combinatorial chemistry, part a

Preface Combinatorial chemistry is a field that did not exist five years ago but is so vibrant today, especially in medicinal chemistry, that almost every major pharmaceutical company has a group working in this area and many start-up companies have been formed with combinatorial chemistry as their raison d'etre. Like many other fast-breaking developments, this field had its main origins in work done in academic research laboratories, and many of the techniques were developed to solve specific problems in basic re- search. The common feature of all combinatorial approaches is the genera- tion of a complex mixture of molecules coupled to screens or selections which can identify out of that mixture a single molecule with desired proper- ties, e.g., as the ligand or inhibitor of an enzyme or as a macromolecule with novel or enhanced properties. At the start most combinatorial libraries were of biological molecules, mostly peptides or nucleic acids, but because these molecules only rarely exhibit good pharmacological properties, in- creasingly the libraries of interest to medicinal chemists are of small mole- cules with a range of pharmacologically attractive properties. Because of the rapid progress in this field, a follow-up to this volume would not be possible in a single volume of Methods in Enzymology, but at the time of the organization of this volume one could identify the main themes that constitute this field and present the key technologies in a single volume. One of the earliest techniques for the generation and screening of a diverse library of peptides was the display of random sequences in the coat protein of single-strand DNA phages. The diversity of these libraries is limited to the titers of phage one can obtain, typically >10 H particles/ml. The phage coat protein can also accommodate entire proteins such as DNA or RNA binding proteins that have been partially randomized so that proteins with novel binding properties can be selected. The techniques for the generation and screening of small molecule libraries originated with peptides, and this volume contains a number of early and still very useful techniques in this area. These libraries can be screened by a number of very clever methods, including deconvolution of different pools and the elegant and potentially very powerful encoded li- braries. The exploration of sequence space is most striking in the case of nucleic acid libraries. Here, due to the power of the polymerase chain reaction, libraries with diversities as high as 1016 different molecules have been explored. This is an extremely exciting area in which we are continually xiii xiv PREFACE being surprised by the diversity of form and function possible within the confines of the polynucleotide backbone. One can select RNA molecules which can bind specifically to virtually any protein or small molecule and also which can catalyze a diverse set of chemical reactions. And not only can one explore sequence space in large libraries but as Tsang and Joyce show in article [23] in this volume, one can expand that sequence space by judicious mutagenesis during amplification between rounds of selection as must have occurred during biological evolution. It is clear, however, that much of the creative energy these days in this field is being directed at inventing sophisticated methods for the generation and screening of diverse kinds of small molecules, such as the pioneering work by Ellman and colleagues on benzodiazepine libraries described in this volume. Interestingly, the need to generate large diversity in these libraries is not the key factor, and, instead, the ingenuity in the selection of scaffolds and functional groups in generating the libraries will probably be most important in generating interesting new pharmacological leads. In this regard, one can expect interactions between computational chemistry and combinatorial chemistry in which libraries are generated and screened by computer methods in a search to find the most appropriate library for a particular target. It is perhaps in that area that we should think now of organizing a new volume in order to have something interesting for the new millenium. JOHN N. ABELSON Contributors to Volume 267 Article numbers are in parentheses following the names of contributors, Affiliations listed are current. STEVEN C. BANVILLE (25), Chiron Corpora- tion, Emeryville, California 94608 JOEL G. BELASCO (9), Department of Microbi- ology and Molecular Genetics, Harvard Medical School, Boston, Massachusetts 02115 SYLV1E E. BLONDELLE (13), Torrey Pines In- stitute for Molecular Studies, San Diego, California 92121 BARRY A. BUNIN (26), Department of Chem- istry, University of California, Berkeley, Berkeley, California 94720 CHARLIE L. CHEN (12), Hoechst Marion Roussel, Tucson, Arizona 85737 JERZEY CIESIOLKA (19), Department of Mo- lecular, Cellular, and Developmental Biol- ogy, University of Colorado, Boulder, Colo- rado 80309 RICHARD C. CONRAD (20), Department of Chemistry, Indiana University, Blooming- ton, Indiana 47405 RICCARDO CORTESE (6, 7), IRBM P. Angel- etti, 00040 Pomezia, Rome, Italy CHARLES CRAIK (3), Departments of Pharma- ceutical Chemistry, Pharmacology, and Biochemistry and Biophysics, University of California, San Francisco, San Francisco, California 94143 MILLARD G. CULL (10), Enzyco, Inc., Denver, Colorado 80206 JEFFREY P. DAVIS (18), NeXstar Pharmaceuti- cals, Inc., Boulder, Colorado 80301 JENNIFER M. DIAS (11), Affymax Research Institute, PaiD Alto, California 94304 BARBARA DORNER (13), Torrey Pines Insti- tute for Molecular Studies, San Diego, Cali- fornia 92121 WILLIAM J. DOWER (11), Affymax Research Institute, Palo Alto, California 94304 ANDREW D. ELLINGTON (20), Department of Chemistry, Indiana University, Blooming- ton, Indiana 47405 JONATHAN A. ELLMAN (26), Department of Chemistry, University of California, Berke- ley, Berkeley, California 94720 FRANCO FELICI (6, 7), IRBM P. Angeletti, 00040 Pomezia, Rome, Italy GIANINE M. FIGLIOZZI (25), Chiton Corpora- tion, EmeryviUe, California 94608 TIM FITZWATER (17), NeXstar Pharmaceuti- cals, Inc., Boulder, Colorado 80301 GIOVANNI GALFR~ (6, 7), IRBM P. Angeletti, 00040 Pomezia, Rome, Italy MARK GALLOP (16), Affymax Research Insti- tute, Palo Alto, California 94304 CHRISTIAN M. GATES (10), Affymax Research Institute, Palo Alto, California 94304 LORI GIVER (20), Division of Chemistry and Chemical Engineering, Californm Institute of Technology, Pasadena, California 91125 RICHARD GOLDSMITH (25), Chiron Corpora- tion, Emveryville, California 94608 HARVEY A. GREISMAN (8), Department of Bi- ology, Massachusetts Institute of Technol- ogy, Cambridge, Massachusetts 02139 HYUNSOO HAN (14), Departments of Molecu- lar Biology and Chemistry, The Scripps Re- search Institute, La Jolla, California 92037 JACQUELINE L. HARRISON (5), United States Biochemicals Pharma Ltd. (Europe), War- ford WD1 8YH, United Kingdom CHRISTOPHER P. HOLMES (16), Affymax Re- search Institute, Palo Alto, California 94304 RICHARD A. HOUGHTEN (13), Torrey Pines Institute for Molecular Studies, San Diego, California 92121 MALI ILLANGASEKARE (19), Department of" Molecular, Cellular, and Developmental Bi- ology, University of Colorado, Boulder, Colorado 80309 X CONTRIBUTORS TO VOLUME 267 KATHRYN M. IVANETICH (15), Biomolecular Resource Center, University of California, San Francisco, San Francisco, California 94143 KIM D. JANDA (14), Departments of Molecu- lar Biology and Chemistry, The Scripps Re- search Institute, La Jolla, California 92037 NEBOJ~A JANJI¢ (18), NeXstar Pharmaceuti- cals, Inc., Boulder, Colorado 80301 GERALD F. JOYCE (23), Departments of Chemistry and Molecular Biology, The Scripps Research Institute, LaJolla, Califor- nia 92037 JACK D. KEENE (21), Department of Microbi- ology, Duke University Medical Center, Durham, North Carolina 27710 ROBERT C. LADNER (2, 4), Protein Engi- neering Corporation, Cambridge, Massa- chusetts 02138 ITE A. LA1RD-OFFRINGA (9), Departments of Surgery and Biochemistry and Molecular Biology, University of Southern California Medical School, Los Angeles, California 90033 KIT S. LAM (12), Departments of Medicine, Microbiology, and Immunology, Arizona Cancer Center, University of Arizona, Col- lege of Medicine, Tucson, Arizona 85724 MICHAE LEBL (12), Hoechst Marion Roassel, Tucson, Arizona 85737 ALLESANDRA LUZZAGO (6, 7), IRBM P. An- geletti, 00040 Pomezia, Rome, Italy DEREK MACLEAN (16), A ffymax Research In- stitute, Palo Alto, California 94304 IRENE MAJERFELD (19), Department of Mo- lecular, Cellular, and Developmental Biol- ogy, University of Colorado, Boulder, Colo- rado 80309 WILLIAM MARKLAND (2, 4), Vertex Pharma- ceuticals, Inc., Cambridge, Massachusetts 02139 EDITH L. MARTIN (10), Affymax Research In- stitute, Palo Alto, California 94304 LARRY C. MATFHEAKIS (11), Affymax Re- search Institute, PaiD Alto, California 94304 PAOLO MONACI (6, 7), IRBM P. Angeletti, 00040 Pomezia, Rome, Italy SIMON C. NG (25), Chiron Corporation, Em- eryville, California 94608 ZHI-JIE NI (16), Affymax Research Institute, PaiD Alto, California 94304 TIM NICKLES (19), Department of Molecular, Cellular, and Developmental Biology, Uni- versity of Colorado, Boulder, Colorado 80309 ALFREDO NICOSIA (6, 7), IRBM P. Angeletti, 00040 Pomezia, Rome, Italy PETER E. NmLSEN (24), Department of Medi- cal Biochemistry and Genetics, Center for Biomolecular Recognition, The Panum In- stitute, DK-2200 N Copenhagen, Denmark AHUVA NISSIM (5), The Institute of Hematol- ogy, The Chaim Sheba Medical Centre, Sachler School of Medicine, Tel Hashomer 52621, Israel JOHN M. OSTRESH (13), Torrey Pines Institute for Molecular Studies, San Diego, Califor- nia 92121 CARL O. PABO (8), Department of Biology, Howard Hughes Medical Institute, Massa- chusetts Insitute of Technology, Cambridge, Massachusetts 02139 MATrHEW J. PLUNKETr (26), Department of Chemistry, University of California, Berke- ley, Berkeley, California 94720 BARRY POLISKY (17), NeXstar Pharmaceuti- cals, Inc., Boulder, Colorado 80301 EDWARD J. REBAR (8), Department of Biol- ogy, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 BRUCE L. ROBERTS (2, 4), Genzyme Corpora- tion, Framingham, Massachusetts O1701 MARGARET E. SAKS (22), Division of Biology, California Institute of Technology, Pasa- dena, California 91125 JEFFREY R. SAMPSON (22), Division of Biol- ogy, California Institute of Technology, Pasadena, California 91125 DANIEL V. SANTI (15), Department of Phar- maceutical Chemistry, University of Cali- fornia, San Francisco, San Francisco, Cali- fornia 94143 PETER J. SCHATZ (10), Affymax Research In- stitute, Palo Alto, California 94304 CONTRIBUTORS TO VOLUME 267 xi GEORGE P. SMITH (1), Division of Biological Sciences, University of Missouri, Columbia, Missouri 65211 PETER STROP (12), Hoechst Marion Roussel, Tucson, Arizona 85737 Yu TIAN (20), Department of Chemistry, Indi- ana University, Bloomington, Indiana 47405 JOYCE TSANG (23), Departments of Chemistry and Molecular Biology, The Scripps Re- search Institute, La Jolla, California 92037 CHENG-I WANG (3), Department of Pharma- ceutical Chemistry, University of California, San Francisco, San Francisco, California 94143 MARK WELCH (19), Department of Molecular, Cellular, and Developmental Biology, Uni- versity of Colorado, Boulder, Colorado 80309 SAMUEL C. WILLIAMS (5), Medical Research Council Centre for Protein Engineering, Cambridge CB2 2QH, United Kingdom GREG WINTER (5), Medical Research Council Centre for Protein Engineering, and Labo- ratory of Molecular Biology, Cambridge CB2 2QH, United Kingdom QING YANG (3), Department of Pharmaceuti- cal Chemistry, University of California, San Francisco, San Francisco, California 94143 MICHAEL YARUS (19), Department of Molec- ular, Cellular, and Developmental Biology, University of Colorado, Boulder, Colo- rado 80309 JINAN YU (1), Department of Pharmacology, School of Medicine, University of Pitts'- burgh, Pittsburgh, Pennsylvania 15261 DOMINIC A. Z1CHI (18), NeXstar Pharmaceu- ticals, Inc., Boulder, Colorado 80301 SHAWN ZXr~NEr~ (19), Department of Molecu- lar, Cellular, and Developmental Biology, University of Colorado, Boulder, Colo- rado 80309 RONALD N. ZUCKERMAN (25), Drug Design and Development, Chiton Corporation, Emeryville, California 94608 [ 1] AFFINITY MATURATION OF PHAGE-BORNE LIGANDS 3 [11 Affinity Maturation of Phage-Displayed Peptide Ligands By JINAN YU and GEORGE P. SMITH Introduction Many experiments in this volume start with large libraries of random amino acid or nucleotide sequences of a certain length from which a tiny subset is selected according to some criterion of "fitness" most often, affinity for a chosen target receptor. In most cases the library represents sequences of the same length exceedingly sparsely. Even the very best (fittest) sequence in a sparse initial library may be much inferior to the globally best sequence of the same length. If the sequences are capable of heritable mutation phage display and random RNA and DNA libraries fall into this category the problem of sparseness might be addressed by encouraging fitter sequences to "evolve" from parent sequences in the initial library. 1'2 This sort of artificial evolution is exemplified by the "greedy" strategy: Step A, from the initial library select the very best sequence; call this the "initial champion." Step B, mutagenize the initial champion randomly, producing a "clan" of closely related mutants. Step C, from that clan select the mutant with the very best fitness. Step D, repeat Steps B and C as needed until an optimal ligand is found. Each round of selection thus selects "greedily" for the very best sequence available in the current population. A drawback of the greedy strategy is that it can only explore close relatives of the initial champion a tiny parish in the vast "space" of possible sequences. Yet, for all we know, the best sequence in that neighbor- hood may be far inferior to sequences lying totally elsewhere in sequence space. Might it not then be worthwhile to explore the neighborhood of the second-best sequence in the initial library? of the third best? of every sequence with fitness above a certain threshold? In order thus to broaden the search for fitter sequences, the stringency (fitness threshold) can be reduced in the early rounds of selection, so as to include sequences some- what inferior to the initial champion: Step A', from the initial library select a mixture of sequences with diverse fitnesses (ideally, above a certain threshold). Step B', mutagenize the entire population of selected sequences 1 D. J. Kenan, D. E. Tsai, and J. D. Keene, Trends Biochem. Sci. 19, 57 (1994). 2 j. W. Szostak, Trends Biochern. Sci. 17, 89 (1992). Copyright © 1996 by Academic Press~ Inc. METHODS IN ENZYMOLOGY. VOL. 267 All rights of reproduction in any form reserved. 4 PHAGE DISPLAY LIBRARIES [ 1] to produce many clans of mutants. Step C', from those clans select a mixture of sequences with diverse fitnesses (ideally, above a slightly higher threshold than in Step A'). Step D', repeat steps B' and C' as often as desired, possibly increasing the stringency of selection with succeeding rounds. Step E', after the final round of mutagenesis, stringently select the very best sequence in the current population. Alternating nonstringent selection with mutagenesis in this way makes it possible to discover "dark horses": sequences in the initial library that are inferior to the initial champion, yet can be mutated to even higher fitness than can that champion. A dark horse will usually lie in a different neighborhood than the initial champion, since in most cases two sequences in the same small neighborhood will be able to mutate to the same local optimum. Even a well-implemented experiment may fail to reveal dark horses in any particular case (see Discussion), most obviously because there are none to reveal. Still, dark horses may appear sufficiently frequently to make this an attractive alternative to the greedy strategy. When the fitness being selected for is affinity for a target receptor molecule, the foregoing program is called "affinity maturation," the term coined by immunologists for the interspersed rounds of selective stimulation by antigen and somatic mutation of antibody genes that is thought to give rise to antibodies with increasing affinity in the course of an immune response. 3 This chapter covers affinity maturation from random peptide libraries displayed on phage. The procedures and underlying principles will be discussed in the context of a specific exemplar experiment in which ligands for a model receptor were selected from a library of random 15- mers. 4 The model receptor was S-protein, a 104-residue fragment of bovine ribonuclease prepared by partial digestion with subtilisin; the other frag- ment, S-peptide, corresponds to the N-terminal 20 amino acids. 5 Neither fragment alone is enzymatically active, but when they are mixed, S-peptide binds strongly to S-protein, restoring enzyme activity. 6 Vector, Initial Library, and Overall Plan The procedures in this article are tailored for libraries in fUSE5 7 and related vectors, which have a tetracycline (Tc) resistance determinant in 3 Eisen, H. N., in "Molecular Evolution on Rugged Landscapes: Proteins, RNA and the Immune System" (A. S. Perelson and S. A. Kauffman, eds.), p. 75. Addison-Wesley, New York, 1991. 4 T. Nishi, H. Tsurui, and H. Saya, Exp. Med. 11, 1759 (1993). s F. M. Richards and P. I. Vithayathil, I. Biol. Chem. 234, 1459 (1959). 6 H. C. Taylor, D. C. Richarson, I. S. Richardson, A. Wlodawer, A. Komoriya, and I. M. Chaiken, J. Mot Biol. 149, 313 (1981). 7 j. K. Scott and G. P. Smith, Science 249, 386 (1990). [ 1] AFFINITY MATURATION OF PHAGE-BORNE LIGANDS 5 BglI BgII CTATTCTCACTCC-GCCGACGIGGGCT(NNK) 15GGGC~CGCT~ GGGCCGAAAcTGTTGAA Forward primer ~ + Reverse primer A D G A X15 G A A G A E T V E FIG. 1. Nucleotide sequence near the beginning of the pill gene in the random 15-mer library. 4 Only the plus strand the strand that is packaged in virions and that is anticomplemen- tary to mRNA is shown. In the initial library, before selection, positions designated N had (theoretically) an equal mixture of all four nucleotides, K an equal mixture of G and T. The corresponding amino acid sequence at the N terminus of mature pill is shown in the one- letter code; X~5 stands for the random 15-mer encoded by the degenerate codons. The PCR priming sites used in construction of mutant libraries (see Mutagenesis) are underlined. Cleavage of the PCR product at the flanking BglI sites releases a degenerate 60-bp fragment that can be spliced to the Sill-cleaved fUSE5 vector. the minus-strand origin 8 (changes required for other vectors 9 are obvious and do not materially affect the discussion). Although the resulting defect in minus-strand replication reduces plaque size to near invisibility, the phage can be cloned and propagated as plasmids by infecting a Tc-sensi- tive host and growing in medium containing Tc (filamentous phage do not kill the host cell); phage are titered as transducing units (TU) by counting Tc-resistant colonies. Only cells bearing F-pili can be infected, but the pilus is not required for phage production by transfected cells. Expression of Tc resistance by newly infected or transfected cells is induced by culturing them ~30 min in a subinhibitory concentration of Tc (0.2 /zg/ml). Phage libraries, including the receptor-specific mutant libraries created in the course of affinity maturation (see Mutagenesis), are constructed by splicing foreign DNA inserts into the gene for coat protein plIl (five copies at one tip of the virus) or pVIII (thousands of copies forming the tube surrounding the DNA). The peptide encoded by the insert is displayed on the virion surface fused to the coat protein and is available to bind macromolecular target receptors for which it has affinity. The fUSE5 vector has two SfiI cloning sites near the beginning of the plII gene, 7 between which a synthetic BglI fragment with 15 degenerate codons was inserted to create the initial library for the exemplar experiment 4 (Fig. 1). Each clone has a particular sequence of 15 codons and displays the corresponding 15-residue peptide. There are 3.3 × 1019 possible 15- mers altogether, but only ~2 × 108 clones in the initial library a sparse library indeed. 8 G. P. Smith, Virology 167, 156 (1988). 9 G. P. Smith and J. K. Scott, Methods Enzymol. 217, 228. 6 PHAGE DISPLAY LIBRARIES [1] Affinity maturation begins with alternating rounds of affinity selection and mutagenesis, the stringency of selection being kept low (see Introduc- tion). The phage population resulting from these alternating rounds hopefully greatly enriched for receptor-binding clones is then subjected to additional rounds of stringent selection without mutagenesis in order to identify the highest-affinity clones, which are analyzed by sequencing and binding studies. Figure 2 outlines the sequential arrangement of selection steps (producing Eluates 1-3, 4A-4F, and 5A-5F) and mutagenesis steps (producing Mutant Libraries 1 and 2) in the exemplar experiment; also Conventional selection "~ 10 lag [ Eluate 2' ] ~ 2-step 100 ng I Eluate 3' I ] Initial librar~ [ ~ l-step selection with 10 lag receptor . 1 ] ~ mutagenesis [ Mutantlibrary 1 1 ,~ l-step selection with I lag receptor I Eluate 2 I ~ mutagenesis ~ l-step selection with I lag receptor I Eluate 3 I ng ~4¢ 2-step lO ng [ Eluate 4A[ I Eluate 4B [ [ Eluate 4C I ] Eluate 4D I LEluate 4E [ [ Eluate 4F I ,-step ~ 1-step ~ 1-step ~ 2-step ~ 2-step % 2-step I lag 100 ng 10 ng I lag 100 ng 10 ng "Eluate5A] ]Eluate5BI ~ ]Eluate5D I [Eluate5E] IEiuate5F] FIG. 2. Outline of the exemplar affinity maturation of ribonuclease S-protein ligands. Arrows labeled "l-step selection" and "2-step selection" correspond to rounds of affinity selection by the one- and two-step methods described under Affinity Selection; the amount of receptor (biotinylated S-protein) used in each round is shown. All eluates but 3' and 5A-5F were amplified (see Quantifying Yield and Amplifying Eluates under Affinity Selection) before being mutagenized or subjected to the next round of affinity selection. Arrows labeled "muta- genesis" correspond to PCR mutagenesis and mutant library construction (see Mutagenesis). Also shown is a conventional affinity selection experiment (without mutagenesis) that was carried out in parallel with affinity maturation. 1° Thus, Eluate 2' was selected directly from Eluate 1, and Eluate 3' from Eluate 2', without mutagenesis. [ l I AFFINITY MATURATION OF PHAGE-BORNE LIGANDS 7 shown is a conventional selection experiment without mutagenesis (Eluates 2' and 3') that was carried out in parallel for comparison. TM In the sections that follow, the principles and practice of affinity matura- tion will be discussed in detail, with the exemplar experiment serving throughout as an illustration. Table I gives the formulas or recipes for solutions and preparations, Table II describes standard procedures, and Table III lists Escherichia coli strains. Affinity Selection Each affinity selection step starts with a mixture of phage and seeks to select from that mixture phage whose displayed peptide binds the target receptor. These phage are specifically "captured" by immobilizing the re- ceptor on a solid surface (e.g., a plastic petri dish); unbound phage are washed away and captured phage are eluted (still in infective form), yielding a selected subset of the original phage mixture that is called an "eluate." Stringency The stringency of affinity selection is controllable in some degree by the choice of conditions, as will be detailed later. The logic of affinity maturation calls for low stringency (thus high yield) in the early rounds of selection (see Introduction). There is an additional argument even in conventional selection without mutagenesis for choosing high yield in the very first round of selection, whose input consists of all clones in the initial library. Because the library has many clones, each clone is represented by few particles (-500 TU/clone on average in the exemplar experiment); consequently, if the yield for a binding clone is not high in the first round (>0.2% in the exemplar experiment), that clone has a good chance of being lost, and of course can never be recovered. In later rounds, especially after the last round of mutagenesis, stringency can be increased in order to select for the tightest binder. There is a limit to stringency, however. The reason is that there is always a background yield of nonspecifically bound phage; if stringency is set too high, the yield of specifically captured phage will fall far below the background of nonspecifically bound phage, and all power of discrimination in favor of high affinity is lost. In practice, because the relationship between selection conditions and stringency is unknown in advance, it is advisable to explore a range of conditions in the final rounds of selection; those whose yields are close 10 D. A. Schultz, J. E. Ladbury, G. P. Smith, and R. O. Fox, unpublished (1995). [...]... [ 1] AFFINITY MATURATION OF PHAGE-BORNE L1GANDS 1l TABLE III Escherichia coli STRAINS Strain Sex Chromosomal genotype MC1061" F K91' K91Kan d Hfr Cavalli Hfr Cavalli hsdR rncrB A( araABC1eu)6779 araD139 Alac174 galU galK strA thi thi lacZ::mkh e thi K91BlueKan Hfr Cavalli lacZAM15 lacY::mkh e lacl ° thi Characteristics Uninfectableb; streptomycin resistant Infectable Infectable; kanamycin resistant Infectable;... Miletich, and G J Broze, Jr., Nature (London) 338, 518 (1989) [2] 31 SELECTION FOR PROTEASE INHIBITORS 1 2 3 4 5 6 7 8 9 I0 A A E M H S F C A F K A D 5'-qlqcclqaqlatqlcat!tcc!ttcltactqcttttclaaa]qct!qatl 3 ' - c t c tac q t a a a a a a a a c a c-5' IEaqI I I N s i l 1 * ** ** ** ** ** ** ** ii 12 13 14 15 16 17 18 19 20 D G P C K A I M K R l~aC1~aTlccGltatlaaalqctlatclatalaaalcatl c t g c c a g g c a c a. .. g a t a g tac ttt g c a I RsrII I I BspHII 21 22 23 24 25 26 27 28 29 30 F F F N I F T R Q C IttcLttclttclaaclattlttclacGlcatlcaaltacl a a g a a g a a g t t g t a a a a g tgc q c a q t c a c q I mul * 1 ** ** ** * * 31 32 33 34 35 36 37 38 39 40 41 42 E E F I X G G C E G N Q l a a a l a a A 1 t t C l a t t t a c l g g t l g g t l t g t l g a a l g g t l a a c l c I g i I l I a ctc ctt a a a t e a a... containing end-labeled primer to the phage pellet; the alkali dissolves and disassembles virions, and after neutralization with acid, the released viral DNA anneals with primer to form primed template Alternatively, when phage are available in solution because they have already been propagated and processed (Table II), portions are dispensed to wells, and an equal volume of twofold concentrated alkali/primer... a t a t e a c c a aca ctt c c a t t g q t c I EcoRI 1 I BstEII l 43 44 45 46 47 48 49 50 N R F E S L E E Iaac IcgGl ttc Igaal tct IctA Ig a g Ig a a I t t q qcc a a q ctt a g a qat ctc ctt I BstBI I I XbaI I I AqeI 51 52 53 54 I S5 56 57 58 59 60 C K K M C T R D G A tgt Ia a g Ia a q Ia t q Itac Iact !cgt Iq a c Iq a c a ttc ttc t a c a c q t q a g c a c t g c c g c g [ KasI I FIG 1 Synthetic LADI-D1... the dark horse's optimum has higher affinity than the initial champion's, that by no means guarantees that the dark horse clan will win For the dark horse starts with a selective disadvantage: its clan expands more slowly in the population than the initial champion's at first, slowing the exploration for affinity-enhancing mutations The dark horse clan thus has limited opportunity to reach a mutant... library is physically linked, via fusion to the coat protein encapsidating the bacteriophage DNA, to its own encoding display gene For this reason, the selection of binding variants and the ready determination of the predicted amino acid sequence of the variants from DNA analysis enable rapid and effective screening of a library against a number of targets Such screening can be performed in a cyclic and... dark horse was discovered in the exemplar experiment, despite the fact that mutagenesis and affinity selection both clearly worked as intended Trying to explain this result will help illuminate how affinity maturation works In the early stages of affinity maturation, a dark horse clan and the clan of the initial champion expand and mutate in a sort of race toward their respective local optima Although... invariant NH2-AIa-Asp-GIy-Ala that precedes the 15-residue random peptide in all phage clones (see Fig 1) is shown in lowercase letters The four "buried" residues of S-peptide have solvent-accessible surfaces areas of 10 ~z or less in the complex with S~rotein, whereas the other S-peptide residues have an average accessible surface area of 48 A 2 [E E Kim, R Varadarajan, H W Wyckoff, and F M Richards,... capability relative to the nondisplay phage and a binding to trypsin comparable to that of the BPTI.III display phage Phage Display Library: Design and Construction Protein variants are generated by the introduction of variegated synthetic oligonucleotide duplexes into a suitably prepared parental gene vector, in this instance LACI-DI.III The library was designed to be made in two stages: phase I and . neutralization with acid, the released viral DNA anneals with primer to form primed template. Alternatively, when phage are available in solution because they have already been propagated and. Technology, Pasadena, California 91125 DANIEL V. SANTI (15), Department of Phar- maceutical Chemistry, University of Cali- fornia, San Francisco, San Francisco, Cali- fornia 94143 PETER J. SCHATZ. QING YANG (3), Department of Pharmaceuti- cal Chemistry, University of California, San Francisco, San Francisco, California 94143 MICHAEL YARUS (19), Department of Molec- ular, Cellular, and