Bevacizumab and trastuzumab are two antibody based antiangiogenic drugs that are in clinical practice for the treatment of different cancers. Presently applications of these drugs are based on the empirical choice of clinical experts that follow towards population based clinical trials and, hence, their molecular efficacies in terms of quantitative estimates are not being explored. Moreover, different clinical trials with these drugs showed different toxicity symptoms in patients. Here, using molecular docking study, we made an attempt to reveal the molecular rationale regarding their efficacy and off-target toxicity. Though our study reinforces their antiangiogenic potentiality and, among the two, trastuzumab has much higher efficacy; however, this study also reveals that compared to bevacizumab, trastuzumab has higher toxicity effect, specially on the cardiovascular system. This study also reveals the molecular rationale of ocular dysfunction by antiangiogenic drugs. The molecular rationale of toxicity as revealed in this study may help in the judicious choice as well as therapeutic scheduling of these drugs in different cancers.
Solid tumor survives by the process of angiogenesis. Angiogenesis is a physiological process by which microvessels are developed around the tumor mass. Tumor cells secrete a variety of tumor associated growth factors (TAF) like VEGF (vascular endothelial growth factor), TGF (transforming growth factor), EGF (epidermal growth factor), PDGF (platelet-derived growth factor), PAI, and TSP-1 to promote the process of angiogenesis [
In control of tumor growth, anti-VEGF antibody is being developed. Application of Avastin (bevacizumab), the commercially available anti-VEGF, has a remarkable success in the control of tumor growth in different clinical trials. For AAG therapy another antibody molecule known as trastuzumab has developed. Trastuzumab has the ability to inhibit a variety of other angiogenic molecules, namely, transforming growth factor (TGF), Ang-1, PAI-1, and thrombospondin 1 (TSP1) that might also respond to HER signaling [
Bevacizumab was the first antiangiogenic drug that was approved by the U.S. Food and Drug Administration (FDA) in 2004 for different metastatic cancers either alone or in combination with standard chemotherapy (Table
FDA-approved different antibody based antiangiogenic drugs.
Drug (MW) | Drug target | Recommended dose (half-life) | Types of cancer that are recommended for treatment |
---|---|---|---|
Bevacizumab, available as Avastin (149 KD) | VEGF receptor | IV infusion of 5–10 mg/kg body wt. in every 2 or 3 weeks (~20 days) | Metastatic colon, colorectal, cervical and peritoneal cancer with std. CT; platinum rst. ovarian or fallopian tube cancer; metastatic HER2 negative breast cancer; renal carcinoma; first-line treatment of non-small-cell lung cancer; second-line treatment of glioblastoma, different types of hematological malignancies |
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Trastuzumab, available as Herceptin (145.5 KD) | HER-2 | IV infusion of 2–8 mg/kg body wt. in every week (~28.5 days) | HER-2 overexpressing including ER/PR negative and node positive or negative breast cancer in combination with either anthracycline based (paclitaxel or docetaxel) or cisplatin and capecitabine or 5-fluorouracil or carboplatin chemotherapy; HER-2 positive metastatic gastric or gastroesophageal junction endocarcinoma without prior chemotherapy |
IV: intravenous administration; std.: standard; CT: chemotherapy; rst.: resistant; TK: tyrosine kinase; wt.: weight.
Trastuzumab is a IgG1 kappa monoclonal humanized antibody, produced in CHO cell line, approved by FDA in 2006 for treatment regimen containing doxorubicin, cyclophosphamide, and paclitaxel for the adjuvant treatment of women with node-positive, Her-2 overexpressing breast cancer. It is active against the human epidermal growth factor receptor 2 or Her-2/Neu and the binding of trastuzumab leads to complement mediated killing of the HER-2 positive cells (Table
Though both drugs are being in clinical use as antiangiogenic drugs, their pharmacological evaluation specially the efficacy and/or toxicity assessment in quantitative terms has not been evaluated. Previously, the molecular rationale of off-target toxicity of different drugs is established by using molecular docking interaction method between an array of receptors present within the physiological system and different adjuvant drugs of breast cancer [
For the present work we have used Hex, an open source, freely available software for academic use. The present work is done with the data resources that are available in the public domain. Table
Sources of PDB files used in the study.
Receptor/drug | Code/accession number | Website reference |
---|---|---|
Androgen receptor | PDB ID 2YHD (edited) |
|
Beta-1 receptor | PDB ID 2VT4 (edited) | ” |
Beta-2 receptor | PDB ID 2R4R (edited) | ” |
Dopamine-2 |
PDB ID 2YOU (edited) | ” |
Estrogen- |
PDB ID 1X7E (edited) | ” |
GABA-A receptor | PDB ID 3D32 (edited) | ” |
GABA-B receptor | PDB ID 1SRZ (edited) | ” |
Histamine (H2) receptor | Univ. of Michigan |
|
Angiotensin II |
PDB ID 3D0G (edited) |
|
Nitric oxide synthase (NOS) | PDB ID 1ED5 (edited) | ” |
Tyrosine kinase (TK) | PDB ID 1M17 (edited TK domain of EGF) |
|
Adrenoceptor alpha 2a (ADRA2A) | PDB ID 1HLL | ” |
Angiotensin converting enzyme (ACE) | PDB ID 4UFA | ” |
Ca-channel | PDB ID 1T3L | ” |
Her-2/Neu | PDB ID 1S78 (edited) |
|
VEGF |
PDB ID 2XIX (edited) | ” |
Angiotensin II | PDB ID 1ZV0 (edited) | ” |
NNA |
PDB ID 8NSE | ” |
Imatinib | Primary Acc. number DB00619 |
|
Cyproterone | Primary Acc. number DB04839 | ” |
Nandrolone | Primary Acc. number DB00984 | ” |
Propranolol | Primary Acc. number DB00571 | ” |
Epinephrine | Primary Acc. number DB00668 | ” |
Risperidone | Primary Acc. number DB00734 | ” |
Cabergoline | Primary Acc. number DB00248 | ” |
Flumazenil | Primary Acc. number DB01205 | ” |
Diazepam | Primary Acc. number DB00829 | ” |
Tamoxifen | Primary Acc. number DB00675 |
|
Ethinyl estradiol | Primary Acc. number DB00977 | ” |
Saclofen | Marvin sketched at |
|
Baclofen | Primary Acc. number DB00181 |
|
Ranitidine | Primary Acc. number DB00863 | ” |
Betazole | Primary Acc. number DB00272 | ” |
Losartan | Primary Acc. number DB00678 | ” |
Yohimbine | Primary Acc. number DB01392 | ” |
Clonidine | Primary Acc. number DB00575 | ” |
Lisinopril | Primary Acc. number DB00722 | ” |
Nifedipine | Primary Acc. number DB01115 | ” |
Bevacizumab/Avastin | Primary Acc. number DB00112 | ” |
Trastuzumab/Herceptin | Primary Acc. number DB00072 | ” |
Substance P | Primary Acc. number DB05875 | ” |
Molecular docking is performed using Hex program. Molecular docking helps in predicting the intermolecular interactions after forming an intermolecular complex between two constituent molecules. It uses spherical polar Fourier (SPF) correlations to accelerate the calculations. Using this program we have docked between receptor/enzyme and AAG drug (antibody)/drug in different combinations [ From the File menu the Receptor and Ligand files were opened. When two molecules are loaded the scene origin is taken as the midpoint between the two molecular centroids. Although both receptor and ligand move during docking, generally more motion is assigned to the ligand and keeping the receptor fixed though this can be changed by pressing the Select origin button. There are few Protein-Protein software programs that give output in terms of energy; Hex is an exception although the energy output is closer to internal energy ( Now the relation between After the Docking is activated from the Controls menu, the Energy is output together with the diagram of the docked complex.
For viewing the results of hex docking, we used Hex itself. After docking, the distance between two different molecules is also determined.
Rigorous docking experiments had been performed to assess the comparative efficacy between two clinically used AAG drugs and their cross-reactivity to different receptors and/or enzymes within the physiological system. The AAG drugs, the receptors, and the corresponding docking results are listed in Table
Hex performed docked energies of drug (antibody) − receptor/enzyme and drug (antagonist/agonist) − receptor/enzyme in
Receptor/enzyme | Drug/ligand | |||
---|---|---|---|---|
Bevacizumab/Avastin | Trastuzumab/Herceptin | Known antagonist | Known agonist | |
( |
−217.19 |
−680.07 |
Cyproterone = −195.13 | Nandrolone = −239.81 |
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( |
0.00 |
−480.80 |
Propranolol = −205.44 | Epinephrine = −150.35 |
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( |
−200.73 |
−655.19 |
Propranolol = −218.25 | Epinephrine = −148.88 |
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( |
−513.80 |
−299.85 |
Risperidone = −114.72 | Cabergoline = −130.19 |
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( |
−327.20 |
−712.68 |
Tamoxifen = −223.14 | Ethinyl estrogen = −186.48 |
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( |
−432.29 |
−680.98 |
Flumazenil = −69.88 | Diazepam = −127.70 |
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( |
−626.88 |
−641.84 |
Saclofen = −170.79 | Baclofen = −176.46 |
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( |
−677.13 |
−687.69 |
Ranitidine = −224.76 | Betazole = −144.17 |
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( |
0.00 |
−369.66 |
Losartan = −268.32 | Angiotensin II = −460.09 |
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( |
−69.39 |
−745.53 |
NNA = −196.39 | Substance P = −458.63 |
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( |
−294.73 |
−567.61 |
Imatinib = −283.36 | Not known |
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( |
−633.40 |
−740.85 |
Yohimbine = −182.45 | Clonidine = −132.03 |
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( |
−243.12 |
−403.71 |
Lisinopril = −234.14 | Not known |
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( |
−241.56 |
−652.58 |
Nifedipine = −221.68 | Not known |
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( |
−376.03 |
−562.51 |
Not known | Not known |
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( |
−741.08 |
−721.08 |
Not known | Not known |
Our docking study reveals that the binding affinity of bevacizumab to VEGF receptor (−741.08) is much higher than its binding to Her-2/Neu receptor (−376.03). Binding affinity of trastuzumab to VEGF receptor (−721.08) is higher than Her-2/Neu receptor (−562.51) though it is much higher than the binding affinity of bevacizumab to Her-2/Neu receptor (−376.03) (Table
Docked conformation of bevacizumab to VEGF (a) and Her-2/Neu receptor (b), and trastuzumab to Her-2/Neu (c) and VEGF receptor (d); the receptor protein is in cyan color.
Both AAG drugs bind to beta-2, tyrosine kinase (TK) receptor, and NO synthase which indicate their antiangiogenic potentiality. Interestingly, compared to bevacizumab, trastuzumab has the higher binding affinity to beta-1, beta-2, tyrosine kinase receptors, and NO synthase. This result may indicate that antiangiogenic potentiality of trastuzumab may be higher than bevacizumab. However, these results also indicate the reason of hypertension and cardiac myopathy in trastuzumab treated patients and why they need special attention when they show symptoms of hypertension and cardiac myopathy. Interestingly, the majority of cases, binding affinity of both the AAG drugs to different receptors/enzymes, are much higher compared to the known ligands (antagonist/agonist) to those receptors/enzymes. Trastuzumab has the highest binding towards NO synthase (−743.53) among the studied receptor/enzyme molecules in this work. Contrarily, bevacizumab has much less binding affinity towards NO synthase compared to their known ligands (antagonist/agonist); therefore there is much less chance of cardiac myopathy by this drug (Table
Docked conformation of bevacizumab (a), trastuzumab (b), NNA (c), and substance P (d) to NO synthase (in cyan color).
Bevacizumab does not have any binding affinity to angiotensin II type I (AT 1) and beta-1 receptor. However, binding affinity of bevacizumab is very close to angiotensin converting enzyme (ACE) antagonist lisinopril. Compared to trastuzumab it has also less affinity for ACE; so the cause of observed hypertension by the use of bevacizumab may be due to destruction of microvessels or it may act as an agonist for ACE, whereas higher binding of trastuzumab to ACE may indicate the cause of infusion reaction by trastuzumab [
Both AAG drugs showed much higher binding affinity towards estrogen receptor (ER); hence, both of them would be effective in estrogen positive breast/ovarian cancer. Compared to bevacizumab, trastuzumab has increased binding affinity to ER-alpha; therefore trastuzumab may also be more effective in controlling of estrogen positive breast/ovarian cancer (Table
Docked conformation of bevacizumab (a), trastuzumab (b), tamoxifen (c), and ethinyl estradiol (d) to estrogen receptor alpha (in cyan color).
Our docking results also reveal that both AAG drugs have a higher binding affinity towards dopamine-2 receptor [bevacizumab (−513.8) > trastuzumab (−299.85)]; this data indicates why the symptom of nausea is more pronounced with bevacizumab treatment than with trastuzumab (Figure
Docked conformation of bevacizumab (a), trastuzumab (b), risperidone (c), and cabergoline (d) to dopamine-2 receptor (in cyan color).
Long-term treatment is necessary for different cancers. But conventional chemotherapies have toxic side effect. Hence there is a search for specificity in cancer treatment. It is expected that monoclonal antibody based drugs may provide that way out. Though both bevacizumab and trastuzumab are FDA-approved antiangiogenic drugs in clinical use for the therapy of a wide variety of cancers, their efficacy and/or selection for clinical use are in empirical state. There are scanty report regarding their selection and drug scheduling for different cancers. Different clinical trials suggest for combination therapy even with the conventional chemotherapy. So our computational prediction is useful due to scanty data availability.
Though different analytical and simulation based studies showed that the efficacies of such drugs may have better in control of tumor growth, different clinical reports suggest that these monoclonal antibody based drugs do not qualify towards the expected criteria of overcoming the physiological toxicity [
Previously different docking studies (using Autodock and/or Hex) have proved the efficacy of macromolecular interactions as well as drug-macromolecular interactions, where docking results indicate the fact that the more the negative energy, the more the binding efficacy [
The present docking based study indicates that trastuzumab has better antiangiogenic potentiality compared to bevacizumab; however, it has much more side effects on the cardiovascular system. The major problems of using AAG drugs are nausea, hypertension, gastric ulceration, and ocular damage. Our docking study reveals its molecular rationale as the binding affinity of both AAG drugs on D2, beta-2, GABA, ACE, Ca-channel, H2, and ADRA2A; most importantly trastuzumab has the highest binding affinity for NOS; this may be the probable cause that in trastuzumab treatment cardiomyopathy needs special attention. Our data also indicate that, in bevacizumab treated patients, synergistic application of other immunotherapy is also possible.
This in silico study may provide the molecular rationale of toxicity within the physiological system and hints towards the probable cause of pathophysiological alteration with the application of AAG drugs in patients. With the availability of time dependent data related to the onset toxicological symptoms by AAG drugs, a correlation study between the two would then be beneficial in the future particularly for the calibration of drug scheduling. Hence, generation of dynamical database regarding cancer treatment along with the onset of toxicological symptoms in humans (for different drugs) is needed. Towards this aspect this study has the significance.
The authors declare that there is no conflict of interests.
The authors acknowledge the critical comments of the eminent founder members of Society for Systems Biology & Translational Research, India.