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+<!DOCTYPE article
+ PUBLIC "-//NLM//DTD Journal Archiving and Interchange DTD v3.0 20080202//EN" "archivearticle3.dtd">
+<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML"
+ article-type="research-article"><?properties open_access?>
+ <front>
+ <journal-meta>
+ <journal-id journal-id-type="nlm-ta">Chem Biol Drug Des</journal-id>
+ <journal-id journal-id-type="publisher-id">jpp</journal-id>
+ <journal-title-group>
+ <journal-title>Chemical Biology & Drug Design</journal-title>
+ </journal-title-group>
+ <issn pub-type="ppub">1747-0277</issn>
+ <issn pub-type="epub">1747-0285</issn>
+ <publisher>
+ <publisher-name>Blackwell Publishing Ltd</publisher-name>
+ </publisher>
+ </journal-meta>
+ <article-meta>
+ <article-id pub-id-type="pmc">2737611</article-id>
+ <article-id pub-id-type="pmid">19519740</article-id>
+ <article-id pub-id-type="doi">10.1111/j.1747-0285.2009.00832.x</article-id>
+ <article-categories>
+ <subj-group subj-group-type="heading">
+ <subject>Research Articles</subject>
+ </subj-group>
+ </article-categories>
+ <title-group>
+ <article-title>On the Origins of Enzyme Inhibitor Selectivity and Promiscuity: A Case Study of Protein
+ Kinase Binding to Staurosporine
+ </article-title>
+ </title-group>
+ <contrib-group>
+ <contrib contrib-type="author">
+ <name>
+ <surname>Tanramluk</surname>
+ <given-names>Duangrudee</given-names>
+ </name>
+ <xref ref-type="aff" rid="au1">1</xref>
+ </contrib>
+ <contrib contrib-type="author">
+ <name>
+ <surname>Schreyer</surname>
+ <given-names>Adrian</given-names>
+ </name>
+ <xref ref-type="aff" rid="au1">1</xref>
+ </contrib>
+ <contrib contrib-type="author">
+ <name>
+ <surname>Pitt</surname>
+ <given-names>William R</given-names>
+ </name>
+ <xref ref-type="aff" rid="au1">1</xref>
+ <xref ref-type="aff" rid="au2">2</xref>
+ </contrib>
+ <contrib contrib-type="author">
+ <name>
+ <surname>Blundell</surname>
+ <given-names>Tom L</given-names>
+ </name>
+ <xref ref-type="aff" rid="au1">1</xref>
+ <xref ref-type="corresp" rid="cor1">*</xref>
+ </contrib>
+ <aff id="au1">
+ <label>1</label>
+ <institution>Department of Biochemistry, University of Cambridge</institution>
+ <addr-line>80 Tennis Court Road, Cambridge CB2 1GA, UK</addr-line>
+ </aff>
+ <aff id="au2">
+ <label>2</label>
+ <institution>UCB Celltech</institution>
+ <addr-line>208 Bath Road, Slough, Berkshire, SL1 3WE, UK</addr-line>
+ </aff>
+ </contrib-group>
+ <author-notes>
+ <corresp id="cor1">*Corresponding author: Tom L. Blundell,
+ <email>tom@cryst.bioc.cam.ac.uk</email>
+ </corresp>
+ <fn>
+ <p>Re-use of this article is permitted in accordance with the Terms and Conditions set out at
+ <ext-link ext-link-type="uri"
+ xlink:href="http://www3.interscience.wiley.com/authorresources/onlineopen.html">
+ http://www3.interscience.wiley.com/authorresources/onlineopen.html
+ </ext-link>
+ </p>
+ </fn>
+ </author-notes>
+ <pub-date pub-type="ppub">
+ <month>7</month>
+ <year>2009</year>
+ </pub-date>
+ <volume>74</volume>
+ <issue>1</issue>
+ <fpage>16</fpage>
+ <lpage>24</lpage>
+ <history>
+ <date date-type="received">
+ <day>24</day>
+ <month>2</month>
+ <year>2009</year>
+ </date>
+ <date date-type="rev-recd">
+ <day>11</day>
+ <month>5</month>
+ <year>2009</year>
+ </date>
+ <date date-type="accepted">
+ <day>11</day>
+ <month>5</month>
+ <year>2009</year>
+ </date>
+ </history>
+ <permissions>
+ <copyright-statement>Journal compilation © 2009 Blackwell Munksgaard</copyright-statement>
+ <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/2.5/">
+ <license-p>Re-use of this article is permitted in accordance with the Creative Commons Deed,
+ Attribution 2.5, which does not permit commercial exploitation.
+ </license-p>
+ </license>
+ </permissions>
+ <abstract>
+ <p>Relationships between ligand binding and the shapes of the binding sites in families of homologous
+ enzymes are investigated by comparing matrices of distances between key binding site atoms. Multiple
+ linear regression is used to help identify key distances that influence ligand binding affinity. In
+ order to illustrate the utility of this generic approach, we study protein kinase binding sites for
+ ATP and the promiscuous competitive inhibitor, staurosporine. We show that the size of the
+ gatekeeper residue and the closure between the first glycine of the GXGXXG motif and the aspartate
+ of the DFG loop act together to promote tight binding. Our web-based tool, ‘mapping
+ analogous hetero-atoms onto residue interactions’ (MAHORI), indicates that the greater the
+ number of hydrogen bonds made by the kinase around the methylamine group of staurosporine, the
+ tighter the binding. The conservation of surrounding atoms identified using our novel grid-based
+ method clearly demonstrates that the most structurally conserved part of the binding site for
+ staurosporine is the main chain of the hinge region. The critical role of interactions that are not
+ dependent on side-chain identities is consistent with the promiscuous nature of this inhibitor.
+ </p>
+ </abstract>
+ <kwd-group>
+ <kwd>ATP-binding site</kwd>
+ <kwd>kinase selectivity</kwd>
+ <kwd>Mantel test</kwd>
+ <kwd>staurosporine</kwd>
+ <kwd>structural analysis</kwd>
+ </kwd-group>
+ </article-meta>
+ </front>
+ <body>
+ <p>Protein kinases catalyze the transfer of a phosphate group, usually from ATP, to a protein substrate. The
+ human genome comprises more than 500 protein kinases (<xref ref-type="bibr" rid="b1">1</xref>), which are
+ known to mediate most of signal transduction crucial to metabolism, cell proliferation and differentiation,
+ membrane transport, and apoptosis. Although they exhibit a variety of regulatory mechanisms and
+ conformational states, protein kinases share the same fold and similar ATP-binding sites (<xref
+ ref-type="bibr" rid="b2">2</xref>).
+ </p>
+ <p>Protein kinases are of considerable interest to the pharmaceutical industry because dysfunction often results
+ in malignancy (<xref ref-type="bibr" rid="b3">3</xref>,<xref ref-type="bibr" rid="b4">4</xref>). Kinases are
+ also validated anti-inflammatory drug targets (<xref ref-type="bibr" rid="b5">5</xref>). Indeed, the success
+ of several high-affinity ATP-mimetic drugs has made the design of selective inhibitors an attractive
+ approach to useful therapeutics, particularly for oncology (<xref ref-type="bibr" rid="b6">6</xref>).
+ Although the structural conservation of the ATP-binding site can lead to off-target ligand binding, kinase
+ inhibitor design has become a promising way forward for discovery of useful therapeutic agents (<xref
+ ref-type="bibr" rid="b7">7</xref>).
+ </p>
+ <p>The major challenge for protein kinase inhibitor design is obtaining selectivity. In order to reduce the
+ chances of undesirable side-effects, potency is usually optimized against a target kinase while reducing
+ off-target activities including those involving homologous proteins. However, the level of selectivity
+ required is dependent on the therapeutic endpoint. Indeed, in some cases, polypharmacology is an advantage,
+ although a multi-target selectivity is very difficult to achieve by design (<xref ref-type="bibr" rid="b8">
+ 8</xref>).
+ </p>
+ <p>Insights into protein kinase selectivity and promiscuity are the major objectives of this article. Although
+ high-affinity targets sometimes have similar residues at positions important for binding of a given kinase
+ inhibitor, others with similar residues at these important positions can be insensitive to such inhibitors,
+ probably because of conformational differences (<xref ref-type="bibr" rid="b9">9</xref>). Therefore,
+ understanding kinase selectivity cannot be achieved only through the analysis of sequences but must also
+ consider three-dimensional structures.
+ </p>
+ <p>Here, in order to understand the relationship between the protein structure and binding affinities, we study
+ complexes of protein kinases with staurosporine (<xref ref-type="bibr" rid="b10">10</xref>), a microbial
+ alkaloid isolated from<italic>Streptomyces staurosporeus</italic>. Although staurosporine is a potent
+ inhibitor of various human protein kinases and has some antifungal activity, it is too toxic to be used as a
+ drug. However, it has been widely used in research as a universal kinase inhibitor (<xref ref-type="bibr"
+ rid="b11">
+ 11</xref>). The three-dimensional structures of a significant number of protein kinases co-crystallized
+ with staurosporine can be found in the Protein Data Bank. They show that staurosporine mimics ATP very well,
+ in spite of the apparent lack of similarity between the two molecules. The availability of dissociation
+ constants (
+ <italic>K</italic>
+ <sub>d</sub>) for staurosporine with 119 kinases (<xref ref-type="bibr" rid="b12">12</xref>), when used in
+ combination with this structural information, allows us to relate binding affinities to differences in the
+ structures of the pockets.
+ </p>
+ <p>We have studied the relationship between the structures of protein kinases and their ability to bind
+ promiscuous ligands, which we define here as compounds that bind several and, in the case of staurosporine,
+ the majority of kinases on which they are tested. In order to investigate the factors that determine whether
+ a particular kinase will bind a particular kinase inhibitor, we have examined the regions around the pockets
+ of a set of medium-to-high-quality X-ray crystal structures; and to group kinases based on the similarity in
+ spatial arrangement of amino acid side chains, we use the Mantel test, a statistically robust method for
+ calculating correlation coefficients between distance matrices (<xref ref-type="bibr" rid="b13">13</xref>).
+ Our shape-based dendrogram shows that similarity in shape alone can sometimes determine the affinity for a
+ set of ligands, regardless of their overall sequence similarity.
+ </p>
+ <p>The study of the shapes of the pockets allows us to identify the factors required for most kinases to bind
+ the promiscuous inhibitor, staurosporine. We examine the similarities of the shapes of the pockets by
+ identifying neighboring entities that are conserved in their positions relative to staurosporine. We show
+ that some are recruited to staurosporine via an induced fit or conformational selection mechanism, which
+ contributes to staurosporine promiscuity. We focus on the differences in distance matrices that define the
+ pockets and show how the side chains affect binding affinities. Based on a quantitative structure activity
+ relationship (QSAR) approach, we select a set of distances that have an influence on binding affinities.
+ These distances indicate that tighter binding is associated with the closure of the N-lobe and C-lobe and a
+ larger size of the gatekeeper residue. The numbers of ionic interactions and hydrogen bonds around the
+ methylamine of staurosporine also affect the binding affinities.
+ </p>
+ <sec sec-type="methods">
+ <title>Methods</title>
+ <sec>
+ <title>Shape correlation by Mantel test</title>
+ <p>Protein Data Bank identification codes of structures with ‘protein kinase activity’,
+ i.e., gene ontology ID GO:0004672 on MSDlite database (<xref ref-type="bibr" rid="b14">14</xref>),
+ were filtered through the PISCES server in order to select representative protein crystal structures
+ based on resolution, R-factor and completeness (<xref ref-type="bibr" rid="b15">15</xref>). The 80
+ chosen structures with resolutions better than 3.0 Å and R-factors less than 0.30 were then
+ superposed onto cyclic AMP-dependent protein kinase (PKA) using the program
+ <sc>baton</sc>
+ based on the method developed in Comparer (<xref ref-type="bibr" rid="b16">16</xref>). PKA, the
+ first protein kinase for which a crystal structure became available (<xref ref-type="bibr"
+ rid="b17">17</xref>), was
+ selected as the template because its residue nomenclature is widely used in kinase analyses (<xref
+ ref-type="bibr" rid="b18">18</xref>). The obtained structural alignment was used to infer
+ equivalent residues in the kinase superfamily. Distances between every residue surrounding the
+ pocket were calculated. This was achieved by selecting a ‘representative’ atom,
+ generally located near the end of the side chain for each amino acid residue. For example, the
+ hydroxyl oxygen was chosen for serine and the beta-carbon was chosen for threonine (see<xref
+ ref-type="supplementary-material" rid="SD2">Appendix S2</xref>). Half-diagonal distance
+ matrices were constructed and the correlations between the matrices were calculated by the Mantel
+ test using program
+ <sc>zt</sc>
+ (<xref ref-type="bibr" rid="b19">19</xref>). Relationships between distance matrices were defined
+ using the neighbor-joining algorithm from the program
+ <sc>phylip</sc>
+ (<xref ref-type="bibr" rid="b20">20</xref>) and the dendrogram was made for comparison using the
+ program
+ <sc>treeview</sc>
+ (<xref ref-type="bibr" rid="b21">21</xref>). Inter-residue distances were used which characterize a
+ particular kinase regardless of the ligand with which it was crystallized. The equivalent set of
+ distances was also measured for another set of 35 non-redundant crystal structures of kinases, which
+ have been assayed by Fabian
+ <italic>et al.</italic>
+ (<xref ref-type="bibr" rid="b12">12</xref>). These structures contain a variety of inhibitors bound
+ in the ATP-binding site. This allows the relationship between the spatial arrangement of residues of
+ different kinases and their binding affinities (
+ <italic>K</italic>
+ <sub>d</sub>) against 10 ligands to be visualized. We used the color gradient representation of the
+ tree plotting program
+ <sc>itol</sc>
+ (<xref ref-type="bibr" rid="b22">22</xref>), where the intensities of the colors were proportional
+ to −log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d</sub>, in order to allow comparison for millimolar to sub-nanomolar values of binding
+ constants (
+ <italic>K</italic>
+ <sub>d</sub>).
+ </p>
+ </sec>
+ <sec>
+ <title>Position-specific interactions</title>
+ <p>The structures of 20 staurosporine–kinase complexes were superposed on the indolocarbazole
+ moiety of staurosporine in PDB ID 1stc in order to compare them with the structures of 24 adenosine
+ phosphate–kinase complexes, which were superposed on the adenine ring from ATP in PDB ID
+ 1atp. The position-specific interactions were considered at two levels: the atom type and the
+ residue type. For the atom-based arrays, atoms in the PDB file were assigned an atom type according
+ to the simplified approach used in the AMBER force field, which has been developed specially for
+ molecular mechanics calculations of proteins and nucleic acids (<xref ref-type="bibr" rid="b23">
+ 23</xref>) (<xref ref-type="supplementary-material" rid="SD1">Appendix S1</xref>). For the
+ residue-based arrays, only ‘representative’ atoms and oxygen of water molecules were
+ assigned a residue type (see<xref ref-type="supplementary-material" rid="SD2">Appendix S2</xref>).
+ We constructed a three-dimensional grid with 1 Å dimensions around the rigid part of the
+ superposed ligands and collected occupancy in the grid boxes based on residue or atom types and x,
+ y, and z coordinates for non-redundant protein kinase structures. For the atomic level, the grid was
+ stored in PDB file format and occupancies of boxes were contoured using the module color_b of
+ program
+ <sc>pymol</sc>
+ (<xref ref-type="bibr" rid="b24">24</xref>) to obtain a transparent surface with the intensity of
+ the color corresponding to the frequency with which the grid boxes are populated. For the residue
+ level, relative positions of neighboring residues for different ligands were observed by superposing
+ the majority of the residue clusters surrounding adenine and staurosporine, and then comparing the
+ positions of these clusters for adenine complexes and staurosporine complexes. For visualizing the
+ cluster, a bond is drawn automatically when two atoms come closer than about 2 Å so the
+ cluster can be easily found. Colors of frequently occurring residues are assigned according to the
+ type of amino acid found in the array.
+ </p>
+ </sec>
+ <sec>
+ <title>Distance-based QSAR</title>
+ <p>We filtered the PDB (<xref ref-type="bibr" rid="b25">25</xref>) for X-ray structures of the kinases
+ for which Fabian
+ <italic>et al.</italic>
+ (<xref ref-type="bibr" rid="b12">12</xref>) report a
+ <italic>K</italic>
+ <sub>d</sub>
+ for staurosporine (
+ <italic>K</italic>
+ <sub>d,STU</sub>), and selected only those structures that are co-crystallized as either
+ staurosporine or adenosine phosphate complexes (40 structures). As in the case of shape analysis,
+ distances from representative atoms between 15 residues surrounding the pocket were measured to find
+ the best correlation of distances with
+ <italic>K</italic>
+ <sub>d,STU</sub>. Multiple linear regression was performed using the program
+ <sc>xlstat</sc>
+ (<xref ref-type="bibr" rid="b26">26</xref>) to find the best equation relating the distances
+ measured between the centre points near the ends of the side chains (see<xref
+ ref-type="supplementary-material" rid="SD2">Appendix S2</xref>) and log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>. Amino acid residues used to create these distance descriptors were extracted by
+ referring to PKA equivalent residues from the ClustalX (<xref ref-type="bibr" rid="b27">27</xref>)
+ multiple sequence alignment of the 113 kinases in Fabian’s data set (<xref ref-type="bibr"
+ rid="b12">
+ 12</xref>). The relationships of these influential residues were drawn from the neighbor-joining
+ algorithm in ClustalX (<xref ref-type="bibr" rid="b27">27</xref>). The abilities of kinases to bind
+ the inhibitors staurosporine, LY-333531, SU11248, and ZD-6474 were calculated from −log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,</sub>
+ and a dendrogram was produced with gradient color representation using program
+ <sc>itol</sc>
+ (<xref ref-type="bibr" rid="b22">22</xref>) in order to reflect these values. The selected
+ inhibitors are among the most promiscuous ligands in the Fabian data set, so that the number of the
+ kinases they can bind is sufficient to demonstrate trends in binding affinities.
+ </p>
+ <p>Because the experimental data depend not only on the method used but also the experimentalist who
+ reports the values, we choose dissociation constants of staurosporine (
+ <italic>K</italic>
+ <sub>d,STU</sub>) from Fabian
+ <italic>et al.</italic>
+ (<xref ref-type="bibr" rid="b12">12</xref>) as the sole source of our experimental binding data.
+ Structures in this training set structure have
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ between 0.5 and 870 n
+ <sc>m</sc>
+ and both adenine-containing and staurosporine-bound structures are considered. We include adenine
+ ring-containing structures in the data set on the assumption that the rigid part of the pockets that
+ harbor adenosine or staurosporine share similar conformations and electronic features. The advantage
+ of assuming that the structure of adenosine phosphate-bound complex resembles that of the same
+ enzyme in the staurosporine-bound complex is that there are many structures in complex with
+ adenosine containing compounds. The greater number of structures with available
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ allowed us then to test our equation by predicting
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ for further kinase structures co-crystallized with adenine ring-containing ligands. We discarded
+ residue points that differ in position when found in contact with ATP or staurosporine, so that we
+ could be sure that the differences in distances were independent of the ligand bound.
+ </p>
+ </sec>
+ <sec>
+ <title>Chemical interactions of staurosporine with various kinases</title>
+ <p>MAHORI (Mapping analogous hetero-atoms onto residue interactions) is our web-based tool designed to
+ observe interactions surrounding specific parts of a ligand<xref ref-type="fn" rid="fn1">a</xref>.
+ The website allows for various types of ligand query e.g., chemical drawing, compound name, PDB
+ ligand three-letter code and SMILES string. Given the PDB ligand three-letter hetID of staurosporine
+ (STU), MAHORI searches the PDB for the staurosporine complexes against the whole PDB using the
+ PDB-ligand database CREDO (<xref ref-type="bibr" rid="b28">28</xref>). This database stores protein–ligand
+ interactions using criteria adapted from Marcou and Rognan (<xref ref-type="bibr" rid="b29">
+ 29</xref>). All atoms from the ligand and their contacting neighbor atoms from the protein have
+ predefined types. Every contacting atom pair is assigned an interaction type by considering the
+ type, the geometry and the threshold distance. The details of residues that interact with the
+ queried atoms are presented according to the type of interaction, so that molecular interactions of
+ multiple structures can be compared at the level of ligand substructure.
+ </p>
+ </sec>
+ </sec>
+ <sec>
+ <title>Results and Discussion</title>
+ <sec>
+ <title>Ability to bind inhibitors correlates with spatial arrangement of residues in the pocket</title>
+ <p>We wished to investigate whether the spatial arrangement of residues in the ATP-binding pocket has an
+ influence on which inhibitor the kinase recognizes. In order to avoid comparing extremely variable
+ regions of the pocket, we focused only on protein structures with staurosporine or adenine
+ ring-containing compounds bound. We selected a set of points to represent common features of the
+ pocket and used the Mantel test to distinguish the pockets of different kinases based on the
+ assumption that the matrix of distances between points surrounding the adenosine pocket can reflect
+ key features of the pocket shape in multi-dimensions; we call a matrix of this sort a ‘quasi-shape’
+ (<xref ref-type="fig" rid="fig01">Figure 1A and 1B</xref>). We used calculated correlation
+ coefficients among distance matrices of the same size and order of elements to estimate the
+ similarities in the spatial arrangements of side chains and hence the relationships between shape
+ and the ability of parent kinases to bind various inhibitors.
+ </p>
+ <fig id="fig01" position="float">
+ <label>Figure 1</label>
+ <caption>
+ <p>Correlation between the shapes of the kinase ATP-binding pockets and their binding affinities
+ to inhibitors. (A, B) The quasi-shape of the adenine-binding pocket of cAMP-dependent
+ protein kinase (PDB ID:1stc, chain E) in complex with staurosporine (orange stick) is
+ illustrated by drawing purple lines between the ‘representative’ atoms of
+ the 17 residues surrounding the pocket. (C) The shape-based dendrogram shows the matrix
+ correlation between the shapes of the kinases and their binding affinities to 10 inhibitors.
+ The method employs 17 active-site residues to construct the distance matrices for each
+ kinase and then find the correlations between them. The pocket of STK10, an STE kinase,
+ shows the greatest similarity in shape to that of LCK, a tyrosine kinase. Their inhibition
+ profiles appear very similar (lower left). (D) The classic dendrogram based on sequence
+ similarity from structure-based sequence alignment using program<sc>baton</sc>. The
+ intensity of the color is proportional to log
+ <sub>10</sub>
+ <italic>K</italic>d of the inhibitor. It clusters the kinase with similar performance to the
+ shape-based dendrogram. Staurosporine is the most promiscuous inhibitor in this data set
+ (red).
+ </p>
+ </caption>
+ <graphic xlink:href="jpp0074-0016-f1"/>
+ </fig>
+ <p>Our preliminary results suggest that Mantel test correlations between the matrices derived from a
+ small set of inter-atomic distances can separate the majority of staurosporine complexes from the
+ adenine-containing complexes. This means that there are observable differences in spatial
+ arrangement of these atoms when staurosporine and adenine are bound. Thus, the Mantel Test appears
+ to work well for classifying different three-dimensional geometric shapes. However, the same kinase
+ in different crystal forms can be scattered throughout the resulting shape-based dendrogram,
+ implying that similarities between conserved atoms are not able to identify identical kinases in
+ different conformational states. Therefore, we investigated the use of ‘representative’
+ atoms as the centers for distance measurements in the construction of the distance matrix, thus
+ allowing the derivation of a quasi-shape from each PDB file. The choice of these atoms, which
+ depends on their residue type, is shown in<xref ref-type="supplementary-material" rid="SD2">Appendix
+ S2</xref>. By gradually increasing the number of residue points, we were able to cluster the
+ same kinase in different crystal forms and different complexes into the same branch of the
+ dendrogram. The most useful shape-based dendrogram is constructed from 17 representative points from
+ 17 residues. These are equivalent to the following residues in PKA: LEU 49, GLY 50, VAL 57, ALA 70,
+ MET 71, LYS 72, VAL 104, MET 120, GLU 121, TYR 122, VAL 123, GLU 170, ASN 171, THR 183, ASP 184, GLU
+ 127, LEU 173. This dendrogram places the same type of kinase in different complexes in the same
+ branch regardless of the bound ligand, and the staurosporine binding structures were clustered into
+ one-half of the tree (<xref ref-type="supplementary-material" rid="SD3">Appendix S3</xref>).
+ </p>
+ <p>We then applied this method to a set of 35 non-redundant protein kinases and 10 inhibitors from the
+ Fabian
+ <italic>et al.</italic>
+ data set (<xref ref-type="bibr" rid="b12">12</xref>) and obtained a dendrogram that characterizes
+ the ability to bind 10 ligands, based on the similarity in quasi-shape (<xref ref-type="fig"
+ rid="fig01">Figure
+ 1C</xref>). The general sequence-based dendrogram is shown for comparison (<xref ref-type="fig"
+ rid="fig01">
+ Figure 1D</xref>). It is evident that kinases with similar pocket quasi-shapes are likely to
+ have similar inhibitor binding profiles, regardless of their family membership. A nice example is
+ serine/threonine kinase 10 (STK10), which is clustered in the sequence-based dendrogram as an STE
+ kinase, or Homolog of yeast Sterile 7, 11, 20 kinases, as defined in the protein kinase phylogenetic
+ tree by Manning
+ <italic>et al.</italic>
+ (<xref ref-type="bibr" rid="b1">1</xref>). When considering STK10 in terms of similarity in spatial
+ arrangement of residues, it is instead paired with leukocyte-specific protein tyrosine kinase (LCK)
+ which is a tyrosine kinase. The sequences are quite different, but the quasi-shape of the pockets
+ and their abilities to bind seven inhibitors are very similar. Many kinases with similar sequences,
+ for example CDK2 and CDK5 or DAPK2 and DAPK3, also have very similar quasi-shapes and inhibition
+ profiles. This quasi-shape-based dendrogram provides a way of visualizing relationships among
+ kinases, complementing that of the classical sequence-based dendrogram. Our dendrogram demonstrates
+ that the similarity in quasi-shape can sometimes explain the ability to bind a set of ligands
+ regardless of the overall sequence identity.
+ </p>
+ </sec>
+ <sec>
+ <title>Conserved interaction shows induced-fit mechanism upon staurosporine binding</title>
+ <p>We hypothesize that if protein features surrounding a particular ligand remain conserved both in atom
+ type and position in complexes of different kinases, they may be required for binding the ligand. We
+ have developed software to extract generalized features that are frequently found in protein kinase
+ structures by constructing four-dimensional arrays to capture different entities that are conserved
+ in atomic position on structure superposition of staurosporine complexes. The array collects
+ occupancies of atoms from superposed structures that satisfy the four criteria, i.e., x,y,z
+ coordinates and atom type. This approach increases signal to noise by superposing a significant
+ number of structures (20 structures of staurosporine complexes).
+ </p>
+ <p>The staurosporine molecule is quite rigid as it contains very few rotatable bonds; hence, we may
+ observe interaction partners that are position-specific by superposing the kinases onto its lactam
+ and indolocarbazole rings. In a similar manner, interactions around the adenosine phosphate
+ complexes can be compared by superposing the non-redundant kinase structures onto the adenine ring
+ (24 structures of adenine-containing complexes). The conserved atomic environment can be found by
+ observing the frequently occurring atoms at a particular location defined by a 1 Å grid box
+ (<xref ref-type="fig" rid="fig02">Figure 2A and 2B</xref>).
+ </p>
+ <fig id="fig02" position="float">
+ <label>Figure 2</label>
+ <caption>
+ <p>Frequently occurring atoms and residues around the ATP- and staurosporine-binding sites. The
+ hinge region is on the left, the N-terminal lobe at the top and the C-terminal lobe at the
+ bottom of the figure. (A,B) Color is related to the frequency of finding atoms at a position
+ (CT = sp
+ <sup>3</sup>
+ carbon, C = carbonyl sp
+ <sup>2</sup>
+ carbon, N = sp
+ <sup>2</sup>
+ amide nitrogen, O = sp
+ <sup>2</sup>
+ oxygen). Both staurosporine (white stick) and the adenine ring (yellow stick) are recognized
+ by the main chain atoms in the hinge region on the left. The atomic environment of adenine
+ (A) shows more variability than that of staurosporine (B) as shown by the maximum occupancy
+ of frequently occurring atoms (58%); this is smaller than that of staurosporine (75%). (C)
+ The first glycine of the GXGXXG motif in purple moves within a rhombohedron-shaped volume
+ when located near the adenine ring. This glycine retains its position in the same grid in
+ 75% of staurosporine structures (15 from 20 structures) indicating induced fit of the
+ glycine-rich loop when located near staurosporine (D).
+ </p>
+ </caption>
+ <graphic xlink:href="jpp0074-0016-f2"/>
+ </fig>
+ <p>The atom type categorization is based on the assumption that atoms around the side chains that have
+ the same functional group can be classified as the same atom type, e.g., carboxylate oxygens of Asp
+ and Glu have sp<sup>2</sup>-oxygen atom types (<xref ref-type="supplementary-material" rid="SD1">
+ Appendix S1</xref>). By this approach, we can capture similar interactions in the pocket made by
+ similar parts of ligands. The resulting atomic level arrays suggest that for both adenine and
+ staurosporine ligand complexes (<xref ref-type="fig" rid="fig02">Figure 2A and 2B</xref>), the main
+ chain atoms of the kinase make the most conserved interactions in terms of type and position, which
+ explains why staurosporine, mimicking ATP, can bind to most of the kinases.
+ </p>
+ <p>The conserved neighboring atoms of ATP are more variable in position than those of staurosporine (38–58%
+ conservation in
+ <xref ref-type="fig" rid="fig02">Figure 2A</xref>
+ versus 50–75% in<xref ref-type="fig" rid="fig02">Figure 2B</xref>). This supports the idea
+ that the two ligands require a different degree of flexibility within the active site of the kinase.
+ The greater number of rotatable bonds in the adenosine phosphate results in lower degree of
+ conservation of neighboring atoms in these complexes than in staurosporine complexes. The ribose
+ moiety of the adenosine complex can adopt several conformations, so the frequently occurring atoms
+ fall in several grid boxes. The main chains of protein kinases in the hinge regions interact with
+ the amine group of the adenine rings and are the most conserved parts of the adenine complexes. In a
+ similar way, the main chains of the hinge regions, which interact with the lactam oxygen, and the
+ α-carbons of the first glycines of the GXGXXG motifs, which interact with the
+ tetrahydropyran, are the most conserved parts for staurosporine complexes. Furthermore, for 15 out
+ of 20 staurosporine-bound structures, the main chain alpha carbons from the first glycine of the
+ G-rich loop fall in the same 1 Å grid box (<xref ref-type="fig" rid="fig02">Figure 2D</xref>
+ ). When superposed on the adenine ring, these atoms are distributed within a rhombohedron-shaped
+ volume (see<xref ref-type="fig" rid="fig02">Figure 2C</xref>). It is perhaps surprising that this
+ glycine can become fixed in position upon staurosporine binding because the glycine-rich loop is
+ generally believed to be highly flexible (<xref ref-type="bibr" rid="b30">30</xref>,<xref
+ ref-type="bibr" rid="b31">31</xref>). The relatively well-conserved position of this
+ glycine, but not for adenine complexes, suggests that the staurosporine causes an induced fit or
+ conformational selection in the kinases upon binding. However, further evidence from apo structures
+ is required to confirm this observation.
+ </p>
+ <p>The residue arrays serve to complement the pictorial representations of the atomic environment. For
+ most of the residues, we chose the penultimate atoms of the side chains to represent the identities
+ and the positions of the residues (<xref ref-type="supplementary-material" rid="SD2">Appendix
+ S2</xref>). In this way, residues with a similar functional group at the end of the side chain
+ in different kinases can be captured as points at similar locations in the superposed structures.
+ For instance, C
+ <sub>β</sub>
+ of valine and C
+ <sub>γ</sub>
+ of leucine at the active sites occupy the same or close-by grid boxes in the superposed structures.
+ We observe that some clusters of amino acids preserve their functional groups in most of the
+ staurosporine and the adenine complexes; examples are the side chains of glutamate and aspartate of
+ the salt-bridges which flank the pocket on both sides, the residues that are equivalent to Ala
+ <sub>70</sub>
+ in PKA which acts as the ceiling of the cleft, and again Gly
+ <sub>50</sub>
+ which interacts with the ether oxygen of the ribose (<xref ref-type="fig" rid="fig02">Figure 2C and
+ 2D</xref>). Several clusters of amino acids are seen to have moved, leading to contraction and
+ expansion of the residues in the pocket to accommodate staurosporine.
+ </p>
+ <p>The ends of some similar hydrophobic side chains, including Cys and Met, or Ala, Val and Leu, which
+ surround the planar indolocarbazole ring, have equivalent positions, implying that these amino acids
+ perform the same function in that part of the active site. On the contrary, the amino acids that
+ make contact around the methyl amino and methoxy groups of staurosporine demonstrate that remarkably
+ different functional groups can occupy the same position and carry out the same structural role.
+ </p>
+ </sec>
+ <sec>
+ <title>Distance descriptors and interaction types correlate with the magnitudes of binding affinities
+ </title>
+ <p>Staurosporine has very few strongly electrostatic features. Its major interactions with protein
+ kinases are largely steric with non-polar groups. Thus, we hypothesized that the tightness of
+ inhibitor binding might be determined by the compactness of residues in the pocket. In order to test
+ this idea and to predict binding affinities from the structures, we assumed that good binding
+ requires certain geometric restraints and investigated which distance descriptors correlate well
+ with the dissociation constants. Thus, if distances are shorter for most of the structures with low
+ binding constants, we investigate whether contraction along that direction is required for tight
+ binding. This approach resembles QSAR, but all the input parameters are measured from the structure
+ in terms of distances that constitute the quasi-shape of the ATP-binding pocket. Although QSAR
+ methodologies have been widely used to try to understand binding affinities through various
+ parameters related to lipophilicity, charge and hydrogen bonding character (<xref ref-type="bibr"
+ rid="b32">
+ 32</xref>), distances between certain atoms in the protein have not been used.
+ </p>
+ <p>In order to select distances from the quasi-shape defined by 15 points in contact with staurosporine
+ (<xref ref-type="fig" rid="fig01">Figure 1A and 1B</xref>;<xref ref-type="supplementary-material"
+ rid="SD4">Appendix S4</xref>), we
+ carried out multiple linear regression with the equations shown in<xref ref-type="table" rid="tbl1">
+ Table 1</xref>. We tested the predictive power of these equations by leaving out randomly
+ selected test sets. While the purpose of using multiple linear regression in this context was simply
+ to select the set of distances that correlate well with the binding affinities, the resulting
+ equations suggest that predictive power might be demonstrated if a larger data set were available.
+ All resulting equations appear to contain the same best sets of distances producing
+ <italic>R</italic>
+ <sup> 2</sup>
+ values for the random test sets of about 0.7 for both equations (<xref
+ ref-type="supplementary-material" rid="SD5">Appendix S5</xref>).
+ </p>
+ <table-wrap id="tbl1" position="float">
+ <label>Table 1</label>
+ <caption>
+ <p>Equations correlating the influential distances with log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ </p>
+ </caption>
+ <table frame="hsides" rules="groups">
+ <thead>
+ <tr>
+ <th align="left" rowspan="1" colspan="1">Random Test</th>
+ <th align="center" rowspan="1" colspan="1"><italic>R</italic> 
+ <sup>2</sup>
+ training
+ </th>
+ <th align="center" rowspan="1" colspan="1"><italic>R</italic> 
+ <sup>2</sup>
+ test set
+ </th>
+ <th align="center" rowspan="1" colspan="1">Equation</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">None</td>
+ <td align="center" rowspan="1" colspan="1">0.6</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ = 3.4 + 0.1D<sub>50_184</sub>−0.4D
+ <sub>120_123</sub>
+ </td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">5 Structures</td>
+ <td align="center" rowspan="1" colspan="1">0.6</td>
+ <td align="center" rowspan="1" colspan="1">0.7</td>
+ <td align="center" rowspan="1" colspan="1">log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ = 3.4 + 0.1D<sub>50_184</sub>−0.4D
+ <sub>120_123</sub>
+ </td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">10 Structures</td>
+ <td align="center" rowspan="1" colspan="1">0.7</td>
+ <td align="center" rowspan="1" colspan="1">0.7</td>
+ <td align="center" rowspan="1" colspan="1">log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ = 3.6 + 0.1D<sub>50_184</sub>−0.4D
+ <sub>120_123</sub>
+ </td>
+ </tr>
+ </tbody>
+ </table>
+ </table-wrap>
+ <p>The distance descriptors which correlate well with binding affinities, either having positive or
+ negative influence on
+ <italic>K</italic>
+ <sub>d,STU</sub>, are called the ‘influential distances’. Although correlation does
+ not imply causation, examination of the crystal structures allows us to interpret these results in
+ terms of structure.
+ <xref ref-type="fig" rid="fig03">Figure 3A</xref>
+ illustrates these influential distances in the structure of PKA, PDB ID 1stc. They can be used to
+ describe how positions of representative side-chain atoms can influence
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ and also to help understand the major changes in neighboring atomic positions around the
+ staurosporine (<xref ref-type="fig" rid="fig03">Figure 3C</xref>).
+ </p>
+ <fig id="fig03" position="float">
+ <label>Figure 3</label>
+ <caption>
+ <p>The interpretation of multiple linear regression equations. (A) Interpretation of the
+ multiple linear regression analysis shows that smaller values of
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ result from the larger size of side chains of the gatekeeper and gatekeeper + 3 residues,
+ i.e., PKA equivalent residue: Met
+ <sub>120</sub>
+ and Val
+ <sub>123</sub>
+ (orange bar). The equation suggests that the closer approach between Gly
+ <sub>50</sub>
+ of the N-terminal lobe and Asp
+ <sub>184</sub>
+ of the C-terminal lobe (purple bar) correlate with tighter binding to staurosporine. (B) A
+ dendrogram displaying relationships between 113 kinases based on neighbor-joining of the 13
+ residues which are in contact with staurosporine and show correlation (<−0.4
+ and >0.4) with
+ <italic>K</italic>
+ <sub>d,STU</sub>. The aim is to investigate whether the similarities between these
+ influential residues, equivalent to PKA residues 49, 50, 57, 70, 71, 72, 120, 121, 122, 123,
+ 170, 171, and 184, give rise to similar binding constants. The resulting dendrogram can
+ cluster staurosporine tight binders into two major groups with better binding affinity to
+ staurosporine (dark red). This group of kinases tends to have large gatekeeper residues,
+ e.g., Phe (F), Met (M). Smaller gatekeeper residues, e.g., Thr or Leu, tend to be associated
+ with weaker binding affinities to staurosporine. A majority of kinases which are inhibited
+ by ZD-6474 (blue) has threonine (T) or valine (V) as a gatekeeper residue. Binding
+ affinities to LY-333531 (green) and SU11248 (yellow) are shown for comparison. (C)
+ Staurosporine structural components. (D) Chemical structure of staurosporine based on
+ annotation from Zhao
+ <italic>et al.</italic>
+ (<xref ref-type="bibr" rid="b33">33</xref>).
+ </p>
+ </caption>
+ <graphic xlink:href="jpp0074-0016-f3"/>
+ </fig>
+ <p>Of the equations shown in<xref ref-type="table" rid="tbl1">Table 1</xref>, the distance between
+ residues 50 and 184, described in equation as D<sub>50_184</sub>, is directly proportional to the
+ value of log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>, and the distance between residue 120 and 123, D<sub>120_123</sub>, is inversely
+ proportional to log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>. A possible interpretation of the equation is that in kinases that are tightly
+ bound to staurosporine, i.e., have a small log
+ <sub>10</sub>
+ <italic>K</italic>
+ <sub>d,STU</sub>, there is a preference for a smaller D
+ <sub>50_184</sub>
+ and a larger D<sub>120_123</sub>. In PKA, the distance between residues 50 and 184 is measured
+ between Cα of Gly
+ <sub>50</sub>
+ of the GXGXXG motif in N-terminal lobe to Cγ of Asp
+ <sub>184</sub>
+ of the DFG loop in C-terminal lobe. Staurosporine is located between the two lobes, and the closer
+ approach of these two motifs in a direction perpendicular to the plane of staurosporine reflects the
+ better binding affinities presumably because of the resultant tighter binding. In contrast, the
+ distance between residue 120 (gatekeeper) and 123 (gatekeeper + 3) implies the expansion of the
+ pocket along this direction. The equation suggests that these two residues should move further apart
+ to accommodate staurosporine. The gatekeeper residue points toward the plane of staurosporine, while
+ the gatekeeper + 3 residue is located under the indolocarbazole ring. The size of the gatekeeper and
+ the gatekeeper + 3 residues appear to have a key role in locking the lactam in the correct
+ orientation while making optimal steric interactions with the indolocarbazole of staurosporine. The
+ larger size of the gatekeeper residue likely results in the larger distance and correlates with good
+ binding because the larger volumes of the side chains in the plane of the lactam ring promote
+ favorable hydrophobic interactions in the pocket.
+ </p>
+ <p>We speculated that the interactions involving the methyl amino (N<sub>4′</sub>) and the
+ methoxy group (O<sub>3′</sub>) of staurosporine should constrain the distance between the N-
+ and C-terminal lobes to the optimal value (<xref ref-type="fig" rid="fig03">Figure 3D</xref>).
+ Indeed, the hydrogen bonds or ionic interactions that the staurosporine can make along this
+ direction are associated with the major differences in the binding affinities. We find that the
+ number of hydrogen bonds made by residues around N
+ <sub>4′</sub>
+ of staurosporine corresponds well with the trend in binding affinities (<xref ref-type="table"
+ rid="tbl2">Table
+ 2</xref>). Kinase structures that have two residues making hydrogen bonds or ionic interactions
+ to N
+ <sub>4′</sub>
+ of staurosporine, i.e., CDK2, PKA, PIM1, and LCK, have binding affinities below 51 n<sc>m</sc>. Most
+ structures that have only one residue contributing hydrogen bonds or ionic interaction to N
+ <sub>4′</sub>
+ have binding affinities between 51 and 440 n<sc>m</sc>, i.e., CSK, EGFR, FYN, M3K5. The kinase STK16
+ which does not make any interaction with N
+ <sub>4′</sub>
+ has a binding affinity of 200 n<sc>m</sc>.
+ </p>
+ <table-wrap id="tbl2" position="float">
+ <label>Table 2</label>
+ <caption>
+ <p>Number of interactions made by the kinases with N
+ <sub>4′</sub>
+ of staurosporine
+ </p>
+ </caption>
+ <table frame="hsides" rules="groups">
+ <thead>
+ <tr>
+ <th align="center" rowspan="1" colspan="1"/>
+ <th align="center" rowspan="1" colspan="1"/>
+ <th align="center" rowspan="1" colspan="1"/>
+ <th align="center" colspan="3" rowspan="1">Number of interactions
+ <hr/>
+ </th>
+ </tr>
+ <tr>
+ <th align="center" rowspan="1" colspan="1">Protein kinase</th>
+ <th align="center" rowspan="1" colspan="1">PDB ID</th>
+ <th align="center" rowspan="1" colspan="1">
+ <italic>K</italic>
+ <sub>d,STU</sub>
+ (n<sc>m</sc>)
+ </th>
+ <th align="left" rowspan="1" colspan="1">H-bond</th>
+ <th align="center" rowspan="1" colspan="1">Ionic</th>
+ <th align="center" rowspan="1" colspan="1">vdW</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">CDK2</td>
+ <td align="center" rowspan="1" colspan="1">1AQ1</td>
+ <td align="center" rowspan="1" colspan="1">8.1</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">PIM1</td>
+ <td align="center" rowspan="1" colspan="1">1YHS</td>
+ <td align="center" rowspan="1" colspan="1">15</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">LCK</td>
+ <td align="center" rowspan="1" colspan="1">1QPJ</td>
+ <td align="center" rowspan="1" colspan="1">20</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">PKA</td>
+ <td align="center" rowspan="1" colspan="1">1STC</td>
+ <td align="center" rowspan="1" colspan="1">50</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">KSYK</td>
+ <td align="center" rowspan="1" colspan="1">1XBC</td>
+ <td align="center" rowspan="1" colspan="1">7</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">FYN</td>
+ <td align="center" rowspan="1" colspan="1">2DQ7</td>
+ <td align="center" rowspan="1" colspan="1">51</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">M3K5</td>
+ <td align="center" rowspan="1" colspan="1">2CLQ</td>
+ <td align="center" rowspan="1" colspan="1">120</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">CSK</td>
+ <td align="center" rowspan="1" colspan="1">1BYG</td>
+ <td align="center" rowspan="1" colspan="1">440</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">MKNK2</td>
+ <td align="center" rowspan="1" colspan="1">2HW7</td>
+ <td align="center" rowspan="1" colspan="1">22</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">EGFR</td>
+ <td align="center" rowspan="1" colspan="1">2ITU</td>
+ <td align="center" rowspan="1" colspan="1">70</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">1</td>
+ <td align="center" rowspan="1" colspan="1">2</td>
+ </tr>
+ <tr>
+ <td align="left" rowspan="1" colspan="1">STK16</td>
+ <td align="center" rowspan="1" colspan="1">2BUJ</td>
+ <td align="center" rowspan="1" colspan="1">200</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ <td align="center" rowspan="1" colspan="1">–</td>
+ </tr>
+ </tbody>
+ </table>
+ </table-wrap>
+ <p>Therefore, in order to modify staurosporine to achieve better affinity for kinases, the strategy
+ might be to identify a residue close to the methyl amino (N<sub>4′</sub>) and to modify the
+ staurosporine to make another hydrogen bond. Making point mutations of active site residues in order
+ to achieve a better binding affinity to staurosporine might also be achieved by selecting the
+ residue type that can make an optimal hydrogen bond to N
+ <sub>4′</sub>
+ and O
+ <sub>3′</sub>
+ of staurosporine.
+ </p>
+ </sec>
+ </sec>
+ <sec>
+ <title>Conclusion</title>
+ <p>Simple comparison of distance matrices, generated from representative atoms toward the ends of
+ side-chains, can be used to describe the geometry of a ligand binding site and this can be related to
+ inhibitor binding. By considering the similarities and differences in the active sites, our
+ computational approach can rediscover several kinase binding determinants that have been previously
+ identified from manual and experimental analyses. We show by grouping structures with similar inhibition
+ profiles that the shape of the pocket can contribute to inhibitor selectivity. The most significant part
+ of the protein kinase structures that remains fixed in type and position for both staurosporine and
+ adenosine structures is the main chain at the beginning of the hinge region. This implies that the
+ reason that staurosporine binds to most kinases is that the lactam from staurosporine and adenine from
+ ATP recognize a similar set of atoms. Our observation gives a more precise picture of the induced fit of
+ the conserved glycine-rich loop upon binding to staurosporine. In addition, our statistical analysis
+ shows that a larger size of the gatekeeper residues normally results in tight binding to staurosporine.
+ We have also learned that the hydrogen bond and ionic interaction made with methylamine is important to
+ the tightness of the binding with staurosporine.
+ </p>
+ <p>These results indicate that by understanding differences in the active sites, we can identify residues
+ that affect the ability to bind the inhibitor and also suggest the part of the inhibitor that might be
+ modified to achieve better binding affinities. This approach offers a new perspective on computational
+ descriptions of specificity determinants when a series of different proteins with the same ligand
+ becomes available.
+ </p>
+ </sec>
+ </body>
+ <back>
+ <fn-group>
+ <fn id="fn1">
+ <label>a</label>
+ <p>
+ <ext-link ext-link-type="uri" xlink:href="http://www-cryst.bioc.cam.ac.uk/mahori">
+ http://www-cryst.bioc.cam.ac.uk/mahori
+ </ext-link>
+ </p>
+ </fn>
+ </fn-group>
+ <ack>
+ <p>We thank Dr Rinaldo Wander Montalvao for recommending the Mantel test to find correlation between the
+ distance matrices, Dr David Burke for the program
+ <sc>baton</sc>
+ for multiple structural alignment, and Dr. Richard Smith for program
+ <sc>kinasemap</sc>
+ used for extracting cAMP-dependent protein kinase equivalent residues from different PDB files. DT is
+ supported by the Royal Thai Government. TLB thanks the Wellcome Trust for research support.
+ </p>
+ </ack>
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