NAR 2026 manuscript: sync M01_abstract.tex with Overleaf edits

Papers/NAR_Update_2026/latex/sections/M01_abstract.tex

@@ -7,4 +7,10 @@
 %% carried them are now Supplementary: PubChem validation, protein-carrier
 %% cofactor standardisation, the reaction-similarity foundation model, and the
 %% v2 draft-model direction-sensitivity study, which is not yet run.
-The ModelSEED Biochemistry Database (\modelseedurl) supplies foundational mass- and charge-balanced reaction networks for metabolic reconstructions. Here we present an update on the biochemistry where the database has been expanded to $\sim46,000$ compounds, and $\sim56,000$ reactions, featuring $\sim37,000$ metabolic structures. We have expanded our approach for handling thermodynamic data, enabling multiple sources of data to be derived, integrated, and presented to the wider research community. We now publish predictions of pKa, reaction energy (and respective uncertainties), and estimates of reaction direction from multiple independent sources. Each reaction is graded gold, silver or bronze according to the strength of the evidence behind it, so that users can weigh its reliability directly. We also release reaction directions predicted by an ensemble of large language models. This multi-source approach exposes agreements and discrepancies between sources for $\sim33,000$ reactions. Finally, to ensure data integrity, a new conflict-resolution pipeline reconciles structures across sources, documenting input from curators. Our work is publicly available at \url{https://github.com/ModelSEED/ModelSEEDDatabase}.
+The ModelSEED Biochemistry Database (\modelseedurl) supplies foundational mass- and charge-balanced reaction networks for metabolic reconstructions.
+Here we present an update on the biochemistry where the database has been expanded to $\sim46,000$ compounds, and $\sim56,000$ reactions, featuring $\sim37,000$ metabolic structures.
+We have expanded our approach for handling thermodynamic data, enabling multiple sources of data to be derived, integrated, and presented to the wider research community.
+We now publish predictions of pKa, reaction energy (and respective uncertainties), and estimates of reaction direction from multiple independent sources.
+Reaction directions are graded gold, silver, or bronze according to the strength of supporting evidence, and are complementarily predicted by an ensemble of large language models.
+These diverse sources empower users to understand agreements or discrepancies in the directionality for $\sim33,000$ reactions.
+Finally, to ensure data integrity, a new conflict-resolution pipeline reconciles structures across sources, documenting input from curators. Our work is publicly available at \url{https://github.com/ModelSEED/ModelSEEDDatabase}.