Antiangiogenic Peptide Research Articles

14K prolactin derived 14-mer antiangiogenic peptide targets bradykinin-/nitric oxide-cGMP-dependent angiogenesis.

Over the past few decades, VEGF-targeted antiangiogenic therapy for cancers has gained increasing attention. Nevertheless, there are still several limitations such as the potential resistance mechanisms arising in cancer cells against these therapies and their potential adverse effects. These limitations highlight the need for novel anti-angiogenesis molecules and better understanding of the mechanisms of tumor angiogenesis. In the present study, we investigated the antiangiogenic properties of a novel 14-mer antiangiogenic peptide (14-MAP) derived from N-terminal 14 kDa buffalo prolactin and characterized its mode of action. 14-MAP at the picomolar concentration inhibited VEGF- and bradykinin (an autacoid peptide expressed in vascular tissues in pathophysiology, BK)-stimulated endothelial nitric oxide (eNO) production, cell migration, and proliferation in endothelial cells and vessel development in the chick embryo. Although this peptide inhibited both VEGF- and BK-dependent angiogenic processes, its action was more pronounced in the latter. Moreover, the interference of 14-MAP with the eNO synthase (eNOS)-cyclic GMP pathway was also identified. A combination of a low dose of Avastin, a widely used drug targeting VEGF-dependent angiogenesis, and 14-MAP significantly reduced tumor size in an in vivo model of human colon cancer. Taken together, our results suggest that 14-MAP, a BK- and eNOS-dependent antiangiogenic peptide, might be useful for overcoming the limitation of VEGF-targeted antiangiogenic therapy in cancer patients. However, further studies will be required to further characterize its mode of action and therapeutic potential.

Improved prediction of anti-angiogenic peptides based on machine learning models and comprehensive features from peptide sequences

Angiogenesis is a key process for the proliferation and metastatic spread of cancer cells. Anti-angiogenic peptides (AAPs), with the capability of inhibiting angiogenesis, are promising candidates in cancer treatment. We propose AAPL, a sequence-based predictor to identify AAPs with machine learning models of improved prediction accuracy. Each peptide sequence was transformed to a vector of 4335 numeric values according to 58 different feature types, followed by a heuristic algorithm for feature selection. Next, the hyperparameters of six machine learning models were optimized with respect to the feature subset. We considered two datasets, one with entire peptide sequences and the other with 15 amino acids from peptide N-termini. AAPL achieved Matthew’s correlation coefficients of 0.671 and 0.756 for independent tests based on the two datasets, respectively, outperforming existing predictors by a range of 5.3% to 24.6%. Further analyses show that AAPL yields higher prediction accuracy for peptides with more hydrophobic residues, and fewer hydrophilic and charged residues. The source code of AAPL is available at https://github.com/yunzheng2002/Anti-angiogenic.

Chondroitin sulfate-based universal nanoparticle delivers angiogenic inhibitor and paclitaxel to exhibit a combination of chemotherapy and anti-angiogenic therapy

Blocking the tumor nutrient supply through angiogenic inhibitors is an effective treatment approach for malignant tumors. However, using angiogenic inhibitors alone may not be enough to achieve a significant tumor response. Therefore, we recently designed a universal drug delivery system combining chemotherapy and anti-angiogenic therapy to target tumor cells while minimizing drug-related side effects. This system (termed as PCCE) is composed of biomaterial chondroitin sulfate (CS), the anti-angiogenic peptide ES2, and paclitaxel (PTX), which collectively enhance antitumor properties. Interestingly, the PCCE system is conferred exceptional cell membrane permeability due to inherent characteristics of CS, including CD44 receptor-mediated endocytosis. The PCCE could respond to the acidic and high glutathione conditions, thereby releasing PTX and ES2. PCCE could effectively inhibit the proliferation, migration, and invasion of tumor cells and cause apoptosis, while PCCE can affect the endothelial cells tube formation and exert anti-angiogenic function. Consistently, more potent in vivo antitumor efficacy and non-toxic sides were demonstrated in B16F10 xenograft mouse models. PCCE can achieve excellent antitumor activity via modulating angiogenic and apoptosis-related factors. In summary, we have successfully developed an intelligent and responsive CS-based nanocarrier known as PCCE for delivering various antitumor drugs, offering a promising strategy for treating malignant tumors.

An arresten-derived anti-angiogenic peptide triggers apoptotic cell death in endothelial cells.

In recent years, anti-angiogenic peptides have received considerable attention as candidates for cancer treatment. Arresten is an angiogenesis inhibitor that cleaves from the α1 chain of type IV collagen and stimulates apoptosis in endothelial cells. We have recently indicated that a peptide corresponding to the amino acid 78 to 86 of arresten, so-called Ars, prevented the migration and tube formation of HUVECs and the colon carcinoma growth in mice significantly. The current study aimed to determine whether induction of apoptotic cell death in endothelial cells is one of the biochemical mechanisms of this anti-angiogenic peptide. This hypothesis was assessed using the MTT assay, cell cycle analysis, Annexin V-FITC/PI staining, BCL2, CASP8, CASP9, p53, and CDKN2A gene expression studies as well as evaluating apoptosis in tumor tissues by TUNEL assay. Results demonstrated that 40µM of Ars significantly stimulated 46.2% of early and late apoptosis in HUVECs compared to 13.6% in the untreated cells and did not significantly alter the cell cycle distribution. Moreover, BCL2 and CASP8 were down-regulated, while CASP9 and p53 were up-regulated in endothelial cells. CDKN2A gene expression, the regulator of G1 cell cycle arrest, was not significantly altered. It might be suggested that Ars induced apoptosis in endothelial cells through the mitochondrial pathway and had no effect on the cell cycle. Besides, Ars induced apoptosis significantly in vivo. However, further studies are required to confirm the detailed molecular mechanism of Ars, this peptide has the potential to be optimized for clinical translations.

Stack-AAgP: Computational prediction and interpretation of anti-angiogenic peptides using a meta-learning framework

Background:Angiogenesis plays a vital role in the pathogenesis of several human diseases, particularly in the case of solid tumors. In the realm of cancer treatment, recent investigations into peptides with anti-angiogenic properties have yielded encouraging outcomes, thereby creating a hopeful therapeutic avenue for the treatment of cancer. Therefore, correctly identifying the anti-angiogenic peptides is extremely important in comprehending their biophysical and biochemical traits, laying the groundwork for uncovering novel drugs to combat cancer. Methods:In this work, we present a novel ensemble-learning-based model, Stack-AAgP, specifically designed for the accurate identification and interpretation of anti-angiogenic peptides (AAPs). Initially, a feature representation approach is employed, generating 24 baseline models through six machine learning algorithms (random forest [RF], extra tree classifier [ETC], extreme gradient boosting [XGB], light gradient boosting machine [LGBM], CatBoost, and SVM) and four feature encodings (pseudo-amino acid composition [PAAC], amphiphilic pseudo-amino acid composition [APAAC], composition of k-spaced amino acid pairs [CKSAAP], and quasi-sequence-order [QSOrder]). Subsequently, the output (predicted probabilities) from 24 baseline models was inputted into the same six machine-learning classifiers to generate their respective meta-classifiers. Finally, the meta-classifiers were stacked together using the ensemble-learning framework to construct the final predictive model. Results:Findings from the independent test demonstrate that Stack-AAgP outperforms the state-of-the-art methods by a considerable margin. Systematic experiments were conducted to assess the influence of hyperparameters on the proposed model. Our model, Stack-AAgP, was evaluated on the independent NT15 dataset, revealing superiority over existing predictors with an accuracy improvement ranging from 5% to 7.5% and an increase in Matthews Correlation Coefficient (MCC) from 7.2% to 12.2%.

Chemokine-derived oncolytic peptide induces immunogenic cancer cell death and significantly suppresses tumor growth

Chemokinostatin-1 (CKS1) is a 24-mer peptide originally discovered as an anti-angiogenic peptide derived from the CXCL1 chemokine. Here, we demonstrate that CKS1 acts not only as an anti-angiogenic peptide but also as an oncolytic peptide due to its structural and physical properties. CKS1 induced both necrotic and apoptotic cell death specifically in cancer cells while showing minimal toxicity in non-cancerous cells. Mechanistically, CKS1 disrupted the cell membrane of cancer cells quickly after treatment and activated the apoptotic pathway at later time points. Furthermore, immunogenic molecules were released from CKS1-treated cells, indicating that CKS1 induces immunogenic cell death. CKS1 effectively suppressed tumor growth in vivo. Collectively, these data demonstrate that CKS1 functions as an oncolytic peptide and has a therapeutic potential to treat cancer.

Chondroitin sulfate-modified antiangiogenic peptide conjugate induces cell apoptosis via the mitochondria-mediated pathway to perform antitumor activity

Tumor growth and metastasis heavily rely on angiogenesis, crucial for solid tumor development. Inhibiting angiogenesis associated with tumors emerges as a potent therapeutic approach. Our previous work synthesized the chondroitin sulfate-modified antiangiogenic peptide CS-ES2-AF (CS-EA), which exhibited better antiangiogenic activity, longer half-life, and more robust targeting. In this work, we further evaluated the stability in vitro, cellular uptake mechanism, cell apoptosis mechanism, antitumor activity in vivo, and safety of CS-EA. The stability of CS-EA was consistently superior to that of EA at different temperatures and in different pH ranges. Furthermore, CS-EA mainly entered EAhy926 cells through the clathrin-mediated endocytosis pathway. CS-EA inhibited endothelial cell proliferation, and induced cell apoptosis through downregulating the Bcl-2, reducing mitochondria membrane potential, upregulating cytochrome c, Caspase 3, and reactive oxygen species levels. CS-EA showed better antitumor activity in the B16 xenografted tumor model, with a tumor inhibition rate 1.92 times higher than EA. Simultaneously, it was observed that CS-EA did not cause any harmful effects on the vital organs of the mice. These findings indicate that CS-EA holds significant promise for the treatment of tumors.

Enhancing the Inhibition of Corneal Neovascularization Efficacy by Self-Assembled into Supramolecular Hydrogel of Anti-Angiogenic Peptide.

Corneal neovascularization (CNV) is a common eye disease that leads to blindness. New treatment strategies are urgently needed due to the limitations of current treatment methods. We report the synthesis of peptide Nap-FFEEPCAIWF ( Comp.3 ) via chemical conjugation of Nap-FFEE ( Comp.2 ) to antiangiogenic peptide PCAIWF (Comp.1). Comp.3 self-assembled into a hydrogel ( gel of 3 ) composed of nanofibers, which enhanced the antiangiogenic function of the epitope. We developed a novel peptide with an amphiphilic framework, Comp.3 , which could self-assemble into a supramolecular hydrogel with a well-ordered nanofiber structure. The nanofibers exhibited good biocompatibility with corneal epithelial cells, presenting a promising strategy to enhance the efficacy of free peptide-based drugs in the treatment of ocular vascular diseases, such as CNV and other angiogenesis-related diseases. Nap-FFEEPCAIWF nanofibers provide an alternative approach to enhancing the therapeutic efficiency of free peptide-based drugs against ocular vascular diseases.

Dual targeting of DR5 and VEGFR2 molecular pathways by multivalent fusion protein significantly suppresses tumor growth and angiogenesis

Destroying tumor vasculature is a relevant therapeutic strategy due to its involvement in tumor progression. However, adaptive resistance to approved antiangiogenic drugs targeting VEGF/VEGFR pathway requires the recruitment of additional targets. In this aspect, targeting TRAIL pathway is promising as it is an important component of the immune system involved in tumor immunosurveillance. For dual targeting of malignant cells and tumor vascular microenvironment, we designed a multivalent fusion protein SRH-DR5-B-iRGD with antiangiogenic VEGFR2-specific peptide SRH at the N-terminus and a tumor-targeting and -penetrating peptide iRGD at the C-terminus of receptor-selective TRAIL variant DR5-B. SRH-DR5-B-iRGD obtained high affinity for DR5, VEGFR2 and αvβ3 integrin in nanomolar range. Fusion of DR5-B with effector peptides accelerated DR5 receptor internalization rate upon ligand binding. Antitumor efficacy was evaluated in vitro in human tumor cell lines and primary patient-derived glioblastoma neurospheres, and in vivo in xenograft mouse model of human glioblastoma. Multivalent binding of SRH-DR5-B-iRGD fusion efficiently stimulated DR5-mediated tumor cell death via caspase-dependent mechanism, suppressed xenograft tumor growth by >80 %, doubled the lifespan of xenograft animals, and inhibited tumor vascularization. Therefore, targeting DR5 and VEGFR2 molecular pathways with SRH-DR5-B-iRGD protein may provide a novel therapeutic approach for treatment of solid tumors.

Vascular endothelial growth factor antagonist peptides inhibit tumor growth and metastasis in breast cancer through repression of c-src and STAT3 genes.

Breast cancer is one of the most decisive causes of cancer death in women worldwide. Cancer progression and tumor metastasis depend on angiogenesis. Vascular endothelial growth factor (VEGF) and its receptors (VEGFR1 and VEGFR2) are critically required for tumor angiogenesis. Src is involved in many of the VEGF-mediated pathways. The VEGFRs activate Src via different mechanisms. Given that Src activates STAT3 (signal transducers and activators of transcription) repressing apoptosis and promoting the cell cycle, it may be an important object for cancer treatment. A series of VEGF antagonistic peptides, referred to as VGB 1,3 and 4, were designed to bind and block both VEGFR1 and VEGFR2 inhibiting the proliferation of different tumoral cells. We investigated c-Src and STAT3 gene expression changes in murine 4T1 tumors treated by the VGBs. The treated group received 1 and 10mgkg-1 of the peptides, while the control mice received PBS, intraperitoneally for two weeks. Both of the groups underwent a resection of breast tissue 14 days after treatment. The results of qRT-PCR showed that the expression levels of c-Src and STAT3 genes were significantly decreased, in a dose-dependent manner, after treatment with the different types of VEGF antagonist peptides, compared to the control groups (P < 0.05). The groups treated with 1mgkg-1 of all three types of VGB showed decreased expression of c-Src and STAT3 less than the groups receiving 10mgkg-1 of the anti-angiogenic peptides. In conclusion, peptides VGB1, 3, and 4, could be effective therapeutic molecules in breast cancer by inhibiting angiogenesis and progression of the disease.

Gel-forming therapeutic peptide exhibits sustained delivery and efficacy in a mouse model of triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a particularly aggressive and invasive subtype of breast cancer that represents a major cause of death of women worldwide. Here we describe the efficacy of an integrin-binding antiangiogenic peptide in a variety of delivery methods and dosing conditions. This peptide, AXT201, demonstrated consistent anti-tumor efficacy when administered intraperitoneally, subcutaneously, and intratumorally, and retained this activity even when dosing frequency was reduced to once every two weeks. Finally, in vivo imaging and biodistribution studies of AXT201 showed a long-term persistence of at least 10 days at the site of injection and a stable detectable signal in the blood over 48 h, indicating a sustained release profile. Taken together, these findings indicate AXT201 exhibits favorable pharmacokinetic properties for a 20-mer peptide.

CD44 targeting nanodrug based on chondroitin sulfate for melanoma therapy by inducing mitochondrial apoptosis pathways

Neovascularization is crucial to the occurrence and progression of tumors, and the development of antiangiogenic drugs has essential theoretical value and clinical significance. However, antiangiogenesis therapy alone cannot meet the needs of tumor therapy. Meanwhile, polysaccharides are ideal drug carriers with promising applications in drug modification and delivery. In this research, we developed a novel redox and acid sensitive nanodrug (CDDP-CS-Cys-EA, CCEA) composed of chondroitin sulfate (CS), antiangiogenic peptide (endostatin2-alft1, EA) and chemotherapeutic drug (cisplatin, CDDP). CCEA exhibited redox and acid responsiveness, better blood hemocompatibility (hemolysis rate < 5 %), the ability to target tumors (CD44-mediated endocytosis), and strong antiangiogenesis and antitumor characteristics in vitro. Moreover, CCEA showed excellent antitumor activity and low toxicity in B16 xenograft mice. It also has been confirmed that CCEA induced tumor cell apoptosis through promoting the expression of Bax, suppressing the expression of Bcl-2, decreasing mitochondrial membrane potential, releasing cytochrome C (Cyto C), and enhancing the activities of Caspase 9 and Caspase 3. The results of this paper provided a theoretical basis and insight for the development of antitumor drugs.

Preclinical Evaluation of CD36-Targeting Antiangiogenic Peptide ABT-510 for Near-Infrared Fluorescence Molecular Imaging of Colorectal Cancer.

Surgical resection constitutes the first choice of treatment for colorectal cancer (CRC). Despite advancements in intraoperative navigation, there remains a considerable lack of effective targeting probes for the imaging-guided surgical navigation of CRC owing to their high heterogeneity. Hence, developing a suitable fluorescent probe to detect the specific types of CRC populations is crucial. Herein, we labeled ABT-510, a small, CD36-targeting thrombospondin-1-mimetic peptide overexpressed in various cancer types, with fluorescein isothiocyanate or near-infrared dye MPA. We found that fluorescence-conjugated ABT-510 exhibited excellent selectivity and specificity toward cells or tissues with high CD36 expression. The tumor-to-colorectal signal ratios were 11.28 ± 0.61 (95% confidence interval) and 10.74 ± 0.07 (95% confidence interval) in subcutaneous HCT-116 and HT-29 tumor-bearing nude mice, respectively. Moreover, high signal contrast was observed in the orthotopic and liver metastatic CRC xenograft mouse models. Furthermore, MPA-PEG4-r-ABT-510 exhibited an antiangiogenic effect via tube information assay with human umbilical vein endothelial cells. Overall, MPA-PEG4-r-ABT-510 presents rapid and precise tumor delineation characteristics, thereby making it a desirable tool for CRC imaging and surgical navigation.

Anti-angiogenic collagen IV-derived peptide target engagement with αvβ3 and α5β1 in ocular neovascularization models

AXT107, a collagen-derived peptide that binds integrins αvβ3 and α5β1 with high affinity, suppresses vascular endothelial growth factor (VEGF) signaling, promotes angiopoietin 2-induced Tie2 activation, and suppresses neovascularization (NV) and vascular leakage. Immunohistochemical staining for αvβ3 and α5β1 was markedly increased in NV compared with normal retinal vessels. After intravitreous injection of AXT107, there was no staining with an anti-AXT107 antibody on normal vessels but robust staining of NV that co-localized with αvβ3 and α5β1. Likewise, after intravitreous injection, fluorescein amidite-labeled AXT107 co-localized with αvβ3 and α5β1 on NV but not normal vessels. AXT107 also co-localized with αv and α5 at cell-cell junctions of human umbilical vein endothelial cells (HUVECs). AXT107-integrin binding was demonstrated by exvivo cross-linking/pull-down experiments. These data support the hypothesis that AXT107 therapeutic activity is mediated through binding αvβ3 and α5β1 which are markedly upregulated on endothelial cells in NV providing selective targeting of diseased vessels which has therapeutic and safety benefits.

Novel Anti-angiogenic Peptide Derived from Canstatin Induces Apoptosis In Vitro and In Vivo

Novel Anti-angiogenic Peptide Derived from Canstatin Induces Apoptosis In Vitro and In Vivo

AAPred-CNN: Accurate predictor based on deep convolution neural network for identification of anti-angiogenic peptides.

Recently, deep learning techniques have been developed for various bioactive peptide prediction tasks. However, there are only conventional machine learning-based methods for the prediction of anti-angiogenic peptides (AAP), which play an important role in cancer treatment. The main reason why no deep learning method has been involved in this field is that there are too few experimentally validated AAPs to support the training of deep models but researchers have believed that deep learning seriously depends on the amounts of labeled data. In this paper, as a tentative work, we try to predict AAP by constructing different classical deep learning models and propose the first deep convolution neural network-based predictor (AAPred-CNN) for AAP. Contrary to intuition, the experimental results show that deep learning models can achieve superior or comparable performance to the state-of-the-art model, although they are given a few labeled sequences to train. We also decipher the influence of hyper-parameters and training samples on the performance of deep learning models to help understand how the model work. Furthermore, we also visualize the learned embeddings by dimension reduction to increase the model interpretability and reveal the residue propensity of AAP through the statistics of convolutional features for different residues. In summary, this work demonstrates the powerful representation ability of AAPred-CNNfor AAP prediction, further improving the prediction accuracy of AAP.

Computational Analysis Comparison Prediction of Anticancer Peptide (ACP)

Abstract: Anticancer peptides (ACPs) contain short peptides composed of 10–60 amino acids that can inhibit tumors cell proliferation or migration, or suppress the formation of tumors blood vessels, and are less likely to cause drug resistance. The aforementioned merits make ACPs the most promising anti-cancer candidate. ACPs may be degraded by proteases and result in cytotoxicity in many cases. To overcome these drawbacks, a plethora of research has focused on the reconstruction or modification of ACPs to improve their anti-cancer activity, while reducing their cytotoxicity. ACPs modification mainly includes main chain reconstruction and side-chain modification. After summarizing the classification and mechanism of action of ACPs, this paper focuses on recent development and progress in their reconstruction and modification. The information collected here may provide some ideas for further research on ACPs, in particular their modification. ACPs were extracted from various search engines like PubMed, Google scholar and Patent lens. Specific searches were carried out using a combination of keywords like ‘ACPs’, ‘antitumor peptides’, ‘anti-angiogenic peptides’, ‘anti-metastatic peptides’ and ‘host defence peptides. The comprehensive information related to a peptide like its source of origin, nature of the peptide, anticancer activity, N- and Cterminal modifications, conformation, etc. Additionally, CancerPPD provides information on around 249 types of cancer cell lines and 16 different assays used for testing the ACPs. In natural peptides, CancerPPD contains peptides having non-natural, chemically modified residues and D-amino acids. Besides this primary information, CancerPPD stores predicted tertiary structures as well as peptide sequences in SMILES format.

Optimized Heterologous Expression and Efficient Purification of a New TRAIL-Based Antitumor Fusion Protein SRH-DR5-B with Dual VEGFR2 and DR5 Receptor Specificity.

In the last two decades, bifunctional proteins have been created by genetic and protein engineering methods to increase therapeutic effects in various diseases, including cancer. Unlike conventional small molecule or monotargeted drugs, bifunctional proteins have increased biological activity while maintaining low systemic toxicity. The recombinant anti-cancer cytokine TRAIL has shown a limited therapeutic effect in clinical trials. To enhance the efficacy of TRAIL, we designed the HRH–DR5-B fusion protein based on the DR5-selective mutant variant of TRAIL fused to the anti-angiogenic synthetic peptide HRHTKQRHTALH. Initially low expression of HRH–DR5-B was enhanced by the substitution of E. coli-optimized codons with AT-rich codons in the DNA sequence encoding the first 7 amino acid residues of the HRH peptide. However, the HRH–DR5-B degraded during purification to form two adjacent protein bands on the SDS-PAGE gel. The replacement of His by Ser at position P2 immediately after the initiator Met dramatically minimized degradation, allowing more than 20 mg of protein to be obtained from 200 mL of cell culture. The resulting SRH–DR5-B fusion bound the VEGFR2 and DR5 receptors with high affinity and showed increased cytotoxic activity in 3D multicellular tumor spheroids. SRH–DR5-B can be considered as a promising candidate for therapeutic applications.

Transforming “cold” tumors into “hot” ones via tumor-microenvironment-responsive siRNA micelleplexes for enhanced immunotherapy

<h2>Summary</h2> It is highly desirable to turn "cold" tumors into "hot" ones to improve the efficacy of antitumor immunotherapy. Herein, we develop the peptide-based small interfering RNA (siRNA) micelleplexes (P^A7R@siPD-L1) for normalizing vascular-immune crosstalk to establish a positive feedback loop in potentiating antitumor immunotherapy. These micelleplexes are equipped with tumor-microenvironment-responsive property for precise drug delivery and release. The prepared P^A7R@siPD-L1-mediated photodynamic therapy could eliminate solid tumors and trigger immunogenic cell death to generate systematic immune responses. Meanwhile, the antiangiogenic peptide A7R normalizes the tumor vasculature by converting chaotic vascular systems into matured and organized ones, thus alleviating tumor hypoxia and promoting intratumoral infiltration by immune cells. Antitumor immunogenicity would be further strengthened with the aid of siPD-L1 by muting the resistance of tumor cells against immune effector cells. This study provides a unique therapeutic strategy in turning "cold" tumors into "hot" tumors enabled by siRNA nanomaterial.

Rational Design of Anti-Angiogenic Peptides to Inhibit VEGF/VEGFR2 Interactions for Cancer Therapeutics.

Angiogenesis is a critical physiological process that plays a key role in tumor progression, metastatic dissemination, and invasion. In the last two decades, the vascular endothelial growth factor (VEGF) signaling pathway has been the area of extensive researches. VEGF executes its special effects by binding to vascular endothelial growth factor receptors (VEGFRs), particularly VEGFR-2. The inhibition of VEGF/VEGFR2 interaction is known as an effective cancer therapy strategy. The current study pointed to design and model an anti-VEGF peptide based on VEGFR2 binding regions. The large-scale peptide mutation screening was used to achieve a potent peptide with high binding affinity to VEGF for possible application in inhibition of VEGF/VEGFR2 interaction. The AntiCP and Peptide Ranker servers were used to generate the possible peptides library with anticancer activities and prediction of peptides bioactivity. Then, the interaction of VEGF and all library peptides were analyzed using Hex 8.0.0 and ClusPro tools. A number of six peptides with favorable docking scores were achieved. All of the best docking scores of peptides in complexes with VEGF were evaluated to confirm their stability, using molecular dynamics simulation (MD) with the help of the GROMACS software package. As a result, two antiangiogenic peptides with 13 residues of PepA (NGIDFNRDFFLGL) and PepC (NGIDFNRDKFLFL) were achieved and introduced to inhibit VEGF/VEGFR2 interactions. In summary, this study provided new insights into peptide-based therapeutics development for targeting VEGF signaling pathway in tumor cells. PepA and PepC are recommended as potentially promising anticancer agents for further experimental evaluations.