Estimating configurational entropy of complex molecules: A novel variable transformation approach

Total free energy analysis of fully hydrated proteins

The total free energy of a hydrated biomolecule and its corresponding decomposition of energy and entropy provides detailed information about regions of thermodynamic stability or instability. The free energies of four hydrated globular proteins with different net charges are calculated from a molecular dynamics simulation, with the energy coming from the system Hamiltonian and entropy using multiscale cell correlation. Water is found to be most stable around anionic residues, intermediate around cationic and polar residues, and least stable near hydrophobic residues, especially when more buried, with stability displaying moderate entropy-enthalpy compensation. Conversely, anionic residues in the proteins are energetically destabilized relative to singly solvated amino acids, while trends for other residues are less clear-cut. Almost all residues lose intraresidue entropy when in the protein, enthalpy changes are negative on average but may be positive or negative, and the resulting overall stability is moderate for some proteins and negligible for others. The free energy of water around single amino acids is found to closely match existing hydrophobicity scales. Regarding the effect of secondary structure, water is slightly more stable around loops, of intermediate stability around β strands and turns, and least stable around helices. An interesting asymmetry observed is that cationic residues stabilize a residue when bonded to its N-terminal side but destabilize it when on the C-terminal side, with a weaker reversed trend for anionic residues.

Information Entropy in Chemistry: An Overview

Basic applications of the information entropy concept to chemical objects are reviewed. These applications deal with quantifying chemical and electronic structures of molecules, signal processing, structural studies on crystals, and molecular ensembles. Recent advances in the mentioned areas make information entropy a central concept in interdisciplinary studies on digitalizing chemical reactions, chemico-information synthesis, crystal engineering, as well as digitally rethinking basic notions of structural chemistry in terms of informatics.

Entropy of Proteins Using Multiscale Cell Correlation

A new multiscale method is presented to calculate the entropy of proteins from molecular dynamics simulations. Termed Multiscale Cell Correlation (MCC), the method decomposes the protein into sets of rigid-body units based on their covalent-bond connectivity at three levels of hierarchy: molecule, residue, and united atom. It evaluates the vibrational and topographical entropy from forces, torques, and dihedrals at each level, taking into account correlations between sets of constituent units that together make up a larger unit at the coarser length scale. MCC gives entropies in close agreement with normal-mode analysis and smaller than those using quasiharmonic analysis as well as providing much faster convergence. Moreover, MCC provides an insightful decomposition of entropy at each length scale and for each type of amino acid according to their solvent exposure and whether they are terminal residues. While the residue entropy depends weakly on solvent exposure, there is greater variation in entropy components for larger, more polar amino acids, which have increased conformational entropy but reduced vibrational entropy with greater solvent exposure.

Information Entropy of Fullerenes

The reasons for the formation of the highly symmetric C60 molecule under nonequilibrium conditions are widely discussed as it dominates over numerous similar fullerene structures. In such conditions, evolution of structure rather than energy defines the processes. We have first studied the diversity of fullerenes in terms of information entropy. Sorting 2079 structures from An Atlas of Fullerenes [ Fowler , P. W. ; Manolopoulos , D. E. An Atlas of Fullerenes ; Oxford : Clarendon , 1995 . ], we have found that the information entropies of only 14 fullerenes (<1% of the studied structures) lie between the values of C60 and C70, the two most abundant fullerenes. Interestingly, buckminsterfullerene is the only fullerene with zero information entropy, i.e., an exclusive compound among the other members of the fullerene family. Such an efficient sorting demonstrates possible relevance of information entropy to chemical processes. For this reason, we have introduced an algorithm for calculating changes in information entropy at chemical transformations. The preliminary calculations of changes in information entropy at the selected fullerene reactions show good agreement with thermochemical data.

Accurate prediction of the binding free energy and analysis of the mechanism of the interaction of replication protein A (RPA) with ssDNA

The eukaryotic replication protein A (RPA) has several pivotal functions in the cell metabolism, such as chromosomal replication, prevention of hairpin formation, DNA repair and recombination, and signaling after DNA damage. Moreover, RPA seems to have a crucial role in organizing the sequential assembly of DNA processing proteins along single stranded DNA (ssDNA). The strong RPA affinity for ssDNA, K(A) between 10(-9)-10(-10) M, is characterized by a low cooperativity with minor variation for changes on the nucleotide sequence. Recently, new data on RPA interactions was reported, including the binding free energy of the complex RPA70AB with dC(8) and dC(5), which has been estimated to be -10 ± 0.4 kcal mol(-1) and -7 ± 1 kcal mol(-1), respectively. In view of these results we performed a study based on molecular dynamics aimed to reproduce the absolute binding free energy of RPA70AB with the dC(5) and dC(8) oligonucleotides. We used several tools to analyze the binding free energy, rigidity, and time evolution of the complex. The results obtained by MM-PBSA method, with the use of ligand free geometry as a reference for the receptor in the separate trajectory approach, are in excellent agreement with the experimental data, with ±4 kcal mol(-1) error. This result shows that the MM-PB(GB)SA methods can provide accurate quantitative estimates of the binding free energy for interacting complexes when appropriate geometries are used for the receptor, ligand and complex. The decomposition of the MM-GBSA energy for each residue in the receptor allowed us to correlate the change of the affinity of the mutated protein with the ΔG(gas+sol) contribution of the residue considered in the mutation. The agreement with experiment is optimal and a strong change in the binding free energy can be considered as the dominant factor in the loss for the binding affinity resulting from mutation.

Near native-state conformational landscape of psychrophilic and mesophilic enzymes: probing the folding funnel model

In recent years, increased interest has been directed to the study of enzyme adaptation to low temperatures. In particular, a peculiar folding funnel model was proposed for the free energy landscape of a psychrophilic alpha-amylase and other cold-adapted enzymes. In the present contribution, the comparison between the near native-state dynamics and conformational landscape in the essential subspace of different cold-adapted enzymes with their mesophilic counterparts, as obtained by more than 0.1 micros molecular dynamics simulations at different temperatures, allows the folding funnel model to be probed. Common characteristics were highlighted in the near native-state dynamics of psychrophilic enzymes belonging to different enzymatic families when compared to the mesophilic counterparts. According to the model, a cold-adapted enzyme in its native-state consists of a large population of conformations which can easily interconvert and result in high structural flexibility.