Thermal decomposition of citric acid, trans- and cis-aconitic acid has been studied using the TG-MS, TG-FTIR and DSC techniques. The measurements were carried out in an argon atmosphere over a temperature range of 293–673 K. The influence of the acid structures and configurational geometry on stability of the transition products and pathways of thermal transformations of the studied compounds studied is discussed.

A unified coarse-grained model of three major classes of biological molecules—proteins, nucleic acids, and polysaccharides—has been developed. It is based on the observations that the repeated units of biopolymers (peptide groups, nucleic acid bases, sugar rings) are highly polar and their charge distributions can be represented crudely as point multipoles. The model is an extension of the united residue (UNRES) coarse-grained model of proteins developed previously in our laboratory. The respective force fields are defined as the potentials of mean force of biomacromolecules immersed in water, where all degrees of freedom not considered in the model have been averaged out. Reducing the representation to one center per polar interaction site leads to the representation of average site–site interactions as mean-field dipole–dipole interactions. Further expansion of the potentials of mean force of biopolymer chains into Kubo’s cluster-cumulant series leads to the appearance of mean-field dipole–dipole interactions, averaged in the context of local interactions within a biopolymer unit. These mean-field interactions account for the formation of regular structures encountered in biomacromolecules, e.g., α-helices and β-sheets in proteins, double helices in nucleic acids, and helicoidally packed structures in polysaccharides, which enables us to use a greatly reduced number of interacting sites without sacrificing the ability to reproduce the correct architecture. This reduction results in an extension of the simulation timescale by more than four orders of magnitude compared to the all-atom representation. Examples of the performance of the model are presented. Components of the Unified Coarse Grained Model (UCGM) of biological macromolecules

Recent improvements in the protein-structure prediction method developed in our laboratory, based on the thermodynamic hypothesis, are described. The conformational space is searched extensively at the united-residue level by using our physics-based UNRES energy function and the conformational space annealing method of global optimization. The lowest-energy coarse-grained structures are then converted to an all-atom representation and energy-minimized with the ECEPP/3 force field. The procedure was assessed in two recent blind tests of protein-structure prediction. During the first blind test, we predicted large fragments of α and α+β proteins [60–70 residues with C ^α rms deviation (rmsd) <6 Å]. However, for α+β proteins, significant topological errors occurred despite low rmsd values. In the second exercise, we predicted whole structures of five proteins (two α and three α+β, with sizes of 53–235 residues) with remarkably good accuracy. In particular, for the genomic target TM0487 (a 102-residue α+β protein from Thermotoga maritima ), we predicted the complete, topologically correct structure with 7.3-Å C ^α rmsd. So far this protein is the largest α+β protein predicted based solely on the amino acid sequence and a physics-based potential-energy function and search procedure. For target T0198, a phosphate transport system regulator PhoU from T. maritima (a 235-residue mainly α-helical protein), we predicted the topology of the whole six-helix bundle correctly within 8 Å rmsd, except the 32 C-terminal residues, most of which form a β-hairpin. These and other examples described in this work demonstrate significant progress in physics-based protein-structure prediction.

Hydrophobicity is a phenomenon of great importance in biology, chemistry, and biochemistry. It is defined as the interaction between nonpolar molecules or groups in water and their low solubility. Hydrophobic interactions affect many processes in water, for example, complexation, surfactant aggregation, and coagulation. These interactions play a pivotal role in the formation and stability of proteins or biological membranes. In the present study, we assessed the effect of ionic strength, solute size, and shape on hydrophobic interactions between pairs of nonpolar particles. Pairs of methane, neopentane, adamantane, fullerene, ethane, propane, butane, hexane, octane, and decane were simulated by molecular dynamics in AMBER 16.0 force field. As a solvent, TIP3P and TIP4PEW water models were used. Potential of mean force (PMF) plots of these dimers were determined at four values of ionic strength, 0, 0.04, 0.08, and 0.40 mol/dm³, to observe its impact on hydrophobic interactions. The characteristic shape of PMFs with three extrema (contact minimum, solvent-separated minimum, and desolvation maximum) was observed for most of the compounds for hydrophobic interactions. Ionic strength affected hydrophobic interactions. We observed a tendency to deepen contact minima with an increase in ionic strength value in the case of spherical and spheroidal molecules. Additionally, two-dimensional distribution functions describing water density and average number of hydrogen bonds between water molecules were calculated in both water models for adamantane and hexane. It was observed that the density of water did not significantly change with the increase in ionic strength, but the average number of hydrogen bonds changed. The latter tendency strongly depends on the water model used for simulations.