Saturday, January 7, 2017

Reviews of Prediction of pKa values for drug-like molecules using semiempirical quantum chemical methods

I have been remiss in posting reviews of my papers. I submitted the paper to Journal of Physical Chemistry A on November 2, 2016, received first round of reviews November 29, and second round of reviews December 12.  The paper was accepted January 5, 2017 and has appeared online.

Round 1
Reviewer(s)' Comments to Author:

Reviewer: 1

Recommendation: This paper is not recommended because it does not provide new physical insights.

Comments:
This is an interesting study on very important subject - prediction of pKa for drug-like molecules. Standard free energy of a molecule is determined as the sum of heat of formation/electronic energy and solvation free energy and these terms are obtained by various semiempirical QM (SQM) methods and two continuous solvent models. Author used SQM methods as a black box and compared them on the basis of their performance to predict pKa. This is, however, not justified since the SQM methods used described differently system under study. For example, PM6-DH+ describes well H-bonding and dispersion energy contrary to e.g. PM3 and AM1. Consequently, structures stabilized by H-bonding and dispersion will be described much better by the former method. Further, PM7 was parametrized to cover dispersion in core parametrization, contrary to PM6 (and PM3) where it should be included a posteriori by e.g. DH+ term. Consequently, PM7 should be also better suited than, e.g. PM6. The question arises how good those methods work and here performance of these methods should be compared with some higher-level method like DFT.

Further, SQM methods were in the last 5 years already used for protein - ligand interactions but these papers were not mentioned at all.

On the basis of above-mentioned arguments I cannot recommend the paper for publication in JPC.

Reviewer: 2

Recommendation: This paper is publishable subject to minor revisions noted.  Further review is not needed.

Comments:
This is simply excellent work on an important topic. The only thing is that the author could put the importance of his work in an even greater perspective. Semi-empirical methods are becoming increasingly important also in materials science and the pKa is of high importance also in this field, as it is a good indicator of general chemical stability (like it is used in organic chemistry) of molecular (especially organic) materials for technical applications. A recent example is the search for new organic electrolyte solvents for Lithium-air battery devices, where current design principles strongly rely on pKa values (see for instance http://pubs.rsc.org/en/Content/ArticleLanding/2015/CP/C5CP02937F#!divAbstract ).

Round 2
Reviewer(s)' Comments to Author:

Reviewer: 1

Recommendation: This paper is not recommended because it does not provide new physical insights.

Comments:
Since the ms was not modified according my comments I cannot recommend it for publication.


Reviewer: 3

Recommendation: This paper is publishable subject to minor revisions noted.  Further review is not needed.

Comments:
This paper evaluates a number of semi-empirical quantum mechanical (SQM) methods for their suitability in calculating the pKa’s of amine groups in drug-like molecules, with the hope that these methods can be used for high-throughput screening.  This paper is suitable for publication in the special issue, subject to minor revision.

(a) The paper shows that pKa’s calculated by some SQM methods is sufficiently accurate for high-throughput screening.

(b) Indicate the accuracy of related QM calculations (e.g. Eckert and Klamt) and the relative cost of QM vs SQM calculations (order of magnitude will do)

(c) How much better is the SQM approach than the empirical methods cited by the author? (add a comparison in the tables)

(d) The need for 26 reference compounds for 53 amine groups in 48 molecules is disturbingly high (so much so that the null hypothesis has errors only a factor of 2 larger than the best results). What are the errors in the SQM calculated pKa’s if a much smaller number of reference compounds are used? (e.g. 6 or less)  If the errors are acceptable, this could make it possible to automate the procedure so that it could be used to screen larger sets of molecules extracted from typical industrial databases (10,000 – 10,000,000 compounds).



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