Poster session v affinity and efficacy models of g protein coupled receptors

R China 'Centre CNR di Studio per le Macromolecole Stereordinate ed Otticamente Attive, Universita ' di Pisa, via Risorgimento 35, I-56126 Pisa, Italy Based on the Walters' s GERM Gene

Poster Session V Affinity and Efficacy Models of G-Protein Coupled Receptors

APPLICATION OF PARM TO CONSTRUCTING AND COMPARING S'HT~A AND

Maria Santagda), Hongming Chen (b5# ), Andrea SantagatiCa), Maria Modica("), Salvatore Guccione(a) , Gloria Uccello Barretta@) , Federica Balzano'')

(a) Diprtimento di Scienze Farmaceutiche, Universitd di Catania, viale Andrea Doria 6, Ed

12, I-95125 Catania, Italy

(b)Laboratory of Computer Chemistry, Institute of Chemical Metallurgy, Chinese Academy of Sciences, P.O Box 353 Beijing 100080, P R China

(')Centre CNR di Studio per le Macromolecole Stereordinate ed Otticamente Attive, Universita ' di Pisa, via Risorgimento 35, I-56126 Pisa, Italy

Based on the Walters' s GERM (Genetic Evolved Receptor Model), PARM (PseudoAtomic Receptor Model) uses a combination of genetic algorithms and a cross-validation technique

to produce atomic-level pseudo-receptor models starting from a set of known ligands These putative pseudo-receptor models can be used to predict bioactivity of virtual

molecules by aligning these molecules with the training set molecules, computing the interac- tion energy between each molecule and interpolating the computed interaction energy in the

QSAR regression equation to obtain a predicted bioactivity, so reducing the trial-error procedure in the synthesis of new chemicalentities

Serotonin modulates many processes in mammalian peripheral and central nervous system through its interactions with at least 14 receptor subtypes, all but one (5-HT3 subtype) of which are G protein (heterotrimeric GTP-binding protein)-coupled

The 5-HT3 subtype is a ligand-gated ion channel that shares functional and structural similarities with nicotinic acetylcholine receptors

Aim of the present investigation is to create a 5-HTlA model capable of aiding the synthesis of new compounds with improved activities elucidating the possible role of heteroaromatic interactions'32 in the receptor binding, and to compare the predictive ability

of the new paradigm PARM334 with two traditional 3D Q S A R techniques such as

@ Present address: Bayer AG, Pharma-Forschung, PH-R Structurforschung, D-42096,

Wuppertal, Germany

433

CoMFA’(Comparative Molecular Field Analysis) and HASL6 (Hypothetical Active Site Lattice), as reported in chapter: APPLICATION OF PARM TO CONSTRUCTING AND COMPARING ~ - H T ~ A AND (xl RECEPTOR MODELS In addition, worth of interest was mapping possible features underlying the ~ - H T ~ A or urpha selectivity, as shown by some ligands in the investigated thienopyrimidinone series7

In the PARM3 computation, 15 kinds of pseudo-receptor atoms are defined first Then, the molecules in the training set are superimposed on a specific pharmacophore model and a set of grid points is generated around the common surface of the superimposed ligands Receptor models are made by placing atoms at these points in 3D space, to simulate a receptor active site These atoms interact with the ligands and the interaction energy

between each ligandand the receptor model is computed By using a genetic algorithm and a

cross-validation technique, a number of atomic-level pseudo-receptor models which have a high correlation between intermolecular energy and bioactivity can be built A QSAR

equation is constructed for each model in the linear form of Bioactivity = A + B*Ehe,

Energetic computation in PARM3 makes use of the TRIPOS 5.0 force field

PARM3 generates the receptor models in the MOL2 file, so that we can check the characteristics of the receptor model within the SYBYL software’

In this study, (forthcoming paper) the initial population of pseudo-receptors was

set to 1500, the maximum generation to 2000, the number of grid points was set to 49 and the cushion distance (the distance between grid point and the closest ligandatom) was 0.5 fL

PARM3 is allowed to run until a series of receptor site models with high conventional correlation coefficients and cross-validated R2 are obtained Usually, the top 20 models are

used to predict bioactivity and compared with a test set

Models fifteen and four (Table I and I0 were found to have the best predictions for the 5-

H T ~ A and q - A R data sets, respectively

These two models are analysed in Figs 1 and 2 See also Fig 6 and 7 of chapter ~ - H T ~ A RECEPTORS MAPPING BY CONFORMATIONAL ANALYSIS (2D NOESYMM)

AND “THREE WAY MODELLING (HASL, CoMFA, PARM)

5069

SDBB 6tW mw BBB(1 980% lW

Fig 1 Analysis of the best predictive 5-HTIA model (model fifteen)

434

P

Table I P A W computation results of tk HT,,- receptor model

*

carbon hydrogen nitrogen oxygen sulphur

Compd Rl R2 R3 R4 Exp -log IC50 Calc -log IC50 Residual &te,(kcaVmol)

11 (61) H Ph H 2-OMe-Ph 6.413 6.898 0.485 4.564

12 ( 6 3 ) H Ph H 1 -naphtyl 5.697 5.609 -0.088 14.773

13 (64) -(CH=CH)Z H 2-OMe-Ph 7.337 7.539 0.202 -0.519

17 (68) Me Me NH2 Ph 8.481 8.616 0.135 -9.047

f

a

Compd Rl

20 (70) Me

21 (71) Me

22 (72) Me

23 (73) Me

1 (43)* Me

R 2 R 3

Me NH2

Me NHPh

Me Me

Me NH2

Me H

6 (50)* -(CH,)4- H

9 (56)* -(CH*)d- H

10(57)* -(CH2)4- H

15 (66)* -(CH1)4- Me

16 (67)* -(CH2)9- NH2

24(74)*' Me Me NH2

25(78)*b - - NHZ

S D*s 0.86

Table I continued

R4 Exg -log IC50 Calc -log IC50 Residual l$,,,,,,(kcaUmol)

-l0gIC50=7.474-0.126*E~,~~ $=1).962, R2cv=0.906 SDzD.353

*In brackets t h e number in the paper (see ref 10)

'Test set compounds

*The piperazine ring has beenreplaced by a piperidine nudeus

The thiophene ring has been replaced by a benzenenudeus

Table I1 PARM computation results of the q - A R model

e

0

carbon hydrogen n i t q e n oxygen sulphur

Compd Rl R2 R3 R4 Exp -log IC50 Calc -log ICSO Residual ILter(kcaUmol)

2 (44) Me Me 3-C1Ph H 6.524 6.652 0.128 16.030

4 (48) Me Me H 1 -naphtyl 6.053 6.136 0.083 20.900

Compd Rl R2 R3 R4 Exp -log IC50 Calc -log IC50 Residual ILte,(kcaVmol)

20 (70) Me Me NH2 2-OMe-Ph 8.137 7.962 -0.175 3.652

21 (71) Me Me NHPh 2-OMe-Ph 7.495 7.403 -0.092 8.932

23 (73) Me Me NH2 2-pyrimidinyl 6.296 6.245 -0.051 19.865

-l0gIC50=8.349.0.106*E,~,, r=0.975, R,,,2=0.941 S D = 0 1 9 7

Table 11 continued (Test set molecules)

1 (43)" Me Me H 2-OMe-Ph

6 (50) -(CH2)4- H 2-CI-Ph

9 (56)* -(CH2)4- H 1-naphtyl

10(57)* -(CH2)4- H 2-pyrimidiny l

16 (67)* -(CH2)4- NH2 2-OMe-Ph

24(74)*' Me Me NH2 2-OMe-Ph

25 (78)*b - - NH2 2-OMe-Ph

S D * = 0 6 1

*In brackets thenumber in the paper (see ref 10)

'Test set oompounds

The piperazine ring has beenreplaced by a piperidine nucleus

bThe thiophene ring has beenreplaced by a benzenenucleus

6.793

6.775

6.352

5.741

7.194

7.409

7.444

8.398

6.886

6.581

6.593

6.830

7.919

7.924

8.217

7.893

0.093

-0.194

0.241

1.089

0.725

0.515

0.773

-0.505

13.811

16.696

16.578

14.341

4.063

4.014

1.251

4.307

A TESTSET

fl PREDICTING SET

Fig 2 Analysis of the best predictive c+AR model (model four)

Acknowledgements Financial support (40%) from Italian MURST and the kind technical

support from TECHNOSOFT (via Galliano, 25, 1-95125 Catania, Italy) are gratefully

S Guccione thanks Prof Eric Walters for the helpful discussion and directions

Hongming Chen thanks Prof J J Zhou for the helpful support and the high scientific

contribution to the ongoing PARM investigations

acknowledged

References (’)

1 T M Fong, H Yu, R R C Huang, M A Cascieri, and C J Swain, Relative contributi-

on of polar interactions and conformational compatibility to the binding of neurokinin- 1

receptor antagonists, Mol Phi-macol., 50: 1605 ( 1996) and enclosed references

2 M Modica, Synthesis of thieno[2,3-d]pyrimidine derivatives Ligands to the ~ - H T ~ A

serotoninergic receptor, Tesi di Dottorato di Ricerca (Ztalian PhD.), University of

Catania (1994)

3 H M Chen, J J Zhou, G R Xie, PARM: A genetic evolved algorithm to predict

bioactivity, J Chem Zn$ Comput Sci., 38: 243 (1998)

4 D E Walters and T D Muhammad, Genetically evolved receptor models (GERM): a

procedure for construction of atomic-level receptor site models in the absence of a

receptor crystal structure, in: Genetic Algorithms in Molecular Modelling, J Devillers,

ed., Academic Press, London (1996)

(’) Refs 5.- 8 -see chapter: 5-HTIA RECEPTORS MAPPING BY CONFORMATIONAL

ANALYSIS (2D NOESYMM) AND “THREE WAY MODELING (HASL, CoMFA,

PARM), by S Guccione et al See refs 13., 7.,10., 11

439

A NOVEL COMPUTATIONAL METHOD FOR PREDICTING COUPLED ANAPHYLATOXIN RECEPTORS, CSAR and C3AR THE TRANSMEMBRANAL STRUCTURE OF G-PROTEIN

Naomi Sew, Anwar Rayan,Wilfried Bautschl and Amiram Goldblum

Department of Medicinal Chemistry, School of Pharmacy, Hebrew University of Jerusalem, Jerusalem, ISRAEL 91 120, and 1Institut fur Medizinische Mikrobiologie, Medizinische

Hochshule, Carl-Neuberg-Str 1, D-30625 Hannover, Germany

Introduction: The receptor C5aR (350 residues) is found in the membranes of

polymorphonuclear leukocytes When activated by its ligand, C5a, a very potent chemoatractant, an amplification of the inflammatory process occurs C3aR (482 residues) is

similarly associated with such events, although to a lesser extent High levels of C5a (74 aa)

and C3a (77 aa) were connected to inflammatory and autoimmunal diseases, such as

Rheumatoid Arthritis and Adult Respiratory Disease Syndrome, that can even lead to death The design and construction of potent antagonists to each of the two receptors is a major avenue that could lead to control of such conditions C5aR and C3aR belongs to the superfamily of G Protein-Coupled Receptors (GPCR), which includes over 700 members, involved in many important biological activities The structure of these proteins has not been determined yet and attempts to rationally design drugs for them are still limited

One of the very few membranal proteins whose structure was solved is bacteriorhodopsin, a membranal proton pump It consists of seven transmembranal helices, connected by extra- and intra-cellular hydrophilic loops, an extra-cellular N-terminal and an intra-cellular C-terminal Bacteriorhodopsin is not a GPCR and has no significant homology with this family, yet there is experimental evidence that demonstrates a similar topology The structure of bacteriorhodopsin has been initially determined by electron microscopy at low resolutions parallel and perpendicular to the membrane (1BAD) More recently, X-ray structure of bacteriorhodopsin was determined at 3.5A resolution (2BRD) Due to the fact that the three dimensional structure of the GPCRs was not solved yet, constructing theoretical models for these receptors, in order to investigate their interactions with their ligands and their activation mechanism, has become very common

Method: We view the process of receptor assembly as a result of two different

mechanisms: An equilibrium of helices between water and the membrane, governed by their hydrophobicity, followed by an association of helices which may be close to interactions in globular proteins We employed a knowledge-based force field constructed from the Protein Data Bank (globular proteins), where all the interactions between pairs of amino acid residues have been evaluated according to their occurrence and the appropriate statistical weights (Miyazawa and Jerniganl ) Seven regions along the sequence, which are assumed to contain the seven transmembranal helices, were found by means of hydrophobicity profiles and multiple sequence alignment with other GPCRs, with the program HOMOLOGY These regions are input to our program THREAD Each region is longer than the sequence that is expected to reside in the membrane in a helical structure The program suggests the limits for each helix It threads the seven sequences simultaneously on the coordinates of bacteriorhodopsin, combining all the possible options for each helix

THREAD employs the template structure of 1bad.pdb or 2brd.pdb (or any other template) and "threads" a GPCR in order to find the best GPCR structure by using two methods:

1) Calculating the overall contact energy of the structure Two residues, whose Ca-Ca

distance is less or equal to 7A (for Gly - 6A) and whose CP-CP distance is less than their

Ca-Ca distance, are considered to be in contact The contact energy value for every pair is summed up for the whole protein.The lowest energy structures are retained for further processing The detailed structure of side chains of residues are not taken into account at this stage

2) Summing up the hydrophobicity values in the membrane and outside For every structure threaded, the hydrophobicity values of each residue in the membrane (i.e in a helix) are summed The program searches for the most hydrophobic structure

Side chains were added by two methods that employ a rotamer library HOMOLOGY

the sequence of addition SCWRL2 adds side chains from a backbone-dependent library, and

optimizes the results by identifying clashes and combining all clashing side-chains into a group, for which all combinatorics for the rotamers are tested

uses a backbone independent library of rotamers, and the side chains are added depending on

Results: THREAD was first tested on the theoretical set of coordinates for

bacteriorhodopsin, lbad 9.3* 105 structures were threaded The best result was obtained (table l), but for some helices other results had very close weights The hydrophobicity method is least accurate in the case of helix B (A=two turns), which is more hydrophilic than other helices Contact energy gave accurate results for most helices, with helix F being about one turn distant from experimental

Table 1 The beginnings of the helices of bacteriorhodowin

For CSaR, 1.7*107 structures were checked The two methods gave fairly close results

(table 2) For helix C we got two possibilities for the beginning in the hydrophobicity

method: residue 104 or residue 111 Helix G could begin at residue 281 or residue 284 In

the contact energy method, helix C fluctuates between 107 and 109, helix F between 245 and

241, and helix G between 281 and 284 The two best solutions for each method are depicted

in table 2 However, quite a few other results with close energies exist The results for C3aR

based on lbad coordinates gives as helix starts: A, 24; B, 57; C, 98; D, 141; E, 342; F, 379;

G, 410 (contact energy only)

REFERENCES

1 Miyazawa, S and Jernigan, R (1985) Macromolocules 18: 534-552

2 R L Dunbrack, Jr and M Karplus (1993) J Mol Biol 230: 543-571

44 1