## 3 Results and Discussion
### Motif Discovery Assisted by Complex Networks
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**No** & **Motif** & **Cluster** & **Cluster Size** & **Matches in ABFPs** & **Matches in Control** & **Sites (\%)** & **Score** & **Enrichment Ratio \({}^{*}\)** \\ \hline
1 & FKKA & & & 7 & 0 & 46.7 & 3.3e-003 & (\(-\))/(3.33) \\ \hline
2 & **GGGR** & & & 7 & 0 & 46.7 & 3.3e-003 & (\(-\))/(2.11) \\ \hline
3 & **WIKJRJWF** & 4 & 15 & 7 & 0 & 46.7 & 3.3e-003 & (\(-\))/(1.38) \\ \hline
4 & FIH & & & 6 & 0 & 40.0 & 8.4e-002 & - \\ \hline
5 & **RLFNR** & & & 5 & 0 & 33.3 & 2.1e-003 & - \\ \hline
6 & **KKK** & & & 2 & 0 & 100 & 1.7e-001 & - \\ \hline
7 & **LLLLL** & & & & 2 & 0 & 100 & 1.7e-001 & - \\ \hline
8 & **RGG** & & & 8 & 0 & 100 & 7.8e-005 & (3.0)/(1.56) \\ \hline
9 & **ISWIK** & & & 4 & 0 & 50 & 3.8e-002 & (\(-\))/(2.83) \\ \hline
10 & **NKRKQ** & 7 & 8 & 4 & 0 & 50 & 3.8e-002 & - \\ \hline
11 & **RPRVS** & & & 3 & 0 & 37.5 & 1.0e-001 & (\(-\))/(3.71) \\ \hline
12 & **RRRRR** & & & 3 & 0 & 37.5 & 1.0e-001 & - \\ \hline
13 & SAC & & & 16 & 1 & 69.6 & 3.3e-006 & - \\ \hline
14 & AKA & 9 & 23 & 5 & 0 & 21.7 & 2.85e-002 & - \\ \hline
15 & CD[VI] & & & 5 & 0 & 21.7 & 2.85e-002 & - \\ \hline
16 & IA[GVK] & & & 5 & 0 & 21.7 & 2.85e-002 & - \\ \hline
17 & LFKKL & & & 9 & 0 & 33.3 & 8.8e-004 & (\(-\))/(2.40) \\ \hline
18 & KVLK & 11 & 27 & 8 & 0 & 29.6 & 2.1e-003 & (3.0)/(4.0) \\ \hline
19 & KRFL & & & 6 & 0 & 22.2 & 1.1e-002 & (3.0)/(1.8) \\ \hline
20 & **VRLRI** & 14 & 23 & 12 & 0 & 52.2 & 3.5e-005 & - \\ \hline
21 & **RVIR** & & & 10 & 0 & 43.5 & 2.8e-004 & (\(-\))/(1.32) \\ \hline
22 & VWVI & 15 & 26 & 14 & 3 & 53.8 & 1.3e-003 & (3.0)/(3.0) \\ \hline
23 & VIWRR & & & 8 & 0 & 30.8 & 2.1e-003 & (\(-\))/(2.50) \\ \hline
24 & **LRK** & 17 & 23 & 9 & 0 & 39.1 & 7.4e-004 & (3.0)/(1.27) \\ \hline
25 & WRRK & & & 6 & 0 & 26.1 & 1.1e-002 & (\(-\))/(1.67) \\ \hline
26 & **WRIR** & & & 5 & 5 & 1 & 100 & 2.4e-002 & (\(-\))/(3.25) \\ \hline
27 & IRR & 22 & 5 & 2 & 3 & 40.0 & 9.0e-001 & (1.67)/(\(-\)) \\ \hline
28 & **APWTN** & 28 & 2 & 2 & 0 & 100 & 1.7e-001 & (\(-\))/(3.0) \\ \hline
29 & KKRK & & & 2 & 0 & 10.0 & 2.3e-001 & - \\ \hline
30 & KKVVF & & & 2 & 0 & 10.0 & 2.4e-001 & - \\ \hline
31 & LLKLL & & & 2 & 0 & 10.0 & 2.4e-001 & - \\ \hline
32 & VKFK & & & 2 & 0 & 10.0 & 2.4e-001 & - \\ \hline
33 & WRWR & & & 2 & 0 & 10.0 & 2.4e-001 & (\(-\))/(1.64) \\ \hline \hline \end{tabular} \({}^{*}\) Enrichment ratio was evaluated on the 14 ABFPs categorized by action mode in ref. [69] (first value) and 192 non-redundant ABFPs extracted from 214 reported in BaAMP (second value).  
\end{table} 
Table 6: Motifs identified by STREME at each network cluster. identified a relatively high number of motifs between 33-35, enrichment analyses were further performed in order to filter the discovery motifs shown in Tables 5 and 6. Motif enrichment analyses are used to determine if a group of sequences contains a statistically significant number of matches to a given motif. In this sense, we used the SEA algorithm [48] to select which motifs from both tables were significantly enriched in two sets of ABFPs. The first set was that reported by [PERSON] et al. consisting of 14 representative ABFPs of antibioticfilm modes of action [69], and the second one encompassed 192 non-redundant ABFPs, extracted from the 214 ABFPs registered in BaAMP database [27] (Supplementary File S3). Eight members from the representative subset were included among the 192 ABFPs, but all of them have shown antibiofilm activity at different levels. As a screening criterion, ABFPs enriched in both the representative and the extended dataset were selected. Table 7 lists the ABFP motifs discovered by the AB and AF approaches in the network communities. Our motif search approach assisted by complex networks produced results that are not so far from the few findings reported in the literature. Recently, [PERSON] et al.