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

Lanning, Maryanna E.; Yu, Wenbo; Yap, Jeremy L.; Chauhan, Jay; Chen, Lijia; Whiting, E. E.; Pidugu, L.S.; Atkinson, Tyler; Bailey, Hala; Li, Willy; Roth, Braden M.; Hynicka, Lauren M.; Chesko, Kirsty L.; Toth, Eric A.; Shapiro, Paul; MacKerell, Alexander D.; Wilder, Paul T.; Fletcher, Steven

doi:10.1016/j.ejmech.2016.02.006

Cited by 41 publications

(37 citation statements)

References 69 publications

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“…A combination of in vitro and in silico approaches clarified that upon binding of an MCL‐1 inhibitor, Compound 3 to the residue Val253, the BH3‐binding groove of MCL‐1 gets narrowed down leading to less availability for PUMA BH3 domain interaction . Another critical residue was also identified recently as Arg263 in the P2 pocket of MCL‐1 . These residues evidently hold mechanistic insights to how MCL‐1 inhibitors most likely act on specific domains leading to a reorganization of the structural components, as well as to how further development on specificity could be achieved.…”

Section: Discussionmentioning

confidence: 99%

Selective targeting of antiapoptotic BCL‐2 proteins in cancer

Timuçin

Başağa

Kütük

2018

Medicinal Research Reviews

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Circumvention of apoptotic machinery is one of the distinctive properties of carcinogenesis. Extensively established key effectors of such apoptotic bypass mechanisms, the antiapoptotic BCL-2 (apoptosis regulator BCL-2) proteins, determine the response of cancer cells to chemotherapeutics. Within this background, research and development of antiapoptotic BCL-2 inhibitors were considered to have a tremendous amount of potential toward the discovery of novel pharmacological modulators in cancer. In this review, milestone achievements in the development of selective antiapoptotic BCL-2 proteins inhibitors for BCL-2, BCL-XL (BCL-2-like protein 1), and MCL-1 (induced myeloid leukemia cell differentiation protein MCL-1) were summarized and their future implications were discussed. In the first section, the design and development of BCL-2/BCL-XL dual inhibitor navitoclax, as well as the recent advances and clinical experience with selective BCL-2 inhibitor venetoclax, were synopsized. Preclinical data from selective BCL-XL inhibitors, which are currently undergoing extensive testing as a single agent or in combination with other therapeutic agents, were further summarized. In the second section, MCL-1 inhibitors developed as potential anticancer agents were reviewed regarding their specificity toward MCL-1. Explicitly, studies leading to the identification of MCL-1, nonselective and selective targeting of MCL-1, and recently initiated clinical trials were compiled in chronological order. Based on these concepts, future directions were further discussed for increasing selectivity in the design of prosurvival BCL-2 member inhibitors.

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Section: Discussionmentioning

confidence: 99%

Selective targeting of antiapoptotic BCL‐2 proteins in cancer

Timuçin

Başağa

Kütük

2018

Medicinal Research Reviews

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“…Also, the discovery of AZD5991 demonstrates selective targeting to Mcl1 [32]. Likewise, a recent study revealed a series of Mcl1 inhibitors that exhibited the potential to inhibit its overexpression activity [33]. Taking advantage of this, the current study is an attempt to understand the mechanistic behavior of the current compound series with Mcl1.…”

Section: Introductionmentioning

confidence: 95%

“…The inhibitor dataset used in the present work was retrieved based on the literature [33] from ChEMBL database (assay id:3779852) (https://www.ebi.ac.uk/chembl) ( Figure 1). An extensive investigation of the dataset revealed that the selected chemical dataset satisfies the necessary features-the same experimental type; covers a range of chemical structures and its inhibitory potency profiles (0.031 to 106 K i (µM))-required for the study.…”

Section: Obtaining Mcl1 Inhibitorsmentioning

confidence: 99%

“…To achieve this, a combination of in silico approaches-pharmacophore-based 3D-Quantitative Structure Activity Relationship, docking, and Molecular Dynamics (MD) simulation-is widely used [34][35][36][37][38][39][40]. Correspondingly, a pharmacophore-based 3D-QSAR model was constructed based on known inhibitors obtained from the literature [33], with the aim of gaining knowledge on the critical chemical features responsible for its maximum activity. Subsequently, the docking approach was used to predict the low-energy conformational pose for the highly active compound.…”

Section: Introductionmentioning

confidence: 99%

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Investigating the Molecular Basis of N-Substituted 1-Hydroxy-4-Sulfamoyl-2-Naphthoate Compounds Binding to Mcl1

2019

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Myeloid cell leukemia-1 (Mcl1) is an anti–apoptotic protein that has gained considerable attention due to its overexpression activity prevents cell death. Therefore, a potential inhibitor that specifically targets Mcl1 with higher binding affinity is necessary. Recently, a series of N-substituted 1-hydroxy-4-sulfamoyl-2-naphthoate compounds was reported that targets Mcl1, but its binding mechanism remains unexplored. Here, we attempted to explore the molecular mechanism of binding to Mcl1 using advanced computational approaches: pharmacophore-based 3D-QSAR, docking, and MD simulation. The selected pharmacophore—NNRRR—yielded a statistically significant 3D-QSAR model containing high confidence scores (R2 = 0.9209, Q2 = 0.8459, and RMSE = 0.3473). The contour maps—comprising hydrogen bond donor, hydrophobic, negative ionic and electron withdrawal effects—from our 3D-QSAR model identified the favorable regions crucial for maximum activity. Furthermore, the external validation of the selected model using enrichment and decoys analysis reveals a high predictive power. Also, the screening capacity of the selected model had scores of 0.94, 0.90, and 8.26 from ROC, AUC, and RIE analysis, respectively. The molecular docking of the highly active compound—C40; 4-(N-benzyl-N-(4-(4-chloro-3,5-dimethylphenoxy) phenyl) sulfamoyl)-1-hydroxy-2-naphthoate—predicted the low-energy conformational pose, and the MD simulation revealed crucial details responsible for the molecular mechanism of binding with Mcl1.

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“…Accordingly, the FragMaps contain contributions from protein-functional group interactions, protein flexibility, and desolvation of both the functional groups and the protein. The FragMaps can then be Boltzmann weighted into a free energy representation, termed grid free energy (GFE) FragMaps, which can be used in various receptor-based computer-aided drug design methods such as identification of cryptic binding pockets, 22 ligand docking and optimization, [23][24][25][26] or pharmacophore searching. 27,28 As the SILCS GFE FragMaps include intrinsic contributions from protein flexibility and desolvation effects, their application in PPI prediction may help solve the main limitations discussed above.…”

mentioning

confidence: 99%

Exploring protein‐protein interactions using the site‐identification by ligand competitive saturation methodology

Lakkaraju

et al. 2019

Proteins

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Protein docking methods are powerful computational tools to study protein‐protein interactions (PPI). While a significant number of docking algorithms have been developed, they are usually based on rigid protein models or with limited considerations of protein flexibility and the desolvation effect is rarely considered in docking energy functions, which may lower the accuracy of the predictions. To address these issues, we introduce a PPI energy function based on the site‐identification by ligand competitive saturation (SILCS) framework and utilize the fast Fourier transform (FFT) correlation approach. The free energy content of the SILCS FragMaps represent an alternative to traditional energy grids and they can be efficiently utilized to guide FFT‐based protein docking. Application of the approach to eight diverse test cases, including seven from Protein Docking Benchmark 5.0, showed the PPI prediction using SILCS approach (SILCS‐PPI) to be competitive with several commonly used protein docking methods indicating that the method has the ability to both qualitatively and quantitatively inform the prediction of PPI. Results show the utility of the SILCS‐PPI docking approach for determination of probability distributions of PPI interactions over the surface of both partner proteins, allowing for identification of alternate binding poses. Such binding poses are confirmed by experimental crystal contacts in our test cases. While more computationally demanding than available PPI docking technologies, we anticipate that the SILCS‐PPI docking approach will offer an alternative methodology for improved evaluation of PPIs that could be used in a variety of fields from systems biology to excipient design for biologics‐based drugs.

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

Cited by 41 publications

References 69 publications

Selective targeting of antiapoptotic BCL‐2 proteins in cancer

Selective targeting of antiapoptotic BCL‐2 proteins in cancer

Investigating the Molecular Basis of N-Substituted 1-Hydroxy-4-Sulfamoyl-2-Naphthoate Compounds Binding to Mcl1

Exploring protein‐protein interactions using the site‐identification by ligand competitive saturation methodology

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