We describe implementation of the REPLACE strategy for targeting protein-protein interactions. REPLACE is an iterative strategy involving synthetic and computational approaches for the conversion of optimized peptidic inhibitors into drug like molecules.
REPLACE is a unique strategy developed to more effectively target protein-protein interactions (PPIs). It aims to expand available drug target space by providing improved methodology for the identification of inhibitors for such binding sites and which represent the majority of potential drug targets. The main goal of this paper is to provide a methodological overview of the use and application of the REPLACE strategy which involves computational and synthetic chemistry approaches. REPLACE is exemplified through its application to the development of non-ATP competitive cyclin dependent kinases (CDK) inhibitors as anti-tumor therapeutics. CDKs are frequently deregulated in cancer and hence are considered as important targets for drug development. Inhibition of CDK2/cyclin A in S phase has been reported to promote selective apoptosis of cancer cells in a p53 independent manner through the E2F1 pathway. Targeting the protein-protein interaction at the cyclin binding groove (CBG) is an approach which will allow the specific inhibition of cell cycle over transcriptional CDKs. The CBG is recognized by a consensus sequence derived from CDK substrates and tumor suppressor proteins termed the cyclin binding motif (CBM). The CBM has previously been optimized to an octapeptide from p21Waf (HAKRRIF) and then further truncated to a pentapeptide retaining sufficient activity (RRLIF). Peptides in general are not cell permeable, are metabolically unstable and therefore the REPLACE (REplacement with Partial Ligand Alternatives through Computational Enrichment) strategy has been applied in order to generate more drug-like inhibitors. The strategy begins with the design of Fragment ligated inhibitory peptides (FLIPs) that selectively inhibit cell cycle CDK/cyclin complexes. FLIPs were generated by iteratively replacing residues of HAKRRLIF/RRLIF with fragment like small molecules (capping groups), starting from the N-terminus (Ncaps), followed by replacement on the C-terminus. These compounds are starting points for the generation of non-ATP competitive CDK inhibitors as anti-tumor therapeutics.
In this article, a case study of applying the REPLACE (Replacement with partial ligand alternatives using computational enrichment) strategy to convert peptidic inhibitors of protein-protein interactions into more pharmaceutically relevant molecules is described1-3. While PPIs represent a rich but underexploited source of potential drug targets, existing methodologies are largely insufficient to make these widely accessible. Current strategies including fragment based design4, high-throughput screening5 and stapled peptides6 have provided advances, however these are in many cases ineffective. As a result, more progress and more efficient approaches are required. REPLACE has been fully validated in the development of kinase inhibitors that have improved drug-like properties and have potential for further development as anti-tumor therapeutics. This strategy is exemplified in the development of non-ATP inhibitors of cell cycle CDKs and involves as follows: 1) obtaining 3D structural information on the interactions of HAKRRLIF/RRLIF with the cyclin binding groove; 2) determining the important binding determinants for peptide interaction; 3) truncation of the peptide N-terminus containing one or more binding determinants; 4) computational identification of potential small molecule alternatives (partial ligand alternatives, PLAs) for the truncated portion of the peptide and which retain key interactions of the parent peptide; 5) synthesis or commercial sourcing of PLAs predicted to bind avidly with the sub site previously occupied by the deleted peptide residue(s); 6) synthesis of FLIPs through ligation of the best PLAs to the truncated peptide using solid phase synthesis; 7) testing of FLIPs in an in vitro binding or functional assay (fluorescence polarization in the CDK/cyclin context) followed by further characterization in a cell viability assay. A schematic representation of REPLACE strategy is shown in Figure 1. In this article, iterations of the REPLACE strategy are discussed and the application to CDK2/cyclin A described in detail. CDKs are believed to be directly or indirectly deregulated in the majority of tumors and are therefore considered appropriate cancer drug targets7. CDKs require association with cyclins for full activation and subsequently phosphorylate key proteins involved in cell cycle regulation8. The two major groups of CDKs are the isotypes that control cell cycle checkpoints [G1/S (CDK4/Cyclin D, CDK6/cyclin D and CDK4/cyclin E), S phase (CDK2/cyclin A) and G2/M (CDK1/cyclin B)] and the regulators of RNA polymerase through phosphorylation (CDK7/cyclin H, CDK8/cyclin C, CDK9/cyclin T). A key step in S phase progression occurs when the E2F1 transcription factor forms a complex with the DP protein which then binds to DNA and initiates gene transcription. CDK2/cyclin A is required to neutralize E2F1 transcriptional activity through phosphorylation thereby leading to release of the E2F1-DP complex and its subsequent degradation. Inhibition of CDK2/cyclin A is believed to maintain E2F1 in its DNA bound state leading to persistent activation. The resultant level of E2F-1 activity will surpass the threshold required to induce p53 independent apoptosis therefore suggesting a therapeutic strategy. Due to deregulated p53 and pRb pathways, high levels of E2F-1 frequently occur in cancer cells and inhibition of CDK2/cyclin A should lead to selective apoptosis in tumors and can be considered as a validated cancer target7.
Clinically investigated CDK inhibitors target the highly conserved ATP binding site leading to cross reactivity among the greater than 500 protein kinases in the human kinome and potentially giving rise to side effects and toxicity9. An alternate approach is non-ATP competitive inhibition by targeting substrate recruitment through the CBG present on cyclin positive regulatory subunit and which is therefore distinct and distant from ATP binding site10,11. The CBG is primarily a hydrophobic groove present in cyclin A, cyclin D and cyclin E and has been shown to recognize a consensus sequence found in substrates and tumor suppressors. As an isolated peptide, the cyclin binding motif (CBM) binds to the CBG and has been shown to inhibit kinase activity of the cell cycle CDKs. The CBM has been optimized to an octapeptide (HAKRRLIF, CDK2/cyclin A IC50 0.07±0.02 µM , CDK4/cyclin D, IC50 0.88±0.34 µM) and furthermore truncated to a pentapeptide representing a good compromise between molecular weight for drug-likeness and potency (RRLIF, CDK2/cyclin A IC50 1.01±0.17 µM, CDK4/cyclin D, IC50 25.12±2.97 µM)12,13. The CBGs consist of a large primary and smaller secondary hydrophobic pocket which are bridged by an acidic region (includes Glu220, Glu224 and Asp283). The key binding determinants of HAKRRLIF include the interaction of Ala2 with the secondary hydrophobic pocket, ion pairing and hydrogen bonds of Lys3, Arg 4 and Arg5 with the acidic region and a high degree of complementarity of Leu6 and Phe8 with the primary lipophilic site. In addition, numerous hydrogen bonds are contributed from the peptide backbone while Ile7 acts as a spacer residue allowing optimal contact with the primary pocket. The binding mode and interactions of HAKRRLIF with CBG is shown in Figure 2.
Targeting the CBM/CBG protein-protein interaction will inhibit kinase activity of CDK2/cyclin A, CDK2/cyclin E & CDK4/cyclin D and this should trigger E2F1 mediated apoptosis of cancer cells while not affecting normal cells7. Although CBM derived peptides are effective inhibitors of cell cycle CDKs, it is unlikely that they will be useful as drugs due to their metabolic instability and general lack of cell permeability. To this end, we have applied the REPLACE strategy in order to convert these potent peptidic inhibitors into more drug-like compounds for further development of anti-tumor therapeutics exploiting deregulated E2F1 through CDK2/cyclin A inhibition. The following protocol summarizes work that has been completed in the application of REPLACE to the cyclin groove. In the first instance, drug-like capping group replacements for the N-terminal tetrapeptide of HAKRRLIF were identified. Furthermore improvements in these groups were investigated in an additional validation study for REPLACE. Representative results from these studies are also presented.
1. Computational Identification of Potential Small Molecule Capping Groups
Note: In principle, a variety of docking or pharmacophore search methods can be used to predict potential capping groups. The main purpose of computational studies in REPLACE is to identify small molecules that retain the features and interactions of the amino acids that are substituted.
Note: In previous studies, the docking method (LigandFit15, a module in the molecular modeling program suite, Discovery Studio 3.0) was validated to ensure that this algorithm is sufficient to reproduce binding modes of known Ncaps and to show that the results obtained for unknown compounds are predictive14.
2. Synthesis and Characterization of Potential N-capping Groups
3. Solid Phase Synthesis for the Generation of FLIPs 2
4. Fluorescence Polarization Binding Assay for the Determination of Competitive Binding 2,14
The interactions of HAKRRLIF with the cyclin groove are shown in Figure 2. The peptide residues that represent the key binding determinants include Ala2, Arg4, Leu6 and Phe8 with other residues providing smaller contributions12,13,18. In this case study the REPLACE strategy has been utilized in order to find fragment alternatives for residues in the N-terminal tetrapeptide of HAKRRLIF, primarily mimicking the interactions of Ala2 and Arg4. A library of potential Ncap fragments (Table 1) was constructed based on the criteria. Each molecule was docked into the vacated binding site created by truncation of the N-capping group from its crystal structure with cyclin A (PDB ID: 2UUE). Potential ligand alternatives were selected based on pose analysis and PLP1 scoring as a prediction of affinity (examples of docked poses are shown in Figure 4). The synthesis of a confirmed Ncap (1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid) is shown in Figure 5 where this molecule was generated in three steps and purified by automated flash chromatography (Supplementary Figure 1). The 1HNMR, 13CNMR, MS and HPLC characterization data of a representative compound 1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid are shown in Supplementary Figures 1-5 respectively. The synthesis of N-capped FLIPs and N-capped-C-capped FLIPs are represented in Figures 7 and 8 and the characterization data are shown in Table 2. The binding affinity for both CDK2/cyclin A and CDK4/cyclin D was determined using the described FP assay and the results are shown in Table 3. Of the compounds tested, FLIPs containing triazole based N-caps were determined to have the greatest affinity for CDK2/cyclin A and CDK4/cyclin D and representative compounds were tested in cell based assays. As a whole, FLIP molecules identified were found to be more drug like, and to retain most of the interactions of the HAKRRLIF octapeptide. Capped tetrapeptides possessed lower potency compared to HAKRRLIF however were of comparable activity to the RRLIF pentapeptide (Tables 3 and 4). These results show that the compounds obtained had improved drug likeness but this was obtained at the cost of somewhat compromised binding affinity.
The anti-proliferative activity these CGI ligands was evaluated and cellular IC50’s below 30 µM were observed in U2OS and DU145 cancer cell lines.
Figure 1. Overview of the REPLACE strategy. Please click here to view a larger version of this figure.
Figure 2. Binding and interactions of HAKRRLIF in CBG. Left panel: Modeled structure of HAKRRLIF bound to the CBG. The cyclin groove consists of two hydrophobic pockets — a larger primary pocket (right, occupied by Leu6 and Phe8) and a smaller secondary pocket (left, occupied by Ala2) and which are bridged by acidic residues depicted in red. Right panel: Other important interactions include hydrogen bonding contacts of the peptide backbone (with Trp217, Gln254, Ile281), and ion-pairing interactions of the three basic residues of the peptide (with Glu220, Glu224, Asp283). Please click here to view a larger version of this figure.
Figure 3. Binding mode of 3,5-DCPTRLIF in CBG. Binding of 3,5-DCPT-RLIF is shown with hydrogen bonding interactions (depicted by green dotted lines) with sidechain atoms of Trp217 and Gln254. Please click here to view a larger version of this figure.
Figure 4. Selected docking results. Docked poses of 3 representative N-capping groups are shown. Each of these compounds make H-bonds with the interaction filter atoms of Trp217 and Gln254 and as depicted by green dotted lines. The phenyl substituent makes van der Waals interactions with the secondary hydrophobic pocket. Please click here to view a larger version of this figure.
Figure 5. Synthesis of 1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid. Please click here to view a larger version of this figure.
Figure 6. Synthesis of N-capped FLIPs by solid phase synthesis. Please click here to view a larger version of this figure.
Figure 7. Synthesis of N-capped-C-capped FLIPs. Please click here to view a larger version of this figure.
Table 1. Library of small molecules docked and the resulting predictions of binding energy using the PLP1 scoring function.
Peptide | Purity | Column Dimensions | Method | Flow Rate | HPLC Retention Time | Theoretical MW | Observed MW |
5843 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 23.9 | 732 | 732.6 |
5773 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 22.4 | 801.77 | 800.55 |
5774 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 24.2 | 767.33 | 766.5 |
5762 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 9.0 | 731.91 | 731.65 |
5763 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 11.2 | 800.8 | 799.5 |
5764 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 10.1 | 766.34 | 765.55 |
5771 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 9.4 | 749.9 | 749.6 |
5765 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 10.1 | 766.35 | 755.65 |
5766 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 9.4 | 761.9 | 761.55 |
5767 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 20.4 | 761.9 | 761.55 |
5776 | >75% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 23.3 | 785.7 | 784.55 |
5775 | >90% | 4.6 × 250 mm | 5-65% acetonitrile/water/0.1% TFA | 1 ml/min | 9.9 | 751.34 | 750.45 |
Table 2. Analytical Data for CGI Binding Peptides and FLIPS.
Table 3. In vitro binding of selected N-capped FLIPs to CDK2CA and CDK4CD.
Table 4. In vitro binding of selected N & C capped FLIPs to CDK2CA and CDK4CD.
Supplementary Figure 1-5. Purification and characterization of 1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid.
Supplementary Figure 1. Flash chromatogram of product obtained from step 1. There are four peaks eluting, the major peak eluting at 55% ethyl acetate / 45% hexanes was found to be the desired product. Please click here to view a larger version of this figure.
Supplementary Figure 2. 1HNMR of 1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid. The NMR spectrum shows 3 aliphatic methyl protons and 3 aromatic protons. The integration for all the three peaks is shown below the NMR spectrum. Please click here to view a larger version of this figure.
Supplementary Figure 3. 13CNMR 1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid. There are ten carbon atoms in the structure, 13CNMR with 10 signals for each carbon atom. The integration for each peak is shown below the NMR spectrum. Please click here to view a larger version of this figure.
Supplementary Figure 4. MS of 1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid. The molecular weight of the compound is shown as parent peak at 237. The actual molecular weight of the compound is 237.64. Please click here to view a larger version of this figure.
Supplementary Figure 5. HPLC of 1-(3-chlorophenyl)-5-methyl-1H-1,2,4-triazole-3-carboxylic acid. The purity of the product is determined as 100% as shown in the HPLC chromatogram. Please click here to view a larger version of this figure.
Targeting protein-protein interactions (PPI) in drug discovery is highly challenging as these typically involve a large shallow contact interface comprised of numerous and diffuse contacts19. Furthermore, peptidic compounds which inhibit PPI’s that are amenable to drug discovery are problematic due to their higher molecular mass, metabolic instability and poor bioavailability20. Current strategies that have been applied for the development of PPI inhibitors include design of proteomimetics and fragment based design. Examples of proteomimetics include stapled peptides, porphyrin scaffolds and cyclic α-helical mimetics although these are not without disadvantages21,22. Porphyrins (heterocyclic macrocycles comprised of pyrrole rings) are high molecular weight structures and are very hydrophobic23. Stapled peptides can be complex to synthesize and their mechanism of cell permeability is currently not fully known6. Conventional fragment based approaches require a highly sensitive detection method for testing weakly binding compounds and which also must be highly soluble. REPLACE is an iterative strategy comprised of computational prediction, synthetic organic chemistry and biological evaluation in order to convert peptidic inhibitors into FLIPs and ultimately non-peptidic drug-like compounds. Using REPLACE, fragment alternatives are designed and identified to mimic the interactions of binding determinants of a peptidic inhibitor. The combination of structural analysis along with synthetic methodologies and biological evaluation results in the efficient design of molecules that interact with hot spots (sites of critical interaction) and complement the large contact surface area of the PPI binding site1. REPLACE overcomes the disadvantages of conventional fragment based design since the peptide acts as an affinity and solubility scaffold. Also the iterative nature of REPLACE means that the inhibitor is gradually converted in several steps therefore minimizing the possibility of complete potency loss through conformation change. PLAs are optimized in the context of the peptide prior to further truncation. In the case study we describe, REPLACE has been exploited to generate more drug-like inhibitors that selectively inhibit cell cycle CDK/cyclin complexes and possess significant anti-proliferative activity. Capped peptides have been identified as more drug-like mimics of the lead octapeptide. Key fragment alternatives discovered include N-caps based on (i) phenyl heterocyclic carboxylic acids2, (ii) furan and thiazole carboxylic acids substituted with alkylamino groups and (iii) pyridine carboxylic acids combined with alkoxy or basic groups14.
In this case study, the first stage of the REPLACE strategy was identification of fragment alternatives for key peptide determinants using high-throughput docking. LigandFit, a shape based docking method was employed for evaluating binding of fragments in the cyclin groove. LigandFit15 generates poses that have high complementarity with a binding site through the use of Monte Carlo conformational search methods in conjunction with a shape based comparison filter. Use of a LigandFit protocol with the PLP1 energy grid and a minimization step to refine generated poses, was shown to reproduce known binding modes of previously determined N-capping groups. An accurate prediction of the binding affinity of the generated poses was provided by using the PLP1 scoring function which was shown to obtain the best results since it takes into account hydrogen bonding between the ligand and receptor. Specific H-bonds of CGI ligands with the cyclin groove have been shown to be important determinants of high affinity binding. Potential fragment alternatives for the N-terminus were synthesized or obtained from commercial sources and then used to generate FLIP molecules through coupling to an assembled peptide on a solid support. The ability of FLIPs to recapitulate the affinity of the native peptide is determined in a competitive binding assay using a known cyclin groove inhibitory peptide which is fluorescently labeled. After confirmation of the ability of FLIPs to bind with sufficient avidity to the CBG, the potency of the peptide-fragment hybrids can then be further refined through modifications to the Ncapping group. In addition, REPLACEments for C-terminus can explored for eventual combination with the optimized Ncaps. Further to this N terminal and C-terminal capping groups can be combined into a single more drug-like molecule2. Using this approach, compounds were obtained that have anti-proliferative activity in cancer cells lines that have deregulated CDK/cyclin/Rb/E2F1 pathways. Although REPLACE has been successfully applied, this strategy is not without limitations. These include the inaccuracy of any computational technique in predicting binding of docked molecules and synthetic issues in generating capping groups and FLIPs. Despite these, we have utilized REPLACE to generate more drug-like compounds that are cell permeable and have anti-proliferative activity. These compounds therefore have significant potential for further development as anti-tumor therapeutics.
The authors have nothing to disclose.
We thank Dr’s. Douglas Pittman and Michael Wyatt for their assistance with cell culture and Dr Wyatt and Ms. Erin Anderson for help in development of the binding assays. We acknowledge Mike Walla and Bill Cotham in the Department of Chemistry and Biochemistry at the University of South Carolina for assistance with Mass Spectrometry, Helga Cohen and Dr. Perry Pellechia for NMR spectrometry. This work was funded by the National Institutes of Health through the research project grant, 5R01CA131368.
Computational Chemistry | |||
Accelyrs Discovery studio 3.0 | |||
Dell Optiplex Workstations | |||
Synthetic Organic Chemistry | |||
Silica gel (GF-254 plates) for TLC, Biotage (Uppsala, Sweden) for flash chromatography, Waters Alliance 2695 HPLC with a 2996 diode-array detector and equipped with a C18 (2) 100 A, 250 x 4.6mm, 5μm column (Phenomenox Luna) for purity determination, 1H NMR and 13C NMR spectra were recorded with a Varian Mercury 300 and 400 Spectrometer, respectively. Mass spectra were measured with a Micromass QTOF (Tandem quadruple-1 time of flight mass spectrometer), electrospray ionization (ESI) and VG 70S (Double-focusing magnetic sector mass spectrometer, EI). | |||
Flourescence Polarization Assay | |||
384 micro well plates, , Micro pipets, | Grenier Bio-one | 110256602 | |
CDK4D1 and CDK2CA (well purified recombinant human kinase complex) | BPS Bio Sciences | 40094(CDK4/Cyclin D), 41101(CDK2/Cyclin A) | |
assay buffer (25 nM HEPES pH 7, 10 mM NaCl, 0.01% Nonidet P-40, 1mM dithiothretiol (DTT), | |||
25 nM HEPES | CALBIOCHEM | 375368 | |
NaCl | Fisher | 127838 | |
Nonidet P-40 | US Biological | N3500 | |
DTT | Aldrich | ||
-70c freezer | Revco (Ultima II) | ||
DTX880 multimode detector fitted with 485 nm/535 nm excitation/emission filters and a dichroic mirror suitable for fluorescein | Beckman Coulter, Brea, CA | ||
Cell Culture | |||
96 well plates, | Fisher | ||
Frozen stocks of U2OS (osteosarcoma) and DU145 (prostate cancer) cell lines | ATCC | ||
NU serum, DMEM media, trypsin, PEN/STRIP, MTT reagent, | Fisher, Life technology, Alfa Aesar | ||
Heamocytometer | VWR | ||
-70c freezer | Revco (Ultima II) | ||
Incubator | Thermo electron corporation | ||
Centrifuge | Eppendorf | 5804 R | |
Refrigerator 4-8C | Isotemp Fisher | ||
DTX880 multimode detector fitted with 595nm filter. | Beckman Coulter, Brea, CA |