analysis. The structural factors influencing thermal decomposition behavior are identified and discussed. The dependence of dehydrogenation on the formation of dihydrogen bonds may be an important consideration in the design of solid-state hydrogen storage materials

A compendium of genetic regulatory effects across pig tissues

The Farm Animal Genotype-Tissue Expression (FarmGTEx) project has been established to develop a public resource of genetic regulatory variants in livestock, which is essential for linking genetic polymorphisms to variation in phenotypes, helping fundamental biological discovery and exploitation in animal breeding and human biomedicine. Here we show results from the pilot phase of PigGTEx by processing 5,457 RNA-sequencing and 1,602 whole-genome sequencing samples passing quality control from pigs. We build a pig genotype imputation panel and associate millions of genetic variants with five types of transcriptomic phenotypes in 34 tissues. We evaluate tissue specificity of regulatory effects and elucidate molecular mechanisms of their action using multi-omics data. Leveraging this resource, we decipher regulatory mechanisms underlying 207 pig complex phenotypes and demonstrate the similarity of pigs to humans in gene expression and the genetic regulation behind complex phenotypes, supporting the importance of pigs as a human biomedical model.</p

Theoretical study of the low-lying electronic states of iron hydride cation

Both FeH and FeH+ are predicted to be abundant in cool stellar atmospheres and proposed to be molecular components of the gas phase interstellar medium (ISM). However, experimental and simulated data for both species are lacking, which have hindered astronomical detection. There are no published laboratory data for the spectroscopy of FeH+ in any frequency regime. It is also not established if FeH+ possesses salient multireference character, which would pose significant challenges for ab initio modeling of geometric and spectroscopic properties. With a set of high-level coupled cluster and multireference configuration interaction computations, a study of the electronic structure of the ground state and seven excited states of FeH+ was carried out. An X 5Δi electronic ground state of FeH+ is found, in agreement with previous theoretical studies. Including corrections for spin-orbit coupling and anharmonic vibrational effects, the ω = 3, ν = 0 spin ladder of the A 5Πi electronic state lies 872 cm-1 higher in energy than the ω = 4, ν = 0 spin ladder of the ground state. Combined with previous work in our laboratory, the ionization energy of FeH is computed to be 7.4851 eV. With modern multireference configuration interaction and coupled cluster methods, spectroscopic constants (re, Be, ωe, ωexe, αe, and De) for several bound excited states (A 5Πi, B 5ςi+, a 3ςr-, b 3φi, c 3Πi, d 3Δr, and 7ς+) were characterized. This study will lead efforts to identify FeH+ in the ISM and help solve important remaining questions in quantifying metal-hydride bonding

Acylation and deacylation mechanism and kinetics of penicillin G reaction with Streptomyces R61 DD-peptidase

Two quantum mechanical (QM)-cluster models are built for studying the acylation and deacylation mechanism and kinetics of Streptomyces R61 DD-peptidase with the penicillin G at atomic level detail. DD-peptidases are bacterial enzymes involved in the cross-linking of peptidoglycan to form the cell wall, necessary for bacterial survival. The cross-linking can be inhibited by antibiotic beta-lactam derivatives through acylation, preventing the acyl-enzyme complex from undergoing further deacylation. The deacylation step was predicted to be rate-limiting. Transition state and intermediate structures are found using density functional theory in this study, and thermodynamic and kinetic properties of the proposed mechanism are evaluated. The acyl-enzyme complex is found lying in a deep thermodynamic sink, and deacylation is indeed the severely rate-limiting step, leading to suicide inhibition of the peptidoglycan cross-linking. The usage of QM-cluster models is a promising technique to understand, improve, and design antibiotics to disrupt function of the Streptomyces R61 DD-peptidase

QM-Cluster Model Study of the Guaiacol Hydrogen Atom Transfer and Oxygen Rebound with Cytochrome P450 Enzyme GcoA

The key step of the O-demethylation of guaiacol by GcoA of the cytochrome P450-reductase pair was studied with DFT using two 10-residue and three 15-residue QM-cluster models. For each model, two reaction pathways were examined, beginning with a different guaiacol orientation. Based on this study, His354, Phe349, Glu249, and Pro250 residues were found to be important for keeping the heme in a planar geometry throughout the reaction. Val241 and Gly245 residues were needed in the QM-cluster models to provide the hydrophobic pocket for an appropriate guaiacol pose in the reaction. The aromatic triad Phe75, Phe169, and Phe395 may be necessary to facilitate guaiacol migrating into the enzyme active site, but it does not qualitatively affect kinetics and thermodynamics of the proposed mechanism. All QM-cluster models created by RINRUS agree very well with previous experimental work. This study provides details for better understanding enzymatic O-demethylation of lignins to form catechol derivatives by GcoA

A Case Study of the Glycoside Hydrolase Enzyme Mechanism Using an Automated QM-Cluster Model Building Toolkit

Glycoside hydrolase enzymes are important for hydrolyzing the β-1,4 glycosidic bond in polysaccharides for deconstruction of carbohydrates. The two-step retaining reaction mechanism of Glycoside Hydrolase Family 7 (GH7) was explored with different sized QM-cluster models built by the Residue Interaction Network ResidUe Selector (RINRUS) software using both the wild-type protein and its E217Q mutant. The first step is the glycosylation, in which the acidic residue 217 donates a proton to the glycosidic oxygen leading to bond cleavage. In the subsequent deglycosylation step, one water molecule migrates into the active site and attacks the anomeric carbon. Residue interaction-based QM-cluster models lead to reliable structural and energetic results for proposed glycoside hydrolase mechanisms. The free energies of activation for glycosylation in the largest QM-cluster models were predicted to be 19.5 and 31.4 kcal mol for the wild-type protein and its E217Q mutant, which agree with experimental trends that mutation of the acidic residue Glu217 to Gln will slow down the reaction; and are higher in free energy than the deglycosylation transition states (13.8 and 25.5 kcal mol for the wild-type protein and its mutant, respectively). For the mutated protein, glycosylation led to a low-energy product. This thermodynamic sink may correspond to the intermediate state which was isolated in the X-ray crystal structure. Hence, the glycosylation is validated to be the rate-limiting step in both the wild-type and mutated enzyme

The Glycine -Methyltransferase Case Study: Another Challenge for QM-Cluster Models?

The methyl transfer reaction between SAM and glycine catalyzed by glycine -methyltransferase (GNMT) was examined using QM-cluster models generated by Residue Interaction Network ResidUe Selector (). is a Python-based tool that can build QM-cluster models with rules-based processing of the active site residue interaction network. This way of enzyme model-building allows quantitative analysis of residue and fragment contributions to kinetic and thermodynamic properties of the enzyme. Many residue fragments are important for the GNMT catalytic reaction, such as Gly137, Asn138, and Arg175, which interact with the glycine substrate, and Trp30, Asp85, and Tyr242, which interact with the SAM cofactor. Our study shows that active site fragments that interact with the glycine substrate and the SAM cofactor must both be included in the QM-cluster models. Even though the proposed mechanism is a simple one-step reaction, GNMT may be a rather challenging case study for QM-cluster models because convergence in energetics requires models with \u3e350 atoms. Maximal QM-cluster models built with either qualitative contact count ranking or quantitative interaction energies from functional group symmetry adapted perturbation theory provide acceptable results. Hence, important residue fragments that contribute to the energetics of the methyl-transfer reaction in GNMT are correctly identified in the RIN. Observations from this work suggest new directions to better establish an effective approach for constructing atomic-level enzyme models