No Arabic abstract
The conformational change of biological macromolecule is investigated from the point of quantum transition. A quantum theory on protein folding is proposed. Compared with other dynamical variables such as mobile electrons, chemical bonds and stretching-bending vibrations the molecular torsion has the lowest energy and can be looked as the slow variable of the system. Simultaneously, from the multi-minima property of torsion potential the local conformational states are well defined. Following the idea that the slow variables slave the fast ones and using the nonadiabaticity operator method we deduce the Hamiltonian describing conformational change. It is proved that the influence of fast variables on the macromolecule can fully be taken into account through a phase transformation of slow variable wave function. Starting from the conformation- transition Hamiltonian the nonradiative matrix element is calculated in two important cases: A, only electrons are fast variables and the electronic state does not change in the transition process; B, fast variables are not limited to electrons but the perturbation approximation can be used. Then, the general formulas for protein folding rate are deduced. The analytical form of the formula is utilized to study the temperature dependence of protein folding rate and the curious non-Arrhenius temperature relation is interpreted. The decoherence time of quantum torsion state is estimated and the quantum coherence degree of torsional angles in the protein folding is studied by using temperature dependence data. The proposed folding rate formula gives a unifying approach for the study of a large class problems of biological conformational change.
Many biological electron transfer (ET) reactions are mediated by metal centres in proteins. NADH:ubiquinone oxidoreductase (complex I) contains an intramolecular chain of seven iron-sulphur (FeS) clusters, one of the longest chains of metal centres in biology and a test case for physical models of intramolecular ET. In biology, intramolecular ET is commonly described as a diffusive hopping process, according to the semi-classical theories of Marcus and Hopfield. However, recent studies have raised the possibility that non-trivial quantum mechanical effects play a functioning role in certain biomolecular processes. Here, we extend the semi-classical model for biological ET to incorporate both semi-classical and coherent quantum phenomena using a quantum master equation based on the Holstein Hamiltonian. We test our model on the structurally-defined chain of FeS clusters in complex I. By exploring a wide range of realistic parameters we find that, when the energy profile for ET along the chain is relatively flat, just a small coherent contribution can provide a robust and significant increase in ET rate (above the semi-classical diffusive-hopping rate), even at physiologically-relevant temperatures. Conversely, when the on-site energies vary significantly along the chain the coherent contribution is negligible. For complex I, a crucial respiratory enzyme that is linked to many neuromuscular and degenerative diseases, our results suggest a new contribution towards ensuring that intramolecular ET does not limit the rate of catalysis. For the emerging field of quantum biology, our model is intended as a basis for elucidating the general role of coherent ET in biological ET reactions.
The SARS-CoV-2 spike (S) protein facilitates viral infection, and has been the focus of many structure determination efforts. This paper studies the conformations of loops in the S protein based on the available Protein Data Bank (PDB) structures. Loops, as flexible regions of the protein, are known to be involved in binding and can adopt multiple conformations. We identify the loop regions of the S protein, and examine their structural variability across the PDB. While most loops had essentially one stable conformation, 17 of 44 loop regions were observed to be structurally variable with multiple substantively distinct conformations. Loop modeling methods were then applied to the S protein loop targets, and loops with multiple conformations were found to be more challenging for the methods to predict accurately. Sequence variants and the up/down structural states of the receptor binding domain were also considered in the analysis.
We study local conformational biases in the dynamics of {alpha}-synuclein by using all-atom simulations with explicit and implicit solvents. The biases are related to the frequency of the specific contact formation. In both approaches, the protein is intrinsically disordered, and its strongest bias is to make bend and turn local structures. The explicit-solvent conformations can be substantially more extended which allows for formation of transient trefoil knots, both deep and shallow, that may last for up to 5 {mu}s. The two-chain self-association events, both short- and long-lived, are dominated by formation of contacts in the central part of the sequence. This part tends to form helices when bound to a micelle.
Intrinsically disordered proteins (IDPs) do not possess well-defined three-dimensional structures in solution under physiological conditions. We develop all-atom, united-atom, and coarse-grained Langevin dynamics simulations for the IDP alpha-synuclein that include geometric, attractive hydrophobic, and screened electrostatic interactions and are calibrated to the inter-residue separations measured in recent smFRET experiments. We find that alpha-synuclein is disordered with conformational statistics that are intermediate between random walk and collapsed globule behavior. An advantage of calibrated molecular simulations over constraint methods is that physical forces act on all residues, not only on residue pairs that are monitored experimentally, and these simulations can be used to study oligomerization and aggregation of multiple alpha-synuclein proteins that may precede amyloid formation.
Many proteins carry out their biological functions by forming the characteristic tertiary structures. Therefore, the search of the stable states of proteins by molecular simulations is important to understand their functions and stabilities. However, getting the stable state by conformational search is difficult, because the energy landscape of the system is characterized by many local minima separated by high energy barriers. In order to overcome this difficulty, various sampling and optimization methods for conformations of proteins have been proposed. In this study, we propose a new conformational search method for proteins by using genetic crossover and Metropolis criterion. We applied this method to an $alpha$-helical protein. The conformations obtained from the simulations are in good agreement with the experimental results.