Significance
Of the more than 120,000 protein–protein interactions (PPIs) in the human body, very few are directly modulated by FDA-approved small-molecule PPI inhibitors, highlighting a huge untapped opportunity for drug discovery. Here, we analyze the molecular mode of action of three recent breakthrough successes in the design of clinical-stage small-molecule PPI inhibitors, all of which inhibit the previously undruggable protein myeloid cell leukemia 1 (Mcl-1). We discovered that all the three clinical Mcl-1 inhibitors are rigidly prestructured free in solution and that the much larger Mcl-1 pries open to bind these small molecules. We suggest that small-molecule prestructuring could become a more general strategy for PPI inhibitor medicines and point out methods how synthetic chemists can build in such molecular rigidity.
Keywords: AMG176, AZD5991, S64315, AMG-397, PPI inhibitor
Abstract
The structure-based design of small-molecule inhibitors targeting protein–protein interactions (PPIs) remains a huge challenge as the drug must bind typically wide and shallow protein sites. A PPI target of high interest for hematological cancer therapy is myeloid cell leukemia 1 (Mcl-1), a prosurvival guardian protein from the Bcl-2 family. Despite being previously considered undruggable, seven small-molecule Mcl-1 inhibitors have recently entered clinical trials. Here, we report the crystal structure of the clinical-stage inhibitor AMG-176 bound to Mcl-1 and analyze its interaction along with clinical inhibitors AZD5991 and S64315. Our X-ray data reveal high plasticity of Mcl-1 and a remarkable ligand-induced pocket deepening. Nuclear Magnetic Resonance (NMR)-based free ligand conformer analysis demonstrates that such unprecedented induced fit is uniquely achieved by designing highly rigid inhibitors, preorganized in their bioactive conformation. By elucidating key chemistry design principles, this work provides a roadmap for targeting the largely untapped PPI class more successfully.
The human proteome comprises approximately 19,000 expressed proteins, which form an estimated 505,000 protein–protein interactions (PPIs) (1, 2). By mid-2020, merely six PPIs have been successfully targeted by FDA-approved small-molecule inhibitors, whose PPI mode of action is structurally confirmed (1), leaving most PPIs unexploited for disease intervention. Here, we report a potential breakthrough methodology for small-molecule PPI inhibitor development, which promises a much wider reach of PPI medicines in human therapy. We exemplify our approach for the hematological cancer target Mcl-1 (myeloid cell leukemia sequence 1), for which a total of seven small-molecule PPI inhibitors have reached clinical Phase 1 trials (3, 4).
Mcl-1 belongs to the family of apoptosis regulator proteins, which are comprised of three subfamilies: the multi-BH motif antiapoptotic proteins Bcl-2, Bcl-xL, Bcl-w, Mcl-1, Bfl-1/A1, and Bcl-b; the multi-BH motif proapoptotic effector proteins Bax and Bak; and the single BH (BH3) motif proapoptotic sensitizers or initiators, such as Bim, Bad, Bid, Bik, Bmf, Hrk, Noxa, and Puma (5). Once activated, proapoptotic Bax and Bak homo-oligomerize at the outer membrane of the mitochondria, leading to pore formation and release of downstream apoptotic proteins, such as Cytochrome C and Smac. Cytochrome C release activates caspases and ultimately leads to apoptotic cell death. By contrast, antiapoptotic proteins, such as Bcl-2 and Mcl-1, bind and neutralize Bax and Bak, thereby preventing Bax/Bak oligomerization and finally apoptosis (3).
The balance between proapoptotic and antiapoptotic proteins is tightly controlled during and after embryonic development, but dysregulated in a wide range of cancers (6), both triggering cancer and causing resistance to chemotherapy and targeted agents (3). The potential of targeting antiapoptotic proteins is evidenced by the selective Bcl-2 PPI inhibitor venetoclax, which is becoming the new standard of care in combination with hypomethylating agents and low-dose chemotherapy in elderly acute myeloid leukemia (AML) patients, and which is extending patient survival for the first time in this population (7, 8).
Mcl-1 overexpression is associated with tumor cell survival, resistance to radiotherapy, chemotherapy, and venetoclax therapy, leading to poor prognosis in multiple myeloma, non-Hodgkin’s lymphoma, and AML (3). Coadministration of Mcl-1 inhibitors with venetoclax shows synergistic activity in preclinical AML studies, promising that selective Mcl-1 PPI inhibitors will deliver another leap forward for the treatment of hematological malignancies (3, 9).
Here, we show the 3D crystal structure of the clinical Phase 1 Mcl-1 inhibitor AMG-176 bound to Mcl-1 and compare it with three additional potent small-molecule inhibitor/Mcl-1 crystal structures. By determining the free-in-solution 3D conformations of these four inhibitors, we found a surprising level of inhibitor preorganization, enabling the induction of druggable binding pockets in previously intractable, flat PPI surfaces. This induced-fit interaction mechanism common to Mcl-1 clinical-stage inhibitors could set a new chemistry design strategy for the thousands of yet untargeted PPIs in the human proteome.
Results
The Impossible Mcl-1 PPI Site.
Despite the pivotal role of Mcl-1 in leukemia, Mcl-1 inhibitor development has lagged behind its antiapoptotic family members Bcl-2 and Bcl-xL by almost 20 y. Compared with Bcl-2 and Bcl-xL, the PPI pocket of Mcl-1 is shallower and less flexible, which substantially exacerbates the development of potent oral small-molecule inhibitors (10). We analyzed the PPI pocket of Mcl-1 in its apo and Bim peptide-bound crystal structures in detail, using the two scoring methods, number of probe points (PP) (11, 12), and protein-ligand binding (PLB) index (13) (Fig. 1A). The PP method scores protein crevices by volume and small-molecule drug-like shape, whereas the PLB index method additionally weighs such PP scores by the abundance of pocket amino acids frequently found in drug-like sites, such as Trp, His, Phe, and Met, thereby ruling out high scores for highly hydrophilic pockets. Apo Mcl-1 and Bim-bound Mcl-1 possess PP scores of 26 and 10, respectively, which are far below average druggable pocket PP scores of 30 and above. Similarly, the PLB indices for apo and Bim-bound Mcl-1 show low values of 0.0 and 0.1, respectively, while drug-like pockets often show PLB indices of 1.0 and above.
Fig. 1.

PPI pocket analysis of Mcl-1. (A) Crystal structures of Mcl-1 unbound (Top Left) and bound to the Bim peptide (red a-helix, Top Right), 3 (Middle Left), 4 (Middle Right), 1 (Bottom Left), and 2 (Bottom Right) in identical orientations. (B) Binding site surfaces of Mcl-1. PLB indices (Top number) and number of probe points (Bottom number) are shown in the same order as in A. (C) Chemical structure of inhibitors 1 to 5.
Nevertheless, we and researchers at Amgen and Servier took on this challenge and delivered small-molecule Mcl-1 PPI inhibitors, which advanced to clinical Phase 1 or 2 oncology studies and were previously thought impossible (Fig. 1B). Three additional Mcl-1 inhibitors, namely ABBV-467, PRT1419, and GS-9716, by teams from AbbVie, Prelude Therapeutics, and Gilead Sciences, respectively, have entered the clinic, but have not been disclosed in chemical structure detail yet (4, 14). Thereof, the clinical trials of AMG-397 and AZD5991 have been terminated by now (15, 16). Nevertheless, this impressive number of clinical small molecules gives evidence of the crossorganizational breakthrough made in Mcl-1 drug development.
Clinical Small-Molecule Inhibitors Induce Druggable Pocket.
We set out investigating the drug–protein interactions in atomic detail by determining the 3D crystal structure of the clinical Phase 1 inhibitor AMG-176 (1) bound to Mcl-1 (SI Appendix, Fig. S1). Our structure reveals that 1 occupies an overlapping pocket to the BH3 cognate peptides, here exemplified by the pan-selective Bim peptide bound to Mcl-1 (Fig. 2A) (17). The superimposition of the Mcl-1-bound crystal structures of 1 and Bim illustrates that Bim binds as an a-helix to an extended surface groove between helices a3 and a4 of Mcl-1, whereas the synthetic inhibitor 1 cuts deeply into the hydrophobic core of Mcl-1. The important salt bridge interaction between Arg263 of Mcl-1 and the conserved Asp15 of the BH3 peptides (residue numbering as in PDB-code = 2PQK) is formed by the acidic acylsulfonamide of 1. However, the intraprotein interactions of Arg263 differ markedly. In Bim-bound Mcl-1, the guanidinium of Arg263 is salt bridged to the carboxylate of Asp256 at the C terminus of a4, forcing the NH of Asp256 out of the a-helical H-bond network. By contrast, in Mcl-1 bound to 1, the guanidinium of Arg263 forms H-bonds with the carbonyls of V253 and F254. In effect, the entire helix a4 is shifted toward its N terminus by 3 Å compared with Bim-bound Mcl-1. Hydrophobic core-forming residues on a4, such as Leu246, Val249, and Met250, are shifted along, opening up the sizeable crevice utilized by the 6-chlorotetralin of 1.
Fig. 2.

Crystal structure of human Mcl-1 bound to 1 vs. Bim. (A) Superimposition of 1 (green) and Bim (orange a-helix) bound to Mcl-1 (hydrophobic surface with dark green = hydrophobic and pink = hydrophilic) shows that 1 inserts much deeper than Bim into the BH3 peptide pocket. (B) Molecular interactions and conformational changes of Mcl-1 bound to 1 (dark green residues) and Bim (gray residues). The 3.0 to 4.5 Å move of a-helix three residues L246, M250, and D256 is indicated by arrows. H-bond contacts of R263 are shown as dotted lines.
This exceptional move of a4 in a folded a-helical bundle protein is made possible by the NH of Val258 losing its H-bond to the carboxylate of Asp256, and by Gly257 losing its a-helical H-bond in favor of an extended conformation. The side chain of Leu267 in helix a5 rearranges in concert to fill the void left by the shifted a4 hydrophobic core residues. As a consequence, a PPI binding site shallow and not drug like in both apo and cognate peptide-bound Mcl-1 becomes unexpectedly voluminous and druggable in the presence of 1.
Mcl-1 Plasticity upon Inhibitor Binding.
We extended our binding site analysis to additional potent, crystal structure-defined, synthetic inhibitors of Mcl-1, of which two, S64315 (2) (18) and AZD5991 (3) (19), have entered clinical trials, and the discovery tool compound 4, derived from a DNA-encoded library screening hit (20). One key mutually conserved interaction of 1, 2, 3, 4, and Bim is with Arg263, which forms salt bridges with the carboxylates of 2 and 3 and Asp15 of BH3 peptides. The synthetic inhibitor 4 adopts a cation-π interaction between its para-chlorobenzyl and Arg263. The remaining interactions differ markedly.
1 and 3 show large binding site volume increases, as quantified by more than a doubling of PP and higher PLB indices compared with apo and Bim-bound Mcl-1 (Fig. 1A), consistent with both inhibitors 1 and 3 inserting their 6-chlorotetralin and naphthalin moieties, respectively, deeply into the Mcl-1 core. By contrast, 2 and 4 show merely moderate PP and PLB index increases with respect to apo and Bim-bound Mcl-1. Molecular analysis of their pocket interaction reveals that 2 fails to pry open the Mcl-1 core between helices a3 and a4 and does not engage with Met250 and Phe270, thereby explaining the low probe point and PLB scores. Inhibitor 4 does penetrate the Mcl-1 core with its flat chloro-(2-phenylethyl)benzene substituent, but opens up much less pocket volume than 1 and 3. Since 4 still sandwiches in between the high-scoring pocket residues Met250 and Phe270, it achieves a PLB index elevation to 0.57.
Allosteric Mcl-1 Plasticity by Crystallography and in Solution.
Next, we looked for Mcl-1 plasticity beyond its Bim-binding site. Comparison of the Ca backbone rmsd values between the whole protein and residues within 4 Å of the pocket of 1 demonstrates that conformational rearrangements of around 1 Å occur throughout the protein and between all ligated complexes investigated here (Fig. 3). Prominent pocket movements of helices a3 and a4 as well as the a4–a5 loop of Mcl-1 trigger plasticity throughout the entire protein (Fig. 3). Previous exploration of Mcl-1 peptide ligand–induced conformational changes identified systematic differences in protein backbone rmsd values of approximately 0.7 Å between crystal and NMR-derived solution structures (17). Alerted by these potential crystal-packing effects, we investigated the binding of inhibitors 1, 2, 3, 5, and Bim by 15N-HSQC NMR spectroscopy in solution. Inhibitor 5 is the 15-fold more potent methylsulfon analog of 4 (Fig. 1) and expected to bind to the same site as 4 (20).
Fig. 3.
Inhibitor-induced plasticity of Mcl-1. (A) Crystal structure backbone overlay of Mcl-1 unbound (cyan) and bound to Bim (green), 1 (magenta), 2 (blue), 3 (orange, inhibitor displayed), and 4 (skin color) shows the four major backbone rearrangements (cyan arrows) in and around a-helix three upon inhibitor binding. (B) Mcl-1 Ca rmsd values (in Å) for 4 Å binding pocket around 1 (Left Bottom matrix) and entire backbone (Right Top matrix) indicating that each ligand interaction induces a new Mcl-1 conformation different by 0.5 to 1.8 Å.
Protein conformational changes produce chemical shift perturbations in backbone amide 1H-15N chemical shifts that can be quantified by the ECHOS-NMR (easy comparability of higher order structure by NMR) analysis of two-dimensional 15N-HSQC spectra. This method yields spectral correlation coefficient (R) values of 1.0 for no change at all and R values as low as 0.0 for maximum changes, such as protein unfolding (21). We validated this statistical quantification method by studying different batches of 15N-labeled Mcl-1 unbound and bound to the low-affinity binder 1-methylindole-2-carboxylate (6) (22). We obtained R values of >0.99 and 0.97 for unbound and Mcl-1 bound to 6, respectively (SI Appendix, Fig. S2). By contrast, inhibitors 1, 2, 3, 5, and Bim produced R values of 0.57, 0.48, 0.56, 0.53, and 0.59, respectively, indicating substantial Mcl-1 rearrangement upon ligand binding in solution. Hence, Bim and inhibitors 1 to 5 induce Mcl-1 plasticity of similar magnitude both in solution and in single crystals, but deep druggable pocket inductions are unique to these inhibitors.
Preorganization Inhibitor Design Is Key to Success.
While ligand-induced protein rearrangements are universal in biology, the creation of unprecedented drug-like pockets is certainly not. We were intrigued to further investigate the landmark differences between BH3 peptide ligands and inhibitors 1 to 5. Affinity and potency measurements in vitro showed similar interaction strengths for Bim and 1 to 5, thereby not explaining the stark pocket volume changes unique to 1 to 4 (Table 1).
Table 1.
Affinities & cellular potencies of Mcl-1 inhibitors
| Entry | Cpd name | PL bind score | Probe Pts pocket | FRET IC50 (μM) * | SPR Kd (μM) † | kon (106 M−1.s−1)† | koff (10−4 s−1) † | Cell EC50 (μM) ‡ | LE [kcal/mol/#HA] | Mw |
|---|---|---|---|---|---|---|---|---|---|---|
| apo | 0.0 | 26 | ||||||||
| Bim§ | peptide | 0.09 | 10 | 0.0140 | <0.002 | 0.05 | 3248 | |||
| 1 | AMG176 | 1.51 | 65 | 0.0005 | 0.0003 | 2.4 | 6.5 | 0.125 | 0.30 | 613 |
| 2 | S64315 | 0.15 | 28 | 0.0008 | 0.0007 | 1.8 | 5.1 | 0.012 | 0.22 | 829 |
| 3 | AZD5991 | 0.33 | 71 | 0.0007 | 0.0002 | 3.8 | 6.0 | 0.033 | 0.28 | 672 |
| 4 | Cpd29 | 0.57 | 28 | 0.0450 | 0.34 | 0.4 | 730 | >32 | 0.18 | 783 |
| 5 | Cpd26 | <0.0030 | 0.02 | 3.3 | 660 | 13 | 0.20 | 826 |
*In vitro competitive binding inhibition assay of Mcl-1.
†Surface plasmon resonance (SPR) direct binding to Mcl-1 assay.
‡Inhibition of caspase activity in MOLP-8 cells with 10% fetal calf serum.
§Kd by fluorescence polarization assay (17).
Rather, we asked whether the macrocyclic structures of 1, 3, and 5 could be a root cause. We studied 1 to 3, and 5 by free-in-solution conformational analysis. This method utilizes the experimental NMR restraint NOE distances, scalar couplings, and 1H chemical shifts to calculate the 3D conformers that a small molecule predominantly populates free in solution (23). We found that the free inhibitor 1 adopts a 3D conformation identical to the crystal-defined conformer of 1 bound to Mcl-1 within the accuracy of the forcefield calculations (Fig. 4A). This stunning preorganization of 1 free in solution is not trivial, as the computational molecular dynamics (MD) simulation of the theoretical conformer space produces several important diversions (SI Appendix, Fig. S3). The methoxy substituent on the macrocycle of 1 can fold inward to H bond with the NH of the sulfonamide, and the 6-chlorotetralin can adopt many poses. However, our NMR experimentation demonstrates that 1 free in solution is entirely preorganized to induce the exact binding pocket observed by crystallography.
Fig. 4.
Preorganized Mcl-1 inhibitors. Superimposition of the predominant free-in-solution conformer (gray) with the crystal-defined Mcl-1-bound conformer (green) shows that the clinical-stage inhibitors 1 to 3 are prepositioned in the bioactive conformation, whereas the lower affinity tool inhibitor 5 lacks preorganization in key pocket interactions, such as R263 and M250. Flexible vs. rigid torsion angles free in solution are labeled by rotation vs. crossed-out rotation arrows, respectively. Aromatic ring packings are highlighted by double-headed arrows, which show the distance between the aryl and the hydrogen with the characteristic upfield chemical shift. Ligand orientations as in Figs. 1 and 3.
Analogous free ligand analysis of 2 again reveals an unexpected degree of preorganization free in solution (Fig. 4B). The 2-chloro-3-methyl-phenol and the 2-hydroxy-3-phenyl-propanoate of 2 adopt identical 3D poses free in solution as in the bound crystal structure. In the absence of a macrocyclic backbone, this lack of rotational space sampling is a well-designed conformational property of 2. By NMR experimentation, we found that the ortho hydrogen of the 2-hydroxy-3-phenyl-propanoate packs within 2.8 Å against the 2-chloro-3-methyl-phenol ring, as evidenced by intramolecular NOE and a characteristic upfield chemical shift for this hydrogen, which is 0.9 ppm smaller than predicted by the 3D-insensitive HOSE method (24) (Fig. 5). In effect, this edge-to-face aromatic ring alignment generates a tiny hydrophobic core that stabilizes 2 in a largely bioactive conformation. Only its methyl-piperazine and anisole substituents are unstructured in solution, both of which form merely solvent-exposed surface interactions with Mcl-1 in the crystal structure.
Fig. 5.

Free-in-solution conformer analysis. Free ligand 3D conformers of Mcl-1 inhibitors (A) 1; (B) 2; (C) 3; and (D) 5 are shown next to their 2D chemical structures. Fingerprint 1H-NMR signals indicating aromatic ring packing are highlighted in green in the 1H-NMR spectrum (axis in ppm) and chemical structures. Signals shifted >0.8 ppm upfield compared with the 2D-HOSE prediction method were considered indicative. Experimental, HOSE-predicted, and Density Function Theory (DFT)-calculated chemical shifts are tabularized in SI Appendix, Supplementary Notes 1–4.
Free-in-solution conformer analysis of 3 confirmed the findings of our previous chemical shift study (19). 3 is fully preorganized to bind Mcl-1 in the very same pose as observed in the bound crystal structure (Fig. 4C). Similar to 2, the 3D conformer of 3 shows two aromatic rings packed edge to face, as determined by intramolecular NOE and a chemical shift of the involved pyrazole hydrogen shifted by 1.1 ppm upfield as compared with the HOSE prediction method (Fig. 5).
Finally, inhibitor 5, despite being macrocyclic, shows much less preorganization than 1 to 3 (Fig. 4D). The methylsulfonylbenzene of 5, forming the important interaction with the guanidinium of Arg263, shows complete rotational freedom in the unbound state. Likewise, the 1-chloro-2-(2-phenylethyl)benzene, inserting deeply into the Mcl-1 core to contact Met250 in the crystal structure of 4, is unstructured free in solution. Merely its methylene connection to the macrocyclic backbone is rotationally restricted through a face-to-face aromatic ring packing, as evidenced by intramolecular NOE. The 1.3 ppm upfield chemical shift of the 9-hydrogen of the tetrahydro-1-benzazepin-2-one as compared with its HOSE-predicted chemical shift supports this aromatic ring packing (Fig. 5). The cis/trans amide bond configurations are preserved between unbound 5 and bound 4, but the macrocycle backbone still shows larger deviation from its bioactive conformer than observed for the macrocycles 1 and 3. Taken together, this lack of preorganization goes along with an approximately 100-fold lower affinity for Mcl-1 than 1 to 3 in our surface plasmon resonance assay, and a harsh 1000-fold drop-off in cellular potency in our MOLP-8 cell assay (Table 1).
Discussion
The marketed oral Bcl-2 inhibitor venetoclax with an Mw of 868 Da and ligand efficiency (LE) of 0.25 kcal/mol/heavy-atom sparked hope that LE values below 0.30, previously considered the lower limit, are feasible for oral medicines (25). The three very recent clinical-stage Mcl-1 inhibitors 1–3 with LE values of 0.30, 0.22, and 0.28, respectively, substantiate that the frontiers of small-molecule druggability have indeed been moved for Bcl family PPI targets. Here, we structurally explored how this unprecedented conversion of undruggable PPI sites into drug-like pockets has been achieved. Our analysis of inhibitor-bound Mcl-1 crystal structures reveals that previous rules of minimum binding pocket volume and shape still apply. However, to our great surprise, such binding pockets are proactively induced by inhibitor binding rather than preexist in either apo Mcl-1 nor cognate peptide-bound Mcl-1 complexes.
This finding intrigued us to investigate how smart inhibitor design can deliver so much more drug-like inhibitors than mimicry of endogenous peptides and PPI partners. By using free ligand conformer analysis, we discovered that inhibitor preorganization in the bioactive conformation is the outstanding discriminator between successful clinical-stage inhibitors 1 to 3 and failed preclinical discovery compounds, as exemplified by the low-nanomolar IC50 macrocycle 5.
In order to achieve such sweet spot bioactive preorganization, we found that three successful chemical drug design principles apply: synthetic cyclization, hydrophobic core interactions, and use of atropisomers. 1 utilizes a cyclization linker with five stereocenters, one transsubstituted alkenyl, the rigidity of carbonylsulfonamide, and discrimination between potential atropisomers. This signals that higher-than-average synthetic effort was applied in a thorough rigidity design strategy, as described previously (26).
By a similar design strategy, four aryl rings were synthetically cyclized to yield the bioactive conformer of 3. Two of them, the indole and cis pyrazole, are conformationally locked into one atropisomer by di-ortho-substitution on both rings. The trans pyrazole is locked against the indole by edge-to-face hydrophobic core interactions, which boost potency even in acyclic precursors of 3, as reported previously (19). Short hydrophobic thioether linkers restrict the remainder of 3 around this core.
The preorganization of 2 stems from an atropisomer and hydrophobic core interaction strategy, in which the two benzenes off the four and five positions of the thieno[2,3-δ]pyrimidine form the edge-to-face aryl core. Additionally, a trans positioning between the oxygen and 3-nitrogen of the 4-(hydroxymethyl)pyrimidine moiety is achieved by utilizing their electrostatic repulsion. However, the overall ligand efficiency and pocket PP of 2 are substantially lower than those for 1 and 3, suggesting that the induced-fit opportunity was incompletely exploited, resulting in a clinical inhibitor heavier by 216 Da than 1.
Tailing not much behind 2 in ligand efficiency, macrocycle 5 lacks preorganization of substituents crucial for potent Mcl-1 inhibition. Although successfully inducing the deep pocket between Met250 and Phe270 of Mcl-1, its lack of conformational rigidity coincides with losses in both direct binding affinity and cellular potency, which are unacceptable for a clinical candidate. Conversely, this suggests that rigidity design is a success strategy for small-molecule PPI medicines.
As target protein plasticity is at the heart of this strategy, we researched how commonly induced-fit or cryptic pockets occur. Examples are reported for diverse protein classes, such as induced subpockets in the ATP-binding domain of chaperon HSP90, an induced adjacent pocket in the PPI target interleukin-2 (IL-2), an induced allosteric pocket in the protein kinase P38 MAPK, an induced ligand channel in nonspecific lipid transfer protein (ns-LTP), and a positive allosteric modulator pocket in the GPCR M1 muscarinic acetylcholine receptor (27, 28). A landmark cryptic pocket discovery in the GTPase K-Ras mutant G12C, which is the most frequent K-Ras mutation in lung cancer, opened the door for new small-molecule medicines sotorasib and adagrasib after almost four decades of unsuccessful pharmaceutical research (29, 30). Further systematic analysis of diverse protein–ligand pockets identified a higher plasticity in PPI sites than small ligand pockets and catalytic sites of enzymes (31), suggesting that PPI targets are a promising hunting ground for unprecedented druggable pockets. Designing and screening rigid, preorganized ligands will help to conquer the huge PPI target space more successfully in the future.
Materials and Methods
Detailed methods, including statements of data availability and associated references, are available online as SI Appendix. Chemical synthesis of 1 to 6, biological assays, and Mcl-1 protein production were performed as published previously. For crystallization, crystals of the Mcl-1–Fab complex were soaked with 1, diffraction data were collected at the Diamond Light Source, and final crystallography data were deposited in Protein Data Bank [PDB ID: 8AV9] and will be accessible upon publication. Conformational free ligand analysis of 1 to 4 was performed by solution NMR spectroscopy, MD, and DFT computation as previously described.
Supplementary Material
Appendix 01 (PDF)
Acknowledgments
We wish to thank Erin Code, Ning Gao, and Xaihui Zhu for protein production, Steven Kazmirski for structural biology support, and Jian Huang and Alan Rosen for expert technical assistance in generating biological data. Moreover, we thank the many current and former colleagues involved in the design, generation, purification, analytical quality control, and management of the compounds for this project.
Author contributions
D.H., R.J.C., M.S.B., K.E., P.B.R., M.P., S.L.D., A.W.H., J.W.J., E.C., and M.S. designed research; D.H., R.J.C., M.S.B., K.E., P.B.R., M.P., S.L.D., A.W.H., and J.W.J. performed research; D.H., R.J.C., M.S.B., K.E., P.B.R., M.P., S.L.D., A.W.H., J.W.J., and M.S. analyzed data; and D.H., R.J.C., M.S.B., K.E., and M.S. wrote the paper.
Competing interests
The authors declare no competing interest.
Footnotes
This article is a PNAS Direct Submission.
Data, Materials, and Software Availability
All study data are included in the article and/or SI Appendix.
Supporting Information
References
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Appendix 01 (PDF)
Data Availability Statement
All study data are included in the article and/or SI Appendix.


