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Objective of Methods in MOPAC

Over the years, the purpose of the methods in MOPAC has steadily changed.  In the 1980's, their purpose was to reproduce the properties of molecules.  At that time, the most important properties were heat of formation, geometry, dipole moment and ionization potential.  The relative importance of each property was defined (and still is) defined using weighting factors.  As time went by it became more and more apparent that accurate reproduction of all four properties was simply not possible.  Whether this failure was due to errors in the set of approximations used, faulty or inadequate reference data, incomplete parameter optimization or insufficient skill of the method developers, was not important, the fact remained that simultaneous accurate prediction of all four properties was not achieved.  At the same time, the importance of predicting the the purely chemical quantities DHf and geometry increased, and the importance of predicting the electronic quantities dipole moment and ionization potential decreased.  As a result of the changing priorities, the purpose of the more recent methods in MOPAC has changed.

As the importance of accurate prediction of chemical properties increased, the definition of reference data has had to be re-visited.  The first of the NDDO methods, MNDO (published in 1977) was a great improvement over even earlier methods, but it was so inaccurate that comparison of MNDO results with experimental reference data and with high-level computed reference data gave essentially the same results.  This should not be construed as disparaging MNDO - it was much faster than ab-initio methods, and was really the first of the modern semiempirical methods.  Several other methods were developed over the years, and as the accuracy improved the difference between experimental reference data and reference data obtained from high-level calculations became more and more important. Where experiment and high-level theory agreed, there was no problem - obviously either would do as the source of reference data.  Where they disagreed, a decision had to be made regarding which data to use.  If an experimental datum was reliable - and often this was hard to determine - then that was used, otherwise the theoretical prediction was used. 

Current methods  

The two recent methods, PM6 (and its variants, PM6-DH2, PM6-DH+, and PM6-D3) and PM7 were designed to allow chemical systems to be modeled.  This means that increased emphasis has been given to geometries and heats of formation, at the expense of dipole moments and I.P.s.  Because non-covalent interactions are important in proteins and other complicated systems, e.g., crystals of organic compounds, increased emphasis has been given to long-range effects, specifically hydrogen bonds and dispersion effects.  Electrostatics are a special case, in that these, although very important, are easy to calculate, even in solids.

A consequence of this increased emphasis on chemical properties and weak interactions is that properties such as salt bridges,  p - p interactions, p-stacking, VDW interactions, etc., are now predicted with good accuracy.   Because of this, PM7 now predicts many protein properties with good accuracy.

Despite the increased accuracy, there are several known small but important faults in PM7.  Two of the most important being the approximations for dispersion and for hydrogen bonding.  These can amount to 0.2 kcal/mol or more.  In biochemistry and other branches of organic chemistry, errors in non-covalent interactions are considerably more important than the equivalent errors in covalent interactions.  This is because these interactions, although much weaker than covalent interactions, have a greater influence the properties of the system.  These faults could be removed, but, if that were done, it is likely that other faults would appear elsewhere. 

Changes to methods after they are released

 First and most important: MOPAC is a computational chemistry tool. Its purpose is to allow researchers and students to model chemical phenomena. A pre-requisite for this is that each new version of MOPAC, whether it be a big version change, e.g. MOPAC2009 going to MOPAC2012, or a small change, version 13.284 going to version 13.306, should give exactly the same results for the same data-set. This requirement for perfect continuity means that a job that had been run 10, 20, or even 30 years ago should have the same results as the equivalent job run today. Many research programs take years to complete, so there is a strong reason to ensure reproducibility. Put another way, MOPAC is not intended to be a show-case for semiempirical methods. If it was, then only the latest and most accurate methods would be supported, and as improvements are made in methodology, those improvements would be immediately incorporated into the program. As such, each new version would be the most accurate, but the program would then be essentially useless as a research tool, because users could not trust that results obtained on one day could be related to results obtained on a different day.

There are two exceptions to the rule that methods in MOPAC are not changed.

(a) As each new method is released, the default method changes to the new method. This could potentially cause unpleasant surprises as results obtained with the previous default method would change when a new default method is used. To minimize the potential for surprises of this type, when a new method is first released there is no default method. Jobs will fail unless a method is explicitly specified. Thus before PM7 became available the default method was PM6. When PM7 became available, MOPAC jobs required the method (PM6 or PM7) to be specified as a keyword. After a while a default method is re-introduced, so, in the case of PM7, the need to explicitly specify the keyword PM7 was dropped after several months.

(b) If, after a new method is released, a fault is found that could be corrected by a simple change, then that change might be made. The decision of whether or not to make the change depends on two competing factors: (1) is the change sufficiently important to justify modifying a method, and (2) how much harm would result from the change potentially compromising the integrity of research projects already underway. With over 18,000 licensed sites world-wide, the potential for causing disruption to research projects is obvious. Because of this, only important changes are made to methods, and then only in the first few months after a method is released. That is, at a time when a user's investment in effort is still small and it would still be easy for users to re-run jobs. The procedure for making such a change is similar to that for introducing a new method, i.e., a keyword to alert the user to the change is required and then, after a few months, the changed method becomes the default.

At the time when a new method is being designed, all the notes on faults in the existing current method and on suggestions for improvement are reviewed, and, where appropriate, incorporated into the design of the new method. After a method has been available for many months, and a fault is discovered in that method or a change is made that results in a significant improvement in accuracy, no action is taken to modify the method to eliminate the fault or to implement the improvement.  To do so would cause more harm to the large number of users whose projects would be affected by the change.  Instead, a note is made of the issue.  For an example of such notes, see PM6 Accuracy and PM7 Faults. Later on, when a new method is being designed, all the notes on faults in the existing current method and on suggestions for improvement are reviewed, and where appropriate, incorporated into the design of the new method.