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Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning

<p>With the development of advanced predictive modelling techniques, we are witnessing a steep increase in model development initiatives in genomics that employ high-end machine learning methodologies. Of particular interest are models that predict certain genomic or biological characteristics based solely on DNA sequence information. These models, however, treat the DNA sequence as a mere collection of four, A, T, G and C, letters, thus dismissing the past physico-chemical advancements in science that can enable the use of more intricate information about nucleic acid sequences. Here, we provide a comprehensive database of quantum mechanical and geometric features for all the permutations of 7-meric DNA in their representative B, A and Z conformations. The database is generated by employing the applicable high-cost and time-consuming quantum mechanical methodologies. This can thus make it seamless to associate a wealth of novel molecular features to any DNA sequence, by scanning it with a matching k-meric window and pulling the pre-computed values from our database for further use in modelling. We demonstrate the usefulness of our deposited features through their exclusive use in developing a model for A to C mutation rate constants.</p> <p>The DNA k-mer quantum mechanical parameters can also be found <a href="https://github.com/SahakyanLab/DNAkmerQM" target="_blank" rel="noopener">https://github.com/SahakyanLab/DNAkmerQM</a>, the corresponding research and development code from <a href="https://github.com/SahakyanLab/NucleicAcidsQM" target="_blank" rel="noopener">https://github.com/SahakyanLab/NucleicAcidsQM</a>, and the associated pre-print from <a href="https://doi.org/10.1101/2023.01.25.525597" target="_blank" rel="noopener">https://doi.org/10.1101/2023.01.25.525597</a>.</p>