Discrepancy when calulating mol weights with ChemSketch and Python RDKit

Question

I am an IT guy with little knowledge of Chemistry, so please bear with me...

For context: I am working with a system that has a lot of structures, their .mol files and some metadata (like mol weights) in a database. Due to an error, some of the metadata was lost and needs to be recalculated. Since there are a lot of structures, I need to automate this.

Originally, the mol weights were calculated using the Freeware version of ACD ChemSketch. Since I did not find a way to call ChemSketch and have it return the mol weight or otherwise automate ChemSketch itself, I looked at RDKit for Python as an alternative.

In my tests, I noticed that ChemSketch and RDKit produced slightly different results when calculating the mol weights. I used m = Chem.MolFromMolFile('amisalin.mol') to load the file and then MolWt(m) respectively ExactMolWt(m).

Example mol file amisalin.mol:

  -ACD/LAB-

 18 17  0  0  0  0  0  0  0  0  0 V2000
   18.3905   -6.6892    0.0000 C   0  0  0  0  0
   19.4429   -6.0748    0.0000 C   0  0  0  0  0
   18.3905   -8.0661    0.0000 C   0  0  0  0  0
   17.2059   -5.9960    0.0000 C   0  0  0  0  0
   20.5930   -6.7427    0.0000 N   0  0  0  0  0
   19.4429   -4.2757    0.0000 O   0  0  0  0  0
   17.2059   -8.7560    0.0000 C   0  0  0  0  0
   16.0211   -6.6892    0.0000 C   0  0  0  0  0
   21.7398   -6.0748    0.0000 C   0  0  0  0  0
   16.0211   -8.0661    0.0000 C   0  0  0  0  0
   22.5401   -6.5380    0.0000 C   0  0  0  0  0
   14.8742   -8.7309    0.0000 N   0  0  0  0  0
   23.6965   -5.8762    0.0000 N   0  0  0  0  0
   24.8434   -6.5380    0.0000 C   0  0  0  0  0
   23.6965   -4.0709    0.0000 C   0  0  0  0  0
   25.9934   -5.8762    0.0000 C   0  0  0  0  0
   24.8434   -3.4124    0.0000 C   0  0  0  0  0
   21.0845  -12.6663    0.0000 Cl  0  0  0  0  0
  1  2  1  0  2  0  0
  1  3  2  0  1  0  0
  1  4  1  0  1  0  0
  2  5  1  0  2  0  0
  2  6  2  0  2  0  0
  3  7  1  0  1  0  0
  4  8  2  0  1  0  0
  5  9  1  0  2  0  0
  7 10  2  0  1  0  0
  9 11  1  0  2  0  0
 10 12  1  0  2  0  0
 11 13  1  0  2  0  0
 13 14  1  0  2  0  0
 13 15  1  0  2  0  0
 14 16  1  0  2  0  0
 15 17  1  0  2  0  0
  8 10  1  0  1  0  0
M  END

Results:

	Average molar weight	Exact molar weight
Chemsketch	271.78628	271.14514
RDKit	271.7919999999999	271.145140004

As you can see, the results are slightly different. Since the input data is identical, I assume this is due to some internal differences when calculating the weights, possibly due to rounding (?).

My question now is: Is the difference negligible? Does anyone know where it comes from? Is one of the results "correct" / more accurate than the other?

Answer 1

In first place, you must clarify with the users of the database the purpose of the entries about molecular weight because average molecular weight and exact molecular weight differ in their meaning and subsequent use. It may be that the documentation of the database provides this information. Later, once this target is set, use either one of the program to compute the entries for all compounds of this database to ensure consistency in the data. RDKit's current release 2021_03_1 is just some weeks old and probably the easier route to cover eventually all entries in your database.

• Molecules consist of atoms (like oxygen, nitrogen, etc). For some of them, say nitrogen, despite they are all nitrogen, there might be more than one form and these differ slightly in their mass per individual atom (isotopes).

• The mass of these isotopes is published. Equally, biannually, there are updated public records about the probability that an atom of e.g., nitrogen either is $\ce{^{14}N}$ (about 99.6%) or $\ce{^{15}N}$ (about 0.4%).

• These probabilities are equally valid for molecules, if you have 1000 molecules each containing one atom of nitrogen, than 4 of them should contain the heavier isotope $\ce{^{15}N}$. Similar there are such probabilities about other atoms, like carbon, oxygen, etc., which are all independent of each other. Among carbon atoms, for example, 98.9% are $\ce{^{12}C}$, and 1.1% are $\ce{^{13}C}$, respectively. (Except in radiochemistry / nuclear chemistry.)

• Exact molecular weight is used, e.g. in databases eventually used for e.g., mass spectroscopy. An analysis of your sample will recognize these different probabilities and may yield different, separate signals about the molecules with $\ce{^{14}N}$ from the ones about $\ce{^{15}N}$. Thus exact molecular weight is about molecules of one isotopic composition.

  Say our sample were $\ce{(CN)2}$ of two carbon atoms and two nitrogen atoms per molecule, than there would be four mass signals for all combinations of the two isotopes of carbon and nitrogen possible. Their intensity correlate with these probabilities. Exact molecular weight is a monoisotopic mass, typically to consider only the mass of the molecules consisting with the most frequently observed isotopes per element, i.e., only about $\ce{^{12}C}$ and $\ce{^{14}N}$. Depending on the intended analysis, it may be worth to retain six (or even more) decimals.

• Average molecular weight now accounts not only for the molecules consisting of the most frequently seen isotopes per element, but for any combination of the elements with each other. These weights are are averaged by the probability that these combinations occur, e.g that there is a molecule $\ce{(^{13}C^{14}N)2}$ consisting only of the heavier carbon isotope and the lighter nitrogen isotope among all $\ce{(CN)2}$ molecules of your sample. Average molecular weights are typically used in to set up a reaction in the lab, to know how many grams of compound A shall react with how many grams of compound B. Depending on the scale of the reaction and the needs of your clients, to retain two decimals of this value may suffice.

The pace these IUPAC publishes the data about these isotopes is independent from the one the programs are updated by the developers, and later by the users. This contributes why an old program still may include outdated values.