proteins , which are essential to all biological systems , function by interacting with other molecules .
consequently , multiple alignment of the protein binding regions can help in defining the properties that are essential for the interaction with certain binding partners and in inferring the function . here , we consider two related problems of multiple alignments : that of protein - binding sites and of protein  protein interfaces , ppis , which are formed between pairs of interacting binding sites .
, a dissimilarity in the global properties does not necessarily imply different functions ; indeed , it has been shown that convergent evolution of binding sites is not a rare phenomenon ( 2 ) .
several methods have been developed to identify specific 3d patterns of protein catalytic residues ( 37 ) .
however , many binding sites of small molecules such as atp and estradiol do not share common patterns of amino acids ( 810 ) ; rather , they present a set of surface regions with similar physico - chemical properties and shapes .
while several approaches have been proposed for recognition and pairwise alignment of such functional sites ( 1013 ) , no multiple alignment methods are available .
since pairwise alignments may contain a large number of features that are not essential for the binding , multiple alignment methods are required to determine the smallest set of features , a consensus , that is necessary to achieve a desired biological consequence .
consideration of pairs of interacting binding sites , which form ppis , provide additional valuable information of the actual interactions formed between the molecules .
analysis of a set of protein  protein complexes helped in gaining important insights toward deciphering the principles of protein  protein interactions ( 1420 ) and their modular architecture ( 21 ) .
previous ppi alignment methods , which considered the backbone c atoms ( 22 ) or the physico - chemical binding patterns ( 23,24 ) aligned only pairs of ppis .
however , multiple alignment methods are required for recognition of conservation of the spatial interaction patterns formed between the molecules . in this article
, we present two webservers for multiple spatial alignment of protein - binding sites and ppis .
the difference between the two methods is in the input representation . while the first method , multibind ( 25 ) , looks at the binding site surface of one molecule , the second method , mappis ( 26 ) , constructs interaction edges between two interacting proteins .
multibind aligns a set of binding sites and recognizes the common spatial arrangements of their physicochemical properties . on the other hand
both methods consider the physico - chemical properties formed by groups of atoms and are independent of the overall similarity in the protein sequences or folds .
given a set of binding sites that bind the same small molecule , our goal is to reveal the common physico - chemical pattern that may be responsible for the binding .
figure 1a illustrates the binding site representation , which is crucial for the description of the chemistry of the recognized patterns .
each binding site is determined by the solvent accessible surface points ( 27 ) that are located < 4 from the surface of the binding partner . following the definition of schmitt et al .
( 28 ) , each amino acid in a binding site is represented by points in 3d space termed pseudocenters .
each pseudocenter represents one of the following properties important for protein  ligand interactions : hydrogen - bond donor ( don ) , hydrogen - bond acceptor ( acc ) , mixed donor / acceptor ( dac ) , hydrophobic aliphatic ( ali ) and aromatic contacts ( pi ) .
the pseudocenters and the surfaces are assigned such attributes as charge , normal vectors of the surface direction , ring plane orientation as well as surface patch size and curvature ( 25,29 ) . 
 figure 1.physico-chemical representation of binding sites and ppis .
hydrogen bond donors are blue , acceptors are red , donors / acceptors are green , hydrophobic aliphatic are orange and aromatic are white / gray . the surface is represented as dots and are colored according to the property of the corresponding , surface exposed , pseudocenters .
the rightmost figure illustrates the definition of pseudocenters and the bar at the bottom illustrates the complementarity of the pseudocenter properties .
hydrogen bond donors are blue , acceptors are red , donors / acceptors are green , hydrophobic aliphatic are orange and aromatic are white / gray .
the surface is represented as dots and are colored according to the property of the corresponding , surface exposed , pseudocenters .
the rightmost figure illustrates the definition of pseudocenters and the bar at the bottom illustrates the complementarity of the pseudocenter properties .
multibind ( 25 ) is an efficient method , which achieves this goal by local multiple alignment of protein binding sites , which are not assumed to share any sequence or fold similarity .
multibind utilizes a time efficient geometric hashing method ( 30 ) , which allows recognition of the candidate 3d transformations that align pairs of structures .
then , by applying a branch - and - bound procedure , multibind recognizes a combination of multiple 3d transformations that give the highest scoring common 3d pattern .
the score of a pattern is the sum of similarity scores of the matched pseudocenters .
these are measured by a scoring function that compares properties like spatial proximity ( after the superimposition ) , charge , surface curvature as well as aromatic ring plane orientation .
the input to the multibind webserver consists of set of protein  small molecule complexes ( defined by the pdb codes or uploaded files ) .
the binding sites of each complex are automatically extracted according to the ligands bound to the input structure .
the output of multibind is a set of physico - chemical properties shared by all the input binding sites .
we provide the details of the properties and the amino acids that contribute to these as well as the 3d transformation that superimposes the binding sites in 3d space .
we provide a pdb file with the spatial superimposition of the input complexes , which can be viewed online with a jmol script that visualizes the shared patterns ( figure 2 ) . 

( b ) selection of the binding sites of interest by the description of the bound ligands .
only ligands listed as hetatm records with more than seven non - hydrogen atoms are considered .
( c ) example of an output page , which details the matched pseudocenters of the common pattern .
each three columns present the details of a specific pseudocenter : ( i ) chain identifier and residue number ; ( ii ) residue type ; ( iii ) pseudocenter type .
although the pseudocenters are not required to have the same amino acid identity or origin ( backbone or side chain ) , we indicate the conservation of these ( b / s or * , respectively ) .
the ligands , represented as sticks , are not considered by multibind , but their spatial alignment supports the correctness of the solution .
the buttons at the bottom detail the web page options that should be selected to obtain this visualization automatically . web interface and output of multibind .
( b ) selection of the binding sites of interest by the description of the bound ligands .
only ligands listed as hetatm records with more than seven non - hydrogen atoms are considered .
( c ) example of an output page , which details the matched pseudocenters of the common pattern .
each three columns present the details of a specific pseudocenter : ( i ) chain identifier and residue number ; ( ii ) residue type ; ( iii ) pseudocenter type .
although the pseudocenters are not required to have the same amino acid identity or origin ( backbone or side chain ) , we indicate the conservation of these ( b / s or * , respectively ) .
the ligands , represented as sticks , are not considered by multibind , but their spatial alignment supports the correctness of the solution .
the buttons at the bottom detail the web page options that should be selected to obtain this visualization automatically .
given a set of protein  protein complexes , our goal is to align them in 3d space and recognize the shared spatially conserved interaction patterns . similarly to multiple sequence and structure alignment , the main motivation is the assumption that an interaction common to a number of interfaces is functionally more significant than a similar interaction found in a single or a pair of ppis .
the uniqueness of mappis lies in its ability to detect spatially conserved patterns of interactions even when there is no sequence or fold similarity between the corresponding proteins .
recently , we have applied mappis to different families of ppis and observed that most of the conserved physico - chemical interactions are contributed by the hot spot residues , and consequently , mappis predicts hot spots with a high success rate ( 29 ) .
figure 1b , illustrates the ppi representation by its physico - chemical properties and interactions .
specifically , an interaction across ppis is defined by a pair of close enough pseudocenters , one from each side of the interface , possessing complementary physico - chemical properties ( hydrogen bond donors are complementary to acceptors , while hydrophobic aliphatic and aromatic centers can interact with similar ones ) .
mappis calculates a set of transformations , which superimpose the ppis according to their similar interactions that can be of the following three types : hydrogen bonds , hydrophobic aliphatic and aromatic (  ) contacts .
two interactions are considered similar if they are created by similar pseudocenters that are superimposed to nearby spatial locations ( e.g. within 3 ) .
the similarity of interactions from two different ppis is scored according to the similarity of the corresponding pseudocenters and the complementarity of their properties . specifically , we measured the complementarity in terms of the pseudocenter proximity , charge complementarity , surface fit as well as aromatic ring orientations ( favoring perpendicular and parallel  stacking ) .
mappis finds a set of transformations that superimpose the input ppis in 3d space in a way that maximizes the spatial and chemical similarity of their interactions and pseudocenters .
the input to mappis is a set of protein  protein complexes with at least one pair of interacting protein chains .
the interacting chains , which define the ppi , can be either specified by the user or selected from a list of automatically recognized interactions .
the chain definition is followed by the automatic construction of the ppis and their multiple alignment with mappis .
the output of mappis is a set of the physico - chemical interactions shared by all the ppis .
we provide a pdb file with the superimposed complexes , which can be viewed online with a jmol script that visualizes the shared properties and interactions ( figure 3 ) . 

( b ) an option for the automatic selection of the interacting protein chains ( if not specified manually ) .
two protein chains are considered as interacting if there are at least five atoms of one chain that are within the distance of 6.0  from the other .
( c ) example of an output page , which details the common pattern of matched interactions .
each pair of rows details a shared interaction , which is defined by the interacting pseudocenters from two different chains of a ppi . as in multibind
the corresponding common interactions are represented as yellow sticks . web interface and output of mappis .
( b ) an option for the automatic selection of the interacting protein chains ( if not specified manually ) .
two protein chains are considered as interacting if there are at least five atoms of one chain that are within the distance of 6.0  from the other .
( c ) example of an output page , which details the common pattern of matched interactions . each pair of rows details a shared interaction , which is defined by the interacting pseudocenters from two different chains of a ppi . as in multibind
although the running times of each algorithm are several minutes , the server overload may lead to longer running times .
consequently , the user has an option to supply an email address to which the link to the output page will be sent upon the completion .
users who are interested in performing large scale database analysis and classification are advised to download the freely available software packages .
the packages contain the linux executable programs as well as user manuals and a set of scripts for the extraction of binding sites and ppis .
 analysis of protein  ligand complexes and recognition of spatially conserved physico - chemical properties is important for the prediction of binding and function . here 
 , we present two webservers for multiple alignment and recognition of binding patterns shared by a set of protein structures . the first webserver , multibind ( http://bioinfo3d.cs.tau.ac.il/multibind ) , performs multiple alignment of protein binding sites . 
 it recognizes the common spatial chemical binding patterns even in the absence of similarity of the sequences or the folds of the compared proteins . 
 the input to the multibind server is a set of protein - binding sites defined by interactions with small molecules . 
 the output is a detailed list of the shared physico - chemical binding site properties . 
 the second webserver , mappis ( http://bioinfo3d.cs.tau.ac.il/mappis ) , aims to analyze protein 
  protein interactions . 
 it performs multiple alignment of protein  protein interfaces ( ppis ) , which are regions of interaction between two protein molecules . 
 mappis recognizes the spatially conserved physico - chemical interactions , which often involve energetically important hot - spot residues that are crucial for protein  
 protein associations . 
 the input to the mappis server is a set of protein - protein complexes . 
 the output is a detailed list of the shared interaction properties of the interfaces . 
INTRODUCTION
MULTIBIND: MULTIPLE ALIGNMENT OF PROTEIN-BINDING SITES
MAPPIS: MULTIPLE ALIGNMENT OF PPIs
PERFORMANCE AND AVAILABILITY