## 3 Discussion  
Among the various natural products synthesized in all living organisms, terpenoids are the most chemically, structurally, and functionally diverse array of metabolites with numerous applications in many aspects of our daily life [27]. Despite their enormous diversity, terpenoid carbon skeletons are all derived from polyprenyl pyrophosphate substrates of various chain lengths, which are determined by the reaction catalyzed by prenyltransferases [8]. Structurally and evolutionarily distinct from the short-chain _cis_-phenyltransferases reported in limited species [28; 29], short-chain _trans_-phenyltransferases provide precursors for the vast majority of commonly found terpenoids including mono-, sesqui-, di-, and triterpenes, thus determining the types of terpenoid metabolites synthesized in a specific species [6]. The chemodiversity of terpenoids is further expanded by TPS enzymes, which often display promiscuous substrate specificities from in vitro assays [30; 31]. However, the genuine in vivo activities of TPS enzymes necessarily depend on the substrate pools they can use [32]. With the fast development of genome sequencing, a rising number of prenyltransferases have been predicted in public databases, but a substantial portion of them were incorrectly annotated simply according to sequence similarities. A reliable method for the functional prediction of _trans_-PIs is important for the investigation of terpenoid biosynthetic pathways and will benefit the discovery of hidden natural products. On the basis of our previously established \"three floors\" model [10], an automatic algorithm was designed using 11 searching templates that covered 85% of 7840 _trans_-PT sequences in the SFLD database (Figure 2A). The final equation was developed as a web tool named PTS-Pre for the precise functional prediction of _trans_-PIs (Figure 2B). Our analyses show that PTS-Pre yielded an 86% high prediction accuracy for 141 experimentally characterized _trans_-PIs covering Archaea, Bacteria, and Eukarya (Figure 3C), and the accuracy was as high as 90% when the predicted function was within one C5 unit. Compared with MD-Pre, the only known functional prediction method for _trans_-PIs [14], which had 58% accuracy over 74 experimentally determined _trans_-PTs, PTS-Pre displayed a 77% high accuracy over the same testing sequences (Figure 3A, Tables S3 and S4). The method was then validated by characterizing randomly selected genes from three species ranging from Actinobacteria to Cyanobacteria and Viridiplantae, revealing 100%, 75%, and 50% accuracies, respectively (Table 1). It seemed that more primitive genes yielded lower prediction accuracies. The sequence similarity network and phylogenetic tree further suggested the prediction accuracy may be related to the gene's evolutionary position in the tree with a lower accuracy closer to the root (Figure S6). To further explore the molecular \begin{table}
\begin{tabular}{c c c c} \hline
**Protein ID** & **Organism** & **PTS-Pre Predicted** & **Experimentally Determined** \\ \hline WP\_084743876 & _Tolypothrix campylonemoides_\({}^{\ast}\) & C20/C25 & C25 \\ RCJ15756 & _Nostoc_ sp. _ATCC_ 43529 \({}^{\ast}\) & C20/C25 & C25 \\ WP\_100897628 & _Nostoc flagelliforme_\({}^{\ast}\) & C20/C25 & C25 \\ XP\_009395333 & _Mus ac actimulata_ & C20/C25 & C20 \\ XP\_025814700 & _Panicum halli_ & C25 & C20 \\ XP\_021311468 & _Sorghum bicolor_ & C25 & C20 \\ RCV24163 & _Setaria italica_ & C25 & C20 \\ XP\_009406992 & _Musa acuminata_ & C25 & C20 \\ XP\_009386740 & _Musa actimulata_ & C25 & C25 \\ RWW69357 & _Ensette verritcosum_ & C25 & C25 \\ PIA55534 & _Aquileia corella_ & C25 & C20 \\ XP\_023881877 & _Quercus suber_ & C25 & NA \\ PIA55630 & _Aquilegia ccerulea_ & C25 & C25 \\ XP\_017622622 & _Gosspium arboreum_ & C25 & C25 \\ OMO95617 & _Corchorus alitorius_ & C25 & C25 \\ XP\_021296398 & _Herrania umbratica_ & C25 & C25 \\ \hline \end{tabular} \({}^{\ast}\) Species belonging to Cyanobacteria.  
\end{table} 
Table 2: The prediction and identification of potential GFPPSs in plants.