Discovery of Novel Ligands for TNF-Î± and TNF Receptor-1 through

Subscriber access provided by ORTA DOGU TEKNIK UNIVERSITESI KUTUPHANESI

Article

Discovery of Novel Ligands for TNF-# and TNF Receptor-1 through Structure-Based Virtual Screening and Biological Assay Si Chen, Zhiwei Feng, Yun Wang, Shifan Ma, Ziheng Hu, Peng Yang, Yifeng Chai, and Xiang-Qun (Sean) Xie J. Chem. Inf. Model., Just Accepted Manuscript • Publication Date (Web): 19 Apr 2017 Downloaded from http://pubs.acs.org on April 20, 2017

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Journal of Chemical Information and Modeling is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Journal of Chemical Information and Modeling

Discovery of Novel Ligands for TNF-α and TNF Receptor-1 through Structure-Based Virtual Screening and Biological Assay Si Chena, b , Zhiwei Fenga, , Yun Wangb, , Shifan Maa, Ziheng Hua, Peng Yanga, Yifeng Chaib,* and Xiangqun Xiea,* a, Department of Pharmaceutical Sciences and Computational Chemical Genomics Screening Center, School of Pharmacy; National Center of Excellence for Computational Drug Abuse Research; Drug Discovery Institute; Departments of Computational Biology and Structural Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States. b, School of Pharmacy, Second Military Medical University, 325 Guohe Road, Shanghai, 200433, China

ACS Paragon Plus Environment

Journal of Chemical Information and Modeling 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

ABSTRACT Tumor Necrosis Factor alpha (TNF-α) is overexpressed in various diseases, and it has been a validated therapeutic target for autoimmune diseases. All therapeutics currently used targeting TNF-α are biomacromolecules, and limited numbers of TNF-α chemical inhibitors have been reported, which makes the identification of small molecule alternatives in urgent need. Recent studies mainly focused on identifying small molecules that directly bind to TNF-α or TNF receptor-1 (TNFR1), and/or inhibit the interaction between TNF-α and TNFR1, and/or regulate related signaling pathways. In this study, we combined in silico methods with biophysical and cell-based assays to identify novel antagonists binding with TNF-α or TNFR1. Pharmacophore model and molecular docking were applied to identify potential TNF-α antagonist. As to TNFR1, we constructed the 3D model of TNFR1-TNF-α complex, and carried out molecular dynamics (MD) simulations to sample the conformations. The residues in TNF-α that have been reported to play important roles in TNFR1-TNF-α complex were removed to form a pocket for further virtual screening of TNFR1 binding ligands. We obtained 20 virtual hits and tested them using surface plasmon resonance (SPR) based assays, which resulted in one ligand binding with TNFR1 and four ligands of different scaffolds binding with TNF-α. T1 and R1, the two most active compounds with respective Kd values of 11 and 16 µM for TNF-α and TNFR1, showed similar activity to those of known antagonists. Further cell-based assay also demonstrated that T1 and R1 had similar activities compared to the known TNF-α antagonist C87. Our work not only produces several TNF-α and TNFR1 antagonists with novel scaffolds for further structural optimization, but also showcases the power of our in silico methods for TNF-α and TNFR1 based drug discovery.


Page 2 of 32

Page 3 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


INTRODUCTION TNF-α

is

an

important

immunomodulatory effects.1,

cytokine 2

with

powerful

proinflammatory

and

Overexpression of TNF-α is widely observed in

HIV,3 asthma,4 and in autoimmune diseases, such as rheumatoid arthritis,5 Crohn’s disease6 and psoriasis.7, 8 TNF-α has become a therapeutic target for autoimmune diseases with the successful launch of TNF-α antagonists, including infliximab, etanercept, adalimumab, certolizumab and glolimumab.9 However, these biologic therapies exhibited inevitable weakness, such as risk of infection,10 high cost and requirement for intravenous injections. By contrast, small molecule inhibitors were relatively cheaper and could be taken orally. Therefore, the identification of small molecules that can inhibit TNF-α regulated pathway presents a promising and current focus area. Recent researches mainly focused on identifying small molecules that directly bind to TNF-α or TNFR1,11, 12 and/or inhibit the binding of TNF-α and TNFR1,13, 14 and/or regulate related signal pathways.15 As shown in Figure 1, we summarized all published small molecule inhibitors that bind to TNF-α or TNFR1 with Kd50 µM). Kd (TNFR1) and Kd (TNF-α) were equilibrium dissociation constant showing compound binding affinity with TNFR1 and TNF-α by SPR analysis. IC50 (TNFR1-TNF-α) represented inhibitor activity tested with competitive inhibition of TNFR1 binding to immobilized TNF-α by ELISA. IC50 (TNF-α-TNFR1) was inhibitor activity tested with competitive inhibition of TNF-α binding to immobilized TNFR1 by ELISA. IC50 (cell based assay) indicated inhibition of TNF-α and TNFR1 related apoptosis or signaling change.


Page 22 of 32

Page 23 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2. (a) Residues in TNF-α (blue) binding with TNFR1 (hotpink). (b) Binding pocket (light blue) of TNFR1 (hotpink). The pocket was formed by TNFR1 and a monomer from TNF-α (blue). The important residues were shown in sticks, including residues in TNFR1 (Phe60, Ala62, Asn65, His66, Leu67 and Leu71) and residues in TNF-α (Arg82, Pro90, Gly129 and Arg131).



Figure 3. Time evolutions for the deviation of TNF-α-TNFR1 complex during 50 ns MD simulations.


Page 24 of 32

Page 25 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 4. Two-dimensional pharmacophore model H3 showed three aromatic centers (A). The model was based on SPD-304, which was crystallized with TNF-α (PDB code: 2AZ5).



Figure 5. Measurement of affinity constant by SPR analysis. (a) and (c) are sensograms recorded after injection of different concentrations of positive control (C87) and T1 respectively. (b) and (d) are the affinity constant Kd values of positive control (C87) and T1. The affinity constant Kd values were calculated by global fitting using a steady-state affinity model. Data in (a), (b), (c) and (d) were representatives of three independent experiments.

Figure 6. (a) Chemical structure of R1 from in silico screening. (b) The affinity constant Kd value of R1. The value was calculated by global fitting using a steadystate affinity model. Data in (b) was a representative of three independent experiments.


Page 26 of 32

Page 27 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 7. The inhibition activity of C87, R1, T1, T2, T3 and T4 on TNF-αmediated cytotoxicity on L929 cells. L929 cells were treated for 18 h with 10 ng/ml TNF-α and 1 µg/ml Actinomycin D in the presence of indicated concentrations of C87, R1, T1, T2, T3 and T4. C87 was used as a positive control. (a) Cell viability was examined under microscope (×200). (b), (c), (d), (f) and (g) TNF-α-mediated cytotoxicity on L929 cells were measured with CCK-8 assay.



Data were obtained from three independent experiments performed in triplicate and presented as means (±S.E.M.). *P < 0.05 vs. TNF-α only.

Figure 8. Detailed binding modes of antagonists with TNF-α, including (a) SPD304 and (b) T1. Three same hydrophobic interactions are formed in both SPD-304 and T1.

Figure 9. Detailed binding modes of antagonists with TNFR1, including (a) Residues (Ala84, Val85, Ser86, Tyr87, Gln88 and Thr89) in TNF-α and (b) R1.


Page 28 of 32

Page 29 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Two residues in TNFR1 (Ala62 and His66), formed strong hydrogen bonds with the antagonists. Table 1. Chemical structures, properties and TNF-α binding values of the hits from virtual screening. Compound

Structure

SPECS

ID

ID

T1

AG-

AlogP

MW

Kd (µM) TNF-α

5.5

442.45

11

5.11

479.53

58

5.81

562.50

72

4.81

422.50

113

690/11190 044

T2

AG690/15438 091

T3

AG205/37136 129

T4

AG667/37281 063


Journal of Chemical Information and Modeling 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Page 30 of 32

Table 2. Toxicity properties prediction of all biological hits. Compound

Structure

SPECS ID

Target

ID T1

Mutagenic

Tumorigenic

protein AG-

Reproductive

Irritant

effective

TNF-α

none

none

high

none

TNFR1

none

none

none

none

TNF-α

high

high

none

none

TNF-α

none

none

low

none

690/11190044

R1

AO022/43452581

T2

AG690/15438091

T3

AG205/37136129


Page 31 of 32 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


T4

AG-

TNF-α

high

667/37281063


high

none

none

Journal of Chemical Information and Modeling 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Graphical abstract


Page 32 of 32

Discovery of Novel Ligands for TNF-Î± and TNF Receptor-1 through

Recommend Documents