Hyun, Bora

Contents Introduction Background & Motivation PreSPI++ Evaluation of PreSPI++ Method DCPPW++ Evaluation Conclusion 2ISI LABORATORY

Introduction Domain combination based approach Uses domain combination and domain combination pair information for the prediction of the protein interactions. PreSPI++ A protein interaction prediction system based the Interaction Significance(IS) matrix which quantified an influence of domain combination pair on a protein interaction. 3ISI LABORATORY

Motivation & Objective In PreSPI++, Consider Possibilities of domain collaboration and, Weighted Domain Combination Pair(WDCP) Consider being the main body on a protein interaction Domain Combination Pair’s coupling Power(DCPPW) However, No explanation and evaluation of relationship between DCPPW and physical interaction structures 4ISI LABORATORY

Motivation & Objective Verify whether value of DCPPW is given consistently based on PDB crystal structures, especially in protein interactions which have multi-domain interactions Propose advanced weighting method for domain combination pairs considering PDB crystal structures We can provide more reliable and meaningful weighted domain combination information for prediction of protein-protein interaction 5ISI LABORATORY

PreSPI++ IS matrix contains Possibilities of domain collaboration Using all-confidence 6ISI LABORATORY

PreSPI++ IS matrix contains Possibilities of domain collaboration Possibilities of being main body on interaction WDCP 7ISI LABORATORY a b A e D a c B e D a d C e D Weight of = Weight of,, ?

PreSPI++ IS matrix contains Possibilities of domain collaboration Possibilities of being main body on interaction WDCP DCPPW Using frequency information as relative power 8ISI LABORATORY

Evaluation of PreSPI++ Using PDB crystal structure information PPIs have single domain interaction Among 169 pairs, 146 pair correctly predicted 9 DCPPW Compare with PDB crystal structure MatchUn-Match 0.0< DCPPW< %00.00% 0.1< DCPPW< %63.55% 0.2< DCPPW< %31.78% 0.3< DCPPW< %00.00% 0.4< DCPPW< %63.55% 0.5< DCPPW< %00.00% 0.6< DCPPW< %10.59% 0.7< DCPPW< %00.00% 0.8< DCPPW< %10.59% 0.9< DCPPW< %10.59% DCPPW= %52.96% Total 14686%2314%

Evaluation of PreSPI++ Using PDB crystal structure information PPIs have multi domain interaction Among 56 pairs, only 1 pair correctly predicted 10ISI LABORATORY DCPPW Compare with PDB crystal structure MatchUn-Match 0.0< DCPPW<0.1 00%0% % 0.1< DCPPW<0.2 00%0% % 0.2< DCPPW< %00%0% 0.3< DCPPW<0.4 00%0%47.14% Total 11.79% %

Evaluation of PreSPI++ WDCP Since the weight of single domain is always one, the weight of a DC made by two or more domains is not higher than one of single domain. DCPPW Freq ({a,b,c}) ≤ Freq ({a}), Freq({b}), Freq({c}) So, DCPPW({a,b,c}) ≤ DCPPW({a}), DCPPW ({b}), DCPPW({c}) It is rational because PDB has only few interaction pairs caused by multi-domain interaction 11ISI LABORATORY

Method We need additional processing and weight scheme to compensate DCPPW for multi-domain interactions Pre-processing Filter out DCs have low all-confidence value Weight scheme Reduce effect caused by difference of all-confidence and frequency between single and multi domain pairs All coefficient will experimentally determined. 12ISI LABORATORY

Method Using rooted all-confidence value to compensate large difference between single and multi DC Distribution of all-confidence by DC size change 13ISI LABORATORY

Method Using size of DC information Multiply of each size of DC Sum of each size of DC C=Coefficient 14ISI LABORATORY

Evaluation Data (iPfam) PPI with multi-domain interaction : 65 개 PPI with single-domain interaction : 169 개 Evaluation Coefficient change from 0 to 30 All-confidence + multiply Rooted all-confidence + multiply Rooted all-confidence + sum Pre-processing (filter out all-confidence is lower than 0.2, 0.3, 0.4) 15ISI LABORATORY

Evaluation PPIs have Multi-domain interaction Best : Rooted AC +sum Worst: AC>0.4 + multiply 16ISI LABORATORY

Evaluation PPIs have single-domain interaction Best : AC>0.4 + multiply Worst : Rooted AC + sum 17ISI LABORATORY

Future works Effect of modified learning method is not significant Even coefficient is 100, there are matched results Matched results in single DDI reduced by coefficient increase About +13 / -24 Need other processing Directly using PDB information to weight their DC Using all inter/intra DC How much larger than other DC? How to evaluate? 18ISI LABORATORY

Future works Need to update domain data Need more evaluation 19ISI LABORATORY