Davis NucleicAcidsRes 2006

Protein complex compositions predicted by structural similarity Fred P. Davis 1,2 , Hannes Braberg 1,2 , Min-Yi Shen 1,2 , Ursula Pieper 1,2 , Andrej Sali 1,2, * and M.S. Madhusudhan 1,2, * 1 Department of Biopharmaceutical Sciences and 2 Department of Pharmaceutical Chemistry, California Institute for Quantitative Biomedical Research, University of California, San Francisco, 1700 4th Street, Byers Hall, San Francisco, CA 94143-2552, USA Received March 15, 2006; Revised April 1, 2006; Accepted April 20, 2006 ABSTRACT Prot ein s functi on thr ough int eracti ons wit h oth er mol ecu les. Thus , the net work of phy sical int erac- tio ns amo ng protei ns is of great int ere st to bot h exp eri mental and comput ati onal biologists. Her e we pre sent st ructure- based predicti ons of 3387 binary and 123 4 higher order prot ein comple xes in Saccharomyces cere visiae inv olving 924 and 195 prote ins, respe ctive ly. To genera te candi date comple xes, comparati ve models of individual prote ins we re buil t an d co mbined to geth er using complexes of known structure as templates. These can dida te complexes wer e the n assess ed usi ng a sta tistical potential, der ive d from binary domain int erfaces in PIBASE (ht tp: //sali lab.or g/pibase) . The sta tis tic al potent ial dis cri minate d a bench- mar k set of 100 interface structures from a set of seq uence-ran domi zed negati ve exa mpl es wit h a false positive rate of 3% and a true positive rate of 97%. Moreover, the predi ct ed complexes were also filtered using functional annota tion and sub- cellular localization data. The ability of the method to select the correct binding mode among alternates is demo nstrated for thr ee cameli d VHH domain— porcine a –amylase interactions. We also highlight the prediction of co-complexed domain superfami- lie s tha t are not present in templa te comp lex es. Through integration with MODBASE, the application of the meth od to prot eomes th at are le ss we ll charac terized than that of S.cerevisiae will contri- bute to expansion of the structural and functional coverage of protein interaction space. The predicted compl exes ar e deposited in MODBASE (htt p: // salilab.org/modbase). INTRODUCTION Rec ent dev elopme nts in hig h-t hro ugh put scr eening have generated large datasets identifying protein complexes. The Sacch aromyc es cerevisiae pr ote ome has bee n especi all y wel l cha rac ter ize d thr oug h yea st- two-hy bri d (Y2 H) (1, 2) and tandem afﬁnity puriﬁcati on (TAP) experime nts (3–5 ). Exper iment ally obser ved inter actio ns, resul ting from both high -thro ughpu t and tradi tiona l low-t hroug hput metho do- logies, are deposited in databases such as the Biomolecular Interaction Network Database (BIND) (6) and the Database of Interacting Proteins (DIP) (7). Concomitant with these experimental advances, a spate of computational techniques to predict protein–protein interaction s have also been develop ed. Sever al appro aches based on protein sequence, structure, function and genomic features have been described (8). In an effort to reduce the prediction errors, several methods integr at e mult iple type s of exp eri men tal ly det ermine d inf ormati on and theoretical considerations (9–11). Structure-based methods have been developed for the prediction of binary protein interactions. InterPreTS (12) uses a statistical potential derived from known hetero-dimer structures and MULTIPROSPECTOR (13) relies on threading to score pairs of proteins that are similar to binary interactions of known structure. In addition to predicting new interactions, structure- based methods can also annota te inter actio ns that hav e bee n pre vio usl y obs erv ed exp eri men tal ly. A rec ent study use d comput ati onal met hods in con juncti on wit h experimentally determined complex compositions and elec- tr on densit y ma ps from negati ve-stain elec tr on cr yo- microscopy to generate structural models of yeast complexes (14). In a similar vein, structural knowledge has been used to pre dic t the domains tha t are most lik ely to mediat e bin ary protein interactions (15). Here, we describe predictions of proteins that form comple xes in S.cerevisiae bas ed on simila rit y to comple xes whose atomic struc tures have been solve d exper iment ally. *To whom correspondence should be addressed. Tel: + 1 415 514 4232; Fax: +1 415 514 4231; Email: [email protected] *Correspondence may also be addressed to A. Sali. Tel: +1 415 514 4227; Fax: +1 415 514 4231; Email: [email protected] 2006 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creati vecommo ns.org/lice nses/ by-nc/2.0/uk/) which permits unrestricted non-commerical use, distribution, and reproduction in any medium, provided the original work is properly cited. Nucleic Acids Research, 2006, Vol. 34, No. 10 2943–2952 doi:10.1093/nar/gkl353 Published online May 31, 2006

Davis NucleicAcidsRes 2006

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