Avoiding Patents: Mapping Innovation Boundaries in Protein Sequences

From an industry perspective, every protein sequence with commercial value is like a piece of 'virtual territory' that you can claim exclusive rights to. From the core binding regions of antibodies to the catalytic centers of industrial enzymes, from fusion protein linkers to targeted modifications of functional domains, over a million sequence-related patents worldwide have already staked their claim.

Unlike territorial boundaries in the physical world, the rules for defining protein patents are more specialized: patent documents fully disclose the sequence and its functional validation data, then carefully outline the scope of protection in legal terms. Once examined and found to be novel, inventive, and useful, the patent is granted, giving the holder exclusive rights. More crucially, the protection boundary isn't a clear, precise line but rather a zone of 'clear core and fuzzy edges':

- The core boundary is literal infringement: if your sequence falls within the range described in the patent claims, it’s typically considered clear literal infringement—the recognized core no-go area.

- The edge zone is defined by the doctrine of equivalents: even if the sequence isn’t exactly the same as the one in the patent claims, it could theoretically still be considered equivalent infringement for 'achieving essentially the same mechanism, performing essentially the same function, or producing essentially the same effect.'

This fuzzy edge doesn’t have a fixed legal threshold—there’s no universal rule for how similar sequences need to be to count as 'equivalent.' Two sequences that appear different but have highly similar functions might either be a legal workaround or fall within the scope as equivalent infringement, often needing court cases to decide.

This means sequence design in protein engineering is never just a scientific issue. Every amino acid you change brings up two intertwined questions: functionally, will the change ruin the activity? Legally, does the change escape the patent coverage?

Two-Layer Boundary of Patent Protection

I. Three Major Structural Blind Spots of Traditional Patent Avoidance

Traditional patent avoidance follows a linear process: the legal team searches for patents and identifies risk areas → the R&D team designs avoidance variants → the legal team re-evaluates infringement risk → synthesis and testing → cycle iteration. This model worked when there were fewer patents, but in today's dense patent landscape, it exposes three hard-to-solve structural issues.

Blind Spot 1: Knowing 'where not to touch,' but not 'where you can touch'

A typical protein patent claim may define a protection scope like 'at least X% identity with a reference sequence, specific amino acids at particular positions, having a specific function,' or use narrower specific sequence limits or broader functional limits. From a conservative risk management perspective, lawyers can mark high-risk no-go zones: avoid certain amino acids at specific positions, keep overall sequence identity below a threshold. But they can’t provide positive guidance—will the function still hold if a site is changed to another amino acid? If a residue is essential for function, can surrounding modifications reconstruct the mechanism, achieving the same effect with a completely different sequence? These questions go beyond legal expertise and can't be answered by ordinary sequence comparison tools.

Blind Spot 2: Claimed scope ≠ actual enforceable scope

To get broader protection, applicants often use general statements in their claims. But during examination, they may be asked to narrow the scope to distinguish prior art; in litigation, courts may further limit the scope based on estoppel rules. As a result, there’s a large gray area between the claimed scope on paper and what the court would actually support. Traditional strategies usually take the most conservative view, marking the entire claimed range as off-limits, wasting many actually usable sequence options.

Blind Spot 3: Avoidance comes too late, R&D investments get sunk

In most companies, patent avoidance is triggered only when ‘a candidate molecule is ready to move forward, so we do an FTO (freedom-to-operate) search.’ By this point, most R&D investments are already sunk: gene synthesis is done, expression systems are set up, initial activity data generated. If major patent risks are discovered now, the team faces a dilemma: starting over means huge time and cost losses, while continuing means unpredictable legal risks.

This 'develop first, avoid later' timeline is essentially limited by technical bottlenecks: in the early design stage when only sequence information is available, researchers can’t predict the functional outcome of modifications, so they can’t boldly experiment with avoidance designs.

II. AI Breakthrough: From Passive Avoidance to Precise Design

To address the above blind spots, relying solely on faster sequence alignment tools is far from enough. What’s really needed is an integrated technical system that can simultaneously define legal boundaries and predict functional outcomes. Represented by the MatwingsVenus™ AI agent protein engineering platform, this system integrates three core capabilities—function prediction, structural analysis, and combinatorial design—transforming patent avoidance from a passive, experience- and luck-based defense into a quantifiable, proactive design.

1. Functional Constraint Map: Identifying Safely Modifiable Sequence Spaces

To tackle the first blind spot of "only knowing forbidden zones but not feasible zones," protein function prediction technology can convert an entire amino acid sequence into a "functional constraint map": accurately pinpointing active sites, substrate-binding pockets, conformationally constrained residues, and variable surface regions. This clearly distinguishes which residue changes may easily lose core functions, which can be replaced with biophysically equivalent residues, and which are purely structural fillers that can be extensively modified.

Take an industrial lipase as an example: its substrate-binding loop region is fully covered by a patent. Using the functional constraint map, this 28-residue loop can be broken down into three levels: four residues directly participate in the substrate hydrogen-bond network and are essential for function, so they should not be changed lightly; eight residues maintain loop flexibility and can be swapped with amino acids of similar physicochemical properties; the remaining 16 residues serve only as spatial fillers and have a large potential for modification.

Researchers only need to focus on creating sequence variations in these 16 high-flexibility residues, perform equivalent substitutions for the 8 flexible constraint residues, and retain the core features of the 4 essential residues. For this loop region, the final variant loop sequence has about 57% identity while retaining over 90% of the enzyme activity, successfully avoiding the patented sequence space while still meeting functional requirements.

Industrial Lipase

2. Structural Perspective Penetration: Clarifying the True Scope of Patent Protection

For the second blind spot of “mismatch between the paper scope and actual scope,” 3D structural modeling provides a more precise basis for judgment.

Take the example of avoiding the antibody’s core binding region (CDR). Patents usually define protection based on amino acid sequences, and sequences that are highly similar on paper are considered high-risk areas. But 3D structural analysis can reveal a deeper logic: what plays a crucial role in binding specificity is often just a few key residues’ spatial positions and chemical properties, not the arrangement of the entire sequence backbone. If an avoidance variant changes large portions of the backbone sequence but retains the spatially equivalent positions of the key contact residues, the function can be preserved at the engineering level, while proving equivalence infringement risk legally requires more precise reasoning.

The value of AI platforms isn’t to replace legal judgment but to provide molecular-level precise input for legal evaluation—turning a rough risk description like “75% sequence identity” into a precise statement such as “the chemical properties and spatial positions of 5 key contact residues are retained, but there are 11 differences in the sequence backbone involving 3 secondary structure units.” This allows legal teams to make more grounded risk assessments and gives R&D plans stronger technical justification.

3. Front-Loading Design: Embedding Avoidance at the Molecular Birth Stage

For the third blind spot of “post-hoc avoidance with sunk costs,” the fundamental value of AI technology is to shift avoidance work from the end of R&D to the very source of design.

In traditional workflows, molecule development follows a linear process of “sequence design → synthesis & expression → activity testing → FTO evaluation,” with avoidance as the last step. With end-to-end AI capabilities, avoidance can be embedded at every stage of sequence design:

- When screening natural templates, AI can prioritize candidates with superior activity that are outside dense patent areas;

- When designing mutation schemes, the “degree of difference from known patented sequences” can be included as an optimization goal, automatically generating mutation combinations that balance activity and avoidance properties;

- When screening candidate molecules, rapid structure modeling can pre-assess the risk of structural equivalence and potential infringement.

This isn’t just an efficiency improvement—it fundamentally reshapes the logic of patent avoidance: it’s no longer a reactive step of “fixing problems after they appear,” but a proactive strategy of “avoiding risk at the design stage.”

III. Beyond Risk Avoidance: Three Layers of Strategic Value in Patent Avoidance

When patent avoidance upgrades from passive compliance to an active strategy, its value is far more than just “avoiding infringement lawsuits.” It can bring three tiered strategic benefits to a company.

Three-Tier Strategic Values

The first level is market access. This is the most basic business value—finding a legal path to enter the market despite competitors' patent barriers. For biosimilars, successfully avoiding core sequence patents is a key prerequisite for gaining the qualification to compete alongside the original products; for industrial enzymes, successfully circumventing the core patent protection scope means entering specific application markets without needing a license from the other party.

The second level is independent intellectual property. New variants generated through design avoidance, if they have unexpected substantial improvements in function or process, can themselves become new patentable subjects. This achieves a shift from 'defense' to 'offense': not only do you avoid others' patent scope, but you also establish your own exclusive rights.

The third level is negotiation leverage. Complete avoidance is not always the optimal strategy. A well-designed avoidance variant may derive its real value from creating room for cross-licensing negotiations. Having a technically equivalent alternative that can be argued as non-infringing can significantly change a company's passive position when relying solely on one side in patent negotiations.

Conclusion

The patent landscape for protein sequences continues to expand day by day. Finding room for innovation in the gaps of law and technology used to be a difficult process relying heavily on legal experience, R&D intuition, and a lot of luck. But when AI can simultaneously handle sequence-level function prediction, structure-level equivalence analysis, and design-level mutation modeling, patent avoidance begins to transform from a defensive risk action into a proactive 'territory planning' capability.

This doesn’t mean AI can replace professional legal judgment and careful business decisions. Its real significance is giving R&D and legal teams a unified analytical base map built on molecular data itself. On this map, legal boundaries and technical constraints are no longer two disconnected systems of discourse but different annotation layers on the same innovation map.

When avoiding patents becomes more predictable and rationally designed, the domain of protein innovation can find its own growth space within territories defined by others.