Analysis of Flexibility and Hotspots in Bcl-xL and Mcl-1 Proteins for the Design of Selective Small-Molecule Inhibitors

Enhancing SILCS-MC via GPU Acceleration and Ligand Conformational Optimization with Genetic and Parallel Tempering Algorithms

In the domain of computer-aided drug design, achieving precise and accurate estimates of ligand-protein binding is paramount in the context of screening extensive drug libraries and performing ligand optimization. A fundamental aspect of the SILCS (site identification by ligand competitive saturation) methodology lies in the generation of comprehensive 3D free-energy functional group affinity maps (FragMaps), encompassing the entirety of the target molecule structure. These FragMaps offer an intricate landscape of functional group affinities across the protein, bilayer, or RNA, acting as the basis for subsequent SILCS-Monte Carlo (MC) simulations wherein ligands are docked to the target molecule. To augment the efficiency and breadth of ligand sampling capabilities, we implemented an improved SILCS-MC methodology. By harnessing the parallel computing capability of GPUs, our approach facilitates concurrent calculations over multiple ligands and binding sites, markedly enhancing the computational efficiency. Moreover, the integration of a genetic algorithm (GA) with MC allows us to employ an evolutionary approach to perform ligand sampling, assuring enhanced convergence characteristics. In addition, the potential utility of parallel tempering (PT) to improve sampling was investigated. Implementation of SILCS-MC on GPU architecture is shown to accelerate the speed of SILCS-MC calculations by over 2-orders of magnitude. Use of GA and PT yield improvements over Markov-chain MC, increasing the precision of the resultant docked orientations and binding free energies, though the extent of improvements is relatively small. Accordingly, significant improvements in speed are obtained through the GPU implementation with minor improvements in the precision of the docking obtained via the tested GA and PT algorithms.

Structure-based assessment and druggability classification of protein-protein interaction sites

The featureless interface formed by protein–protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.

Computational Cosolvent Mapping Analysis Leads to Identify Salicylic Acid Analogs as Weak Inhibitors of ST2 and IL33 Binding

Cytokine signaling initiated by the binding of the cytokine receptors to cytokines plays important roles in immune regulation and diseases. Structurally, cytokine receptors interact with cytokines via an extensive, rugged interface that represents a challenge in inhibitor development. Our computational analysis has previously indicated that butyric acid, mimicking acidic residues, preferentially binds to sites in ST2 (Stimulation-2) that interact with acidic residues of IL33, the endogenous cytokine for ST2. To investigate if a charged group in small molecules facilitates ligand binding to ST2, we developed a biochemical homogeneous time resolved fluorescence assay to determine the inhibition of ST2/IL33 binding by five molecules containing an aromatic ring and a charged group. Three molecules, including niacin, salicylic acid, and benzamidine, exhibit inhibition activities at millimolar concentrations. We further employed the computational cosolvent mapping analysis to identify a shared mode of interaction between niacin, salicylic acid, and ST2. The mode of interaction was further confirmed by four analogous compounds that exhibited similar or improved activities. Our study provided the evidence of inhibition of ST2 and IL33 binding by salicylic acid and analogs. The results suggest that biological activity of salicylic acid may be partly mediated through modulating extracellular cytokine receptors and cytokine interaction.

Application of Site-Identification by Ligand Competitive Saturation in Computer-Aided Drug Design

Site Identification by Ligand Competitive Saturation (SILCS) is a molecular simulation approach that uses diverse small solutes in aqueous solution to obtain functional group affinity patterns of a protein or other macromolecule. This involves employing a combined Grand Canonical Monte Carlo (GCMC)-molecular dynamics (MD) method to sample the full 3D space of the protein, including deep binding pockets and interior cavities from which functional group free energy maps (FragMaps) are obtained. The information content in the maps, which include contributions from protein flexibilty and both protein and functional group desolvation contributions, can be used in many aspects of the drug discovery process. These include identification of novel ligand binding pockets, including allosteric sites, pharmacophore modeling, prediction of relative protein-ligand binding affinities for database screening and lead optimization efforts, evaluation of protein-protein interactions as well as in the formulation of biologics-based drugs including monoclonal antibodies. The present article summarizes the various tools developed in the context of the SILCS methodology and their utility in computer-aided drug design (CADD) applications, showing how the SILCS toolset can improve the drug-development process on a number of fronts with respect to both accuracy and throughput representing a new avenue of CADD applications.

Computational Design of BH3-Mimetic Peptide Inhibitors That Can Bind Specifically to Mcl-1 or Bcl-XL: Role of Non-Hot Spot Residues

Interactions between pro- and anti-apoptotic Bcl-2 proteins decide the fate of the cell. The BH3 domain of pro-apoptotic Bcl-2 proteins interacts with the exposed hydrophobic groove of their anti-apoptotic counterparts. Through their design and development, BH3 mimetics that target the hydrophobic groove of specific anti-apoptotic Bcl-2 proteins have the potential to become anticancer drugs. We have developed a novel computational method for designing sequences with BH3 domain features that can bind specifically to anti-apoptotic Mcl-1 or Bcl-X_L. In this method, we retained the four highly conserved hydrophobic and aspartic residues of wild-type BH3 sequences and randomly substituted all other positions to generate a large number of BH3-like sequences. We modeled 20000 complex structures with Mcl-1 or Bcl-X_L using the BH3-like sequences derived from five wild-type pro-apoptotic BH3 peptides. Peptide-protein interaction energies calculated from these models for each set of BH3-like sequences resulted in negatively skewed extreme value distributions. The selected BH3-like sequences from the extreme negative tail regions have highly favorable interaction energies with Mcl-1 or Bcl-X_L. They are enriched in acidic and basic residues when they bind to Mcl-1 and Bcl-X_L, respectively. With the charged residues often away from the binding interface, the overall electric field generated by the charged residues results in strong long-range electrostatic interaction energies between the peptide and the protein giving rise to high specificity. Cell viability studies of representative BH3-like peptides further validated the predicted specificity. This study has revealed the importance of non-hot spot residues in BH3-mimetic peptides in providing specificity to a particular anti-apoptotic protein.

AlphaSpace 2.0: Representing Concave Biomolecular Surfaces Using β-Clusters

Modern rational modulator design and structure-function characterization often concentrate on concave regions of biomolecular surfaces, ranging from well-defined small-molecule binding sites to large protein-protein interaction interfaces. Here, we introduce a β-cluster as a pseudomolecular representation of fragment-centric pockets detected by AlphaSpace [J. Chem. Inf. Model. 2015, 55, 1585], a recently developed computational analysis tool for topographical mapping of biomolecular concavities. By mimicking the shape as well as atomic details of potential molecular binders, this new β-cluster representation allows direct pocket-to-ligand shape comparison and can be used to guide ligand optimization. Furthermore, we defined the β-score, the optimal Vina score of the β-cluster, as an indicator of pocket ligandability and developed an ensemble β-cluster approach, which allows one-to-one pocket mapping and comparison among aligned protein structures. We demonstrated the utility of β-cluster representation by applying the approach to a wide variety of problems including binding site detection and comparison, characterization of protein-protein interactions, and fragment-based ligand optimization. These new β-cluster functionalities have been implemented in AlphaSpace 2.0, which is freely available on the web at http://www.nyu.edu/projects/yzhang/AlphaSpace2.

Discovery of Mcl-1 inhibitors from integrated high throughput and virtual screening

Protein-protein interactions (PPIs) represent important and promising therapeutic targets that are associated with the regulation of various molecular pathways, particularly in cancer. Although they were once considered “undruggable,” the recent advances in screening strategies, structure-based design, and elucidating the nature of hot spots on PPI interfaces, have led to the discovery and development of successful small-molecule inhibitors. In this report, we are describing an integrated high-throughput and computational screening approach to enable the discovery of small-molecule PPI inhibitors of the anti-apoptotic protein, Mcl-1. Applying this strategy, followed by biochemical, biophysical, and biological characterization, nineteen new chemical scaffolds were discovered and validated as Mcl-1 inhibitors. A novel series of Mcl-1 inhibitors was designed and synthesized based on the identified difuryl-triazine core scaffold and structure-activity studies were undertaken to improve the binding affinity to Mcl-1. Compounds with improved in vitro binding potency demonstrated on-target activity in cell-based studies. The obtained results demonstrate that structure-based analysis complements the experimental high-throughput screening in identifying novel PPI inhibitor scaffolds and guides follow-up medicinal chemistry efforts. Furthermore, our work provides an example that can be applied to the analysis of available screening data against numerous targets in the PubChem BioAssay Database, leading to the identification of promising lead compounds, fuelling drug discovery pipelines.

Caspase cleavage of Mcl-1 impairs its anti-apoptotic activity and proteasomal degradation in non-small lung cancer cells

Global cleavage of cellular proteins by activated caspases is a hallmark of apoptosis, which causes biochemical collapse of the cell. Recent studies suggest that, rather than completely destroying a protein, caspase cleavage can confer novel characteristics or functions. In this respect, the post-caspase role of Bcl-2 family proteins remains uncharacterized. Here, we showed that Mcl-1, a pro-survival member of the Bcl-2 family, was cleaved by caspase-3 in non-small cell lung cancer (NSCLC) cells undergoing chemotherapeutic agent-triggered apoptosis. Caspase cleavage partially impaired the anti-apoptotic activity of Mcl-1 by reducing its mitochondrial localization and impeding its association with the permeability transition pore-forming protein Bak. However, the stability of cleaved Mcl-1 was markedly enhanced because it was more refractory to ubiquitination-dependent proteasomal degradation, thereby improving cell viability to a greater extent than full-length Mcl-1 when transiently expressed in NSCLC cells. These findings shed new light on the role of Mcl-1 in apoptosis and suggest potential novel targets for optimizing the tumoricidal capacity of chemotherapy.

In silico structure-based approaches to discover protein-protein interaction-targeting drugs

A core concept behind modern drug discovery is finding a small molecule that modulates a function of a target protein. This concept has been successfully applied since the mid-1970s. However, the efficiency of drug discovery is decreasing because the druggable target space in the human proteome is limited. Recently, protein-protein interaction (PPI) has been identified asan emerging target space for drug discovery. PPI plays a pivotal role in biological pathways including diseases. Current human interactome research suggests that the number of PPIs is between 130,000 and 650,000, and only a small number of them have been targeted as drug targets. For traditional drug targets, in silico structure-based methods have been successful in many cases. However, their performance suffers on PPI interfaces because PPI interfaces are different in five major aspects: From a geometric standpoint, they have relatively large interface regions, flat geometry, and the interface surface shape tends to fluctuate upon binding. Also, their interactions are dominated by hydrophobic atoms, which is different from traditional binding-pocket-targeted drugs. Finally, PPI targets usually lack natural molecules that bind to the target PPI interface. Here, we first summarize characteristics of PPI interfaces and their known binders. Then, we will review existing in silico structure-based approaches for discovering small molecules that bind to PPI interfaces.

A potent small-molecule inhibitor of the DCN1-UBC12 interaction that selectively blocks cullin 3 neddylation

The Cullin-RING E3 ubiquitin ligases (CRLs) regulate homeostasis of ~20% of cellular proteins and their activation require neddylation of their cullin subunit. Cullin neddylation is modulated by a scaffolding DCN protein through interactions with both the cullin protein and an E2 enzyme such as UBC12. Here we report the development of DI-591 as a high-affinity, cell-permeable small-molecule inhibitor of the DCN1-UBC12 interaction. DI-591 binds to purified recombinant human DCN1 and DCN2 proteins with K i values of 10-12 nM, and disrupts the DCN1-UBC12 interaction in cells. Treatment with DI-591 selectively converts cellular cullin 3 into an un-neddylated inactive form with no or minimum effect on other cullin members. Our data firmly establish a previously unrecognized specific role of the DCN1-UBC12 interaction for cellular neddylation of cullin 3. DI-591 is an excellent probe compound to investigate the role of the cullin 3 CRL ligase in biological processes and human diseases.

Deciphering Cryptic Binding Sites on Proteins by Mixed-Solvent Molecular Dynamics

In recent years, molecular dynamics simulations of proteins in explicit mixed solvents have been applied to various problems in protein biophysics and drug discovery, including protein folding, protein surface characterization, fragment screening, allostery, and druggability assessment. In this study, we perform a systematic study on how mixtures of organic solvent probes in water can reveal cryptic ligand binding pockets that are not evident in crystal structures of apo proteins. We examine a diverse set of eight PDB proteins that show pocket opening induced by ligand binding and investigate whether solvent MD simulations on the apo structures can induce the binding site observed in the holo structures. The cosolvent simulations were found to induce conformational changes on the protein surface, which were characterized and compared with the holo structures. Analyses of the biological systems, choice of probes and concentrations, druggability of the resulting induced pockets, and application to drug discovery are discussed here.

A natural product-like JAK2/STAT3 inhibitor induces apoptosis of malignant melanoma cells

The JAK2/STAT3 signaling pathway plays a critical role in tumorigenesis, and has been suggested as a potential molecular target for anti-melanoma therapeutics. However, few JAK2 inhibitors were being tested for melanoma therapy. In this study, eight amentoflavone analogues were evaluated for their activity against human malignant melanoma cells. The most potent analogue, compound 1, inhibited the phosphorylation of JAK2 and STAT3 in human melanoma cells, but had no discernible effect on total JAK2 and STAT3 levels. A cellular thermal shift assay was performed to identify that JAK2 is engaged by 1 in cell lysates. Moreover, compound 1 showed higher antiproliferative activity against human melanoma A375 cells compared to a panel of cancer and normal cell lines. Compound 1 also activated caspase-3 and cleaved PARP, which are markers of apoptosis, and suppressed the anti-apoptotic Bcl-2 level. Finally, compound 1 induced apoptosis in 80% of treated melanoma cells. To our knowledge, compound 1 is the first amentoflavone-based JAK2 inhibitor to be investigated for use as an anti-melanoma agent.

Driving Structure-Based Drug Discovery through Cosolvent Molecular Dynamics

Identifying binding hotspots on protein surfaces is of prime interest in structure-based drug discovery, either to assess the tractability of pursuing a protein target or to drive improved potency of lead compounds. Computational approaches to detect such regions have traditionally relied on energy minimization of probe molecules onto static protein conformations in the absence of the natural aqueous environment. Advances in high performance computing now allow us to assess hotspots using molecular dynamics (MD) simulations. MD simulations integrate protein flexibility and the complicated role of water, thereby providing a more realistic assessment of the complex kinetics and thermodynamics at play. In this review, we describe the evolution of various cosolvent-based MD techniques and highlight a myriad of potential applications for such technologies in computational drug development.

Structure-based design of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoates as selective inhibitors of the Mcl-1 oncoprotein

Structure-based drug design was utilized to develop novel, 1-hydroxy-2-naphthoate-based small-molecule inhibitors of Mcl-1. Ligand design was driven by exploiting a salt bridge with R263 and interactions with the p2 pocket of the protein. Significantly, target molecules were accessed in just two synthetic steps, suggesting further optimization will require minimal synthetic effort. Molecular modeling using the Site-Identification by Ligand Competitive Saturation (SILCS) approach was used to qualitatively direct ligand design as well as develop quantitative models for inhibitor binding affinity to Mcl-1 and the Bcl-2 relative Bcl-xL as well as for the specificity of binding to the two proteins. Results indicated hydrophobic interactions in the p2 pocket dominated affinity of the most favourable binding ligand (3bl: Ki = 31 nM). Compounds were up to 19-fold selective for Mcl-1 over Bcl-xL. Selectivity of the inhibitors was driven by interactions with the deeper p2 pocket in Mcl-1 versus Bcl-xL. The SILCS-based SAR of the present compounds represents the foundation for the development of Mcl-1 specific inhibitors with the potential to treat a wide range of solid tumours and hematological cancers, including acute myeloid leukemia.

Enrichment of druggable conformations from apo protein structures using cosolvent-accelerated molecular dynamics

Here we describe the development of an improved workflow for utilizing experimental and simulated protein conformations in the structure-based design of inhibitors for anti-apoptotic Bcl-2 family proteins. Traditional structure-based approaches on similar targets are often constrained by the sparsity of available structures and difficulties in finding lead compounds that dock against flat, flexible protein-protein interaction surfaces. By employing computational docking of known small molecule inhibitors, we have demonstrated that structural ensembles derived from either accelerated MD (aMD) or MD in the presence of an organic cosolvent generally give better scores than those assessed from analogous conventional MD. Furthermore, conformations obtained from combined cosolvent aMD simulations started with the apo-Bcl-xL structure yielded better average and minimum docking scores for known binders than an ensemble of 72 experimental apo- and ligand-bound Bcl-xL structures. A detailed analysis of the simulated conformations indicates that the aMD effectively enhanced conformational sampling of the flexible helices flanking the main Bcl-xL binding groove, permitting the cosolvent acting as small ligands to penetrate more deeply into the binding pocket and shape ligand-bound conformations not evident in conventional simulations. We believe this approach could be useful for identifying inhibitors against other protein-protein interaction systems involving highly flexible binding sites, particularly for targets with less accumulated structural data.

Identification of potential small molecule allosteric modulator sites on IL-1R1 ectodomain using accelerated conformational sampling method

The interleukin-1 receptor (IL-1R) is the founding member of the interleukin 1 receptor family which activates innate immune response by its binding to cytokines. Reports showed dysregulation of cytokine production leads to aberrant immune cells activation which contributes to auto-inflammatory disorders and diseases. Current therapeutic strategies focus on utilizing antibodies or chimeric cytokine biologics. The large protein-protein interaction interface between cytokine receptor and cytokine poses a challenge in identifying binding sites for small molecule inhibitor development. Based on the significant conformational change of IL-1R type 1 (IL-1R1) ectodomain upon binding to different ligands observed in crystal structures, we hypothesized that transient small molecule binding sites may exist when IL-1R1 undergoes conformational transition and thus suitable for inhibitor development. Here, we employed accelerated molecular dynamics (MD) simulation to efficiently sample conformational space of IL-1R1 ectodomain. Representative IL-1R1 ectodomain conformations determined from the hierarchy cluster analysis were analyzed by the SiteMap program which leads to identify small molecule binding sites at the protein-protein interaction interface and allosteric modulator locations. The cosolvent mapping analysis using phenol as the probe molecule further confirms the allosteric modulator site as a binding hotspot. Eight highest ranked fragment molecules identified from in silico screening at the modulator site were evaluated by MD simulations. Four of them restricted the IL-1R1 dynamical motion to inactive conformational space. The strategy from this study, subject to in vitro experimental validation, can be useful to identify small molecule compounds targeting the allosteric modulator sites of IL-1R and prevent IL-1R from binding to cytokine by trapping IL-1R in inactive conformations.

Parameter choice matters: validating probe parameters for use in mixed-solvent simulations

Probe mapping is a common approach for identifying potential binding sites in structure-based drug design; however, it typically relies on energy minimizations of probes in the gas phase and a static protein structure. The mixed-solvent molecular dynamics (MixMD) approach was recently developed to account for full protein flexibility and solvation effects in hot-spot mapping. Our first study used only acetonitrile as a probe, and here, we have augmented the set of functional group probes through careful testing and parameter validation. A diverse range of probes are needed in order to map complex binding interactions. A small variation in probe parameters can adversely effect mixed-solvent behavior, which we highlight with isopropanol. We tested 11 solvents to identify six with appropriate behavior in TIP3P water to use as organic probes in the MixMD method. In addition to acetonitrile and isopropanol, we have identified acetone, N-methylacetamide, imidazole, and pyrimidine. These probe solvents will enable MixMD studies to recover hydrogen-bonding sites, hydrophobic pockets, protein–protein interactions, and aromatic hotspots. Also, we show that ternary-solvent systems can be incorporated within a single simulation. Importantly, these binary and ternary solvents do not require artificial repulsion terms like other methods. Within merely 5 ns, layered solvent boxes become evenly mixed for soluble probes. We used radial distribution functions to evaluate solvent behavior, determine adequate mixing, and confirm the absence of phase separation. We recommend that radial distribution functions should be used to assess adequate sampling in all mixed-solvent techniques rather than the current practice of examining the solvent ratios at the edges of the solvent box.

3-Substituted-N-(4-hydroxynaphthalen-1-yl)arylsulfonamides as a novel class of selective Mcl-1 inhibitors: structure-based design, synthesis, SAR, and biological evaluation

Mcl-1, an antiapoptotic member of the Bcl-2 family of proteins, is a validated and attractive target for cancer therapy. Overexpression of Mcl-1 in many cancers results in disease progression and resistance to current chemotherapeutics. Utilizing high-throughput screening, compound 1 was identified as a selective Mcl-1 inhibitor and its binding to the BH3 binding groove of Mcl-1 was confirmed by several different, but complementary, biochemical and biophysical assays. Guided by structure-based drug design and supported by NMR experiments, comprehensive SAR studies were undertaken and a potent and selective inhibitor, compound 21, was designed which binds to Mcl-1 with a Ki of 180 nM. Biological characterization of 21 showed that it disrupts the interaction of endogenous Mcl-1 and biotinylated Noxa-BH3 peptide, causes cell death through a Bak/Bax-dependent mechanism, and selectively sensitizes Eμ-myc lymphomas overexpressing Mcl-1, but not Eμ-myc lymphoma cells overexpressing Bcl-2. Treatment of human leukemic cell lines with compound 21 resulted in cell death through activation of caspase-3 and induction of apoptosis.

A novel small-molecule inhibitor of mcl-1 blocks pancreatic cancer growth in vitro and in vivo

Using a high-throughput screening (HTS) approach, we have identified and validated several small-molecule Mcl-1 inhibitors (SMI). Here, we describe a novel selective Mcl-1 SMI inhibitor, 2 (UMI-77), developed by structure-based chemical modifications of the lead compound 1 (UMI-59). We have characterized the binding of UMI-77 to Mcl-1 by using complementary biochemical, biophysical, and computational methods and determined its antitumor activity against a panel of pancreatic cancer cells and an in vivo xenograft model. UMI-77 binds to the BH3-binding groove of Mcl-1 with Ki of 490 nmol/L, showing selectivity over other members of the antiapoptotic Bcl-2 family. UMI-77 inhibits cell growth and induces apoptosis in pancreatic cancer cells in a time- and dose-dependent manner, accompanied by cytochrome c release and caspase-3 activation. Coimmunoprecipitation experiments revealed that UMI-77 blocks the heterodimerization of Mcl-1/Bax and Mcl-1/Bak in cells, thus antagonizing the Mcl-1 function. The Bax/Bak-dependent induction of apoptosis was further confirmed using murine embryonic fibroblasts that are Bax- and Bak-deficient. In an in vivo BxPC-3 xenograft model, UMI-77 effectively inhibited tumor growth. Western blot analysis in tumor remnants revealed enhancement of proapoptotic markers and significant decrease of survivin. Collectively, these promising findings show the therapeutic potential of Mcl-1 inhibitors against pancreatic cancer and warrant further preclinical investigations.

BcL-xL conformational changes upon fragment binding revealed by NMR

Protein-protein interactions represent difficult but increasingly important targets for the design of therapeutic compounds able to interfere with biological processes. Recently, fragment-based strategies have been proposed as attractive approaches for the elaboration of protein-protein surface inhibitors from fragment-like molecules. One major challenge in targeting protein-protein interactions is related to the structural adaptation of the protein surface upon molecular recognition. Methods capable of identifying subtle conformational changes of proteins upon fragment binding are therefore required at the early steps of the drug design process. In this report we present a fast NMR method able to probe subtle conformational changes upon fragment binding. The approach relies on the comparison of experimental fragment-induced Chemical Shift Perturbation (CSP) of amine protons to CSP simulated for a set of docked fragment poses, considering the ring-current effect from fragment binding. We illustrate the method by the retrospective analysis of the complex between the anti-apoptotic Bcl-xL protein and the fragment 4′-fluoro-[1,1′-biphenyl]-4-carboxylic acid that was previously shown to bind one of the Bcl-xL hot spots. The CSP-based approach shows that the protein undergoes a subtle conformational rearrangement upon interaction, for residues located in helices 2, 3 and the very beginning of 5. Our observations are corroborated by residual dipolar coupling measurements performed on the free and fragment-bound forms of the Bcl-xL protein. These NMR-based results are in total agreement with previous molecular dynamic calculations that evidenced a high flexibility of Bcl-xL around the binding site. Here we show that CSP of protein amine protons are useful and reliable structural probes. Therefore, we propose to use CSP simulation to assess protein conformational changes upon ligand binding in the fragment-based drug design approach.

The novel BH3 α-helix mimetic JY-1-106 induces apoptosis in a subset of cancer cells (lung cancer, colon cancer and mesothelioma) by disrupting Bcl-xL and Mcl-1 protein-protein interactions with Bak

Background

It has been shown in many solid tumors that the overexpression of the pro-survival Bcl-2 family members Bcl-2/Bcl-xL and Mcl-1 confers resistance to a variety of chemotherapeutic agents. We designed the BH3 α-helix mimetic JY-1-106 to engage the hydrophobic BH3-binding grooves on the surfaces of both Bcl-xL and Mcl-1.

Methods

JY-1-106–protein complexes were studied using molecular dynamics (MD) simulations and the SILCS methodology. We have evaluated the in vitro effects of JY-1-106 by using a fluorescence polarization (FP) assay, an XTT assay, apoptosis assays, and immunoprecipitation and western-blot assays. A preclinical human cancer xenograft model was used to test the efficacy of JY-1-106 in vivo.

Results

MD and SILCS simulations of the JY-1-106–protein complexes indicated the importance of the aliphatic side chains of JY-1-106 to binding and successfully predicted the improved affinity of the ligand for Bcl-xL over Mcl-1. Ligand binding affinities were measured via an FP assay using a fluorescently labeled Bak-BH3 peptide in vitro. Apoptosis induction via JY-1-106 was evidenced by TUNEL assay and PARP cleavage as well as by Bax–Bax dimerization. Release of multi-domain Bak from its inhibitory binding to Bcl-2/Bcl-xL and Mcl-1 using JY-1-106 was detected via immunoprecipitation (IP) western blotting.

At the cellular level, we compared the growth proliferation IC₅₀s of JY-1-106 and ABT-737 in multiple cancer cell lines with various Bcl-xL and Mcl-1 expression levels. JY-1-106 effectively induced cell death regardless of the Mcl-1 expression level in ABT-737 resistant solid tumor cells, whilst toxicity toward normal human endothelial cells was limited. Furthermore, synergistic effects were observed in A549 cells using a combination of JY-1-106 and multiple chemotherapeutic agents. We also observed that JY-1-106 was a very effective agent in inducing apoptosis in metabolically stressed tumors. Finally, JY-1-106 was evaluated in a tumor-bearing nude mouse model, and was found to effectively repress tumor growth. Strong TUNEL signals in the tumor cells demonstrated the effectiveness of JY-1-106 in this animal model. No significant side effects were observed in mouse organs after multiple injections.

Conclusions

Taken together, these observations demonstrate that JY-1-106 is an effective pan-Bcl-2 inhibitor with very promising clinical potential.

Structure-based design of high-affinity macrocyclic peptidomimetics to block the menin-mixed lineage leukemia 1 (MLL1) protein-protein interaction

Menin is an essential oncogenic cofactor for mixed lineage leukemia 1 (MLL1)-mediated leukemogenesis through its direct interaction with MLL1. Targeting the menin-MLL1 protein-protein interaction represents a promising strategy to block MLL1-mediated leukemogenesis. Employing a structure-based approach and starting from a linear MLL1 octapeptide, we have designed a class of potent macrocyclic peptidomimetic inhibitors of the menin-MLL1 interaction. The most potent macrocyclic peptidomimetic (MCP-1), 34, binds to menin with a K(i) value of 4.7 nM and is >600 times more potent than the corresponding acyclic peptide. Compound 34 is also less peptide-like and has a lower molecular weight than the initial MLL1 peptide. Therefore, compound 34 serves as a promising lead structure for the design of potent and cell-permeable inhibitors of the menin-MLL1 interaction.

Fragment-based design, synthesis, and biological evaluation of N-substituted-5-(4-isopropylthiophenol)-2-hydroxynicotinamide derivatives as novel Mcl-1 inhibitors

We have previously reported a nanomolar inhibitor of antiapoptotic Mcl-1 protein, 3-thiomorpholin-8-oxo-8H-acenaphtho [1,2-b] pyrrole-9-carbonitrile (S1). S1 plays its function by binding to the BH3 groove of Mcl-1. Basing on this spacial structural characteristic, we developed a novel class of Mcl-1 inhibitor using fragment-based drug discovery approach. By dissecting S1, we identified the compound 4 with a 2-hydroxypyridine core as the starting fragment. In the following molecular growth, we used the ligand efficiency evaluation and fit quality score to assess the fragments. A novel potent compound, N-benzyl-5-(4-isopropylthiophenol)-2-hydroxyl nicotinamide (12c), which binds Mcl-1 with an IC(50) value of 54 nM was obtained. Compound 12c demonstrated a better aqueous solubility than S1.