Kahraman Thornton 2010

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proteinsSTRUCTURE O FUNCTION O BIOINFORMATICS

On the diversity of physicochemicalenvironments experienced by identical ligands

in binding pockets of unrelated proteins

Abdullah Kahraman,1,2* Richard J. Morris,3 Roman A. Laskowski,1 Angelo D. Favia,4

and Janet M. Thornton1

1 European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, United Kingdom

2 Swiss Federal Institute of Technology Zurich, Institute of Molecular Systems Biology, Wolfgang-Pauli Strasse 16,

8106 Zurich, Switzerland

3 John Innes Centre, Computational and System Biology, Norwich Research Park, Norwich NR7 7UH, United Kingdom

4 Istituto Italiano di Tecnologia (IIT), Drug Discovery and Development, Via Morego 30, 16163 Genoa, Italy

INTRODUCTION

It is generally assumed that the molecular recognitionbetween protein receptors and ligand molecules requiresin addition to geometrical complementarity, a highdegree of physicochemical complementarity between bothbinding partners.1 Shape complementarity in particularplays a crucial role in the recognition process as it per-mits both binding partners to approach each other andform short-range noncovalent bonds.2,3 However, severalstudies have reported that the geometrical complementar-ity is often far from perfect.46 These studies revealed

that ligands sometimes are only partially enclosed bytheir binding sites with the rest of the ligand exposed tothe solvent. Furthermore, even within the enclosedregion, contacts between protein and ligand often occurat relatively few points, involving strong hydrogen bondsor van der Waals interactions7,8 leaving unoccupiedspace like a buffer zone around the remainder of theligand. The buffer zone is partially filled by water mole-cules enhancing the complementarity of the naked

binding pocket. It has also been suggested that the bufferzones provide space for motions of protein, ligand, orwater molecules, thus avoiding the complete loss of the

ligands and binding site residues entropy.9

Physicochemical complementarity also contributes to

molecular recognition, in particular, the complementarity

This work was performed at the European Bioinformatics Institute, Hinxton, UK.

Additional Supporting Information may be found in the online version of this article.

Grant sponsor: BioSapiens Network of Excellence, through the European Commis-

sion within its FP6 Programme, under the thematic area Life Sciences, Genomicsand Biotechnology for Health; Grant number: LHSG-CT-2003-503265; Grantsponsor: EMBL (Predoctoral Fellowship).

*Correspondence to: Abdullah Kahraman, ETHZ, IMSB, HPT C75, Wolfgang-PauliStrasse 16, 8093 Zurich, Switzerland. E-mail: [email protected]

Received 29 September 2008; Revised 21 September 2009; Accepted 22 September2009Published online in WileyInterScience (www.interscience.wiley.com).

DOI: 10.1002/prot.22633

ABSTRACT

Most function prediction methods that identify cognate

ligands from binding site analyses work on the assumption of

molecular complementarity. These approaches build on the

conjectured complementarity of geometrical and physico-

chemical properties between ligands and binding sites so that

similar binding sites will bind similar ligands. We found that

this assumption does not generally hold for proteinligand

interactions and observed that it is not the chemical composi-

tion of ligand molecules that dictates the complementarity

between protein and ligand molecules, but that the ligands

share within the functional mechanism of a protein deter-

mines the degree of complementarity. Here, we present for a

set of cognate ligands a descriptive analysis and comparison ofthe physicochemical properties that each ligand experiences in

various nonhomologous binding pockets. The comparisons in

each ligand set reveal large variations in their experienced

physicochemical properties, suggesting that the same ligand

can bind to distinct physicochemical environments. In some

protein ligand complexes, the variation was found to correlate

with the electrochemical characteristic of ligand molecules,

whereas in others it was disclosed as a prerequisite for the bio-

chemical function of the protein. To achieve binding, proteins

were observed to engage in subtle balancing acts between elec-

trostatic and hydrophobic interactions to generate stabilizing

free energies of binding. For the presented analysis, a new

method for scoring hydrophobicity from molecular environ-

ments was developed showing high correlations with experi-mental determined desolvation energies. The presented results

highlight the complexities of molecular recognition and

underline the challenges of computational structural biology

in developing methods to detect these important subtleties.

Proteins 2010; 00:000000.VVC 2009 Wiley-Liss, Inc.

Key words: molecular recognition; proteinligand interac-

tion; electrostatics; hydrophobicity; noncomplementarity;

cognate ligand; protein function; redox potential.

VVC

2009 WILEY-

LISS,

INC. PROTEINS

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derived from long-range electrostatic interactions isbelieved to be the driving force for molecular interac-tions. For example, proteins binding an adenine or gua-nine were found to discriminate between both molecularmoieties on the basis of electrostatics.10 Copper zinc

superoxide dismutases, a protein family known to havethe highest reaction rate among enzymes, attract posi-

tively charged metal ions into their binding sites througha highly negative electrostatic field,11 and DNA-bindingproteins attract negatively charged DNA moleculesthrough positively charged patches on their molecularsurface.12 Different studies have been performed toquantify the electrostatic complementarity between bind-ing partners. In particular, early works by Nakamuraet al.,1315 Chau and Dean,1618 and Naray-Szabo andNagy19,20 analyzed the electrostatic lock-and-key modelof single ligand- and protein-binding sites by mapping

the molecular electrostatic potential (MEP) of both bind-ing partners on a set of reference points on their surfa-ces. The MEPs on the reference points were eventually

compared following the host-on-guest and guest-on-guest model. These studies came to the conclusion thatlong-range effects of partial charges are essential for cre-ating complementary electrostatic environments betweenbinding site and ligand, but that partial charges on pro-tein and ligand lack face-to-face complementarity.

The same conclusions were drawn for proteinproteininterfaces.21

It has been suggested that physicochemical interactionsin natural complexes lack exact complementarity,22 mostlikely to avoid irreversible ligand binding. Ledvina et al.showed that some phosphate receptors, sulfate-bindingproteins, flavodoxin structures, and DNase proteins exertan intense negative electrostatic potential (ESP) at theirbinding sites despite binding a highly negative ligand.23

The proteins stabilize the anion charges by van der Waals

interactions and an extensive local hydrogen-bonding net-work comprising main-chain NH groups and hydroxylside chains. The question remains open whether in theirevolutionary past these enzymes were binding ligands withcomplementary ESPs. Similarly, Herschlag and coworkersstudy of the electrostatic and geometric complementarityin the oxyanion hole of ketosteroid isomerase concludedthat electrostatic complementarily makes only a modestcontribution to the enzymes catalytic mechanism, which

is primarily driven by geometrical complementarity.

24

Nakamura et al. listed four reasons for the absence of elec-trostatic complementary in some proteinligand com-plexes: (1) the ligand interacts mainly with the solvent, (2)hydrophobic interactions are strong, (3) dissociation ofthe ionizable protein residues was incorrectly assigned,and (4) additional ionic ligands were affecting the experi-enced electrostatic energy of the ligand.13

To gain a wider perspective on physicochemical com-

plementarily, we have analyzed the physicochemical char-acteristics of 100 protein-binding sites that bind either

AMP, ATP, FAD, FMN, glucose, heme, NAD, phosphate,or steroids (estradiol and dehydroepiandrosterone).6

Countless applications have been developed in the pastfor analysing active and binding sites, mainly in the fieldof rational drug design. Most of the programs such as

LigBuilder,25 MCSS,26 PocketFinder,5 and Q-Site-Finder27 are derivatives of the program GRID.28 GRID,

developed by Goodford, analyses the physicochemicalproperties of protein-binding sites by computing theinteraction energy between various spherical probes andthe atoms of the protein using a standard potentialenergy function. Other programs provide different infor-mation about a given binding site. For example,GRASP,29 although primarily a powerful protein struc-

ture visualization software, has a built-in Poisson-Boltz-mann Solver, which allows the calculation and visualiza-tion of the ESP in and around the protein-binding site.

The program HINT30 calculates the hydrophobicity of amolecule using experimental octanol/water partitioncoefficients and constructs a hydropathy field or comple-

mentarity map for a protein binding site. The CASTp31database is a repository of protein clefts and voids andprovides area and volume measurements for each cavity.Our own laboratory has developed CleftXplorer, whichuses spherical harmonic expansion coefficients to analyti-cally describe the shape and size of binding sites and

ligands molecules.6,3234 To obtain a more completepicture also of the physicochemical properties withinbinding pockets, the shape descriptor in CleftXplorer wasextended by various physicochemical descriptors thatcharacterize electrostatic chargedcharged interactions,hydrophobic interactions, hydrogen bonds, and van derWaals interactions (see Methods).

Despite differences in their algorithms, all methodolo-gies that aim to identify a ligand that binds to a givenprotein binding site or, indeed, identify what the cognate

ligand might be assume that ligands and binding sites ex-hibit geometric and physicochemical complementarity. Ifthis assumption is correct, binding sites that bind thesame cognate ligand should share very similar properties.Most studies so far have investigated the physicochemicalproperties of individual proteinligand complexes andhave tried to highlight the complementarity betweenthose (see references earlier and Refs. 3537). Our studysets itself apart by a detailed investigation and compari-

son of the physicochemical properties in sets of nonho-mologous binding sites that all bind the same ligand,thereby revealing a surprising diversity in the proteinenvironments that a single ligand is able to bind.

METHODS

Data set

The analysis in this manuscript was performed on thesame data set as published in Kahraman et al.6 The pro-

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tein structures in this data set were selected from theprotein quaternary structures (PQS)38 database, whichcontains the supposed biological unit of each crystallo-graphically determined entry in the Protein Data Bank39

(PDB). Only structures containing a cognate ligand were

considered, that is, where the bound ligand is known tobe involved in the function of the protein as given by EC

number40 or by the proteins corresponding UniProtentry.41 These structures were filtered such that, for anyspecific ligand type, the proteins binding the ligand werenonhomologous, as defined by the homology (H) levelin the CATH protein structure classification database.42

The final selection stage required that for each ligandtype at least five nonhomologous proteinligand struc-

tures remained. The net result of this selection procedurewas nine ligand typesAMP, ATP, FAD, FMN, glucose,heme, NAD, phosphate, and steroid molecules (estradiol

and dehydroepiandrosterone) and 100 protein-bindingpockets containing one of these ligands.

Nine protein structures in the data set had loop

regions in the proximity of their binding sites for which,because of insufficient experimental data, no atom coor-dinates were available in the PDB file. These loopsregions probably exhibited high flexibility. Flexible loopregions can play a major role in binding different ligandmolecules into a binding site, often enclosing the ligand

in a cage-like structure. The flexible loop regions in ourdata set however remained or became flexible after theligand had bound to the protein structure, preventingthem from being a stable integral part of the protein-binding site. As the contribution of these loop regions tothe ligands binding free energy varies with their flexibil-ity, we assumed that their contribution can be neglectedand therefore have not attempted to include them in thephysicochemical property calculations.

Mapping protein physicochemical properties

on ligand molecules

The computer program CleftXplorer6 was modified sothat in addition to describing a 3D shape of a binding

pocket or a ligand molecule using spherical harmonics, itcould describe physicochemical properties mapped onto adot surface of that shape. The physicochemical propertiesincluded ESPs, hydrophobicity scores, hydrogen bond do-

nor, acceptor, and van der Waals potential energies. Thesewere computed using standard software packages, supple-mented by own code as described later. For the purpose ofthis manuscript, the physicochemical properties were notmapped on the surface of a shape, but rather onto the atomcenter coordinates of each ligand in the data set, thereby

following a similar approach to the GRID.28 CleftXplorersalgorithm is simple and consists of three steps:

1. Remove all crystallographically observed water mole-cules from the protein structure file. The computed

ESP and hydrophobicity score implicitly account forsurrounding water molecules.

2. For each ligand, identify and remove those polypep-tide chains and neighboring chemical compounds(NCCs) that lie within 9 A of any ligand atom. NCCs

correspond to HET groups such as metals, cofactors,and coenzymes. The cutoff distance of 9 A is in ac-

cordance with interaction ranges of nonbonded inter-actions.43 This speeds up the calculations while hav-ing negligible effects10,44 on the calculated properties(data not shown).

3. At the center of each ligand atom, calculate the valueof each physicochemical property, using the atoms ofthe retained protein chains and NCCs.

Electrostatic potential

The ESPs were calculated by solving the nonlinear

Poisson-Boltzmann equation45 using APBS46 (version1.1). A grid size of 1 A was chosen and the finite differ-ence discretization technique47 was applied. Calculationswere run at room temperature with a counterion concen-

tration of 0.1M. The continuum solvent model was allo-cated a dielectric constant of es 5 78. Protein and ligand

atoms as well as NCCs were assigned a dielectric constantof e 5 4. Hydrogen atoms were added to the proteinstructure using the program REDUCE48 (version 3.13),which optimizes the proteins hydrogen bond network,while flipping ASN or GLN side-chain amides whereappropriate. Protonation states of histidine residues wereapproximated using PROPKA49 at a pH given for themother liquor in the PDB or in the primary literature ofthe crystal structure. Partial charges and atom radii fromthe PARSE50 parameter set were assigned to all protein

atoms using the automated procedure of PDB2PQR51

(version 1.4.0). The reported potentials from APBS wereconverted from kT/e to kcal/mol/e by applying the con-version factor of 0.592.

The ligands in our data set as well as all NCCs wereassigned Paulings van der Waals radii (which are alsoused in the PARSE parameter set). All ligands in ourdata set were left uncharged in the binding sites, toaccount for the reduction of the screening effect by the

ligand molecule. Partial charges for the NCCs wereobtained from the Merck molecular force field(MMFF94)52 as implemented in an in-house modifiedversion of the Chemistry Development Kit (CDK, version2.0.2)53 for Java. The correctness of the MMFF94 partialcharges was checked against the MMFF94 validation suite(http://www.ccl.net/cca/data/MMFF94/). For simplicity,metal ions were assigned partial charges equal to theirformal charge following the approach of MMFF94. Iron

ions in heme molecules were treated as an integral partof the molecule and assigned a partial charge of 12e

Physicochemical Variation in Binding Pockets

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irrespective of their oxidation state. Hydrogens wereadded automatically to the ligands and NCCs at pH 7using OpenBabel54 (version 2.1.1) and in the few caseswhere the automatic assignment failed were added man-ually using PyMOL (version 1.0).55 Phosphate molecules

were always assumed to be unprotonated. The spatialposition of the hydrogen atoms was optimized within the

binding site using REDUCE.

Scoring the hydrophobic environment

The calculation of CleftXplorers hydrophobicity scores

follows the approach of HINT30 and the hydrophobicitypotential of Fauchere et al.56 in relating the hydropho-bicity score to octanolwater partition coefficients(log P) values. CleftXplorer differs in that it uses atomic-based rather than fragment-based log P values. Thismakes CleftXplorer applicable to a wider spectrum ofmolecules especially those for which HINT has no frag-ment parameters. The atomic log P values were calcu-

lated using a modified version of the XlogP57

algorithmin the CDK. Modifications were required to add log P

values for charged molecules, as by default, log P valuesare defined only for neutral molecules. Some of theligands in our data set, as well as some of the NCCs,contain charged moieties (e.g., PO4 groups), whichincrease the solubility of the molecule in water. If themolecule is treated as neutral its hydrophobicity will beoverestimated. To reduce the log P value for chargedatoms, a correction factor of 21.083 was introduced thatcorresponds to half of the zwitterion correction factor

used in the XlogP algorithm for the hydrophobicity cal-culation of amino acids. Metal ions were assigned an ar-

bitrary log P 5 23, assuming that metal ions in solutionminimally interfere with the water network. For proteinatoms log P values were calculated considering eachamino acid within the tripeptide Gly-X-Gly, where X isthe amino acid of interest. The values were calculated rel-ative to glycine, following the method of calculating theHansch p-constant,58 by subtracting the mean atomic

log P value for glycine atoms from each of the atomiclog P values giving an atomic log Prel value. Based on logPrel, the energy of transfer from water to organic solvent,DGlog P, was inferred following the approach of Eisenbergand McLachlan59 by applying the Boltzmann equationfrom statistical thermodynamics:

DGlog P log Prel 3 2:30 3 RT log Prel 3 1:36 kcal=mol;

where R is the Boltzmann factor and T is the room tem-perature in Kelvin. The XlogP-based hydrophobicityenergy correlates with the experimental free energy oftransfer59 with R2 5 0.92. A similar approach to themolecular lipophilic potential (MLP)60,61 was used to

map the hydrophobicity energy of the protein to theatom center coordinates of the ligand molecules with a

sigmoid potential function as suggested by Levitt andBrylinski et al.62,63:

f distrel

1 0:5

3 7 3 distrel2

9 3 distrel4

5 3 distrel6

distrel8

;

where the value of distrel ranges from 0 to 1 and corre-sponds to the distance between a ligands atom center

and the center of the protein or NCC atom divided bythe cutoff distance of 9 A.

To calculate the total hydrophobic environment score(HES) at a ligands atom center, it was further necessaryto sum the product between the distance function

f(distrel) and the energy of transfer DGlog P over all nneighboring atoms. The following equation expresses thissimple sum and gives the final equation for HES:

HES X

n

i1f dist

rel i 3DG

log P

i :

Other physicochemical properties

CleftXplorer calculates van der Waals potential energiesusing the buffered 14-7 potential equation from theMMFF94 force field.64 Hydrogen bond donor andacceptor potential energies are calculated according to

the knowledge-based potential energies from Kortemmeet al.65 These orientation-dependent hydrogen-bondingpotentials were derived from geometric features found in

a large set of high-resolution protein structures. For

more details, see the cited publications.

Average properties and their variation

Once the physicochemical properties of all proteinsin a ligand set were mapped onto their ligand mole-cules, the physicochemical property scores from differ-ent binding sites were averaged and their standarddeviation computed. For this purpose, an atom-map-ping table was created mapping corresponding atomsbetween ligand A and ligand B, where both were fromthe same ligand set. In cases in which the molecularmoiety had rotational symmetry, atoms at similar spa-

tial positions were associated to each other, after themolecules were manually aligned on the neighboringmoieties. Atoms in the phosphate ligand set weremapped randomly as a unique mapping due to sym-metry was not possible. However, the small size ofphosphate molecules should generally result in similarphysicochemical property scores over the whole mole-cule.

In addition to the standard deviation, the relative

number of sign changes in the property scores for eachatom was calculated as a further means to assess the vari-

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ation of the physicochemical properties in binding sites.The sign change ratio (SCR) is given by

SCRi 1 max Ni ; N

i

Ntotali

for an atom i in a ligand. Ni1 is the number of positive

score values, Ni2 the number of negative score values,

and Nitotal is the size of the ligand set. The functional

range of SCR is between 0 and 0.5, with 0 denoting novariation (all corresponding atoms have equal sign) and0.5 indicating highest variation (one half of correspond-ing atoms are positive, the other half negative).

RESULTS

All calculations shown in this section were performedwith all five physicochemical properties; that is, ESPs,hydrophobicity scores, hydrogen bond donor, acceptor,

and van der Waals potential energies. Hydrogen bondpatterns were found to vary most within all ligand sets,

whereas van der Waals potential energies were found tovary hardly. Nevertheless, all results and discussions inthe following were focused on the ESP and the HES,

because of their importance and discriminative power inmolecular recognition events.

For each ligand, ESP and HES were calculated in thepresence of any NCC (see Methods). The inclusion of

NCCs in the calculation of physicochemical propertieswas crucial as without them most proteins in our dataset lacked the physicochemical properties required tobind their cognate ligand.66 Of the 100 ligands in ourdataset, 67 had 144 NCCs, of which 63 were metals,

mostly coordinated to AMP, ATP, or phosphate mole-cules. For the remaining 33 ligands (mostly HEM, NAD,

and steroid), no NCC was found in the PQS entry, buttheir presence in vivo can, of course, not be excluded.

Physicochemical properties of proteins in

ligand-binding sites

Electrostatic potential on ligands

Figure 1 shows examples of the ESP experienced by allATP, NAD, and heme ligands in the data set. For the ESPof the remaining ligand sets, see Figure X1 in SupportingInformation.

Adenosine-50-triphosphate

An adenosine-50-triphosphate (ATP) molecule consists

of an aromatic adenine ring, a ribose sugar, and a nega-tively charged triphosphate group. For recognition andbinding, the protein is expected to provide a positive

ESP for complementarity to the aromatic ring and inparticular the triphosphate tail. Figure 1(a) confirms thisexpectation showing positive ESPs for all ATP-bindingsites. An inspection of the ATP-binding sites revealed

Figure 1

Electrostatic potential that (a) ATP, (b) NAD, and (c) heme molecules experience within their binding sites. The ligands are horizontally orderedfrom top left to bottom right with increasing positive potential. The potential is colored from red to white to blue for values below 25 kcal/mol/eto 0 to values above 5 kcal/mol/e. The PQS-Id of the protein structure in which the ligand was found is given below each ligand. Note that tomake the visual comparison easier, each type of molecule is represented by a single conformer and may not be the conformer in the given PQS file.The representative conformers are 1e2q, 1mi3, and 1po5 and have yellow labels. NAD molecules bound to oxidoreductases are labeled green; thosebound to transferases are labeled orange.


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that the high positive potentials on the ATP molecules(on average 11.33 kcal/mol/e, see Table I) were causedprimarily by metal ions that are coordinated to one ortwo phosphates at ATPs triphosphate tail. Metal ionswere found coordinated in all ATP-binding sites except

in the DNA ligase (1a0i) and the biotin carboxylase(1dv2). The function of those metals varies but most

often they act as catalytic stabilisers for transition statesof the enzymesubstrate complex67,68 or as chargeneutralizers between charged protein and phosphategroups.69,70 In particular, the latter function is impor-tant with respect to the molecular recognition of ATP asmetal ions can shield negative charges between the pro-tein and ATP and lock the otherwise loose triphosphate

tail of ATP to the protein.71,72 The charge neutralizingeffect can increase ATPs-binding affinity by severalorders of magnitude, as in the case of the bovine cAMP-

dependent protein kinase.73 The mouse homologue ofthe same protein, 1rdq, in our data set shows, after theexclusion of the divalent magnesium ion from the ESP

calculation, negative repulsive potentials toward the ATPmolecule. Only when the metal ion is included in thecalculation, the repulsive forces are neutralized andbecome attractive (see Fig. 2). Similar neutralizing effectsof metal ions were observed in the PQS structures 1a49,1b8a, 1e8x, 1o9t, and 1tid.

Not all ATP molecules require a metal ion to bind totheir receptor protein. As mentioned earlier, ATPs in thebinding sites of the DNA ligase (1a0i) and the biotin car-boxylase (1dv2) were found without a metal ion or anyother NCCs. Although they are important for the cata-lytic reaction of these enzymes, magnesium ions are notessential for ATP binding. A detailed inspection of theirbinding sites revealed that the proteins created attractivepositive ESPs [see Fig. 1(a)] toward the ATP phosphatetails through phosphate-binding motifs. These motifs are

characterized by positive electrostatic fields originatingfrom positively polarized N-termini of a-helices and/orpositively charged lysine and arginine side chain and/orionic hydrogen bonds (O2HN) between backbone NHgroups and phosphate oxygen ions.74

Nicotinamide adenine dinucleotide

Nicotinamide adenine dinucleotide (NAD) molecules

consist of three functional groups, namely the mainly ar-omatic adenosine moiety, the negatively charged pyro-phosphate group, and the aromatic nicotinamide ringthat can carry a formal positive charge when oxidized toNAD1.75 The ESP that a NAD molecule experiences inbinding sites depends on the enzymatic function of theNAD molecule. In our data set, the two most prominentfunctions were the redox function in oxidoreductases(1hex, 1ib0, 1jq5, 1mew, 1mi3_1, 1o04_1, 1qax, 1t2d,

2npx) and the group transfer function in transferases(1ej2, 1og3, 1s7g, 1tox_1, 2a5f). As a redox partner inTa

ble

I

AverageandStandardDeviationoft

heExperiencedElectrostaticPotentialandHyd

rophobicityEnvironmentalScoresforDifferentLigandSets

Physicochemicalproperty

All

AMP

ATP

FAD

FMN

GLC

HEM

NAD

PO

4

Steroid

ElectrostaticPotential

(kcal/mol/e)

1.96

6.7

5

1.5

3

5.8

7

11.3

3

9.1

3

5.2

7

5.9

3

4.8

1

7.4

4

27.1

74.6

5

23.1

1

8.3

0

0.0

3

6.4

1

17.14

14.6

4

21.9

4

3.9

3

HydrophobicityEnvironmental

Score(HES)

0.70

1.5

3

20.6

5

2.5

3

21.0

2

2.0

0

0.9

4

1.2

1

0.0

0

1.3

9

20.4

51.8

3

2.3

0

1.4

6

0.3

9

1.2

2

23.65

4.2

4

2.8

7

1.1

9

Thelowestandhighestaveragescorevalu

esforeachpropertyarecoloredpurpleandgreen,re

spectively.

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NAD-dependent dehydrogenases, a NAD1 molecule sup-ports the oxidation of a substrate by accepting a hydridegroup (H2). As a substrate in ADP-ribosyltransferase reac-

tions, NAD1 molecules are cleaved into an ADP-ribosyland a nicotinamide group, where the former is transferredto an arginine group within the active site as part of aposttranslational modification and the latter is released

into the solvent. For dehydrogenases, the nicotinamidemoiety should experience negative ESP due to the H2

group transfer, whereas in ribosyl-transfer reactions thepositively charged nicotinamide moiety should experiencerepulsive positive ESP. Figure 1(b) shows the ESP of allNAD molecules in our data set ordered by the total ESPexperienced by the molecules from top left to bottomright. NAD molecules that are functioning as oxidationpartners were labeled green, whereas molecules acting assubstrates in transferase reactions were labeled orange.

All NAD molecules bound to oxidoreductases con-firmed the expectation and showed an attractive negative

ESP at the majority of their nicotinamide moiety withthe exception of 1ib0, a rat cytochrome b5 reductase,which experienced repulsive positive ESP. As the reduc-tase name indicates 1ib0 distinguishes itself by using thesubstrate NADH as a reducing agent. To increase the af-finity toward NADH over NAD1, the enzyme was foundto use the observed positive ESP over the nicotinamidemoiety as a repulsive force against NAD1. The positiveESP was created mainly at a conserved binding motif

CGPPPM

76

with three prolines located at a positivelypolarized N-terminus of an adjoining a-helix (see Fig. 3)The transferase structure of the ADP-ribosyltransferase

1og3 and partially the structure of the NAD-dependentdeacetylase 1s7g exerted as expected repulsive electroposi-tive potentials toward the nicotinamide moiety of NAD1.The structure of the nicotinamide mononucleotideadenylyltransferase 1ej2 however exerted attractive nega-tive ESP. Closer inspections showed that the attractive

ESP was necessary for the function of 1ej2, namely tosynthesize NAD1 molecules. Although transferases dis-

card the nicotinamide moiety after cleavage for which re-pulsive forces are advantageous, adenylyltransferases musttightly bind the substrate nicotinamide ribonucleotide to

fuse it to an ATP substrate molecule leading to the reac-tion product NAD1.

For the bacterial NADH peroxidase (2npx) repulsivepotentials were found for the adenine moiety of NADH

(2npx is the only protein in our data set having boundNADH. All other NAD proteins have bound the oxidized

NAD1). The negative electrostatic field is created by sixnegatively charged glutamate and aspartate amino acidsin close proximity. An examination of the residuesaround the nicotinamide moiety revealed that the repul-sive potentials were overridden by aromatic interactionsto a hydrophobic valine and an isoleucine side chain [seeFig. 4(a)]. Similar aromatic interactions were found for

Figure 3

NAD1-binding site of the rat cytochrome b5 reductase. The molecularsurface around the NAD molecule is shown transparent and coloredaccording to the electrostatic potential from red to white to blue forvalues below 25 kcal/mol/e to 0 to values above 5 kcal/mol/e. Theadjacent FAD molecule is shown in green, whereas the three prolineresidues of the conserved CGPPPM motif are shown in yellow.

Figure 2

Electrostatic potential of the mouse cAMP-dependent protein kinase (PQS-Id 1rdq) as experienced by the cognate ligand ATP ( a) without and (b)with two coordinated magnesium ions (green-colored spheres). The potential is colored from red to white to blue for values below 25 kcal/mol/eto 0 to values above 5 kcal/mol/e.


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the nicotinamide group of 1og3 [see Fig. 4(b)], where

pp stacking interaction to a phenylalanine from one side

and an aromatic-backbone-amide interaction from theother side provide the necessary binding free energy forthe nicotinamide moiety of the NAD molecule. The im-

portance of aromatic interactions in our data set will bedescribed later in the text. Similar observations were madeon adenine groups that were found to bind protein-bind-ing sites primarily with intermolecular hydrogen bonds to-gether with pp stacking and cationp interactions.77,78

Heme type B

The heme molecule consists of an aromatic porphyrinring system with a central coordinated iron ion and twonegatively charged propionate groups sitting on top of theporphyrin ring system. Arginine residues form ionic bondsto the propionate groups and anchor the heme molecule to

the protein structure, whereas histidine and less frequentlycysteine residues coordinate the hemes iron ion and affectthe electrochemical character of the iron metal ion (Fe).

Based on these characteristics, one would expect posi-tive ESP around the propionate groups and negativepotential in the porphyrin ring system around the ironion. Visually, this prediction seemed true for the PQSstructures 1d7c, 1dk0, 1iqc_1, 1naz, and 1np4. However,the remaining heme-binding sites, in particular, 1d0c,

1po5, 1qla, and 2cpo, show repulsive positive electrostaticfields around the hemes porphyrin group, causing theheme molecules to have a diverse range of ESP valueswith an average of 23.11 kcal/mol/e and a standard devi-ation of 8.30 kcal/mol/e (see Table I). Heme moleculesare bound by more than 20 different protein folds79

leading to a large diversity of environments around themolecules. In-depth inspection of the protein environ-ments around the heme molecules shows that, like

NADs nicotinamide moiety, repulsive ESPs are overrid-den by aromatic interactions. Aromatic interactions are

well known to contribute strongly to the binding energyof heme molecules.7981

Among all 16 heme-binding pockets analyzed, the bo-vine endothelial nitric oxide synthase (eNOS) (PQS-Id:1d0c) was the only enzyme that exposes the Fe of its

heme ligand to a repulsive positive ESP. The positive ESPwas mainly created by a loop region on the proximal siteof the heme molecule (see Fig. 5). The loop regionincludes the Cys 186, which coordinates Fe, and three ar-

Figure 5

Binding site of the bovine endothelial nitric oxide synthase (eNOS)with the blue-colored electrostatic potential isosurfaces at 10 kcal/mol/e.The heme molecule is shown in stick representation and on itsproximal site are depicted the loop region with Cys 186 (yellow color)coordinated to the hemes iron ion (dashed line) and Arg 189 (redcolor). The loop main-chain amine groups are also shown in stickrepresentation. NCCs, here the inhibitor 7-NIBr (PDB-ligand nameINE) and the crystallization agent acetate (PDB-ligand name INE), areshown in green color.

Figure 4

(a) The repulsive electrostatic potential of NADH peroxidase toward the adenine moiety of NADH is compensated via pCH interactions betweenthe adenine moiety of NADH (varicolored) and Ile 180 (green colored) and Val 242 (green colored). (b) ADP-ribosyltransferase stabilizes thebinding of NAD1 via a pp interaction with Phe160 (green colored), pNH interaction with the backbone amide of Ser148 (green colored), and aninternal hydrogen bond (black dashed line) between the amide group and the phosphate group.

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ginine residues of which Arg 189 is located right on top

of Fe. Main-chain NH groups in the loop region that arepointing inward into the loop were further strengthening

the positive ESP. Although the observed repulsive ESPseemed counterintuitive, it demonstrated once more thatthe complementarity between proteins and ligands wasdriven by the ligands role in the enzyme function andnot by its chemical composition. eNOS must bind a pos-itively charged L-Arg substrate molecule to perform itsfunction, namely creating nitric oxide. A heme Fe ironion in a reduced oxidation state Fe(II) is thereby advan-tageous as it increases the binding affinity toward L-Argby 80-fold compared with the oxidized state Fe(III).82

Therefore, there is an interest from the enzyme to stabi-lize the Fe(II). The positive ESP on the Fe of eNOS isthereby advantageous, as it stabilizes the less positivelycharged Fe(II) state. Furthermore, the positive electro-static field increases the redox potential of Fe making theelectron transfer from a distant FMN molecule thermo-dynamically favorable.83 Finally, the field stabilizes thenegatively charged Cys 186, which again increases the re-dox potential of the heme molecule.

In fact, the redox potential of the hemes iron ion isone of the most important electrochemical characteristicsof heme molecules. Heme redox potentials can varybetween 2550 mV (in the hemophore HasA84) and1450 mV (in peroxidases85) versus the standard hydro-gen electrode. Correlating the redox potential to proteinelectrostatics might be obvious; however, such a correla-tion is not straightforward as the redox potential is influ-enced by many different factors such as the type of the

hemes axial ligands, heme burial, and localcharges.80,86,87 Nevertheless, our calculations show that

higher ESP on the Fe ion generally induces a higher redoxpotential for the heme molecule (see Fig. 6 and Table II).

The quinol:fumarate reductase (QFR) of Wolinella succi-nogenes (PQS Id: 2bs2) binds two heme molecules, namelya heme at the proximal site of the protein structure (heme

bP) and a heme at a distal site (heme bD). Both heme mol-ecules have distinct redox potential. For many years it was

unclear, which of the heme molecules corresponded to thelow-potential (heme bL) and high-potential (heme bH)heme molecule. With the computational simulation of theelectrochemical redox titration behavior of both heme mol-ecules using electrostatic calculations, Haas and Lancaster97

were able to identify the low-potential heme as heme bDand the high-potential heme as heme bP. Using the above

relationship between ESP and redox potential, we wereable to confirm Haas and Lancasters finding with an ESPof 218.84 kcal/mol/e for heme bD and a much higher ESP

of 28.02 kcal/mol/e for heme bP.

Remaining ligand sets

AMP-binding sites often generate positive ESPs towardtheir ligands phosphate group (see Fig. X1 in Supporting

Information). Five of the proteins, namely 1amu, 1ct9_1,1jp4, 1qb8, and 1tb7, had at least one metal ion boundwithin 9 A proximity inducing a positive potential on

the phosphate tail. The AMP molecule in asparagine syn-thetase (12as) compensated the repulsive global negativeESPs through a local network of eight hydrogen bonds.The flavin moiety in FAD as well as in FMN experiencedboth negative and positive potentials in our data set. Thephosphate group in both ligands was however alwaysattracted by positive potentials. In the riboflavin kinase

Figure 6

Plot showing the correlation between heme redox potential and theelectrostatic potential that was measured on the hemes iron ion (seealso Table II).

Table IIComparison Between the Electrostatic Potential (ESP) on the HemesIron Ion and Its Redox Potential Against the Standard HydrogenElectrode (Em)

PQS-Id ESP (kcal/mol/e) Em (mV) Reference

1naz 242.81 ?

1dk0 233.13 2550 881np4 224.67 2259 89

1qpa 223.65 2130 90

1sox 221.45 168 911pp9 220.03 210 92

1qhu 19.20 ?

1iqc_1 217.81 1450 85

1d7c 216.49 1169 931eqg 210.69 250 94

2bs2 28.02 29 95

1po5 27.30 ?

1ew0 25.82 ?1gwe 25.36 ?

2cpo 20.61 2140 96

1d0c 3.55 ?

See also Figure 6.?, No redox potential was found in the literature for the protein at near crystalli-

zation condition.


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(1p4m), the pyrophosphate of the product ADP locatednext to FMN caused the repulsive negative potential atthe phosphate group. The negative potential on the aro-matic ring of the same ligand was compensated by aro-matic interactions.

Glucose-binding sites were electrostatically most neg-ative in our data set with an average ESP of 27.17

kcal/mol/e (see Table I). In contrast, phosphate-bindingsites were most positive with an average potential of17.14 kcal/mol/e (see Table I). Metal ions were foundwithin 9 A proximity in nine cases (1a6q, 1e9g, 1ew2,1h6l, 1ho5_1, 1l7m_1, 1lby, 1qf5, and 1tco) generatingpositive potentials around the PO4 molecules. An inter-esting exception was the binding site of the bacterial

dethiobiotin synthetase (1dak). This particular bindingsite apparently completely lacked the expected physico-chemical properties to bind a phosphate molecule. Not

only it did exert repulsive negative potentials, but alsoit lacked any compensating polar interactions and/orhydrogen bonds toward its ligand. Also, van der Waals

interactions could be ruled out as the phosphate mole-cule was solvent accessible on up to 70% of its molec-ular surface. We could not find evidence that the mol-ecule has bound at a crystal contact interface. Unfortu-nately, the structure factors for 1dak were available atneither the PDB nor the Electron Density Server,98

preventing further investigations of the electron densityof the phosphate molecule at its current location. The50% occupancy value given for the entire phosphatemolecule in the current crystal structure of 1dak mightindicate an alternative location of the phosphate mole-cule in the protein structure. And finally, as for hememolecules, the molecular recognition of steroid mole-cules is driven by hydrophobic and aromatic interac-tions99 that override the observed repulsive ESP in ste-roid-binding sites in our data set.

Nonelectrostatic interactions between protein and ligand

Our results show that binding events are not solelydirected by classical electrostatic interactions betweenpartially charged atoms, as there are many examples ofnoncomplementary ESPs between protein and boundligand. Thus, other nonelectrostatic forces acting betweenligand and protein must contribute and result in negative

binding free energies and lead to the binding of theligand to its binding site. With the exception of glucoseand phosphate, all our ligands possess at least one aro-matic ring complex, and most of the variation in termsof ESP is observed at these ring systems. Ligand moietiesthat are highly charged, like the phosphate groups, expe-rience rather constant complementary electrostatic fields.Close inspections of the binding site ligand complexes inour data set showed that almost all aromatic ring groups

undergo various forms of aromatic interactions. Most ofthese interactions were of a hydrophobic nature toward

aliphatic hydrocarbons, such as valine, leucine, or isoleu-cine side chains, forming pCH interactions.100,101 Thesecond most often observed aromatic interactions werepp interactions between aromatic ring groups mostlyfrom phenylalanine and tyrosine residues.102 Other aro-

matic interaction types were pcation interactionsbetween aromatic rings and positively charged side chains

of arginine and lysine103 and pHN interactions withbackbone amide groups that act as a hydrogen bond do-nor toward an aromatic ring.104 Also observed were p-proline interactions.105 Aromatic interactions, in partic-ular pCH and pp, are in general dominated by van derWaals dispersion and hydrophobic interactions.106,107

Electrostatic interactions play only a secondary role and

only contribute where aromatic interactions involve pro-tein hydroxyl or amine groups that have a high electro-static dipole moment.108 Accurate dispersion energy cal-

culations require sophisticated and computationallydemanding quantum chemistry calculations106 that arebeyond the scope of this work. Instead, we analyzed the

hydrophobicity of the surrounding protein residues andNCCs and assessed the contribution of hydrophobicinteractions in overriding electrostatic repulsion betweenprotein and ligand.

Figure 7 depicts the HES (see Methods) for the bind-ing sites in Figure 1, colored from magenta to white to

green for 21 to 0 to 1 HES for polar, neutral, andhydrophobic environments, respectively. From Figure 7,it is clear that aromatic ring systems are generally locatedin a hydrophobic environment. In particular, the varia-tion observed for ESP in heme-binding sites does notexist for HES. All heme molecules are located entirely inhydrophobic-binding pockets whether facing attractive orrepulsive ESP. Similar dominant HES were observed forsteroid molecules and flavin moieties (see Fig. X2 in Sup-

porting Information). The adenine moieties of ATP andNAD were usually found in a hydrophobic environment,whereas their charged phosphate groups tend to face apolar environment. The NAD molecules (PQS Ids 1ibo,1hex, 1mew, 1og3, 1qax, and 2npx) that were found toexperience repulsive electrostatic forces at their adenineand nicotinamide moieties simultaneously form attractivearomatic-hydrophobic interactions.

Average and variation of physicochemical properties

Despite the various conformations of a ligand in dif-ferent protein-binding sites, one can calculate the averageESP and HES and its standard deviation for each ligandatom in the protein-binding pocket. The average atomicESP and HES were calculated for each ligand set andplotted in Figures 8 and 9. Next to the figures aredepicted ESP and HES generated by the ligands in isola-tion. In contrast to many single cases (see in particular

NAD and heme in Fig. 1), the average values of the phys-icochemical properties show complementary characteris-

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tics between protein and ligand for the majority of thecases. From Figure 8, it becomes evident that usuallyelectrostatically positive protein potentials are neutralizedby electrostatically negative ligand potentials and viceversa.

A closer look at the ESP in Figure 8(a) reveals averagepositive ESPs for all adenine groups and all phosphategroups, whether as separate entities or part of larger mol-ecules. Note that despite the similarity between AMP andATP, the latter is usually bound in pockets with higher

positive potential because of the larger number of metalions coordinated to the phosphate tail of ATP. The highlyhydrophobic heme and steroid molecules, as well as glu-cose and the nicotinamide moiety in NAD, are mainlysurrounded by negative potential. Figure 9(a) shows thatsteroids and the porphyrin core of heme molecules arebound in very hydrophobic environments together withthe flavin moieties in FAD and FMN. Because of thelarge number of pCH and pp interactions involving

adenine moieties in our data set, these moieties experi-ence large HES despite being of moderate polar nature.The comparison of the averaged ESPs from the pro-

teins [Fig. 8(a)] and the ligands [Fig. 8(b)] on eachligand atom reveals a correlation of only R2 5 0.25. Thecorrelation for HES is higher with R2 5 0.66. Both num-bers are relatively small and indicate rather little interde-pendence between the proteins or ligands physicochemi-cal properties. However, they still exceed the correlation

between all 100 individual binding site/ligand complexes,with R2 5 0.14 for ESP and R2 5 0.35 for HES, demon-

strating that the average physicochemical properties showa higher complementarity than individual proteinligandpairs.

The standard deviation of the absolute ESP and theHES is given in Table I. ESP shows large variations withstandard deviations several times larger than the averagevalue. The highest variation is seen for phosphate-bind-ing pockets having a standard deviation of 14.64 kcal/mol/e, whereas the lowest variation is seen in steroid-binding pockets with 3.93 kcal/mol/e. The variation of

HES is generally less and is around four times smallerthan the average standard deviation of ESP.

Although the absolute values of ESP and HES have ahigh standard deviation and thus are very variable, theirvalues are consistently of the same sign. Figure 10 showsfor each ligand atom the SCR (see Methods) for ESP andHES. Cyan color indicates no variation (0%) for a ligandatom with score values all with the same sign; the highestvariation (50%) is colored orange reflecting half positive

and half negative score values. According to Figure 10,half of all ligand atoms in the data set experience ESPand hydrophobicity scores of low SCR, whereas half ex-perience high SCR. Hydrophobic moieties in ligand mol-ecules often occupy equivalent hydrophobic environ-ments, like the flavin groups in FAD, FMN or the por-phyrin core in heme molecules or steroid molecules, buthave their electrostatic environments change. Similarobservations can be made for central phosphate groups

in FAD and NAD. Thus, the interactions are on averagecomplementary but vary widely in their magnitude.

Figure 7Hydrophobicity experienced by (a) ATP, (b) NAD, and (c) heme molecules within their binding pockets. The level of experienced hydrophobicity isgiven by the hydrophobic environment scores (HES) (see Methods) and is colored from magenta to white to green for polar environments with lessthan 21 HES to 0 to hydrophobic environments with values above 1 HES. The ligands are ordered as in Figure 1. The PQS-Id of the proteinstructure in which the ligand was found is given below each ligand. The representative conformer for each set has a yellow label.


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Figure 8

(a) Average electrostatic potential that each ligand set in the data set experiences within protein-binding sites. ( b) Electrostatic potentialcalculated for each ligand molecule in isolation. The electrostatic potential is colored from red to white to blue for values below 25 kcal/mol/eto 0 to above 5 kcal/mol/e.

Figure 9

(a) Average hydrophobicity that each ligand set in the data set experiences within protein-binding sites. ( b) Hydrophobicity of the ligandmolecule in isolation. The level of experienced hydrophobicity is given by the hydrophobic environment scores (HES) (see Methods) and is coloredhere from magenta to white to green for polar environments with less than 21 HES to 0 to hydrophobic environments with values above 1 HES.

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DISCUSSION

Our starting point for this work was to explore the va-

lidity of the assumption that binding sites, which bind

the same ligand, achieve their selectivity by providing asimilar physicochemical environment. To analyze this

ligand binding pocket relationship, we have performed

semiempirical calculations to compute and then compare

the electrostatic and hydrophobic environments in 100

protein binding sites. The binding sites were analyzed in

groups with each group member binding the same

ligand. The results reveal large variations in protein envi-

ronments experienced by each ligand. These large quanti-

tative differences indicate the absence of perfect physico-

chemical complementarity between binding sites and

ligands. A biochemical explanation for this variation

could often be deduced from the differing requirements

of proteins to carry out their function. Nevertheless, this

work gives evidence thatsimilar to the concept of con-

vergent evolution of gene and protein functionnature

has evolved multiple binding solutions for the same

ligand. For some proteins, it may not matter how the

ligand binds to its receptor, but merely that it binds and

so a diverse range of strategies of binding the same

ligand have evolved.Regardless of the simplicity of our approach, we were

able to observe some general principles of molecular rec-

ognition, including the contribution of hydrophobicinteractions to molecular recognition.109,110 To investi-gate hydrophobic interactions, we have developed a newhydrophobicity environment score that is based on a sta-tistical thermodynamic description of atomic log P values.In this work, the hydrophobicity was observed to vary rel-

atively little among each set of ligands. In contrast, theESP varies widely and is highly influenced by NCCs. Theimportance of entropic energy contributions is also sup-ported by the buffer zone, that is, the free spacebetween a binding pocket and its bound ligand,6 whichcan stabilize entropically the proteinligand complex byallowing the ligand and the binding site residues to retainsome of their vibrational motion and flexibility.9 Itshould be pointed out that the correlation of our com-puted properties with experimental observations (e.g., re-

dox potentials) is modest at best. Herein, we have notconsidered any kinetics that accompany proteinligandinteraction or the binding specificity and discriminationpower of proteins toward their cognate ligands, which alladd a further level of complexity to the analysis of theproteinligand interaction in silico. It is well known thatconformational changes in particular in allosteric enzymeshave large effects on the molecular recognition of sub-strate molecules and thus on the protein function. In fact,

recent results on in vivo proteins have shown that pro-teins, in particular cell signaling proteins and transcrip-

Figure 10

Variation of physicochemical property scores measured by the sign change ratio of the scores at each atom. Variation is colored from cyan to whiteto orange for relative sign changes of 02550%. 0% represents no score variation for the property. 50% illustrates highest variation with half ofthe ligand set having positive and half of the ligand set having negative score values.


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tion factors, are commonly partially or fully intrinsicallydisordered.111 They usually undergo transitions fromtheir disordered conformation to an ordered structureupon ligand binding, thereby adopting different isomericstates. Experiments on antibodyantigen complexes

showed that each of the isomeric states could bind differ-ent antigens with high specificity though with low affin-

ity.112 Furthermore, most allosteric and induced-fitenzymes lack a correlation between binding affinity andspecificity because of the smaller magnitude of DDG

when compared with the free binding energy DG.113

Consequently, proteins often lack physicochemical com-plementarity toward their ligands, which can reduce thebinding affinity but retain a high binding specificity.

Our observations confirm the results found by someearlier studies that were made on limited datasets (seereferences in the Introduction), yet the myth of exact

complementarity remains. The results of our analysishave consequences for a number of applications, particu-larly those related to function prediction and virtual

screening. Function prediction methods from structureare frequently based on detecting similarities betweenannotated and functionally unknown binding sites. Thevery basis of these approaches is, however, challenged ifcomplementarity is not a given. Such methods must copewith this variation and include a probabilistic term in

their similarity search that accounts for our observationthat the same ligand can bind in one binding site viaelectrostatic interactions, in another via entropic contri-butions or in a third via purely van der Waals interac-tions. A workaround to the probabilistic descriptioncould be the utilization of 3D consensus binding pro-files. Such profiles would represent the physicochemicalenvironment that a ligand on average experiences in vari-ous proteins. A similarity search would then involve thecomparison of the physicochemical properties of a poten-

tial ATP-binding site against a set of 3D consensus bind-ing profiles. Not only would this decrease the screeningtime for a whole database, but it also might increase theprediction accuracy, as the average properties tend tohave higher complementarity to the ligand propertiesthan single binding-site/ligand-complexes.

Despite well-developed theory and extensive progressin molecular simulations, computational approaches tocalculate both enthalpic and entropic energies are still

limited in accuracy.

109

The accurate computation ofthese terms is, however, necessary to understand the finebalance of binding forces underlying proteinligand inter-actions and to make reliable predictions of binding ener-gies. Scoring functions implemented in docking applica-tions typically use a rather simplistic model of molecularrecognition to allow the screening of a myriad bindingposes.114 As a result, the average accuracy of dockingapplications lies within 1.52 A root-mean-square devia-

tion in about 7080% of cases. Most of these successesare cases in which ligand and protein are relatively

rigid.115 Our own docking calculations with a MM-GBSA model116 on our data set showed unfavorable pos-itive energies of up to 1170 kcal/mol/e for 20 proteinligand complexes (data not shown). The results in this ar-ticle show that computational shortcuts based on comple-

mentarity can be dangerous and that more sophisticatedmodels would be required for accurate predictions of

binding energies and binding poses that take into accountall factors and forces currently known to contribute tomolecular binding. In particular, desolvation energies117

at the protein-binding site and entropy gain/loss of ligandand binding site molecules109 will need addressing. Thiscomplexity will provide a challenge for computationalbiology, be it for the accurate calculation of binding free

energies or the derivation of more empirical approaches.

CONCLUSIONS

This manuscript expands on previous work on the ge-

ometrical variation in protein-binding pockets and

ligands6 by analyzing the same binding-pocket/ligand-complexes with respect to their physicochemical proper-

ties. Our analysis of the binding pocket geometriesshowed that binding pockets that bind the same ligandhad a greater variation in their shapes than can beaccounted for by the conformational variability of theirligand. Here, we have continued our analysis on thesame binding sites and found that it is not the chemicalcomposition of a ligand molecule that determines thedegree of complementarity between protein and ligand,but rather the ligands role within the function of the

protein. Our analyses show that the physicochemicalproperties ligands experience when bound to different

binding pockets can vary significantly (Figs. 1 and 7 andTable I). This high variation reflects large energy fluctua-tions that are sometimes functionally necessary (Figs. 3and 5). Some of the variation included even changes inthe sign of the potentials for corresponding atoms in aligand set (see Fig. 10). To overcome repulsive electro-static interactions, proteins were observed to use NCCs

(see Fig. 2) and attractive aromatic interactions (see Fig.4) to their ligands. Complementarity was observed tosome extent only for averaged properties in the ligandset (Figs. 8 and 9). With our in-depth analysis, we werealso able to identify false binding sites and determine theidentity of electrochemically active molecules in proteins(Fig. 6 and Table II).

ACKNOWLEDGMENTS

The authors thank Rafael J. Najmanovich for valuablecomments and discussion throughout the work andJames D. Watson for his valuable comments on earlydrafts of this manuscript. All figures containing mole-

cules were rendered using PyMOL (W.L. DeLano, http://pymol.sourceforge.net/).

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