All rights reserved. No reuse allowed without permission.(which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/210039 doi: bioRxiv preprint first posted online Oct. 27, 2017; 2 AUTHORS SUMMARYThe recent advances in pathway generation tools have resulted in a wealth of de novo hypothetical enzymatic reactions, which lack knowledge of the protein-encoding genes associated with their functionality. Moreover, nearly half of known metabolic enzymes are orphan, i.e., they also lack an associated gene or protein sequence. Proposing genes for catalytic functions of de novo and orphan reactions is critical for their utility in various applications ranging from biotechnology to medicine. In this work, we propose a novel computational method that will bridge the knowledge gap and provide candidate genes for both de novo and orphan reactions. We demonstrate that information about a small chemical structure around the reactive sites of substrates is sufficient to correctly assign genes to the functionality of enzymatic reactions. ABSTRACTThousands of biochemical reactions with characterized biochemical activities are still orphan. Novel reactions predicted by pathway generation tools also lack associated protein sequences and genes.Mapping orphan and novel reactions back to the known biochemistry and proposing genes for their catalytic functions is a daunting problem. We propose a new method, BridgIT, to identify candidate genes and protein sequences for orphan and novel enzymatic reactions. BridgIT introduces, for the first time, the information of the enzyme binding pocket into reaction similarity comparisons. It ascertains the similarity of two reactions by comparing the reactive sites of their substrates and their surrounding structures, along with the structures of the generated products. BridgIT compares orphan and novel reactions to enzymatic reactions with known protein sequences, and then, it proposes protein sequences and genes of the most similar non-orphan reactions as candidates for catalyzing the novel or orphan reactions. We performed BridgIT analysis of orphan reactions from KEGG 2011 (Kyoto Encyclopedia of Genes and Genomes, published in 2011) that became non-orphan in KEGG 2016, and BridgIT correctly predicted enzymes with identical third-and fourth-level EC numbers for 91% and 56% of these reactions, respectively. BridgIT results revealed that it is sufficient to know information about six atoms together with their connecting bonds around the reactive sites of the substrates to match a protein sequence to the catalytic activity of enzymatic reactions with maximal accuracy. Moreover, the same information about only three atoms around the reactive site allowed us to correctly match 87% of the analyzed enzymatic reactions. Finally, we used BridgIT to provide candidate protein sequences for 137000 novel enzymatic reactions from the recently introduced ATLAS of Biochemistry...