iGEM 2025 — Team must-macau

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## Lab Notebook

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## Overview

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Our project began with bioinformatic analysis and flow cytometry experiments, which revealed that breast and pancreatic cancers—particularly in cases resistant to trastuzumab and gemcitabine—frequently exhibit upregulation of both CD47 and HER2 receptors. To address this challenge, we designed a bispecific fusion protein incorporating an active antibody fragment targeting HER2 and a nanobody targeting CD47. This design aims to simultaneously inhibit both receptors on resistant tumor cells, thereby inducing cell death and overcoming a major obstacle in cancer treatment: therapy resistance. In the initial design phase, we employed AI-based de novo design to generate active fragments targeting the functional epitopes of these two receptors. These designed fragments, along with those retrieved from existing databases, formed a library of candidate antibody fragments. The structures of these candidates were predicted using AlphaFold 3, followed by protein-protein docking to perform preliminary screening and evaluation. The top 10% of fragments—based on docking scores—underwent further refinement through molecular dynamics simulations and MM-PBSA binding free energy calculations. The most stable fragments with the lowest binding free energy were selected for the assembly of the active bispecific antibody, NanosphinX. Two assembly strategies were tested to link the two selected active antibody fragments into the final bispecific format. Cell viability assays demonstrated that NanosphinX exhibits cytotoxic effects against wild-type breast cancer cells and maintains strong activity even in trastuzumab-resistant cells, effectively inhibiting tumor growth. It also enhanced the cytotoxicity of gemcitabine in gemcitabine-resistant cell lines, providing a rational basis for combination therapy with gemcitabine. Further detailed studies are currently underway to fully explore the therapeutic potential of this bispecific nanobody in cancer treatment.

## Design of Active Monoclonal Antibodies Targeting Specific Receptor Epitopes

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![Workflow for Screening Active Monoclonal Antibodies](https://static.igem.wiki/teams/6012/project/engineering/1.webp)

Fig. 1 Workflow for Screening Active Monoclonal Antibodies

### Phase 1: De Novo Generation of Antibodies Based on Hotspot Residue Localization within Antigenic Epitopes

![AI-Designed Antibody Fragments](https://static.igem.wiki/teams/6012/project/engineering/2.webp)

Fig. 2 AI-Designed Antibody Fragments (A) Structural design of the CD47-targeting active antibody fragment (shown in yellow).(B) Structural design of the HER2-targeting active antibody fragment (shown in green and blue).

We utilized AI tools (RFdiffusion, RoseTTAFold2, and ProteinMPNN) to design 10 active antibody fragments targeting HER2 and CD47. For HER2, we adopted distinct strategies inspired by the binding modes of trastuzumab and pertuzumab, selecting different hotspot residue regions to guide the design process. For CD47, the design was based on the binding site of Lemzoparlimab (TJC4). By specifying these hotspot residues, we successfully directed the designed antibody fragments to bind to the intended antigenic epitopes (Fig. 2). (Refer to the Dry Lab section for detailed design methodology.)

### Phase 2: Screening of Active Antibody Fragments via Protein Docking and Molecular Dynamics Simulations

![RMSD Analysis from Molecular Dynamics Simulations](https://static.igem.wiki/teams/6012/project/engineering/3.webp)

Fig. 3 RMSD Analysis from Molecular Dynamics Simulations

![Free Energy Landscape](https://static.igem.wiki/teams/6012/project/engineering/4.webp)

Fig. 4 Free Energy Landscape

![AlphaFold3-Predicted Structures](https://static.igem.wiki/teams/6012/project/engineering/5.webp)

Fig. 5 AlphaFold3-Predicted Structures of Selected Active Antibody Fragments for Subsequent Bispecific Antibody Design (A) Structure of the CD47-targeting active antibody fragment (B) Structure of the HER2-targeting active antibody fragment (single-chain)

To identify the optimal antibody fragments, we integrated AI-generated designs with existing antibody databases. The structures of candidate fragments were predicted using AlphaFold3, followed by initial screening through protein-protein docking. Candidates ranking in the top 10% by Glide Score were selected for further evaluation.

These candidates then underwent molecular dynamics (MD) simulations and MM-GBSA binding free energy calculations for refined screening. For HER2, since two candidates (HER2\_001 and HER2\_002) received similar docking scores, we conducted 500 ns MD simulations and free energy landscape analysis. The results confirmed that HER2\_002 exhibited superior binding stability (Fig. 4). For CD47, the optimal candidate CD47\_001 was selected directly based on MM-GBSA scores.

The finally selected fragments, HER2\_002 and CD47\_001, both demonstrated stable binding to their respective targets throughout computational simulations (Fig. 3) and were thus chosen for subsequent bispecific antibody development.

## Design of Bispecific Antibody Fusion Protein

### Phase 1: Initial BioBrick Design of the Bispecific Antibody Fusion Protein

This phase aims to design a novel bispecific antibody, NanosphinX, using the active antibody fragments selected from the initial screening (structures shown in Fig. 5). The objective is to construct a bispecific antibody capable of simultaneously binding both CD47 and HER2. In our first construction strategy, we attempted to connect the CD47-targeting active fragment to the heavy chain of the HER2-targeting antibody fragment via a flexible linker (Fig. 6).

![BioBrick Design of NanosphinX_01](https://static.igem.wiki/teams/6012/project/engineering/6.webp)

Fig. 6 BioBrick Design of NanosphinX\_01

This design was anticipated to exhibit dual-receptor blockade against both CD47 and HER2 on cancer cells, thereby synergistically eliminating cancer cells and addressing resistance to trastuzumab and gemcitabine. However, this initial BioBrick design—though demonstrating strong binding affinity toward HER2—was found to yield a bispecific antibody with insufficient binding affinity for CD47. As shown in Fig. 7 to Fig. 9, NanosphinX\_01 exhibited very low dual affinity for both CD47 and HER2. Further investigation using flow cytometry confirmed that this lack of affinity was primarily due to reduced binding to CD47. Consequently, additional modifications were undertaken to improve the design.

![ELISA Assay Results](https://static.igem.wiki/teams/6012/project/engineering/7.webp)

Fig. 7 ELISA Assay Detecting the Simultaneous Binding Capacity of NanosphinX\_01 and NanosphinX\_02 to HER2 and Human CD47 Protein

![Flow Cytometry Analysis HER2](https://static.igem.wiki/teams/6012/project/engineering/8.webp)

Fig. 8 Flow Cytometry (FCM) Analysis of the Binding Capacity of NanosphinX\_01 and NanosphinX\_02 to HER2 Protein

![Flow Cytometry Analysis CD47](https://static.igem.wiki/teams/6012/project/engineering/9.webp)

Fig. 9 Flow Cytometry (FCM) Analysis of the Binding Capacity of NanosphinX\_01 and NanosphinX\_02 to CD47 Protein

### Phase 2: BioBrick Optimization of the Bispecific Antibody Fusion Protein

![BioBrick Design of NanosphinX_02](https://static.igem.wiki/teams/6012/project/engineering/10.webp)

Fig. 10 BioBrick Design of NanosphinX\_02

To address the insufficient affinity for CD47 observed in the initial BioBrick design from Phase 1, we hypothesized that connecting the CD47-targeting active fragment to the heavy chain of the HER2-targeting antibody via a flexible linker might have caused steric hindrance between the CD47-binding module and the Fc region of the HER2 antibody. This constraint could have limited the freedom of movement and structural flexibility required for efficient CD47 binding. Therefore, we modified the design by instead connecting the CD47-targeting active fragment to the light chain of the HER2-targeting antibody using a flexible linker (Fig. 10). The light chain is located on the outer side of the characteristic Y-shaped antibody structure. Positioning the CD47-binding fragment here allows it greater freedom to extend outward, minimizing potential steric clashes with the core antibody structure—particularly the Fc region—and thereby facilitating more effective binding to the CD47 target on the cell membrane.

![Predicted Structure of Bispecific Antibody](https://static.igem.wiki/teams/6012/project/engineering/11.webp)

Fig. 11 Predicted Structure of the Bispecific Antibody with the CD47-Targeting Active Fragment Connected to the Light Chain of the HER2-Targeting Antibody via a Flexible Linker Red: Heavy chain of HER2nb Green: Light chain of HER2nb Purple: CD47nb Blue: Linker

Accordingly, we designed NanosphinX\_02 by connecting the CD47-targeting active fragment to the light chain of the HER2-targeting antibody. Molecular experiments confirmed that NanosphinX\_02 exhibits significantly enhanced dual affinity for both HER2 and CD47 (Figs. 7–9).

Consequently, we selected the NanosphinX\_02 design strategy, in which the CD47-targeting fragment was fused to the N-terminus of the light chain of the HER2-targeting antibody. The construct was then expressed using a CRO (Contract Research Organization): a signal peptide was added, the plasmid was constructed, and transient transfection was performed followed by expression and purification to obtain the NanosphinX\_02 protein in sufficient quantity.

![Heavy Chain Positive Clones](https://static.igem.wiki/teams/6012/project/engineering/12.webp)

Fig. 12 Heavy Chain Positive Clones

![Light Chain Positive Clones](https://static.igem.wiki/teams/6012/project/engineering/13.webp)

Fig. 13 Light Chain Positive Clones

![Plasmid Sequencing Results HER2 Light Chain](https://static.igem.wiki/teams/6012/project/engineering/14.webp)

Fig. 14 Plasmid Sequencing Results of HER2 Light Chain + CD47nb

![Plasmid Sequencing Results HER2 Heavy Chain](https://static.igem.wiki/teams/6012/project/engineering/15.webp)

Fig. 15 Plasmid Sequencing Results of HER2 Heavy Chain

![SDS-PAGE and SEC-HPLC Results](https://static.igem.wiki/teams/6012/project/engineering/16.webp)

Fig. 16 SDS-PAGE and SEC-HPLC Results After Antibody Purification

After obtaining the specific active bispecific antibody, we evaluated its efficacy against trastuzumab-resistant tumor cells (HCC1954 cell line), gemcitabine-resistant tumor cells (PANC-1 cell line), and triple-negative breast cancer cells (MDA-MB-231 cell line). Detailed experimental results can be found in the Experimental Results section.

![Efficacy in HCC1954 Cells](https://static.igem.wiki/teams/6012/project/engineering/17.webp)

Fig. 17 Efficacy of NanosphinX in HCC1954 Cells

![Efficacy in PANC-1 Cells](https://static.igem.wiki/teams/6012/project/engineering/18.webp)

Fig. 18 Efficacy of NanosphinX in PANC-1 Cells

![Efficacy in MDA-MB-231 Cells](https://static.igem.wiki/teams/6012/project/engineering/19.webp)

Fig. 19 Efficacy of NanosphinX in MDA-MB-231 Cells

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# Results

## Part I: Design of active monoclonal antibodies targeting specific receptor epitopes

![Screening flowchart](https://static.igem.wiki/teams/6012/project/results/1.webp)

Figure 1. Screening flowchart for active monoclonal antibodies.

### Phase 1: De novo antibody generation based on the localization of antigenic epitope hotspot residues

![AI-designed antibody fragments](https://static.igem.wiki/teams/6012/project/results/2.webp)

Figure 2. AI-designed antibody fragments. A: Structural diagram of the designed active antibody fragment for CD47 (the active antibody fragment is shown in yellow). B: Structural diagram of the designed active antibody fragment for HER2 (the active antibody fragments are shown in green and blue).

In the initial stage, our goal was to design a bispecific fusion protein-drug conjugate targeting CD47 and HER2, which are upregulated in tumor cells, especially in cases of gemcitabine and trastuzumab resistance. We aimed to design a construct composed of two nanobodies—one for CD47 and one for HER2. Therefore, we first needed to design and screen active antibody fragments for HER2 and CD47 respectively (as shown in Figure 1).

Using AI tools (RFdiffusion, RoseTTAFold2, ProteinMPNN), we designed 10 active antibody fragments targeting HER2 and CD47. For HER2, we drew on the binding modes of trastuzumab and pertuzumab, selecting different hotspot residue regions to guide the design. For CD47, the design was based on the binding site of Lemzoparlimab. By specifying hotspot residues, we successfully guided the designed antibody fragments to the intended antigenic epitopes (Figure 2).

### Phase 2: Screening of active fragments based on protein-protein docking and molecular dynamics simulations

![RMSD analysis](https://static.igem.wiki/teams/6012/project/results/3.webp)

Figure 3. RMSD analysis from MD simulation.

![Free energy landscape](https://static.igem.wiki/teams/6012/project/results/4.webp)

Figure 4. Free energy landscape.

![Alphafold3 predicted structures](https://static.igem.wiki/teams/6012/project/results/5.webp)

Figure 5. Alphafold3 predicted structures of active antibody fragments for subsequent active bispecific antibody design. (A) Structure of the active CD47 antibody fragment. (B) Structure of the active HER2 antibody fragment (single chain).

To select the optimal antibody fragments, we integrated AI design with existing databases. We utilized Alphafold3 to predict structures, followed by an initial screening via protein docking. The top 10% of candidate fragments, ranked by Glide Score, were selected. A secondary screening was then conducted using molecular dynamics (MD) simulations and MM-GBSA calculations. For HER2, because the two candidate fragments (HER2\_001, HER2\_002) had similar scores, we performed a 500 ns MD simulation. Free energy landscape analysis confirmed that HER2\_002 had more stable binding (Figure 4), as it exhibited a narrower and deeper free energy landscape valley, indicating that its low-energy conformations were more clustered and stable. For CD47, the optimal fragment, CD47\_001, was directly selected via MM-GBSA. The finally selected HER2\_002 and CD47\_001 both demonstrated stable binding with their targets in computational simulations (Figure 3) and can be used for the subsequent design of the bispecific antibody.

## Part II: Design of the Bispecific Antibody Fusion Protein

![BioBrick design](https://static.igem.wiki/teams/6012/project/results/6.webp)

Figure 6. BioBrick design of NanosphinX\_02

### Phase 1: BioBrick Design

This section aims to design a novel bispecific antibody, NanosphinX, using the active antibody fragments screened in the first step (structures shown in Figure 5) to simultaneously bind both CD47 and HER2. This design is expected to exhibit a dual receptor blockade effect on CD47 and HER2 in cancer cells, thereby synergistically eliminating cancer cells and addressing the problem of trastuzumab and gemcitabine resistance in tumors. We attempted to connect the CD47-targeting active fragment to the light chain of the HER2-targeting antibody fragment via a flexible linker (Figure 6). The light chain is located on the outer side of the antibody's "Y" shape. Placing the CD47-binding fragment here allows it to extend more freely, reducing the potential for steric hindrance with the core antibody structure (especially the Fc region), thus facilitating easier binding to the CD47 target on the cell membrane. After designing the BioBrick, whole gene synthesis was performed.

![Heavy chain plasmid map](https://static.igem.wiki/teams/6012/project/results/7.webp)

Figure 7. Heavy chain plasmid map

![Light chain plasmid map](https://static.igem.wiki/teams/6012/project/results/8.webp)

Figure 8. Light chain + CD47nb plasmid map

### Phase 2: Plasmid Construction and Verification

After whole gene synthesis of the light & heavy chains, they were constructed into the pCDNA3.4 plasmid using SphI and BamHI, followed by plasmid amplification, purification, and positive clone selection. The light chain (HER2nb light chain + CD47nb) and the heavy chain (HER2nb heavy chain) were synthesized as whole genes and constructed into the intermediate plasmids pUC-HER2nb light chain + CD47nb and pUC-HER2nb heavy chain, respectively. (This step was carried out by General Biosystems' whole gene synthesis service). The pCDNA3.4 target empty vector, as well as the pUC-HER2nb light chain + CD47nb and pUC-HER2nb heavy chain vectors, were digested with SphI and BamHI restriction enzymes to generate compatible ends. The restriction digestion products were then analyzed by DNA agarose gel electrophoresis. The results showed that the plasmids with the genes of interest should display two bands: one large, linearized empty plasmid backbone band, and another smaller band for the gene of interest (HER2nb-LC+CD47nb and HER2nb-HC). This indicates that the double digestion was successful and the corresponding plasmids are likely correct. The empty pCDNA3.4 vector should appear as a single, clear linear band migrating slightly slower than the supercoiled plasmid form.

![DNA gel electrophoresis](https://static.igem.wiki/teams/6012/project/results/9.webp)

Figure 9. DNA agarose gel electrophoresis of restriction digestion products.

Purification of restriction enzyme digestion products by DNA gel extraction: After separating DNA fragments by size using agarose gel electrophoresis, the gel slice containing the target DNA band is excised under UV light. The gel is then dissolved using heat or a high-salt buffer. A silica-membrane spin column is used to specifically adsorb the DNA under high-salt conditions. After washing away impurities, the pure DNA is eluted in a low-salt buffer.

Ligation of light/heavy chain genes and pCDNA3.4: T4 DNA ligase is used to catalyze the formation of phosphodiester bonds between the 5'-phosphate and 3'-hydroxyl ends of the double-stranded DNA. Since both the vector and the inserts were prepared by double digestion with SphI and BamHI, they possess complementary sticky ends, allowing the ligase to efficiently "stitch" them together to reform a complete, circular plasmid molecule.

Transformation of ligation products into TOP10 competent cells: The transformed bacterial culture was plated on LB agar plates containing ampicillin (as pCDNA3.4 carries the AmpR resistance gene) and incubated inverted at 37°C for 12-16 hours. The observation of multiple bacterial colonies on the LB agar plates indicated the presence of ampicillin-resistant transformants, confirming the successful transformation of TOP10 cells with the target plasmids (Figures 10-11). On plates containing antibiotics, only bacteria that have successfully taken up the recombinant plasmid can grow to form monoclonal colonies. Theoretically, each colony is a population of cells derived from a single ancestral cell and therefore has an identical genetic background. By picking and amplifying a single colony, we can obtain a pure bacterial culture containing the plasmid of interest for subsequent plasmid extraction, verification, and storage.

![Heavy chain transformants](https://static.igem.wiki/teams/6012/project/results/10.webp)

Figure 10. LB agar plate with heavy chain transformants (TOP10).

![Light chain transformants](https://static.igem.wiki/teams/6012/project/results/11.webp)

Figure 11. LB agar plate with Light chain+CD47nb transformants (TOP10).

### Phase 3: Sequencing Verification

![Light chain sequencing](https://static.igem.wiki/teams/6012/project/results/12.webp)

Figure 12. HER2nb light chain + CD47nb.

![Heavy chain sequencing](https://static.igem.wiki/teams/6012/project/results/13.webp)

Figure 13. HER2nb heavy chain

To verify the correctness of the plasmids we designed and synthesized, we sent the positive clones to a sequencing company to obtain their sequence information. The sequencing results confirmed that our designed plasmids contained the correct sequences (Figures 12-13).

### Phase 4: Plasmid Extraction

After amplifying the positive clones, plasmids were extracted using a TIANGEN Plasmid Maxi Kit to obtain high-purity and correct plasmids.

Lane 1: The undigested, original plasmid was loaded. It appeared on the gel as a primary band, which is typically the supercoiled conformation of the plasmid that migrates faster than its linear form.

Lane 2: The plasmid digested with two restriction endonucleases, XbaI and BamHI, was loaded. After digestion, the circular plasmid was cut, producing two linear DNA fragments of different sizes: a larger band, which is the vector backbone, and a smaller band, which is the excised gene fragment of interest. The results from the restriction enzyme digestion gel electrophoresis of our extracted plasmids confirmed that the gene for our fusion protein was successfully constructed into the plasmid vector.

![Plasmid gel electrophoresis](https://static.igem.wiki/teams/6012/project/results/14.webp)

Figure 14. Plasmid agarose gel electrophoresis

### Phase 5: Protein Expression and Purification

![SDS-PAGE and SEC-HPLC](https://static.igem.wiki/teams/6012/project/results/15.webp)

Figure 15. SDS-PAGE and SEC-HPLC of the antibody fusion protein.

The purified plasmids were transiently transfected into CHO cells for protein expression, followed by purification and validation using SDS-PAGE and SEC-HPLC. We found that our synthesized antibody not only met the required molecular weight but also achieved a purity of 98.74%.

## Part III: Activity Testing of the Bispecific Antibody Fusion Protein

### Phase 1: Effect on trastuzumab-resistant tumor cells (HCC1954 cells)

We investigated the inhibitory effect of the bispecific antibody on trastuzumab-resistant tumor cells by testing the cell viability under different treatments. As shown in the results, HCC1954 cells exhibit a degree of resistance to trastuzumab. However, upon the addition of our designed bispecific antibody, NanosphinX, the tumor cell viability was significantly reduced. Therefore, our designed active bispecific antibody, NanosphinX, can inhibit trastuzumab-resistant tumors, thus addressing the issue of trastuzumab resistance.

![Effect on HCC1954](https://static.igem.wiki/teams/6012/project/results/16.webp)

Figure 16. Effect of NanosphinX on HCC1954.

### Phase 2: Effect of NanosphinX on PANC-1

![Effect on PANC-1](https://static.igem.wiki/teams/6012/project/results/17.webp)

Figure 17. Effect of NanosphinX on PANC-1.

We explored the inhibitory effect of the bispecific antibody on gemcitabine-resistant tumor cells by testing cell viability under different treatments. As shown, PANC-1 cells are resistant to gemcitabine. However, when our designed bispecific antibody NanosphinX was added, tumor cell viability significantly decreased. This indicates that NanosphinX can inhibit gemcitabine-resistant tumor cells, offering a solution to gemcitabine resistance. Furthermore, the results from the Gemcitabine + NanosphinX treatment show that NanosphinX can be used in combination with gemcitabine to enhance its efficacy and overcome resistance.

### Phase 3: Effect of NanosphinX on MDA-MB-231

![Effect on MDA-MB-231](https://static.igem.wiki/teams/6012/project/results/18.webp)

Figure 18. Effect of NanosphinX on MDA-MB-231.

![Growth of MDA-MB-231](https://static.igem.wiki/teams/6012/project/results/19.webp)

Figure 19. Growth of MDA-MB-231 after NanosphinX treatment.

Triple-negative breast cancer has long been a major challenge regarding drug resistance, as its surface lacks many biological targets, making it difficult to treat with targeted therapies. We further investigated whether our bispecific antibody could inhibit triple-negative breast cancer cells through its ability to alter the tumor immune microenvironment. As shown in Figure 18, the inhibition of MDA-MB-231 cells by NanosphinX was significantly stronger than that of trastuzumab. Additionally, Figure 19 shows that the number of MDA-MB-231 cells was markedly reduced after the addition of NanosphinX, indicating significant growth inhibition.

### Phase 4: Changes in Chemokine CXCL9 and CXCL10 Secretion after NanosphinX Addition

![Chemokine changes](https://static.igem.wiki/teams/6012/project/results/20.webp)
![Chemokine changes](https://static.igem.wiki/teams/6012/project/results/21.webp)

Figure 20. Changes in chemokine CXCL9 and CXCL10 secretion after NanosphinX treatment.

Having understood the superiority of NanosphinX in addressing drug resistance, we wanted to further investigate whether NanosphinX could combat cancer not only by directly attacking tumor cells but also by mobilizing the patient's own immune system. Through literature research, we found that antibodies can potentially increase the secretion of chemokines CXCL9 and CXCL10 by macrophages, thereby modulating the tumor microenvironment to strongly attract immune killer cells like T cells and NK (Natural Killer) cells into the tumor tissue, achieving an anti-tumor effect. Therefore, we designed a co-culture experiment with NanosphinX, tumor cells, and macrophages. The results (Figure 20) showed that NanosphinX can effectively induce an increase in the secretion of chemokines CXCL9 and CXCL10 by macrophages in the tumor microenvironment, thereby enhancing our tumor-killing effect.

## Conclusion

In summary, the bispecific antibody fusion protein we designed, NanosphinX, can effectively address the problem of drug resistance in cancer therapy by targeting two overexpressed molecular targets on the surface of resistant tumor cells. Furthermore, it can further inhibit tumor cells by modulating the tumor microenvironment. The experimental results clearly demonstrate that NanosphinX has a potent inhibitory effect on both trastuzumab-resistant and gemcitabine-resistant cells, providing a new approach for overcoming resistance to these commonly used drugs and for combination therapy. Designing rational bispecific antibody fusion proteins that target overexpressed molecules on the surface of resistant cells appears to be a promising breakthrough in solving the problem of tumor drug resistance. We will continue to validate our designed bispecific antibody, NanosphinX, in multiple animal studies.

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