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Predicting receptor-ligand interactions
Predicting receptor-ligand interactions Stanley K. Burt, Charles W. Hutchins and Jonathan Greer A b b o t t Laboratories, A b b o t t Park, Illinois, USA
Advances in computational methodology and increased structural information about receptors have increased our ability to model and predict ligand-receptor interactions. This review summarizes current computational methods used to develop models of ligand-receptor complexes and new methods that can use these structural models to discover novel ligands. Current Opinion in Structural Biology 1991, 1:213-218
Introduction Recent advances in computational chemist~', computer graphics, NMR, X-ray crystallography, biochemistry and molecular biology have suggested that rational design us ing structural information can be an increasingly valu able method of discovering novel pharmaceutical agents. Central to this method is the difficult problem of understanding the nature of specific molecular recogni tion between ligands and their receptors. The prob lem is compounded by the fact that, in most cases ex cept for crystallized soluble proteins, the structure of the receptor molecule is unknown. This review will focus on progress made in enhancing our ability to predict how ligands will bind to their receptors. The re view is divided into two sections focusing on the tech niques used to predict intermolecular interactions: on the one hand, when the three-dimensional structure of the receptor is unknown, and on the other hand, when information is available about the three-dimensional structure of the receptor. In both cases, two ma jor challenges are faced: the identification of the bioactive conformation of the ligand; and extrapolation from the bioactive conformation to novel molecules that agonize, antagonize or inhibit receptor function, as desired. The major molecular interactions involved in ligandreceptor binding are van der Waals interactions, electro statics, hydrogen bonding and hydrophobic effects. Hydrophobic interactions are usually the major driving force whereas electrostatics and hydrogen bonding are responsible for providing specificity. The age-old Fischer con cept of lock-and-key fit is still a valid starting point, but we have come to realize that not only the key but also the lock can be quite flexible. Nevertheless, steric complementarity remains a major factor in intermolecular recog nition.
Strategies used when the receptor structure is unknown The first objective is to find the bioactive conformation. When the structure of the receptor protein is not available and there are a number of ligands that interact with the protein at the same site, the goal is to develop some type of model of the receptor's binding site. One begins with constrained ligands and then superimposes more flexible analogues, usually to overlap groups believed to be critical for function, which are often called pharmacophores. I,)oking at the union surface of these superimposed ligands, the receptor may be mapped by de termining the relative three-dimensional location of the sterically allowed and forbidden regions, as well as the electrostatic nature of these regions. The model binding site should be able to accommodate all known potent ligands and should be able to predict, to some degree, the potency of new ligands. Inactivity of a ligand may be explained either by its failure to superimpose properly upon the pharmacophoric groups or by its overlap with forbidden regions, which corresponds to collision of the ligand with the receptor. For flexible small molecules and for peptides, conformational calculations on the ligand are performed to deduce the structure of low-energy conformations. This can be a major computational challenge. Furthermore, there is no requirement that the lowest-energy form of the iso lated ligand is the one that binds to the receptor. Consequently, it is often necessary to generate numerous lowenergy conformations, within a certain energy range of the global minimum, all of which must be considered as potential candidates for the bioactive conformation. As the size of the ligand and the number of conformational degrees of freedom increases, various techniques beyond a simple brute-force systematic conformational
Abbreviations DHFR--dihydrofo[ate reductase; CoMF~comparative molecular field analysis.
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Theory and simulation search must be employed. The techniques currently in use include molecular dynamics [1], Monte Carlo [2] dis tance geometry [3], simulated annealing [4] and quan turn chemistry [5]. With the exception of quantum chemistry, all these techiliques produce numerous conformations, many of which can be redundant. One of the ma jor problems in conformational searches, aside from the perennial one of finding the global minimum, is that of classifying and categorizing confonnations to find repre sentative family structures. Simulated annealing is a general technique that can be ap plied to many problems to find a minimumenergy con formation. In simulated annealing, a molecular system is heated to high temperatures, allowed to vary its confor mation, and then cooled slowly to produce a low energ3 structure. As the temperature is lowered, the system is confined to smaller regions of conformational space and the probability of going uphill over an energy barrier is reduced. When the ,system has cooled sufficiently, the system is trapped in a local minimum. If high enough temperatures are used and the cooling process is done properly, a global minimum should be reached. Simu lated annealing can be applied in both Monte Carlo and molecular dwmmics simulations. Some pitfalls of s i n s lated annealing have been pointed out in a paper by Wil son and Cui [6"] in applications to amino acids, pcptides mad polH)eptides, as well as by Barakat and l)can [-~,8i m matching C a structures of Esd~ericbia coli dihydrofolatc rcductasc (I)IIFR) and Lctcl~bacilh¢,s easel I)tlFR. Fronl both of these papers, it is clear thai the cooling schedule. as well as the equilibration time, are crucial to obtaining a g o o d representation ~)f the t~ohzmann distribution ot conformations. For peptides, w h i c h are vei3 lh'xilflc, ct)nf()rmationa[ constraints must be introduced t() limit conlormational
space. One way of doing this is to substitute individual amino acids, fi)r example, replacing a polar amino acid by a non-polar amino acid. or by introducing a l ) w p e amim) acid. If a change in receptoi binding or in acii\ ity is observed, then it must be determined whether this is due to a change in the conformation of the ligand, a perturbation of the receptor interaction, or both. Specifi, local constraints can be introduced in an attempt to bias a l)eptide towards a particular conl()rmation, or to explore' hgand-receptor interactions. These types of substitutions might R)ster or disrupt s e c o n d a w structure (i.e. an a-he lix or [3-sheet) in the peptide ligand, or be inwJved in confming a particular side chain. Conformational llexi bility may be decreased bv introducing covalent cross bridges, such as disulfide bridges [9], the linking of side chains [10"] or tying a side chain back to the peptidc backbone to form a macrocycle 111",12]. A review ()t these sorts of modifications can be found in an article bv Hruby [13]. The latter technique is particularly powertkd because several locally constrained amino acids, particularly when coupled with D-amino acid substitutions, can greatly restrict the confommfional freedom of the peptide and lead to the identification o f models for the bioactive conformation. These types of constraints have been suc cessfully applied to opiate peptides, not only to help de
tennine bioactive conformations but also to identify compounds that are highly selective for the Ix and 8 opiate receptors ]14"-16"]. When one of these conformational constraints is incorporated and the ligand maintains high potency, some of the important sites of binding to the receptor may b e c o m e evident. A recently introduced technique for mapping the receptor is known as comparative molecular field analysis (CoMFA) [17]. In this procedure, a molecular forcefiekt calculation is performed to evaluate the interac tion e n e r ~ ~ of a probe atom that is placed along a reg ular grid around the molecule, using a program such as GRID I18]. The p r o b e can be of various types, the usual choices being a metlwl probe to explore steric requirements or a hydrogen ion to explore electrostatics, but other choices can be used. The energy values obtained for each grid point are then c o m b i n e d with the biological poten( T and run through a partial least squares statistical analysis to determine three di mensional quantitative contributions of these energy valties to the potency. The problem of how to super mlpose ligand molecules can also be addressed with this procedure by positioning the molecules so that their en ergy fields are optmmlly aligned, rather than just max imizing the overlap of their chemical structures. This method has been applied to the mapping of the benzo diazepinc receptol inverse agonist-binding site, where the CoMFA results correlated well with results from other Bpcs of studies [19]. Another potentially interesting approach t(~ receptor mapping is that of RI£MOq~I)ISC [20J. In this method, c~ac'h aural of the various ligands is a~ssignc~l three physicochemical properties: partition coefficient, molar refractivity and charge density. A stnmgly bound ligand is taken as the reference model and other ligands are super imposed on it by matching physicochemical properties. Next, the active site is mapped by assigning points of coincidence and non-coincidence to the various ligands. These points are then used to assign the relative impor tance of the physicochemical properties at various sites of the receptor binding pocket. This procedure was ap plied to a range of ligands binding at the benzodiazepine receptor binding site and a prediction of the structures ()f five c,,)mpounds not in thc original training set wa,~ made. Although this method has promise, it is limited by the choice of the initial reterence molecule. The second objective is to identiPy ligands with which to test the receptor model, as welt as the discovery of potential novel compounds. These m w be identified by three dimensional substructure searching programs, such as ALADDIN [21] or CAVEAT [22], that can find c o m p o u n d s whose three-dimensional structures meet specific geo metric and steric criteria. These programs incorporate properties calculated from a reference molecule, which may be the bioactive conformation, such as interatomic distances, torsion angles, distance b e ~ ' e e n planes, forbidden regions and measured physical properties of molecules, such as partition coefficient and pK a. In a re cent stud},, Martin and co workers [21] used this technique in relation to a map of the D2 dopamine receptor
Predicting receptor-ligand interactions Burr, Hutchins, Greer 215 site. Among the search criteria used were the presence of a nitrogen atom, an electronegative atom bonded to a hydrogen and an aromatic carbon, as well as several geometrical constraints. Also included were those regions of the D2 dopamine receptor that allowed substituents and those regions that were forbidden. This led to the successful identification of all the active D2 compounds in their database as well as rejection of those that violated the sterically forbidden regions.
Strategies used when the receptor structure is known When the three-dimensional structure of a receptor molecule is known, it should be possible to determine not only the bioactive conformation of the ligand but also the detailed interactions between the ligand and protein, thereby gaining greater understanding of ligand-protein molecular recognition. This understanding should include changes in the conformations of both the ligand and the receptor upon complex formation. A variety of methods is now available with which u) deter mine the structure of receptor molecules and their corn plexes with the corresponding llgands. High-resolution X-ray crystallography can show which regions of the lig and are fitting into which pockets of the receptor and where hydrogen bonds and hydrophobic interactions occur. Similarly, two- and three-dimensional NMR methods can now produce high-resolution solution structures for proteins, protein-llgand complexes and nucleic acids [23]. It is valuable knowing the experimental structures of several different ligands bound to the same recep tor. In the case of proteins for which no experimental structure is available, comparative or homology-modeling methods may permit the construction of a tentative model structure of the receptor-llgand complex [24-]. Knowing the three-dimensional structure of a receptor, one can combine computer graphics and computational chemistry to design novel llgands. The best results are obtained when the design, computation, synthesis, biological testing and structure-determination methods are performed in a cyclic, iterative manner. A striking example of this procedure is its use in the design of new, more potent inhibitors of carbonic anhydrase for the treatment of glaucoma [25,26]. One way in which the nature of the intermolecular in teractions can be explored is by a different use of the GRID program mentioned above [18]. In this program, various probe atoms are placed at points on a regularly spaced grid and the binding enthalpy of the probe with the atoms of the receptor are calculated. Energy differences can be used to determine which type of probe has a more favorable interaction at particular locations in the ligand-binding site of the receptor molecule. The results of these calculations can be displayed as isoenergy contour maps superimposed on the three-dimensional structure of the receptor using a computer-graphics screen. The contours indicate the positions at which an atom of
the particular probe type may be favorably placed. This analysis can help in placing the ligands in the active site. If the GRID program is m n when the ligand molecule is present at the active site, additional sites of favorable interaction can be identified, thereby assisting the design of new analogues. GRID can also be used to locate the most favorable positions for water molecules in a crystal structure of an enzyme active site [27,28]. In an investigation of the active sites of the dimeric protein aspartate aminotransferase, GRID was used to predict favorable binding subsites for the functional groups of the aspartate ligands [29]. In the first subunit, the GRID results predicted favorable binding sites for the 0t- and 13-carboxylate groups of the aspartare ligand and also for the aspartate amino group. These predicted binding sites corresponded to the positions of the functional groups of the docked ligands. GRID results for the other subunit indicated that it would be unlikely for a ligand to bind in this active site in such a way that would allow transamination to occur. The binding of a ligand to its receptor is an energycontrolled process. Knowledge of the three-dimensional structure of the receptor-ligand complex should permit prediction of the intermolecular interactions and, hence, calculation of the binding energy, allowing us to quantitatively evaluate designed and proposed ligand structures. A technique that has been used to predict intermolecular interactions in this way is that of free-energy perturbation, which is reviewed by McCammon in this issue (pp 196-200). Whereas the van der Waals forces are easily calculated, the electrostatic and entropic factors in~ volved in binding interactions have proven to be more difficult. A number of methods have been used to calculate these terms. These have been successful for some molecules and have been problematic for others [30"]. Using a technique based on solvent-accessible surface areas, Novotny and co-workers [31] have calculated the Gibbs free energy (AG) of an antigen-antibody complex. The calculated and experimentally determined AG values agreed, suggesting interestingly, that only a small number of amino acids contribute to the binding energies of this complex. Thermodynamic studies of inhibitors of renin [32"] and crystallographic studies of anti-cancer agents binding to DNA [33"], have suggested that free energy is not necessarily the sum of contributions from independent subsite interactions with the receptor, but may also depend upon subtle effects associated with solvation and entropy. The program DOCK has been used to search databases of known structures in order to identify compounds that may bind to the active site of an enzyme or receptor where the structure of the binding site is known [34]. In this way, haloperidol was identified as a potential ligand for the active site of the protease of human immunodeficiency vires 1 [35"]. Upon testing, haloperidol was indeed found to be an inhibitor of the protease, but only a weak one. This 'lead' structure can now be modified to provide more potent, less toxic analogues. The weak activity of haloperidol may b e due to the fact that the native
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Theory and simulation structure of the enzyme was used in the search process rather than the structure of the with HWq protease with a bound inhibitor: crystal structures of peptide ligands in the active site of the HIV-1 protease have shown that the enzyme undergoes a significant structural change upon ligand binding [36"]. This illustrates the pitfall of using the native structure of a protein without a bound ligand to guide the search for new molecules. The crystal structures of HW-1 protease, both in its n a tive form [37,38"] and complexed with an inhibitor [36] have shown that the protease functions as a C2 symmetric homodimer, confirming the previous speculations based upon comparative-modeling studies [39]. The approximate C2 symmetry of the dimer has suggested the design of novel sTmmetric HIV protease inhibitors [40",41"] that are less peptide-like than inhibitors based on clas sical transition-state analogues, and so may have a higher specificity for retroviral proteinases than for the related mammalian aspartic proteinases, whose substrate-binding sites are less symmetrical. The inhibitor was designed as follows: a hexapeptide inhibitor was placed in the active site. Knowing that the catalytically active aspartate residues arc close to the C2 axis of the enzyme, the carbonyl carbon undergoing cleavage was positioned on or near the symmetD' axis. One half of the inhibitor was ar bitrarily deleted. A C2-symnlet W operation was then per formed on the remainder of the inhibitor to generate the sTrnmetrical inhibitor. These molecules inhibit HW pro tease at nanomolar concentrations but do not inhibit hu man reran at 10 I.tM. When the crystal structure of a corn plex of the novel inhibitor for HW 1 protease was deter mined, the inhibitor was indeed found to foml symmet ncal interactions with HD" 1 protease [40.,,41.]. C(mlparativc ()r homology modeling is used when the crystal or NMR structure of the target protein is not known, but structures of homologous enzymes are known [24]. One such enzyme that has been exam ined extensively using this approach is renin [42,43]. A number of groups have published renin models based on the kalown structures of homologous aspartic pro teinases. The crystal structure of native recombinant hu man renin at 2.8A resolutkm was recently published [44], but the atomic coordinates have yet to be disclosed. This structure corroborates the general features of mtmy of the renin models; however, neither the published repor! n()r the resolution and refinement of the crystal structure were sufficient to be certain of the details of the con formation. A renin model has been used by Iizuka et aZ [45] to design renin inhibitors; the design of an orally active human renin in.hibitor was based on a transition state analogue of human angiotensinogen. In the past, the experimental determination of the three dimensional structures of proteins has largely been limited to soluble proteins. The structures of membrane bound proteins have resisted analysis, either because they could not be crystallized or because they are not soluble in those solvents that permit NMR analysis. Unfortunately, a large number of the receptor molecules of most interest for drag design are membrane bound; these include the adrenergic, dopaminergic, muscarinic
and serotoninergic receptors, as well as many other hormone and mediator receptors. Consequently, until recently, the structural contribution to the design of new drugs for these receptors has been limited to the methods presented in the first section of this review. However, the recent publication by Henderson e t al. [46,-] of a medium-resolution three-dimensional structure for bacteriorhodopsin based upon electron-diffraction studies of this protein has the potential to dramatically change this situation. The structure shows that bacteriorhodopsin has seven transmembrane helices. The above listed Gprotein-linked receptors are homologous to bacterio'rhodopsin and are therefore themselves likely to be seven-helix membrane proteins. The cloning of many of these receptor genes has provided the amino acid se quences for these receptors; therefore, the method of comparative modeling may now at last be applied to these receptors. For each receptor, the particular sequence can be built onto the seven-helix structure of bacteriorhodopsin. The respective ligand is then placed in its binding site which, like retinal in the case of bacteriorhodopsin, lies in the center of the molecule between the helices. The result ing ligand-binding site should be consistent with the receptor-binding models that have been developed over the years for the binding of the ligands to the particular receptor. To test the models and the importance of predicted interactions further, carefully designed site-spe cific mutagenesis [47"] and chimeric experiments [48.] have been, and will continue to be, used to produce mutant receptors with predicted modified ligand-bind ing properties. The resulting model receptor ligand complex structures provide, for the first time, new information about the detailed interactions of the various ligand substituents with particular groups and pockets on the receptor proteins. The knowledge of these interactions is currently being used to improve our understanding of the ligand-receptor interactions as well as to design novel ligands for these receptors.
Conclusion Within the last several years, advances in experimental and theoretical methods have placed us in a position to better understand how ligands bind to their receptors. Structural information provided by both X-ray crystallography and NMR, in combination with specific information that can be obtained by site-directed mutagenesis experiments, will help to elucidate detailed information about molecular recognition and intermolecular interactions. However, the main obstacle to accurate prediction of ligand-receptor interactions is the ability to accurately calculate the energy of ligand-protein interaction for most complexed systems. Accurate determination of free energy will only occur when we can obtain detailed information, at the molecular level, about the nature of the forces involved in molecular associalion. This is probably best approached by an iterative scheme that involves small changes in the ligand or the
Predicting receptor--ligand interactions Burt, Hutchins, Greet 217 receptor, structural determination of the complex, modeling, prediction of new ligand structures, testing of the hypothesis by synthesis and further structural detremination. From the knowledge gained by these types of procedures, theoretical techniques can be improved and applied to predict ligand-receptor interactions more accurately and, hopefully, design novel ligands in a timely and cost-effective manner.
References and recommended reading Papers of special interest, published within the annual period of review, have been highlighted as: • of interest •• of outstanding interest 1.
McCAMMON JA, HARVEYSC: Dynamics of Proteins and Nucleic Acids. Cambridge: Cambridge University Press, 1987.
2.
METROPOLISN, ROSENBLUTHAW, ROSENBLUTHMN, TELLERAll, TELLER E: Equation of State Calculations by Fast Computing Machines. J Chem Phys 1953, 21:1087-1092.
3.
CR1PPENGM, HAVELTF: Distance Geometry and Molecular Conformation. New York: Research Studies Press, 1988.
4.
KIRKPATRICK S, GELATrl CDJ, VECCHIMP: Optimization by Simulated Annealing. Science 1983, 220:671480.
5.
SZABO A, OSTLUND N: Modern Quantum Chemistry. New York: MacMillan, 1982.
6. WILSONSR, Col W: Applications of Simulated Annealing to • Peptides. Biopolymers 1990, 29:225--235. Simulated annealing is used to search for the global minimum of small peptides and found to be more efficient than Metropolis Monte Carlo. 7.
BARAKATMT, DEAN PM: Molecular Structure Matching by Simulated Annealing. I. A Comparison Between Different Cooling Schedules. J Comput Aided Mol Des 1990, 4:295-316.
8.
BARAKATMT, DEAN PM: Molecular Structure Matching by Simulated Annealing. II. An Exploration of the Evolution of Configuration Landscape Problems. J Comput Aided Mol Des 1990, 4:317-330.
9.
HRUBYVJ, KAO L-F, PErirri BM, KARPLUSM: The Conformational Properties of the Delta Opioid Peptide [D-Pen 2, D-PenS]-Enkephalin in Aqueous Solution Determined by NMR and Energy Minimization Calculations. J Am Chem Soc 1988, 110:3351-3359.
10. •
RODRIGUEZM, LIGNONM-F, GALASM C, AMBLARDM, MARTmaEZJ: Cyclic Cholecystokinin Analogues that are Highly selective for Rat and Guinea Pig Central Cholecystokinin Receptors. Mol Pharmacol 1990, 38:331-341. Cyclization of side chains of residues 28 and 31 in cholecystoldnin produces compounds that are highly selective for central cholecystokinin receptors.
GARVEYDS, MAY PD, NADZANAM: 3,4-Disubstituted 7-Lactam Rings as ConformationaUy Constrained Mimics of Peptide Derivatives Containing Aspartic Acid or Norleucine. J Org G~em 1990, 55:936-940. An efficient method for the synthesis of dipeptide isosteres conformationally constrained by 7-1actam that can mimic aspartic acid or norleucine. 11.
•
12.
ZYIX)WSKYTM, DELLARIAJF, NELLANSHN: Ellicient and Versatile Synthesis of Dipeptide Isosteres Containing y- or 8-lactams. J Org G~em 1988, 53:5607-5616.
13.
HRUBYVJ: Designing Molecules: Specific Peptides for Specific Receptors. El~'lepsia 1989, 30:$42-$50.
14. •
MIERKE DF, SAID-NEJAD O, SCHILLER PW, GOODMAN M: Enkephalin Analogues Containing [3-Naphthyialanine at the Fourth Position. Biopolymers 1990, 29:179--196. Conformationatly constrained enkephalin analogues were studied by molecular dynamics and NM1L 15.
MOSBERG HI, SOBCZYK-KOJIRO K, SUBRAMAHIAN P, CRIPPEN GM, RAMAI/NGAM K, WOODWARD RW: Combined Use of Stereospecific Deuteration, NMR, Distance Geometry, and Energy Minimization for the Conformational Analysis of the Highly 8 0 p i o i d Receptor Selective Peptide [D-Pen 2, D-PenS]-Enkephalin. J Am Chem Soc 1990, 112:822-829. Synthesis and stereospecificaUy deuterated amino acids and their incorporation in a cyclic-enkephalin analogue allow the assignment of all proton resonances, which are then used to model the solution confor mation. •
16. .
WILKESBC, SCHILLER PW: Conformation-Activity Relationships of Cyclic Dermorphin Analogues. Biopolymers 1990, 29:89-95. Conformational analysis of cyclic dermorphin analogues showed a limited number of low-energy conformational families, suggesting a structural requirement for ~t-opioid-receptor selectivity for dermorphin analogues. 17.
CRAMERRD, PATTERSON DE, BUNCE JD: Comparative Molecular Field Analysis (CoMFA). I. Effect of Shape on Binding of Steroids to Carrier Proteins. J Am Cbem Soc 1988, 110:5959-5967.
18.
GOODFORDPJ: A Computational Procedure for Determining Energetically Favourable Binding Sites on Biologically Important Molecules. J Med Cbem 1985, 28:849--857.
19. .
ALLENMS, TAN Y-C, TRUDELL ML, NARAYANANK, SCHINDLER LR, MARTINMJ, SCHULTZ C, HAGEN TJ, KOEHLERKF, CODDING PW, SKOLNICKP, COOK JM: Synthetic and Computer-Assisted Analyses of the Pharmacophore for the Benzodiazepine Receptor Inverse Agonist Site. J Med Chem 1990, 33:2343-2357. A pharmacophore model of the benzodiazepine receptor inverse agonist site is developed using drug-design techniques. 20.
GHOSEAK, CRIPPEN GM: Modeling of the Benzodiazepine Receptor Binding Site by the General Three-Dimensional Structure-Directed Quantitative Structure-Activity Relationship Method REMOTEDISC. Mol Pharmacol 1990, 37:725-734.
21.
VAN DRIE JH, WEININGER D, MARTINYC: ALADDIN: All Integrated Tool for Computer-Assisted Molecular D e s i g n and Pharmacophore Recognition from Geometric, Steric, and Substructure Searching of Three-Dimensional Molecular Structures. J Comput Aided Mol Des 1989, 3:225-251.
22.
BARTLETtPA, SHEA GT, TEI.FER SJ, WATERMANS: CAVEAT: A Program to Facilitate the Strncture-Derived Design of Biologically Active Molecules. Spec Publ R Soc Chem 1989, 78:182-196.
23.
NMR Methods for Elucidating Macromolecule-Ligand Interactions: an Approach to Drug Design. Fourth Biochemical Pharmacology SympoMum. Biochem Pharmacol 1990, 40:1-175.
24. •
GREERJ: Comparative Modeling Methods: Application to the Family of the Mammalian Serine Proteases. Proteins 1990, 7:317-334. Comparative modeling strategies are presented using serine proteases and criteria developed for assessing the reliability of the modeled structures. 25.
BALDWINJJ, PONTICELLO GS, ANDERSON PS, CHRISTY ME, MURCKOMA, RANDALLWC, SCHWAMH, SUGRUEi F , SPRINGERJP, GAUTHERON P, GROVE J, MALLORGA P, VIADER M-P, MCKEEVER BM, NAVIAMA: Thienothiopyran-2-sulfonamides: Novel Topically Active Carbonic Anhydrase Inhibitors for the Treatm e n t of Glaucoma. J Med Chem 1989, 32:2510--2513.
26.
SUGRUEi F , MAILORGAP, SCHWAMH, BALOWINJJ, PONTICELLO GS: Preclinical Studies o n L-671,152, a Topically Effective
218
Theory and simulation Ocular Hypotensive Carbonic Anhydrase Inhibitor. Br J Pharmacol 1989, 98 (suppl):820P. 27.
BOOBBYERDNA, GOODFORD PJ, MCWHINNIE PM, WADE RC: N e w Hydrogen-Bond Potentials for Use in Determining Energetically Favorable Binding Sites on Molecules of Known Structure. J Med Chem 1989, 32:1083-1094.
28.
REYNOLDSCA, WADE RC, GOODFORD PJ: Identifying Targets for Bioreductive Agents: Using GRID to Predict Selective Binding Regions of Proteins. J Mol Graphics 1989, 7:103-108.
KENT SBH: Conserved Folding in Retroviral Proteases: Crystal Structure of a Synthetic HIV-1 Protease. Science 1989, 245:61(>4521. The crystal structure of native synthesized HIV-1 protease at 2.8A resolution is presented. This is the first reported structure of a chemically synthesized protein. 39.
29.
NERO TL, WONG MG, OLIVER SW, ISKANDER MN, ANDREWS PR: Aspartate Aminotransferase: Investigation of the Active Sites. J Mol Graphics 1990, 8:111-115.
KOLLMANPA, MERZKM JR: C o m p u t e r Modeling of the Interac• tions of Complex Molecules. Ace Chem Res 1990, 23:246-252. A review article on computer modeling of intermolecular interactions, focusing on the calculation and prediction of the free energy of protein-ligand complexes. 30.
31.
NOVOTNYJ, BRUCCOLERIRE, SAUL FA: On the Attribution of Binding Energy in Antigen-Antibody Complexes McPC 603, D1.3, and HyHEL-5. Biochemistry 1989, 28:47354749.
32.
EPPS DE, CHENEY J, SCHOSTAREZ 11, SAWYER TK, PRAIPaE M, KRUEGERw e , MANDELF: T h e r m o d y n a m i c s of the Interaction of Inhibitors with the Binding Site of Recombinant t i u m a n Renin. J Med Chem 1990, 33:2080-2086. Independent substrate m~xtels are found to deviate from strict additivity and, even though inhibitor binding to renin is primarily hydrophobic, solution conformational differences between inhibitors are very impor rant. •
FREDEmCKCA, WILLIAMSLD, UGHETTO G, VAN DER MARELGA, VAN BOOM Jtt, RiCH A, WANG AHJ: Structural Comparison of Anticancer Drug-DNA Complexes: Adriamycin and Daunomycin. Biochemistry 1990, 29:2538--2549. Sequence changes close to the intercalation sites influence the bind hag of daunomycin to DNA. Despite the similar conformations of the daunomycin and adriamycin complexes, the corresponding solvation effects are different, causing a surprising effect on the conformation of the bound spermine.
40. *e
ERICKSON J, NEIDHART DJ, VAN DRIE J, KEMPF DJ, WANG XC, NORBECK DW, PIA'ITNER JJ, RITFENHOUSEJW, TURON M, WIDEBURG N, KOHLBRENNERWE, SIMMER R, HELFRICH R, PAUL DA, KN1GGE M: Design, Activity and 2.8 Angstrom Crystal. Structure of a C2 Symmetric Inhibitor Complexed to HIV-1 Protease. Science 1990, 249:527-533. The authors describe the design and synthesis of potent H1V-1 protease inhibitors, based on the C2 ,symmetry, of the protease dimer. The crystal structure of the complex presented confirms the design rationale. 41. •
KEMPFDJ, NORBECKDW, CODACOV1L, WANG XC, KOHLBRENNER WE, WIDEBURG ,Nit, PAUL DA, KNIGGE MF, VASAVANONDA S, CRAIG-KENNARD A, SALDIVAR A, ROSENBROOK W, CLEMENT JJ, PLATFNER JJ, ERICKSONJ: Structure-based, C 2 Symmetric Inhibitors of H1V Protease. J Med Chem 1990, 33:2687 2689. The C2 .symmetry of HIV-1 protease is used to design C2 sTlnmetric inhibitors that are highly potent and selective. ~2.
Bous G, GREERJ: Role of Computer-Aided Molecular Modeling in the Design of Novel lnhibitors of Renin. In Compuleraided Drug Design. Methods a n d Applications edited by Pe m n TJ, Propst CL. New York: Marcel Dekker Inc., 1989, pp 297-326.
t3.
III'TCHINSCW, GREER J: Comparative Mcxleling of Proteins in the Design of Novel Renin lnhibitors. Crit Rev 13iochem 1991, 26: in press.
44.
SIELECK~AR, HAYAKAWAK, FUJINAGA M, MURPHY ME, FRASER M, MUIR AK, CARILLI CT, LEWlCKIJA, BAXTERJD, JAMES MN: Structure of Recombinant Human Renin, a Target for Cardiovascular-Active Drugs, at 2.5A resolution. Science 1989, 243:1346-1351.
45.
I~UKA K, KAMIJO T, I1ARADA H, AKAHANE K, KUBOTA T, UMEYAMAH, ISHIDA T, KISO Y: Orally Potent H u m a n Renin Inhibitors Derived from Angiotensinogen Transition State: Design, Synthesis, and Mode of Interaction. J Med Chem 1990, 33:2707-2714.
33. •
34.
DESJARLAlSRL, SHERIDAN RP, SIEBEL GL, DIXON JS, KUNTZ ID, VENKATARAGHAVAN R: Using Shape Complementarity as an Initial Screen in Designing Ligands for a Receptor Binding Site of K n o w n Three-Dimensional Structure. J Med Chem 1988, 31:722-729.
35. •
DESJARLMSRL, SEIBEL GL, KUNTZ ID, FIIRTH PS, ALVAREZJC, ORTIZ DE MONTELtANO PR, DECAMP DL, BABE LM, CRAIK CS: Structure-based Design of Nonpeptide Inhibitors Specific for the H u m a n lmmunodeficiency Virus I Protease. Proc Natl Acad Sci USA 1990, 87:6644-6648. The program DOCK is used on the crystal structure of native HIV 1 protease to search the Cambridge database of structures for novel lead c o m p o u n d inhibitors. 36. •
MILLER M, SCHNEIDER J, SATHYANARAYANABK, TOTH MV MARSHALLGR, CLAWSON L, SELK L, KENT SBH, WLODAWERA~ Structure of Complex of Synthetic HIV-1 Protease with a Substrate-based Inhibitor at 2.3A Resolution. Science 1989, 246:1149-1152. Crystallographic structure of a peptide inhibitor bound to HIV-1 protease at 2.3 A resolution is presented. 37.
NA'aAMA, FrrZGERALDPMD, MCKEEVERBM, LEU C-T, HEIMBACH JC, HERBERWK, SIGALIS, DARKEPL: Three Dimensional Structure of Aspartyl Protease for H u m a n Immunodeficiency Virus HIV-1. Nature 1989, 337:6154520.
38. •
WLODAWERA, MILLER M, JASKOKSKI M, SATHYANARAYANABK, BALDWINE, WEBER IT, SELK LM, CLAWSON L, SCHNEIDER J,
PEARLLH, TAYLORWR: A Structural Model for the Retroviral Proteases. Nature 1987, 329:351-354.
46. ••
HENDERSONR, BALDWINJM, CESKA TA, ZEMLIN F, BECKMANE, DO"~q',IINGKEt: Model for the Structure of Bacteriorhodopsin Based on High-Resolution Electron Cryo-Microscopy. J Mol Biol 1990, 213:899-929. A seminal paper reporting the three-dimemsional structure of bacteri orhodopsin derived by electron microscopy. The structure has broad implications for the structure of the G-protein receptors. 47. STRADERCD, SIGAI. IS, DIXON RAF: Structural Basis of ~.Adren• ergic Receptor Function. FASEB J 1989, 3:1825-1832. A summary of the mutagenesis data for the [3-adrenergic receptors, and an analysis of the ligand-binding and G protein-interaction regions of the protein. 48. •
DIXON RAF, HILL WS, CANDELORE MR, RANDS E, DIEHL RE, MAP~SHALL MS, S[GAL IS, STRADERCD: Genetic Analysis of t h e Mole.-ular Basis for [~-Adrenergic Receptor Subtype Specificity. Proteins 1989, 6:267 274. A report of the construction and ligand-binding properties of ~1 ~2 adrenergic chimeric receptors.
SK Burt, CW Hutchins andJ Greer, Computer Assisted Molecular Design Group, Abbott laboratories, Abbott Park, Illinois 60064, USA.
Advances in computational methodology and increased structural information about receptors have increased our ability to model and predict ligand-receptor interactions. This review summarizes current computational methods used to develop models of ligand-receptor complexes and new methods that can use these structural models to discover novel ligands. Current Opinion in Structural Biology 1991, 1:213-218
Introduction Recent advances in computational chemist~', computer graphics, NMR, X-ray crystallography, biochemistry and molecular biology have suggested that rational design us ing structural information can be an increasingly valu able method of discovering novel pharmaceutical agents. Central to this method is the difficult problem of understanding the nature of specific molecular recogni tion between ligands and their receptors. The prob lem is compounded by the fact that, in most cases ex cept for crystallized soluble proteins, the structure of the receptor molecule is unknown. This review will focus on progress made in enhancing our ability to predict how ligands will bind to their receptors. The re view is divided into two sections focusing on the tech niques used to predict intermolecular interactions: on the one hand, when the three-dimensional structure of the receptor is unknown, and on the other hand, when information is available about the three-dimensional structure of the receptor. In both cases, two ma jor challenges are faced: the identification of the bioactive conformation of the ligand; and extrapolation from the bioactive conformation to novel molecules that agonize, antagonize or inhibit receptor function, as desired. The major molecular interactions involved in ligandreceptor binding are van der Waals interactions, electro statics, hydrogen bonding and hydrophobic effects. Hydrophobic interactions are usually the major driving force whereas electrostatics and hydrogen bonding are responsible for providing specificity. The age-old Fischer con cept of lock-and-key fit is still a valid starting point, but we have come to realize that not only the key but also the lock can be quite flexible. Nevertheless, steric complementarity remains a major factor in intermolecular recog nition.
Strategies used when the receptor structure is unknown The first objective is to find the bioactive conformation. When the structure of the receptor protein is not available and there are a number of ligands that interact with the protein at the same site, the goal is to develop some type of model of the receptor's binding site. One begins with constrained ligands and then superimposes more flexible analogues, usually to overlap groups believed to be critical for function, which are often called pharmacophores. I,)oking at the union surface of these superimposed ligands, the receptor may be mapped by de termining the relative three-dimensional location of the sterically allowed and forbidden regions, as well as the electrostatic nature of these regions. The model binding site should be able to accommodate all known potent ligands and should be able to predict, to some degree, the potency of new ligands. Inactivity of a ligand may be explained either by its failure to superimpose properly upon the pharmacophoric groups or by its overlap with forbidden regions, which corresponds to collision of the ligand with the receptor. For flexible small molecules and for peptides, conformational calculations on the ligand are performed to deduce the structure of low-energy conformations. This can be a major computational challenge. Furthermore, there is no requirement that the lowest-energy form of the iso lated ligand is the one that binds to the receptor. Consequently, it is often necessary to generate numerous lowenergy conformations, within a certain energy range of the global minimum, all of which must be considered as potential candidates for the bioactive conformation. As the size of the ligand and the number of conformational degrees of freedom increases, various techniques beyond a simple brute-force systematic conformational
Abbreviations DHFR--dihydrofo[ate reductase; CoMF~comparative molecular field analysis.
(~) Current Biology Ltd ISSN 0959-440X
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Theory and simulation search must be employed. The techniques currently in use include molecular dynamics [1], Monte Carlo [2] dis tance geometry [3], simulated annealing [4] and quan turn chemistry [5]. With the exception of quantum chemistry, all these techiliques produce numerous conformations, many of which can be redundant. One of the ma jor problems in conformational searches, aside from the perennial one of finding the global minimum, is that of classifying and categorizing confonnations to find repre sentative family structures. Simulated annealing is a general technique that can be ap plied to many problems to find a minimumenergy con formation. In simulated annealing, a molecular system is heated to high temperatures, allowed to vary its confor mation, and then cooled slowly to produce a low energ3 structure. As the temperature is lowered, the system is confined to smaller regions of conformational space and the probability of going uphill over an energy barrier is reduced. When the ,system has cooled sufficiently, the system is trapped in a local minimum. If high enough temperatures are used and the cooling process is done properly, a global minimum should be reached. Simu lated annealing can be applied in both Monte Carlo and molecular dwmmics simulations. Some pitfalls of s i n s lated annealing have been pointed out in a paper by Wil son and Cui [6"] in applications to amino acids, pcptides mad polH)eptides, as well as by Barakat and l)can [-~,8i m matching C a structures of Esd~ericbia coli dihydrofolatc rcductasc (I)IIFR) and Lctcl~bacilh¢,s easel I)tlFR. Fronl both of these papers, it is clear thai the cooling schedule. as well as the equilibration time, are crucial to obtaining a g o o d representation ~)f the t~ohzmann distribution ot conformations. For peptides, w h i c h are vei3 lh'xilflc, ct)nf()rmationa[ constraints must be introduced t() limit conlormational
space. One way of doing this is to substitute individual amino acids, fi)r example, replacing a polar amino acid by a non-polar amino acid. or by introducing a l ) w p e amim) acid. If a change in receptoi binding or in acii\ ity is observed, then it must be determined whether this is due to a change in the conformation of the ligand, a perturbation of the receptor interaction, or both. Specifi, local constraints can be introduced in an attempt to bias a l)eptide towards a particular conl()rmation, or to explore' hgand-receptor interactions. These types of substitutions might R)ster or disrupt s e c o n d a w structure (i.e. an a-he lix or [3-sheet) in the peptide ligand, or be inwJved in confming a particular side chain. Conformational llexi bility may be decreased bv introducing covalent cross bridges, such as disulfide bridges [9], the linking of side chains [10"] or tying a side chain back to the peptidc backbone to form a macrocycle 111",12]. A review ()t these sorts of modifications can be found in an article bv Hruby [13]. The latter technique is particularly powertkd because several locally constrained amino acids, particularly when coupled with D-amino acid substitutions, can greatly restrict the confommfional freedom of the peptide and lead to the identification o f models for the bioactive conformation. These types of constraints have been suc cessfully applied to opiate peptides, not only to help de
tennine bioactive conformations but also to identify compounds that are highly selective for the Ix and 8 opiate receptors ]14"-16"]. When one of these conformational constraints is incorporated and the ligand maintains high potency, some of the important sites of binding to the receptor may b e c o m e evident. A recently introduced technique for mapping the receptor is known as comparative molecular field analysis (CoMFA) [17]. In this procedure, a molecular forcefiekt calculation is performed to evaluate the interac tion e n e r ~ ~ of a probe atom that is placed along a reg ular grid around the molecule, using a program such as GRID I18]. The p r o b e can be of various types, the usual choices being a metlwl probe to explore steric requirements or a hydrogen ion to explore electrostatics, but other choices can be used. The energy values obtained for each grid point are then c o m b i n e d with the biological poten( T and run through a partial least squares statistical analysis to determine three di mensional quantitative contributions of these energy valties to the potency. The problem of how to super mlpose ligand molecules can also be addressed with this procedure by positioning the molecules so that their en ergy fields are optmmlly aligned, rather than just max imizing the overlap of their chemical structures. This method has been applied to the mapping of the benzo diazepinc receptol inverse agonist-binding site, where the CoMFA results correlated well with results from other Bpcs of studies [19]. Another potentially interesting approach t(~ receptor mapping is that of RI£MOq~I)ISC [20J. In this method, c~ac'h aural of the various ligands is a~ssignc~l three physicochemical properties: partition coefficient, molar refractivity and charge density. A stnmgly bound ligand is taken as the reference model and other ligands are super imposed on it by matching physicochemical properties. Next, the active site is mapped by assigning points of coincidence and non-coincidence to the various ligands. These points are then used to assign the relative impor tance of the physicochemical properties at various sites of the receptor binding pocket. This procedure was ap plied to a range of ligands binding at the benzodiazepine receptor binding site and a prediction of the structures ()f five c,,)mpounds not in thc original training set wa,~ made. Although this method has promise, it is limited by the choice of the initial reterence molecule. The second objective is to identiPy ligands with which to test the receptor model, as welt as the discovery of potential novel compounds. These m w be identified by three dimensional substructure searching programs, such as ALADDIN [21] or CAVEAT [22], that can find c o m p o u n d s whose three-dimensional structures meet specific geo metric and steric criteria. These programs incorporate properties calculated from a reference molecule, which may be the bioactive conformation, such as interatomic distances, torsion angles, distance b e ~ ' e e n planes, forbidden regions and measured physical properties of molecules, such as partition coefficient and pK a. In a re cent stud},, Martin and co workers [21] used this technique in relation to a map of the D2 dopamine receptor
Predicting receptor-ligand interactions Burr, Hutchins, Greer 215 site. Among the search criteria used were the presence of a nitrogen atom, an electronegative atom bonded to a hydrogen and an aromatic carbon, as well as several geometrical constraints. Also included were those regions of the D2 dopamine receptor that allowed substituents and those regions that were forbidden. This led to the successful identification of all the active D2 compounds in their database as well as rejection of those that violated the sterically forbidden regions.
Strategies used when the receptor structure is known When the three-dimensional structure of a receptor molecule is known, it should be possible to determine not only the bioactive conformation of the ligand but also the detailed interactions between the ligand and protein, thereby gaining greater understanding of ligand-protein molecular recognition. This understanding should include changes in the conformations of both the ligand and the receptor upon complex formation. A variety of methods is now available with which u) deter mine the structure of receptor molecules and their corn plexes with the corresponding llgands. High-resolution X-ray crystallography can show which regions of the lig and are fitting into which pockets of the receptor and where hydrogen bonds and hydrophobic interactions occur. Similarly, two- and three-dimensional NMR methods can now produce high-resolution solution structures for proteins, protein-llgand complexes and nucleic acids [23]. It is valuable knowing the experimental structures of several different ligands bound to the same recep tor. In the case of proteins for which no experimental structure is available, comparative or homology-modeling methods may permit the construction of a tentative model structure of the receptor-llgand complex [24-]. Knowing the three-dimensional structure of a receptor, one can combine computer graphics and computational chemistry to design novel llgands. The best results are obtained when the design, computation, synthesis, biological testing and structure-determination methods are performed in a cyclic, iterative manner. A striking example of this procedure is its use in the design of new, more potent inhibitors of carbonic anhydrase for the treatment of glaucoma [25,26]. One way in which the nature of the intermolecular in teractions can be explored is by a different use of the GRID program mentioned above [18]. In this program, various probe atoms are placed at points on a regularly spaced grid and the binding enthalpy of the probe with the atoms of the receptor are calculated. Energy differences can be used to determine which type of probe has a more favorable interaction at particular locations in the ligand-binding site of the receptor molecule. The results of these calculations can be displayed as isoenergy contour maps superimposed on the three-dimensional structure of the receptor using a computer-graphics screen. The contours indicate the positions at which an atom of
the particular probe type may be favorably placed. This analysis can help in placing the ligands in the active site. If the GRID program is m n when the ligand molecule is present at the active site, additional sites of favorable interaction can be identified, thereby assisting the design of new analogues. GRID can also be used to locate the most favorable positions for water molecules in a crystal structure of an enzyme active site [27,28]. In an investigation of the active sites of the dimeric protein aspartate aminotransferase, GRID was used to predict favorable binding subsites for the functional groups of the aspartate ligands [29]. In the first subunit, the GRID results predicted favorable binding sites for the 0t- and 13-carboxylate groups of the aspartare ligand and also for the aspartate amino group. These predicted binding sites corresponded to the positions of the functional groups of the docked ligands. GRID results for the other subunit indicated that it would be unlikely for a ligand to bind in this active site in such a way that would allow transamination to occur. The binding of a ligand to its receptor is an energycontrolled process. Knowledge of the three-dimensional structure of the receptor-ligand complex should permit prediction of the intermolecular interactions and, hence, calculation of the binding energy, allowing us to quantitatively evaluate designed and proposed ligand structures. A technique that has been used to predict intermolecular interactions in this way is that of free-energy perturbation, which is reviewed by McCammon in this issue (pp 196-200). Whereas the van der Waals forces are easily calculated, the electrostatic and entropic factors in~ volved in binding interactions have proven to be more difficult. A number of methods have been used to calculate these terms. These have been successful for some molecules and have been problematic for others [30"]. Using a technique based on solvent-accessible surface areas, Novotny and co-workers [31] have calculated the Gibbs free energy (AG) of an antigen-antibody complex. The calculated and experimentally determined AG values agreed, suggesting interestingly, that only a small number of amino acids contribute to the binding energies of this complex. Thermodynamic studies of inhibitors of renin [32"] and crystallographic studies of anti-cancer agents binding to DNA [33"], have suggested that free energy is not necessarily the sum of contributions from independent subsite interactions with the receptor, but may also depend upon subtle effects associated with solvation and entropy. The program DOCK has been used to search databases of known structures in order to identify compounds that may bind to the active site of an enzyme or receptor where the structure of the binding site is known [34]. In this way, haloperidol was identified as a potential ligand for the active site of the protease of human immunodeficiency vires 1 [35"]. Upon testing, haloperidol was indeed found to be an inhibitor of the protease, but only a weak one. This 'lead' structure can now be modified to provide more potent, less toxic analogues. The weak activity of haloperidol may b e due to the fact that the native
216
Theory and simulation structure of the enzyme was used in the search process rather than the structure of the with HWq protease with a bound inhibitor: crystal structures of peptide ligands in the active site of the HIV-1 protease have shown that the enzyme undergoes a significant structural change upon ligand binding [36"]. This illustrates the pitfall of using the native structure of a protein without a bound ligand to guide the search for new molecules. The crystal structures of HW-1 protease, both in its n a tive form [37,38"] and complexed with an inhibitor [36] have shown that the protease functions as a C2 symmetric homodimer, confirming the previous speculations based upon comparative-modeling studies [39]. The approximate C2 symmetry of the dimer has suggested the design of novel sTmmetric HIV protease inhibitors [40",41"] that are less peptide-like than inhibitors based on clas sical transition-state analogues, and so may have a higher specificity for retroviral proteinases than for the related mammalian aspartic proteinases, whose substrate-binding sites are less symmetrical. The inhibitor was designed as follows: a hexapeptide inhibitor was placed in the active site. Knowing that the catalytically active aspartate residues arc close to the C2 axis of the enzyme, the carbonyl carbon undergoing cleavage was positioned on or near the symmetD' axis. One half of the inhibitor was ar bitrarily deleted. A C2-symnlet W operation was then per formed on the remainder of the inhibitor to generate the sTrnmetrical inhibitor. These molecules inhibit HW pro tease at nanomolar concentrations but do not inhibit hu man reran at 10 I.tM. When the crystal structure of a corn plex of the novel inhibitor for HW 1 protease was deter mined, the inhibitor was indeed found to foml symmet ncal interactions with HD" 1 protease [40.,,41.]. C(mlparativc ()r homology modeling is used when the crystal or NMR structure of the target protein is not known, but structures of homologous enzymes are known [24]. One such enzyme that has been exam ined extensively using this approach is renin [42,43]. A number of groups have published renin models based on the kalown structures of homologous aspartic pro teinases. The crystal structure of native recombinant hu man renin at 2.8A resolutkm was recently published [44], but the atomic coordinates have yet to be disclosed. This structure corroborates the general features of mtmy of the renin models; however, neither the published repor! n()r the resolution and refinement of the crystal structure were sufficient to be certain of the details of the con formation. A renin model has been used by Iizuka et aZ [45] to design renin inhibitors; the design of an orally active human renin in.hibitor was based on a transition state analogue of human angiotensinogen. In the past, the experimental determination of the three dimensional structures of proteins has largely been limited to soluble proteins. The structures of membrane bound proteins have resisted analysis, either because they could not be crystallized or because they are not soluble in those solvents that permit NMR analysis. Unfortunately, a large number of the receptor molecules of most interest for drag design are membrane bound; these include the adrenergic, dopaminergic, muscarinic
and serotoninergic receptors, as well as many other hormone and mediator receptors. Consequently, until recently, the structural contribution to the design of new drugs for these receptors has been limited to the methods presented in the first section of this review. However, the recent publication by Henderson e t al. [46,-] of a medium-resolution three-dimensional structure for bacteriorhodopsin based upon electron-diffraction studies of this protein has the potential to dramatically change this situation. The structure shows that bacteriorhodopsin has seven transmembrane helices. The above listed Gprotein-linked receptors are homologous to bacterio'rhodopsin and are therefore themselves likely to be seven-helix membrane proteins. The cloning of many of these receptor genes has provided the amino acid se quences for these receptors; therefore, the method of comparative modeling may now at last be applied to these receptors. For each receptor, the particular sequence can be built onto the seven-helix structure of bacteriorhodopsin. The respective ligand is then placed in its binding site which, like retinal in the case of bacteriorhodopsin, lies in the center of the molecule between the helices. The result ing ligand-binding site should be consistent with the receptor-binding models that have been developed over the years for the binding of the ligands to the particular receptor. To test the models and the importance of predicted interactions further, carefully designed site-spe cific mutagenesis [47"] and chimeric experiments [48.] have been, and will continue to be, used to produce mutant receptors with predicted modified ligand-bind ing properties. The resulting model receptor ligand complex structures provide, for the first time, new information about the detailed interactions of the various ligand substituents with particular groups and pockets on the receptor proteins. The knowledge of these interactions is currently being used to improve our understanding of the ligand-receptor interactions as well as to design novel ligands for these receptors.
Conclusion Within the last several years, advances in experimental and theoretical methods have placed us in a position to better understand how ligands bind to their receptors. Structural information provided by both X-ray crystallography and NMR, in combination with specific information that can be obtained by site-directed mutagenesis experiments, will help to elucidate detailed information about molecular recognition and intermolecular interactions. However, the main obstacle to accurate prediction of ligand-receptor interactions is the ability to accurately calculate the energy of ligand-protein interaction for most complexed systems. Accurate determination of free energy will only occur when we can obtain detailed information, at the molecular level, about the nature of the forces involved in molecular associalion. This is probably best approached by an iterative scheme that involves small changes in the ligand or the
Predicting receptor--ligand interactions Burt, Hutchins, Greet 217 receptor, structural determination of the complex, modeling, prediction of new ligand structures, testing of the hypothesis by synthesis and further structural detremination. From the knowledge gained by these types of procedures, theoretical techniques can be improved and applied to predict ligand-receptor interactions more accurately and, hopefully, design novel ligands in a timely and cost-effective manner.
References and recommended reading Papers of special interest, published within the annual period of review, have been highlighted as: • of interest •• of outstanding interest 1.
McCAMMON JA, HARVEYSC: Dynamics of Proteins and Nucleic Acids. Cambridge: Cambridge University Press, 1987.
2.
METROPOLISN, ROSENBLUTHAW, ROSENBLUTHMN, TELLERAll, TELLER E: Equation of State Calculations by Fast Computing Machines. J Chem Phys 1953, 21:1087-1092.
3.
CR1PPENGM, HAVELTF: Distance Geometry and Molecular Conformation. New York: Research Studies Press, 1988.
4.
KIRKPATRICK S, GELATrl CDJ, VECCHIMP: Optimization by Simulated Annealing. Science 1983, 220:671480.
5.
SZABO A, OSTLUND N: Modern Quantum Chemistry. New York: MacMillan, 1982.
6. WILSONSR, Col W: Applications of Simulated Annealing to • Peptides. Biopolymers 1990, 29:225--235. Simulated annealing is used to search for the global minimum of small peptides and found to be more efficient than Metropolis Monte Carlo. 7.
BARAKATMT, DEAN PM: Molecular Structure Matching by Simulated Annealing. I. A Comparison Between Different Cooling Schedules. J Comput Aided Mol Des 1990, 4:295-316.
8.
BARAKATMT, DEAN PM: Molecular Structure Matching by Simulated Annealing. II. An Exploration of the Evolution of Configuration Landscape Problems. J Comput Aided Mol Des 1990, 4:317-330.
9.
HRUBYVJ, KAO L-F, PErirri BM, KARPLUSM: The Conformational Properties of the Delta Opioid Peptide [D-Pen 2, D-PenS]-Enkephalin in Aqueous Solution Determined by NMR and Energy Minimization Calculations. J Am Chem Soc 1988, 110:3351-3359.
10. •
RODRIGUEZM, LIGNONM-F, GALASM C, AMBLARDM, MARTmaEZJ: Cyclic Cholecystokinin Analogues that are Highly selective for Rat and Guinea Pig Central Cholecystokinin Receptors. Mol Pharmacol 1990, 38:331-341. Cyclization of side chains of residues 28 and 31 in cholecystoldnin produces compounds that are highly selective for central cholecystokinin receptors.
GARVEYDS, MAY PD, NADZANAM: 3,4-Disubstituted 7-Lactam Rings as ConformationaUy Constrained Mimics of Peptide Derivatives Containing Aspartic Acid or Norleucine. J Org G~em 1990, 55:936-940. An efficient method for the synthesis of dipeptide isosteres conformationally constrained by 7-1actam that can mimic aspartic acid or norleucine. 11.
•
12.
ZYIX)WSKYTM, DELLARIAJF, NELLANSHN: Ellicient and Versatile Synthesis of Dipeptide Isosteres Containing y- or 8-lactams. J Org G~em 1988, 53:5607-5616.
13.
HRUBYVJ: Designing Molecules: Specific Peptides for Specific Receptors. El~'lepsia 1989, 30:$42-$50.
14. •
MIERKE DF, SAID-NEJAD O, SCHILLER PW, GOODMAN M: Enkephalin Analogues Containing [3-Naphthyialanine at the Fourth Position. Biopolymers 1990, 29:179--196. Conformationatly constrained enkephalin analogues were studied by molecular dynamics and NM1L 15.
MOSBERG HI, SOBCZYK-KOJIRO K, SUBRAMAHIAN P, CRIPPEN GM, RAMAI/NGAM K, WOODWARD RW: Combined Use of Stereospecific Deuteration, NMR, Distance Geometry, and Energy Minimization for the Conformational Analysis of the Highly 8 0 p i o i d Receptor Selective Peptide [D-Pen 2, D-PenS]-Enkephalin. J Am Chem Soc 1990, 112:822-829. Synthesis and stereospecificaUy deuterated amino acids and their incorporation in a cyclic-enkephalin analogue allow the assignment of all proton resonances, which are then used to model the solution confor mation. •
16. .
WILKESBC, SCHILLER PW: Conformation-Activity Relationships of Cyclic Dermorphin Analogues. Biopolymers 1990, 29:89-95. Conformational analysis of cyclic dermorphin analogues showed a limited number of low-energy conformational families, suggesting a structural requirement for ~t-opioid-receptor selectivity for dermorphin analogues. 17.
CRAMERRD, PATTERSON DE, BUNCE JD: Comparative Molecular Field Analysis (CoMFA). I. Effect of Shape on Binding of Steroids to Carrier Proteins. J Am Cbem Soc 1988, 110:5959-5967.
18.
GOODFORDPJ: A Computational Procedure for Determining Energetically Favourable Binding Sites on Biologically Important Molecules. J Med Cbem 1985, 28:849--857.
19. .
ALLENMS, TAN Y-C, TRUDELL ML, NARAYANANK, SCHINDLER LR, MARTINMJ, SCHULTZ C, HAGEN TJ, KOEHLERKF, CODDING PW, SKOLNICKP, COOK JM: Synthetic and Computer-Assisted Analyses of the Pharmacophore for the Benzodiazepine Receptor Inverse Agonist Site. J Med Chem 1990, 33:2343-2357. A pharmacophore model of the benzodiazepine receptor inverse agonist site is developed using drug-design techniques. 20.
GHOSEAK, CRIPPEN GM: Modeling of the Benzodiazepine Receptor Binding Site by the General Three-Dimensional Structure-Directed Quantitative Structure-Activity Relationship Method REMOTEDISC. Mol Pharmacol 1990, 37:725-734.
21.
VAN DRIE JH, WEININGER D, MARTINYC: ALADDIN: All Integrated Tool for Computer-Assisted Molecular D e s i g n and Pharmacophore Recognition from Geometric, Steric, and Substructure Searching of Three-Dimensional Molecular Structures. J Comput Aided Mol Des 1989, 3:225-251.
22.
BARTLETtPA, SHEA GT, TEI.FER SJ, WATERMANS: CAVEAT: A Program to Facilitate the Strncture-Derived Design of Biologically Active Molecules. Spec Publ R Soc Chem 1989, 78:182-196.
23.
NMR Methods for Elucidating Macromolecule-Ligand Interactions: an Approach to Drug Design. Fourth Biochemical Pharmacology SympoMum. Biochem Pharmacol 1990, 40:1-175.
24. •
GREERJ: Comparative Modeling Methods: Application to the Family of the Mammalian Serine Proteases. Proteins 1990, 7:317-334. Comparative modeling strategies are presented using serine proteases and criteria developed for assessing the reliability of the modeled structures. 25.
BALDWINJJ, PONTICELLO GS, ANDERSON PS, CHRISTY ME, MURCKOMA, RANDALLWC, SCHWAMH, SUGRUEi F , SPRINGERJP, GAUTHERON P, GROVE J, MALLORGA P, VIADER M-P, MCKEEVER BM, NAVIAMA: Thienothiopyran-2-sulfonamides: Novel Topically Active Carbonic Anhydrase Inhibitors for the Treatm e n t of Glaucoma. J Med Chem 1989, 32:2510--2513.
26.
SUGRUEi F , MAILORGAP, SCHWAMH, BALOWINJJ, PONTICELLO GS: Preclinical Studies o n L-671,152, a Topically Effective
218
Theory and simulation Ocular Hypotensive Carbonic Anhydrase Inhibitor. Br J Pharmacol 1989, 98 (suppl):820P. 27.
BOOBBYERDNA, GOODFORD PJ, MCWHINNIE PM, WADE RC: N e w Hydrogen-Bond Potentials for Use in Determining Energetically Favorable Binding Sites on Molecules of Known Structure. J Med Chem 1989, 32:1083-1094.
28.
REYNOLDSCA, WADE RC, GOODFORD PJ: Identifying Targets for Bioreductive Agents: Using GRID to Predict Selective Binding Regions of Proteins. J Mol Graphics 1989, 7:103-108.
KENT SBH: Conserved Folding in Retroviral Proteases: Crystal Structure of a Synthetic HIV-1 Protease. Science 1989, 245:61(>4521. The crystal structure of native synthesized HIV-1 protease at 2.8A resolution is presented. This is the first reported structure of a chemically synthesized protein. 39.
29.
NERO TL, WONG MG, OLIVER SW, ISKANDER MN, ANDREWS PR: Aspartate Aminotransferase: Investigation of the Active Sites. J Mol Graphics 1990, 8:111-115.
KOLLMANPA, MERZKM JR: C o m p u t e r Modeling of the Interac• tions of Complex Molecules. Ace Chem Res 1990, 23:246-252. A review article on computer modeling of intermolecular interactions, focusing on the calculation and prediction of the free energy of protein-ligand complexes. 30.
31.
NOVOTNYJ, BRUCCOLERIRE, SAUL FA: On the Attribution of Binding Energy in Antigen-Antibody Complexes McPC 603, D1.3, and HyHEL-5. Biochemistry 1989, 28:47354749.
32.
EPPS DE, CHENEY J, SCHOSTAREZ 11, SAWYER TK, PRAIPaE M, KRUEGERw e , MANDELF: T h e r m o d y n a m i c s of the Interaction of Inhibitors with the Binding Site of Recombinant t i u m a n Renin. J Med Chem 1990, 33:2080-2086. Independent substrate m~xtels are found to deviate from strict additivity and, even though inhibitor binding to renin is primarily hydrophobic, solution conformational differences between inhibitors are very impor rant. •
FREDEmCKCA, WILLIAMSLD, UGHETTO G, VAN DER MARELGA, VAN BOOM Jtt, RiCH A, WANG AHJ: Structural Comparison of Anticancer Drug-DNA Complexes: Adriamycin and Daunomycin. Biochemistry 1990, 29:2538--2549. Sequence changes close to the intercalation sites influence the bind hag of daunomycin to DNA. Despite the similar conformations of the daunomycin and adriamycin complexes, the corresponding solvation effects are different, causing a surprising effect on the conformation of the bound spermine.
40. *e
ERICKSON J, NEIDHART DJ, VAN DRIE J, KEMPF DJ, WANG XC, NORBECK DW, PIA'ITNER JJ, RITFENHOUSEJW, TURON M, WIDEBURG N, KOHLBRENNERWE, SIMMER R, HELFRICH R, PAUL DA, KN1GGE M: Design, Activity and 2.8 Angstrom Crystal. Structure of a C2 Symmetric Inhibitor Complexed to HIV-1 Protease. Science 1990, 249:527-533. The authors describe the design and synthesis of potent H1V-1 protease inhibitors, based on the C2 ,symmetry, of the protease dimer. The crystal structure of the complex presented confirms the design rationale. 41. •
KEMPFDJ, NORBECKDW, CODACOV1L, WANG XC, KOHLBRENNER WE, WIDEBURG ,Nit, PAUL DA, KNIGGE MF, VASAVANONDA S, CRAIG-KENNARD A, SALDIVAR A, ROSENBROOK W, CLEMENT JJ, PLATFNER JJ, ERICKSONJ: Structure-based, C 2 Symmetric Inhibitors of H1V Protease. J Med Chem 1990, 33:2687 2689. The C2 .symmetry of HIV-1 protease is used to design C2 sTlnmetric inhibitors that are highly potent and selective. ~2.
Bous G, GREERJ: Role of Computer-Aided Molecular Modeling in the Design of Novel lnhibitors of Renin. In Compuleraided Drug Design. Methods a n d Applications edited by Pe m n TJ, Propst CL. New York: Marcel Dekker Inc., 1989, pp 297-326.
t3.
III'TCHINSCW, GREER J: Comparative Mcxleling of Proteins in the Design of Novel Renin lnhibitors. Crit Rev 13iochem 1991, 26: in press.
44.
SIELECK~AR, HAYAKAWAK, FUJINAGA M, MURPHY ME, FRASER M, MUIR AK, CARILLI CT, LEWlCKIJA, BAXTERJD, JAMES MN: Structure of Recombinant Human Renin, a Target for Cardiovascular-Active Drugs, at 2.5A resolution. Science 1989, 243:1346-1351.
45.
I~UKA K, KAMIJO T, I1ARADA H, AKAHANE K, KUBOTA T, UMEYAMAH, ISHIDA T, KISO Y: Orally Potent H u m a n Renin Inhibitors Derived from Angiotensinogen Transition State: Design, Synthesis, and Mode of Interaction. J Med Chem 1990, 33:2707-2714.
33. •
34.
DESJARLAlSRL, SHERIDAN RP, SIEBEL GL, DIXON JS, KUNTZ ID, VENKATARAGHAVAN R: Using Shape Complementarity as an Initial Screen in Designing Ligands for a Receptor Binding Site of K n o w n Three-Dimensional Structure. J Med Chem 1988, 31:722-729.
35. •
DESJARLMSRL, SEIBEL GL, KUNTZ ID, FIIRTH PS, ALVAREZJC, ORTIZ DE MONTELtANO PR, DECAMP DL, BABE LM, CRAIK CS: Structure-based Design of Nonpeptide Inhibitors Specific for the H u m a n lmmunodeficiency Virus I Protease. Proc Natl Acad Sci USA 1990, 87:6644-6648. The program DOCK is used on the crystal structure of native HIV 1 protease to search the Cambridge database of structures for novel lead c o m p o u n d inhibitors. 36. •
MILLER M, SCHNEIDER J, SATHYANARAYANABK, TOTH MV MARSHALLGR, CLAWSON L, SELK L, KENT SBH, WLODAWERA~ Structure of Complex of Synthetic HIV-1 Protease with a Substrate-based Inhibitor at 2.3A Resolution. Science 1989, 246:1149-1152. Crystallographic structure of a peptide inhibitor bound to HIV-1 protease at 2.3 A resolution is presented. 37.
NA'aAMA, FrrZGERALDPMD, MCKEEVERBM, LEU C-T, HEIMBACH JC, HERBERWK, SIGALIS, DARKEPL: Three Dimensional Structure of Aspartyl Protease for H u m a n Immunodeficiency Virus HIV-1. Nature 1989, 337:6154520.
38. •
WLODAWERA, MILLER M, JASKOKSKI M, SATHYANARAYANABK, BALDWINE, WEBER IT, SELK LM, CLAWSON L, SCHNEIDER J,
PEARLLH, TAYLORWR: A Structural Model for the Retroviral Proteases. Nature 1987, 329:351-354.
46. ••
HENDERSONR, BALDWINJM, CESKA TA, ZEMLIN F, BECKMANE, DO"~q',IINGKEt: Model for the Structure of Bacteriorhodopsin Based on High-Resolution Electron Cryo-Microscopy. J Mol Biol 1990, 213:899-929. A seminal paper reporting the three-dimemsional structure of bacteri orhodopsin derived by electron microscopy. The structure has broad implications for the structure of the G-protein receptors. 47. STRADERCD, SIGAI. IS, DIXON RAF: Structural Basis of ~.Adren• ergic Receptor Function. FASEB J 1989, 3:1825-1832. A summary of the mutagenesis data for the [3-adrenergic receptors, and an analysis of the ligand-binding and G protein-interaction regions of the protein. 48. •
DIXON RAF, HILL WS, CANDELORE MR, RANDS E, DIEHL RE, MAP~SHALL MS, S[GAL IS, STRADERCD: Genetic Analysis of t h e Mole.-ular Basis for [~-Adrenergic Receptor Subtype Specificity. Proteins 1989, 6:267 274. A report of the construction and ligand-binding properties of ~1 ~2 adrenergic chimeric receptors.
SK Burt, CW Hutchins andJ Greer, Computer Assisted Molecular Design Group, Abbott laboratories, Abbott Park, Illinois 60064, USA.