A large number of protein-protein interactions ( PPIs ) are mediated by short linear motifs ( SLiMs ) that are recognized by specific globular domains 1 ., SLiM-mediated interactions are involved in a wide range of biological functions and can regulate the formation of transient protein complexes , orchestrate subcellular localization , modulate post-translational modification state , and determine the fate of proteins 1 ., Such interactions emerged as key mediators of complex regulatory processes in higher eukaryotic cells and their aberrant functioning can contribute to various diseases as well 2 ., The key to the essential nature of SLiMs in biological systems lies in their specific properties ., SLiMs correspond to a stretch of approximately 3–10 residues that generally reside within intrinsically disordered regions ( IDRs ) ., As a result , they usually form transient , weak interactions with micromolar binding affinity 3 ., Due to these specific properties , the identification of linear motif sites is challenging both experimentally and computationally 4 ., Currently , the most comprehensive collection , the Eukaryotic Linear Motif database ( ELM ) holds only 200–300 motif patterns with a few thousands of experimentally verified instances 5 ., This number pales in comparison to the expected number of linear motif mediated interactions in the human proteome , estimated to number at least several hundred thousand 6 ., Linear binding peptides have been systematically analyzed only for a few specific interaction domains , such as SH2 , PTB , 14-3-3 , PDZ and SH3 domains 7 , 8 ., However , for most motif binding domains , the interaction network is largely incomplete ., The identification of linear motif mediated interactions is usually divided into two phases ., The first phase is the characterization of the common consensus sequence motif that is shared among the diverse set of binding partners of a common domain , i . e . defining the motif class 9 , 10 ., The core motif that mediates interactions with a given domain is usually represented by a sequence pattern or a position specific scoring matrix ( PSSM ) ., In the second phase , the core motif is used to identify additional candidate binding sites in the proteome , i . e . finding novel motif instances ., However , as the information content of consensus motifs is usually low , predicted motif matches are overwhelmingly dominated by false positive matches that occur purely by chance 3 , 11 ., Therefore , this phase involves additional filtering steps to remove matches that are unlikely to be functional and to prioritize motif hits for further experimental characterization ., Various computational tools such as ELM , QuasiMotifFinder , MiniMotifMiner , SLiMSearch , ScanProsite or DOReMi 5 , 12–16 have been developed to overcome this problem ., These tools scan a defined set of proteins with a single consensus motif and utilize various discriminatory attributes to prioritize motif hits , including structural context , protein disorder , functional ontology , evidence for PPIs and shared cellular localization ., Evolutionary conservation can highlight functionally relevant positions in proteins and have been used for globular domains to identify conserved motif-like patterns that are indicative of the function of a protein 12 ., However , linear motif sites generally reside within IDRs that are generally less conserved 17 ., Within these regions , SLiMs often show a specific pattern of evolutionary conservation that are characterized by a higher relative conservation of the key motif residues compared to their flanking regions 18 , 19 , and this information can be used to highlight true binding motifs ., Using various sequence attributes , specific filtering pipelines were constructed to identify novel motif instances for several domains 20–24 ., However , the strength and optimality of the filtering steps have never been systematically tested ., In order to build optimal filtering protocols , a more systematic approach is needed that can take into account the specific trade-off between reducing false positive hits while capturing biologically relevant motif matches , which is likely to be specific to individual binding domains ., In this study , we focused on LC8 dynein light chain and its binding partners as a case study , and explored how the interaction network of a specific linear motif binding protein can be expanded in an optimal way ., LC8 is a remarkably conserved eukaryotic hub protein 22 ., Although LC8 was originally suggested to function as a cargo adaptor for the dynein motor complex , its extensive interaction network suggests a more general role , independent of dynein 22 , 25 ., Recently , the prevailing view has become that LC8 functions as a dimerization or oligomerization engine for various proteins 25 , 26 ., Known interaction partners link LC8 to processes such as nuclear transport , tumor suppression , viral replication , DNA damage repair , apoptosis , mitosis and signaling 22 , 25 ., In contrast to their functional heterogeneity , LC8 binding partners generally share a common binding mechanism 22 , 27 ., The known structures of complexes between LC8 and various bound partners show that the binding groove is formed at the dimerization interface of the homodimeric LC8 , favoring binding partners that are also dimerized 28 , 29 , often promoted by coiled coil ( CC ) regions 20 , 30 ., The recognition SLiMs are generally located within intrinsically disordered regions 25 and undergo a disorder-to-order transition upon complex formation ., In their bound form , these segments adopt highly similar conformations that augment the central beta sheet of LC8 on each side of the dimer 27 ., Many of the binding segments contain a Thr-Gln-Thr ( TQT ) motif with additional positions showing larger variations ., Apart from the canonical TQT motif , there are also non-canonical binding motif instances , in which the central Gln is replaced by Met or Asn 22 ., An even more unusual Thr-Ser-Pro ( TSP ) binding motif mediates the interaction between Pak1 and LC8 ., Altogether , more than 50 LC8 binding motif instances were collected from various eukaryotic species 22 ., To reveal the optimal binding motif , a phage display study was also carried out , identifying further LC8 binding motif instances 20 ., The suggested general role for LC8 raises the possibility of many additional binding partners in the human proteome ., In this work we expanded the interaction network of dynein light chain LC8 using a combination of computational and experimental methods ., We introduced a novel measure based on information gain that enabled us to build an optimal bioinformatic pipeline by combining various attributes predicted from the amino acid sequence ., We also incorporated known binding partners from PPI databases and exploited the specific evolutionary conservation of binding motifs to increase the likelihood that the motif hit is biologically relevant ., The resulting procedure enabled us to drastically reduce false positive predictions among putative novel linear motif instances and to expand the interaction network of LC8 with high-confidence predictions ., We experimentally verified the binding of several novel motif instances to LC8 using surface plasmon resonance ( SPR ) assay ., One of the most interesting outcomes of the extended interaction network of LC8 revealed a possible new function of the LC8 protein in the Hippo pathway through interaction with WWC and AMOT protein family members ., The presented study significantly contributes to the better understanding of the functional and evolutionary properties of the LC8 interactome ., Beyond this specific hub protein , it also offers general guidelines for the exploration of additional linear motif-mediated interaction networks ., LC8 recognizes a short linear motif in its partner proteins ., In this case , the binding involves both polypeptide chains of the homodimer LC8 ., However , to emphasize the similar binding mode to many single modular domains that also bind short linear motifs , LC8 is also referred to as a “binding domain” in this article ., We assembled a manually curated database of LC8 interaction partners based on literature search , in which LC8 binding was verified at the motif level ( see Materials and Methods and S1 Table ) ., The final dataset contained 53 partners with 67 motif instances and covered multiple eukaryotic species and viruses ., 40 motifs in 33 proteins belonged to human or could be directly mapped to a human protein based on close homology ., The length of the core binding motif was taken as 8 amino acids ( S1 Fig; for details , see S1 Text ) ., The ELM database describes the LC8 binding motif using the regular expression “^P . K . TQT” ., From the 67 known motif instances , only 13 matched this regular expression , and 24 further motifs contained only the canonical “TQT” motif core ., Considering human partners only , the corresponding numbers were 7 and 17 , respectively ., These numbers indicate that the definition in the ELM database is too restrictive to capture the majority of known instances ., To better describe the common sequential properties of known LC8 binding sites , we used a position specific scoring matrix ., The calculated PSSM is shown in Fig 1 ., Positive scores indicate amino acid residues that are favored at a given position ., The PSSM clearly captures the frequent occurrence of the canonical “TQT” motif ., However , with the exception of Gln in position 0 , there are additional favored amino acids in every position ., The strong preference for Lys at position -3 from the central Gln is not supported by the current collection of known partners , as neighboring positions have stronger preferences according to the bitscore ., Using the obtained PSSM , we scanned the whole human proteome to score every overlapping eight amino acid long peptide segment ( S2 Fig ) ., As expected , all known LC8 binding peptides had a positive score ., While only 2% of human peptides had a positive score , these still represented more than one hundred thousand cases ., This indicates that on the one hand , positive PSSM scores are strongly associated with true binding motifs and can serve as a valid starting point for novel LC8-binding motif discovery ., On the other hand , the very large number of initial motif hits underscore the need for that additional filtering steps ., In order to establish additional filtering criteria , we gathered various predicted features of the PSSM-identified peptides ., The methods we used included PFAM annotations 31 , average disorder prediction scores ( using IUPred , PONDR VSL2 , Espritz and DISOPRED3 ) 32–35 , average score to be part of disordered binding regions ( using ANCHOR , MORF-CHIBI and DISOPRED3-BR ) 35–37 , and secondary structure prediction scores using PSIPRED 38 ., At the protein level , information about predicted cellular localization 20 , 39 and the presence of coiled coil regions was also collected ( See Materials and Methods ) ., The various data for all known true positive motifs from human and other species are available at http://gerdos . web . elte . hu/data/LC8/known_results . html ., These various features can be associated with known motifs to different extents ., The main challenge is to find the best tools and parameter settings that enable the prioritization of peptide segments that are the most likely to be biologically relevant motif hits in an optimal way ., We introduced a metric based on weighted information gain derived from the Shannon entropy to globally attest the discriminatory power of each criterion ., On a dataset containing 40 known human binding partners and 10 , 000 random human segments from the proteome with a higher than zero PSSM score , the weighted information gain was calculated for each criterion ., The suggested measure enabled not only to rank the attributes in terms of their discriminatory power , but also to choose the best parameter settings ., According to this protocol , the strongest criterion based on the information gain was the predicted intracellular localization , which was fulfilled by all known motifs , but only 85 . 53% of random peptides ., The next strongest filtering criterion was based on PFAM annotations ., Using annotation strictly based on the domain type PFAM families , it was possible to filter out 15% of random motifs , while retaining all known motifs ., The third strongest criterion was based on PSSM scores ., The highest information gain was achieved with the cutoff value of 3 . 3 ., This cutoff value was not met by only three known human motifs ( PAK1 , NRF1 , MYZAP ) ., At the next level , disorder prediction methods produced the highest information gain ., Four methods were tested with different cutoff values corresponding to different false positive rates ., The optimal choice was IUPred with the cutoff value of 0 . 42 , which was fulfilled by all but one known motifs ., We also tested three methods ( ANCHOR , MoRFchibi , DISOPRED3 ) 35–37 for predicting disordered binding regions also known as molecular recognition features ( MoRFs ) ., The information gain was much lower , compared to previous criteria ., The optimal information gain was reached using the ANCHOR method with a cutoff value of 0 . 57 ., However , even this criterion would filter out 57 . 5% of the positive examples ., An additional criterion considered was secondary structure prediction ., Based on known structures of the complexes , the binding motif is expected to adopt a beta-strand conformation ., Surprisingly , predicted beta-strands occurred in only four out of 40 cases , and even in these cases only very short segments were predicted to be in beta conformation ., Helical segments were predicted in five cases , including MYO5A , which has been shown to have helical tendencies in the unbound form 40 ., However , the lack of residues predicted to be in helix did not perform well as a filtering criterion as the majority of random hits were also predicted to lack regular secondary structural elements , and the overall information gain was below that of predicting disordered binding regions ., Similarly , the presence of coiled coil regions in the partner proteins predicted by NCoils 41 did not have a strong discriminatory power either ., As these criteria filtered out many known motifs , they were not included in our filtering protocol ., The resulting filtering protocol is shown on Fig 2 , indicating the proportion of random hits and known motifs that were eliminated at each step ., By the stepwise application of the four filtering steps , a drastic reduction of random hits could be achieved , while still retaining the majority of known motifs: 90% of known motifs were kept while 99 . 78% of random hits were filtered out ( i . e . only 0 . 22% was kept ) ., By applying the filtering protocol for the complete human proteome , 335 candidate motifs remained ., We carried out a 3-fold cross validation to measure the generality of the obtained filtering protocol ( see Materials and Methods ) ., On average , we were able to correctly categorize 34 examples from the 40 experimentally validated human binding motifs ., This was only marginally worse compared to using the complete database where 36 motifs were categorized correctly ., The cut-off values for the PSSM and IUPred scores also did not change largely ., This indicates that the protocol is robust and can correctly describe the general attributes of the binding event between LC8 and its known binding partners ., Given the extreme conservation of LC8 , it is of special interest how the interaction motifs are conserved in partner proteins ., To study this , we generated multiple sequence alignments of orthologous proteins harboring known LC8 binding motifs and categorized them into 5 taxonomic groups: Mammalia , Vertebrata , Metazoa , Fungi and Eukarya ., The conservation at the level of protein and motif was tested based on the obtained alignments in each taxonomic group ., The definition of motif conservation applied here depends on the PSSM score of the motif ( see Materials and Methods ) ., Consequently , this approach cannot be applied to motifs that significantly differ from canonical motifs , i . e . their binding motif had a PSSM value below the threshold ., These three examples were excluded from the analysis ., Nevertheless , this strict criterion ensured that not only the general sequence similarity is maintained , but also the similarity to known human LC8 motifs is preserved ., The results of the conservation analysis for the known human motifs are presented in Fig 3 ., Among the known partners , the LC8 binding sites located within dynein intermediate chains ( DYNC1|1 , DYNC1|2 ) exhibited the most pronounced conservation , spreading across a wide range of eukaryotic species ( e . g . starlet sea anemone , C . elegans , slime mold ) ., In contrast , other motifs identified in human or other mammalian species were generally not conserved beyond Vertebrata ( e . g . , BMF , DLGAP1 , MTCL1 ) ., In the majority of cases , not only the LC8 binding motif but the complete protein was lost beyond this evolutionary distance ( e . g . BMF , BSN , SNPH ) ., Similarly , limited conservation of LC8 motifs was observed for binding regions experimentally verified in other species ( S3 Fig ) ., For example , the EGL protein from Drosophila melanogaster had orthologues at each level , but its binding motif showed conservation only in metazoan species ., While the centriole duplication functionality is conserved across metazoan species , the LC8 binding protein ANA2 involved in this process is specific to Drosophila species 42 ., Lowering the PSSM cutoff value used to define the conservation of the motifs perturbed the results only in three cases: NRF1 , FAM83D and MYO5A , but had no major impact on the overall trends ( S4A and S4B Fig ) ., We can conclude from this analysis of motif conservation that while the LC8 binding interface is highly conserved , known partners and especially the binding motifs located within them are significantly less conserved ., We tested the specific conservation pattern of motif binding sites using the SLiMPrints algorithm 19 ., This method identifies short stretches of residues within disordered regions that show high relative conservation compared to their flanking region as calculated from multiple sequence alignments of orthologous sequences ., In our dataset , 13 out of the 40 known human motifs exhibited high relative conservation , which is only 32 . 5% of all cases ., This suggests that the approach based on the island-like conservation identified by SLiMPrints has a limited ability to highlight putative functional binding motifs and overall it is not a good filtering criterion , as it misses the majority of functional motifs ., Here , we suggest an alternative filtering criterion based on the observation that known motifs are generally conserved within their own taxonomic group even if they lack motif level conservation over wider evolutionary distances ., For the majority of the cases , known motifs in human sequences were conserved in at least 80% of mammalian species ., The exceptions included only the three cases that had a PSSM value below our cutoff , and two additional examples ( the MAP4 motif and the second motif of FAM83D at position 405 ) ., In contrast , randomly chosen motif hits located within disordered regions generally did not possess this property ., Applying this discriminatory technique ( see Materials and Methods ) , we could filter out 163 of the possible candidate peptides , reducing the number of candidate motifs to 172 ., Therefore , for human sequences the conservation within mammalian species can be used as an efficient filter to further reduce likely false positives ., The predicted motif hits were also analyzed in relation to experimental data in PPI databases ., Known interaction partners of LC8 were collected using the integrative PSICQUIC approach 43 , which enabled us to search multiple databases simultaneously and to group the experiments based on detection methods and association types ( see Materials and Methods ) ., Altogether , 381 LC8 interaction partners were collected ( S2 Table ) ., Several of these interaction partners were supported by multiple lines of evidence , with a total of 782 independent experiments ., Known motif partners were well represented in current PPI databases , with only three missing out of these 33 partners ., The comparison of interaction partners collected from PPI databases with those that contained known motifs indicated that there is no single criterion that can identify biologically relevant interactions from candidates in PPI databases ., However , PPIs from low-throughput and direct experiments are more likely to be biologically relevant , especially when they are supported by multiple independent measurements ( see S5 Fig ) ., Overall , there were a large number of potential partners recorded in PPI databases ( 323 ) that contained neither known nor predicted LC8 binding motif instances ., By looking at the distribution of partners over the number of supporting experiments , we can see that partners with known and predicted motifs were largely evenly distributed , similarly to the partners detected by direct methods ( Fig 4A ) ., Known and predicted motifs dominated in partners with at least 7 supporting measurements , with a single exception corresponding to KANK2 , in which no motif-like segments could be identified ., In contrast , most of the partners without a likely motif candidate were detected by only a single , indirect method ., Although it cannot be ruled out that some of these interactions represent an alternative binding mechanism to LC8 , the large number of PPIs that are not compatible with the existing binding mode underlines that data from PPI databases should be treated with caution as they may contain several false positives ., Among the 172 predicted motifs in 152 proteins that satisfied our filtering criteria , there were 43 novel motif instances predicted by our pipeline that had corresponding PPI data ., While most of these interactions were based on indirect , high-throughput experiments , many of them were supported by multiple measurements ., 8 of these motifs represented additional instances in proteins that already contained an experimentally verified binding motif ., In 35 cases , the likely binding region for LC8 could be identified for proteins whose interaction were studied only at the level of the protein ( see S2 Table ) ., Furthermore , the presence of PPIs lends support to the biological relevance of the predicted motifs in these cases ., By considering motif hits located in proteins with corresponding PPI data , we created a dataset that contained a list of high confidence motif instances for LC8 ., In addition to PPIs , the presence of island-like conservation was also taken as an indication of likely motif hits ., Altogether , we collected 71 high confidence motif instances , supported by PPI data ( 29 cases ) , the presence of island-like conservation ( 27 cases ) , or both ( 15 cases ) ( Fig 4B ) ., Using these complementary information , the number of interaction partners of LC8 could be practically doubled ( S3 Table ) ., The high confidence motifs are available at http://gerdos . web . elte . hu/data/LC8/HUMAN/high_confidence_hits . html ., The high confidence set together with the already known motif hits was used to carry out a GO enrichment analysis against the human proteome with the DAVID server 44 ., The analysis showed an enrichment of multiple functionalities previously associated with LC8 , such as cytoskeletal organization , microtubule binding or cell morphogenesis ( Fig 5 ) ., Besides the already known activities , the enrichment analysis revealed a highly over-represented , yet previously undiscovered function of LC8 that links the protein to the regulation of cell and tissue growth , and in particular , to the Hippo pathway ., This result suggests that LC8 might play a critical role in the regulation of the Hippo pathway ., In order to understand how LC8 is connected to the Hippo pathway , we took a closer look at the relevant partners ., The motif hits highlighted two families involved in the upstream regulation of the Hippo pathway , the WWC ( WWC1 , WWC2 and WWC3 ) and angiomotin ( AMOT , AMOTL1 , AMOTL2 ) families 45 , 46 , 47 ., The WWC family member WWC1 , also known as KIBRA , was shown previously to interact with LC8 48 , and two binding motifs were also identified , located at positions 278 and 887 ( highlighted in Table 1 ) 49 ., However , no binding sites have been previously identified in the other two members of the family , WWC2 and WWC3 ., Interactions between LC8 and the AMOT family members were previously reported in high-throughput studies to be LC8 interactors 50 , but the binding motif has not been located in any of these proteins as of yet ., Here , we identified the likely LC8 binding regions in all WWC and AMOT family members and analyzed their evolutionary conservation ., The binding of these peptides was verified and quantitatively characterized by SPR ( Table 1 ) ., The list of putative LC8 binding peptides identified by our protocol are shown in Table 1 , together with the measured binding constants , which confirmed the binding of the selected peptides to LC8 ., As an example , results are shown for the motif in AMOTL2 in Fig 6 ., Although the apparent Kd values indicate weak interactions , these binding affinities are similar to other LC8 interactions 25 , 20 , and in biological settings they can increase in strength due to avidity caused by dimerization 30 ., Besides the canonical TQT motifs these peptides also contain SQT and TNT motifs ., Additional peptides that further expand the repertoire of compatible amino acids at various positions were also tested for their binding to LC8 ( S4 Table ) ., In order to properly assess the conservation of LC8 binding motifs in WWC and AMOT family members , we traced the evolutionary history of these proteins and their identified binding regions and additional functional modules ., Almost all vertebrate species have three paralogs of both the WWC and AMOT family members ( Figs 7 and 8 ) ., For both families , the multiple paralogs observed at the level of vertebrates could be traced back to a single common ancestor gene , as shown in the case of Florida lancelet ., KIBRA orthologs were detected beyond the level of chordates , not only in arthropods , but also in cnidaria ( Fig 7 ) ., AMOT was also present in arthropods , but it was missing in the fruit fly ( Fig 8 ) ., The most likely explanation for this is that the angiomotin was originally present in all bilaterian animals , but was lost relatively recently in the dipteran lineage that includes Drosophila 51 ., Altogether , the WWC family members seem to have a more ancient evolutionary origin compared to angiomotins ., Both WWC and AMOT family members showed a highly conserved domain and linear motif organization across a wide range of species ( Figs 7 and 8 ) ., While most LC8 binding motifs verified in human sequences are not conserved beyond vertebrates , KIBRA and the other WWC family members represent an important exception in this regard ., The two LC8 binding motifs of this protein family are well conserved in all three paralogs in vertebrates , lancelet and fruit fly ., Furthermore , one of the motifs is also present in a sea anemone , matching the strong evolutionary conservation of the WW and C2 domains , the defining functional modules of this family ( Fig 7 ) ., The AMOT family members contained a single LC8 binding motif , which seems to have emerged more recently ., While orthologous sequences could be detected in non-vertebrate species based on the conserved coiled coil region together with the angiomotin domain , these sequences lacked the LC8 binding motif ( Fig 8 ) ., The LC8 motif , similarly to the PDZ and WW binding motifs , has become conserved within vertebrate species ., In both of these families , the redundancy and conservation underline the functional importance of LC8 binding motifs in the upstream regulation of the Hippo pathway ., In this work , we established a systematic filtering protocol that can be used to expand the interaction network of a given linear motif binding domain with high confidence motif hits and reduce the number of random motif matches ., While similar bioinformatic pipelines have been used before 14 , the optimality of the applied filtering steps could not be guaranteed or even assessed due to the lack of appropriate measures ., Here , we offered a solution to this problem by introducing a decision tree-like filtering procedure together with the weighted information gain that enabled the construction of an optimal bioinformatic pipeline ., The presented approach was applied to expand the interaction network of LC8 , a highly conserved eukaryotic hub protein that binds its partners via a specific linear motif 22 ., By combining our motif filtering protocol with data collected from protein-protein interaction databases and the information on the presence of island-like conservation , we created a dataset of 71 novel high confidence motif instances ( S3 Table ) ., These novel binding sites significantly enriched the interaction network of LC8 with novel partners and highlighted a previously unknown , important function of LC8 in the Hippo pathway ., A list of predicted LC8 binding motifs was also created in an earlier work 20 ., In this case , the PSSM was calculated based on a library of binding motifs evolved through phage selection instead of using the collection of naturally occurring motif instances ., Although some of the filtering criteria , like IUPred based disorder prediction or intracellular localization were used in both studies , the details of implementation differed significantly , including the optimal cutoff for the PSSM score ., The comparison of the two sets showed that among the top 83 hits identified based on the in vitro evolution and absent from the list of known naturally occurring motifs , 58 ( 70% ) were also uncovered by our presented motif discovery pipeline ., However , our evolutionary filtering criteria reduced this overlap to 38 ( 46% ) ., While to some extent , the limited overlap could be due to the technical differences in the implementation , a more appealing explanation is that binding motifs selected by phage display are optimized for binding strength , while the sequence of naturally occurring motifs were shaped by various evolutionary requirements in the cell , from which strength is just one , and not necessarily the dominant constraint ., Despite these differences , in vitro evolution by phage selection 20 , 52 represent a complementary approach to predict potential motif instances for specific binding domains and to explore the binding preferences of such domains ., While the filtering protocol implemented here is specific to LC8 , the presented work also has important implications beyond this system ., We suggested here a general framework to find the optimal selection of methods for the filtering steps ., The importance of this optimization can be best demonstrated through the example of disorder prediction methods ., Several methods , such as DISOPRED3 , PONDR VSL2 or ESpritz Disprot 33–35 , that were tested in this work , perform better on specific datasets of ordered and disordered proteins 53–55 ., Nevertheless , IUPred achieved the best results for this specific problem , supporting the choice of this approach in motif-centric application of protein disorder 4 , 14 , 19 ., The pipeline applied here also enabled us to identify features that had limited discriminatory power and therefore were not incorporated into the current pipeline ., For example , all known LC8 binding motifs adopt a β-strand conformation upon binding , but the current tools are not capab
Protein-protein interactions ( PPIs ) formed between short linear motifs and globular domains play important roles in many regulatory and signaling processes but are highly underrepresented in current protein-protein interaction databases ., These types of interactions are usually characterized by a specific binding motif that captures the key amino acids shared among the interaction partners ., However , the computational proteome-level identification of interaction partners based on the known motif is hindered by the huge number of randomly occurring matches from which biologically relevant motif hits need to be extracted ., In this work , we established a novel bioinformatic filtering protocol to efficiently explore interaction network of a hub protein ., We introduced a novel measure that enabled the optimization of the elements and parameter settings of the pipeline which was built from multiple sequence-based prediction methods ., In addition , data collected from PPI databases and evolutionary analyses were also incorporated to further increase the biological relevance of the identified motif hits ., The approach was applied to the dynein light chain LC8 , a ubiquitous eukaryotic hub protein that has been suggested to be involved in motor-related functions as well as promoting the dimerization of various proteins by recognizing linear motifs in its partners ., From the list of putative binding motifs collected by our protocol , several novel peptides were experimentally verified to bind LC8 ., Altogether 71 potential new motif instances were identified ., The expanded list of LC8 binding partners revealed the evolutionary plasticity of binding partners despite the highly conserved binding interface ., In addition , it also highlighted a novel , conserved function of LC8 in the upstream regulation of the Hippo signaling pathway ., Beyond the LC8 system , our work also provides general guidelines that can be applied to explore the interaction network of other linear motif binding proteins or protein domains .
Fine-tuning of many cellular processes relies on weak , transient protein-protein interactions ., Such interactions often involve compact functional modules , called short linear motifs ( SLiMs ) that can bind to specific globular domains ., SLiM-mediated interactions can carry out diverse molecular functions by targeting proteins to specific cellular locations , regulating the activity and binding preferences of proteins , or aiding the assembly of macromolecular complexes ., The key to the function of SLiMs is their small size and highly flexible nature ., At the same time , these properties make their experimental identification challenging ., Consequently , only a small portion of SLiM-mediated interactions is currently known ., This underlies the importance of novel computational methods that can reliably identify candidate sites involved in binding to linear motif binding domains ., Here we present a novel bioinformatic approach that efficiently predicts new binding partners for SLiM-binding domains ., We applied this method to the dynein light chain LC8 , a protein that was already known to bind many partners in a wide range of organisms ., With this method , we not only significantly expanded the interaction network of LC8 , but also identified a novel function of LC8 in a highly important pathway controlling organ size in animals .
protein interactions, protein interaction networks, dyneins, molecular motors, network analysis, sequence motif analysis, research and analysis methods, sequence analysis, computer and information sciences, network motifs, bioinformatics, proteins, biological databases, proteomics, biochemistry, cytoskeletal proteins, sequence databases, cell biology, proteomes, database and informatics methods, protein domains, biology and life sciences, microtubule motors