Conformational search Molecular dynamics

The main driver behind developing LFMM is computational efficiency. Although DFT has undoubtedly revolutionized the theoretical treatment of TM systems, there are many instances where all QM methods, even DFT, are simply not viable. Comprehensive conformational searching, molecular dynamics, and virtual screening represent hundreds of thousands of individual calculations and QM methods are too expensive. We are forced to turn to classical models but, for TM centers, this presents a whole new set of challenges. However, since we cannot easily make QM orders of magnitude faster, our only option is to make MM smarter and thus able to cope with the extra demands of coordination complexes. 

Using conformational searching/quench dynamics and 7) relaxation measurements, each back-folded isomer was determined to be smaller than its extended counterpart. Thus, the effective distance of electron transfer was not reflected in the hydrodynamic radius of the molecule. Rather, the back-folded isomers were argued to be less mobile with the iron-sulfur core buried more deeply within them. The extended isomers were more mobile with the iron-sulfur core more able to come closer to the molecular surface. By this reasoning, the back-folded isomers had a larger effective electron transfer distance than the extended isomers. 

Random search of an energy surface (see conformational search, deterministic search, Monte Carlo search, molecular dynamics). 

Conformational search Scanning of a potential energy surface. Only deterministic methods (that is point-by-point searches) are fully reliable. However, these are in practice, due to the enormous computational effort, hardly ever possible. The methods currently used include random search methods (stochastic search, e.g., Monte Carlo methods) and molecular dynamics (see Potential energy surface, Deterministic search, Monte Carlo search, Stochastic search. Molecular dynamics, and Scanning an energy surface). 

Schlitter et al. 1994] Schlitter, J., Engels, M., Kruger, P. Targeted molecular dynamics A new approach for searching pathways of conformational transitions. J. Mol. Graph. 12 (1994) 84-89... 

A molecular dynamics simulation samples the phase space of a molecule (defined by the position of the atoms and their velocities) by integrating Newton s equations of motion. Because MD accounts for thermal motion, the molecules simulated may possess enough thermal energy to overcome potential barriers, which makes the technique suitable in principle for conformational analysis of especially large molecules. In the case of small molecules, other techniques such as systematic, random. Genetic Algorithm-based, or Monte Carlo searches may be better suited for effectively sampling conformational space. 

Molecular dynamics simulations are el ficient for searching the conformational space of medium-sized molecules and peptides. Different protocols can increase the elTicieiicy of the search and reduce the computer time needed to sample adequately the available conformations. 

Figure 4.49 reprinted with permission from Pranata J and W L Jorgensen. Computational Studies on FK506 Conformational Search and Molecular Dynamics Simulations in Water. The Journal of the American Chemical Society 113 9483-9493. 1991 American Chemical Society. 

The input to a minimisation program consists of a set of initial coordinates for the system. The initial coordinates may come from a variety of sources. They may be obtained from an experimental technique, such as X-ray crystallography or NMR. In other cases a theoretical method is employed, such as a conformational search algorithm. A combination of experimenfal and theoretical approaches may also be used. For example, to study the behaviour of a protein in water one may take an X-ray structure of the protein and immerse it in a solvent bath, where the coordinates of the solvent molecules have been obtained from a Monte Carlo or molecular dynamics simulation. 

Model optimization is a further refinement of the secondary and tertiary structure. At a minimum, a molecular mechanics energy minimization is done. Often, molecular dynamics or simulated annealing are used. These are frequently chosen to search the region of conformational space relatively close to the starting structure. For marginal cases, this step is very important and larger simulations should be run. 

For a conformation in a relatively deep local minimum, a room temperature molecular dynamics simulation may not overcome the barrier and search other regions of conformational space in reasonable computing time. To overcome barriers, many conformational searches use elevated temperatures (600-1200 K) at constant energy. To search conformational space adequately, run simulations of 0.5-1.0 ps each at high temperature and save the molecular structures after each simulation. Alternatively, take a snapshot of a simulation at about one picosecond intervals to store the structure. Run a geometry optimization on each structure and compare structures to determine unique low-energy conformations. 

Researchers report that high temperature molecular dynamics searches of many different starting conformations are much more efficient than using one starting structure and longer simulations. 

Quenched dynamics can trap structures in local minima. To prevent this problem, you can cool the system slowly to room temperature or some appropriate lower temperature. Then run room temperature molecular dynamics simulations to search for conformations that have lower energies, closer to the starting structure. Cooling a structure slowly is called simulated annealing. 

Aproblem in searching conformational space using molecular dynamics simulations is repeating a trajectory that generates the same structures. To reduce this possibility, you can randomize the velocities of the atoms. 

One of the most important considerations in using molecular dynamics for a conformational search is determining the sampling interval. HyperChem lets you sample the simulation in two ways ... 

You can often use experimental data, such as Nuclear Overhauser Effect (NOE) signals from 2D NMR studies, as restraints. NOE signals give distances between pairs of hydrogens in a molecule. Use these distances to limit distances during a molecular mechanics geometry optimization or molecular dynamics calculation. Information on dihedral angles, deduced from NMR, can also limit a conformational search. 

A molecular dynamics simulation used for a conformational search can provide a quick assessment of low energy conformers suitable for further analysis. Plot the average potential energy of the molecule at each geometry. This plot may also suggest conformational changes in a molecule. 

The choice of heating time depends on the purpose of the molecular dynamics simulation. If the simulation is for conformational searches, the heating step is not critical for a successful calculation. The heating step may be rapid to induce large structural changes that provide access to more of the conformational space. 

To overcome the limitations of the database search methods, conformational search methods were developed [95,96,109]. There are many such methods, exploiting different protein representations, objective function tenns, and optimization or enumeration algorithms. The search algorithms include the minimum perturbation method [97], molecular dynamics simulations [92,110,111], genetic algorithms [112], Monte Carlo and simulated annealing [113,114], multiple copy simultaneous search [115-117], self-consistent field optimization [118], and an enumeration based on the graph theory [119]. 

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