When conducting research in the field of chemistry, or even teaching chemistry to a student, it is often useful to visualize the structure, or shape, of a molecule.
In the past, when chemists wanted to visualize the shape of a molecule, the chemist built a physical model of the molecule using, for example, molecular structural models comprised of interconnectable plastic balls (representing atoms) and sticks (representing bonds). Not only was the construction of such models a tedious and time consuming task, but, moreover, the calculations required to determine the proper coordinates of the balls were also highly time consuming.
Recently, the use of computer graphics terminals has greatly simplified the task of determining the structure, shape, and properties of molecules. Various graphics systems are currently available for use in generating molecular models. Such systems include the Chem-X, Sybyl, Quanta, and CSC Chem3D systems. While the features of these systems vary to some extent, each provides a graphical representation illustrating the shape of molecules. With, for example, the Chem-X system, a user can create a graphical representation of a molecule in several ways:
1. The User can draw his/her own molecule using, for example, a keyboard and mouse;
2. The User can input experimental data which represents the structure of an actual molecule;
3. The User can retrieve a previously stored molecular structure.
Once the initial structure of a molecule is entered into the system in one of these three ways, then an energy minimization (or molecular dynamics) technique can be used to find the most likely structure of the molecule.
A trained chemist can learn a great deal from looking at the structures of molecules on a computer graphics terminal. For example, biologically active molecules often act by binding to a region of a protein known as the active site. By looking at the minimum energy structures of a set of molecules that bind to an active site, a chemist might be able to determine what features of the molecules were responsible for both good and poor binding energies. He or she could then use this information to propose new molecules that combined the good features of two or more molecules or even propose features that were not present in any of the original molecules.
A trained chemist can also learn a great deal from using a graphics terminal to look at how the atoms in a molecule move during a molecular dynamics calculation. When this is done, the chemist is able to see what is in essence a moving picture of the molecule in action. Since molecules do move and such motions can affect their properties, viewing a molecular dynamics simulation as it evolves can be more informative than looking at still shots of the molecule.
In determining the structure, shape, and thermodynamic properties of molecules and aggregates of molecules, chemists generally calculate the energy of the molecules. The structure and thermodynamic properties are important because they affect many of the other properties of a molecule. For example, the activity of a drug molecule depends on its ability to bind to an active site. Binding occurs only if the shape of the drug molecule allows it to fit into the active site and the binding energy is favorable.
Although the properties obtained from energy calculations can usually be determined experimentally, energy calculations are useful adjuncts to experiments because experiments are time consuming and expensive. An additional advantage of energy calculations is that they can help the chemist in understanding why changes in the molecular structure cause the properties of the molecules to change, while experiments usually reveal only what the change is. Knowing why the properties of existing molecules vary can be very useful in developing new molecules with more desirable properties.
It is generally accepted that the most accurate and reliable energy calculation method is complete quantum mechanics done without using approximations. Doing quantum mechanics without approximations means doing ab initio calculations with an extremely large number basis functions and doing configuration interaction calculations that involve all possible combinations of excited states. Unfortunately, such complete calculations are so computationally intensive that they are seldom done.
Currently ab initio calculations are typically done using a basis set with a moderate number of basis functions and using only a few excited states. Such medium level calculations are felt to give the best trade-off between reliability and cost. Even these medium level calculations, however, take a significant amount of computer time. For example, an ab initio calculation of benzene, which contains 6 carbon atoms and 6 hydrogen atoms, with the RHF/6-31+G basis set and configuration interactions involving only 8 singly excited states requires 2.5 hours on a computer with an Intel.TM. 80486DX2 CPU running at 66 MHz.
The calculation discussed above involved only a single calculation of the energy of a molecule with a fixed geometry. If the geometry had been optimized to find the lowest energy structure the calculation would have been from 10 to 100 times longer. (Note that the terms geometry optimization and energy minimization are interchangeable in the context of this discussion.) Quantum mechanics molecular dynamics calculations take at least 10 times longer than geometry optimizations and are so time consuming that they are seldom performed. In addition, since the mount of computer time required to do a calculation increases as the 4th power of molecular size, even medium level ab initio calculations are usually confined to molecules with less than 20 nonhydrogen atoms. An illustration of the combined effect of increasing the number of atoms and optimizing the geometry is that the geometry optimization of a molecule containing 22 nonhydrogen atoms required over a week of CPU time on a Cray.TM. supercomputer. Cray supercomputers are over 10 times faster than Intel 80486 based computers.
For medium or large molecules, either approximate quantum mechanics methods are used, which reduce the reliability of the calculation, or less expensive methods, such as molecular mechanics, are used.
Molecular mechanics calculations are much faster and cheaper than complete quantum mechanics calculations, and, when used properly, molecular mechanics calculations can approach the accuracy of complete quantum mechanics calculations. Thus they are often the best calculation method for medium sized molecules and are usually the only practical method for large molecules or aggregates of molecules.
Both quantum mechanics and molecular mechanics methods require an initial structure of a molecule. The two most common methods of describing initial structures are Cartesian coordinates and Z-coordinates. The Cartesian coordinate method gives the location of each atom relative to a set of Cartesian coordinates and often includes a list identifying which atoms are bonded to each other. In situations where the bond lengths are known to have typical values, the bond list can be derived from the coordinates. The Z-coordinate method identifies the atoms making up each bond and its length, the atoms making up each bond angle and its value, and the atoms making up each torsional angle and its value. These two methods of describing the molecule contain the same information--each can be generated from the other. It is usually more convenient to do calculations using Cartesian coordinates. Thus Z-coordinates are usually converted into Cartesian coordinates at the start of a computation. People, however, find Z-coordinates easier to understand and calculated structures are often converted into Z-coordinates for display purposes.
Molecular mechanics calculations fall into two categories: energy minimizations and molecular dynamics.
In accordance with energy minimization techniques, the position of each atom is varied over a plurality of iterations until a minimum in the energy of the molecule, as determined by the force field, is found. This static, minimum energy structure, is then taken to represent what occurs in an experiment. This corresponds to doing an experiment in a vacuum at absolute zero. Even though very few experiments are done under these conditions, it has been empirically determined that the time averaged structure of a particular conformation of a molecule is usually similar to that conformation's minimum energy structure.
Molecular dynamics calculations integrate Newton's second law to reproduce the dynamics and movement of the atoms in both single molecules and aggregates containing many molecules. The advantage of molecular dynamics, as opposed to energy minimizations, is that it reproduces the dynamic nature of molecules. For example, if there are many conformations, a molecule will visit all of them during a properly conducted molecular dynamics calculation and the calculated properties will be a statistical average of all the conformations. The ability to obtain average values is important because experimental properties are usually obtained from a sample containing an extremely large number of molecules. Thus, experimental values are averages. The averages that can be obtained from molecular dynamics calculations are believed to be a better approximation of experimental values than the values for a single structure obtained from minimizations.
The large number of terms that must be evaluated in molecular mechanics calculations causes minimizations and molecular dynamics calculations of large molecule to take hours or even days on even the fastest computers. Thus, while molecular mechanics calculations are less expensive than quantum mechanics calculations, they can still be time consuming and expensive. As such, molecular mechanics calculations, while less computationally intensive than quantum mechanics calculations, can be too time consuming for effective use with large molecules in computerized molecular modeling systems.
Consequently, a need existed to design a computer system that reduced the computer time required for such calculations. Thus most programs that perform molecular mechanics calculations use standard techniques for increasing the efficiency of the calculations, such as calculating mathematical expressions that occur in more than one place only once and using methods like those described in J. Bentley, "Writing Efficient Programs" (192). However, such standard techniques are not sufficient to produce the speed increases needed. Thus additional techniques are needed. Since most of the computer's processing time is spent calculating non-bonded interactions, these interactions have received the most attention. The term "interaction" refers to a relationship between atoms, and, in the context of molecular modeling, interactions are generally used to refer to a force or energy that varies depending on the distance and/or orientation of two or more atoms relative to each other.
Two methods have been widely used in both minimizations and molecular dynamics calculations to reduce the time spent calculating non-bonded interactions.
One method takes advantage of the fact that forces between widely separated atoms are small. This method establishes a distance, known as the cut-off distance, and all forces between atoms separated by distances greater than the cut-off distance are assumed to be zero and not calculated. This method was found to be adequate when electrostatic interactions are negligible. However, when electrostatics are important, it was found that a large cut-off distance is required in order for the results to agree with calculations performed without a cut-off distance. Unfortunately, when large cut-off distances are used, large numbers of non-bonded interactions remain inside the cut-off distance.
A second method, which is more commonly used than the first method, also makes use of a cut-off distance. However, the forces beyond the cut-off distance are treated as having a non-zero but constant value. To implement this method, the forces between atoms beyond the cut-off distance are calculated during an initial or set-up step and the sum of these forces that act on each atomic coordinate are saved. Then, in later steps, the previously saved sum of the forces are used for interactions outside the cut-off distance. It has been found that for the same degree of accuracy, that a smaller cut-off distance can be used when the forces beyond the cut-off are treated as constant instead of zero. As such, this second method is less computationally intensive than the first.
Since the movement of atoms during the calculation causes the forces beyond the cut-off distance to slowly change, most implementations of either method periodically recalculate all interactions outside the cut-off distance to update the saved forces. Failure to recalculate a force frequently enough will cause the calculation to be in error. In large molecules, the computer can spend most of its time doing these periodic recalculations. As a result, when performing molecular mechanics calculations to provide a graphical representation of the likely structure of a molecule, it is desirable to do as few recalculations of the forces as possible without reducing the accuracy of the calculation.
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