Proteins quantum chemical methods

The subsequent chapters will describe various quantum-chemical methods, compare them to experimental results and discuss their applications to such biological systems as amino acids, peptides, carcinostatic drugs, and DNA fragments. Proteins and large DNA fragments cannot be treated as yet with quantum-chemical methods, due to their size, but progress is being made continuously. 

Abstract. We report the results of experimental and theoretical studies of 13C and 15N shifts in proteins and model systems, together with 57Fe shifts and Mossbauer quadrupole splittings (electric field gradients) in metalloporphyrins and metalloproteins. The ability to relate these spectroscopic observables to structure by using quantum chemical methods opens up new opportunities for predicting and refining protein structure. 

We therefore set about, with A. C. de Dios and J. G. Pearson, and using the Texas code from P. Pulay (12), the process of computing 13C and 15N shieldingsin proteins using purely quantum chemical methods. To our delight - it worked (13). In particular, we found that we could use quite small amino acid derivatives, N-formyl-amino-acid amides, which contain two peptide-like amide groups ... 

Quantum chemical methods aim to treat the fundamental quantum mechanics of electronic structure, and so can be used to model chemical reactions. Such quantum chemical methods are more flexible and more generally applicable than molecular mechanics methods, and so are often preferable and can be easier to apply. The major problem with electronic structure calculations on enzymes is presented by the very large computational resources required, which significantly limits the size of the system that can be treated. To overcome this problem, small models of enzyme active sites can be studied in isolation (and perhaps with an approximate model of solvation). Alternatively, a quantum chemical treatment of the enzyme active site can be combined with a molecular mechanics description of the protein and solvent environment the QM/MM approach. Both will be described below. 

A noteworthy chemometrical method (CHEMDOCK) for establishing complementary relationships between receptors and ligands has been devised by Oloff et al. [122], Their approach employs atomic descriptors derived by quantum chemical methods (TAE/RECON descriptors [123]), which represent both the ligand structures and the protein binding pockets in global a descriptor space. 

The size and complexity of extended biomacromolecules makes the understanding of the various energy contributions which contribute to their stabilization difficult, since only calculations using simple empirical potential calculations are tractable. Fortunately, the most importance biomacromolecules, DNA and proteins, consist of characteristic building blocks-the nucleic acid bases and amino acids-interacting through noncovalent interactions. The system can therefore be fragmented into smaller components, each of which can be described by means of ab initio quantum chemical methods. 

It is not yet possible to perform accurate quantum chemical calculations on a whole protein. Therefore models have to be constructed that are as realistic as possible but at the same time computationally tractable. We have used a number of techniques, ranging from high-level quantum chemical calculations on small models of the active site to classical simulations of the full protein. At the intermediate level, we have described the protein by quantum chemical methods and incorporated the effects of the surrounding protein and solvent by a variety of... 

MM methods have the advantage that they are much faster than the more robust quantum chemical methods. However, as outlined in a recent review article by Ryde [4], MM methods only yield good bond lengths and angles when the force fields are specifically parameterized for the class of chemical system under consideration. While it is common to describe orthodox protein chains reliably via this approach, available force fields often poorly describe unusual features including substrates, inhibitors, metal sites, and unusual protein conformations. To account for these problems many successful examples were shown by Ryde in which hybrid approaches involving simultaneous application of quantum mechanics (QM) and... 

MM methods, so-called QM/MM schemes, were applied to protein structures (see e.g. Refs. [5-11]). In QM/MM approaches, the important parts of the protein are treated with quantum chemical methods (usually density functional theory (DFT) [12, 13]) and the less important parts by MM approaches. 

Wada M, Sakurai M (2005) A quantum chemical method for rapid optimization of protein structures. J Comput Chem 26 160-168... 

In a 1996 review article on the future of quantum chemical methods, I lead Gordon paints a bleak picture for future conventional calculations. At the time, HF or DFT calculations on 100 atoms were feasible (it is closer to 150 today). He sets a goal of 10,000 atoms as the arrival point for the age of explicit calculations on entire proteins. This is a 100-fold increase from 1996, but due to the scaling of conventional HF and DFT, such a task would require an unrealistic 600-fold increase in computational power. Furthermore, for high-level CCSD(T) calculations, even a 600-fold increase in processing speed would only improve applicability of the method by a factor of five. Clearly, something must be done if this goal is to become a reality [23]. 

Finally, we mention an approach that treats the whole (or a large fraction) of a protein by QM using linear-scaling methods. The ability to treat whole molecules the size of proteins using quantum chemical methods is a significant achievement and may obviate the need for the MM region. Thus, for a moderately sized solute molecule, hundreds of explicit water molecules could easily be treated quantum mechanically. However, at present these models have only limited application [108], as they remain too costly for the purpose of MD simulation and are restricted to semiempirical QM methods which are prone to unpredictable errors. 

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