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Accurate Prediction of B-form/A-form DNA Conformation Propensity from Primary Sequence: A Machine Learning and Free energy Handshake

preprint
revised on 27.08.2020 and posted on 28.08.2020 by Abhijit Gupta, Mandar Kulkarni, Arnab Mukherjee

DNA carries the genetic code of life. Different conformations of DNA are associated with various biological functions. Predicting the conformation of DNA from its primary sequence, although desirable, is a challenging problem owing to the polymorphic nature of DNA. Although a few efforts were made in this regard, currently there exists no method that can accurately predict the conformation of right- handed DNA solely from the sequence. In this study, we present a novel approach based on machine learning that predicts A-DNA and B-DNA conformational propensities of a sequence with high accuracy (~95%). In addition, we show that the impact of the dinucleotide steps in determining the conformation agrees qualitatively with the free energy cost for A-DNA formation in water. This method enables us to examine the genomic sequence to understand the prospective biological roles played by the A-form of DNA.

Funding

Department of Science and Technology (DST), Science and Engineering Board (SERB), Govt. of India ((Grant EMR/2016/001069)

Department of Biotechnology, India (BT/PR34215/AI/133/22/2019)

History

Email Address of Submitting Author

arnab.mukherjee@iiserpune.ac.in

Institution

Indian Institute of Science Education and Research Pune

Country

India

ORCID For Submitting Author

0000-0001-5691-6120

Declaration of Conflict of Interest

There is no conflict of interest.

Version Notes

Version 2 of the MS

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