pMHC 3D Structure Prediction
✓ 已验证DiVo in-house pipeline module · External technical capability report (sanitized)
Step 5 self-developed unique module of DiVo Gen²AI's neoantigen 8-step pipeline. Traditional pipelines stop at affinity values for binding judgment; DiVo builds atomic-level pMHC 3D structures for each candidate neoantigen, with in-house cross-validation--highest confidence 95.4, complex overall score 0.977, approaching X-ray crystallography precision. 400+ complexes validated at scale. This page serves three audiences: patients and public wanting to understand pMHC, CAR-T/neoantigen teams seeking structure prediction partners, and investors and peers evaluating technical capabilities.
Read "What is pMHC Structure" below--understand why affinity values aren't enough, 3D structures are also needed.
Focus on "DiVo's Role", "3-Step Pipeline", "Evidence"--we have 400+ complex real-world data.
Focus on "Differentiation", "Benchmarks", "Glossary"--evaluate the technical barrier of pMHC structure prediction.
pMHC structure prediction is a core differentiation step for the following flagship services
What is pMHC Structure Prediction
In the tumor neoantigen pipeline, MHC binding prediction gives affinity values--quantitative metrics of peptide-MHC molecule binding. Stronger affinity theoretically means more likely to be recognized by T cells. But affinity values only tell you "they bind", not "how they bind".
The spatial conformation of a peptide embedded in the MHC groove determines whether it can be stably presented on the cell surface and correctly recognized by TCR. Peptides that meet affinity thresholds but have unstable spatial conformations--"crooked keys" in the groove--are false positives that the immune system would never see in vivo.
pMHC 3D structure prediction builds full-atom 3D models of "peptide-MHC complexes" for each candidate peptide, validates conformational credibility with confidence metrics, then cross-validates to eliminate false positives. This is not just visualization--it's a qualitative change from "may bind" to "confirmed presentation".
Affinity values only answer "they bind", not "how they bind". Peptides with unstable spatial conformations are false positives--affinity passes but conformation is skewed, won't be stably presented.
Single prediction may overfit. Structure prediction + conformational stability cross-validation, two checkpoints filtering layer by layer, ensuring remaining candidates are truly credible at the atomic level.
DiVo Gen²AI's Role
pMHC structure prediction is Step 5 of DiVo's neoantigen 8-step pipeline, and CT5 core capability of the CAR-T 5-step pipeline. We complete the full loop from structure prediction to cross-validation--validating conformational credibility, eliminating false positives, with structure scores directly participating in immunogenicity ranking at 25% weight. This is not third-party tool stitching, but a complete capability loop orchestrated by in-house pipeline.
Underlying implementation details--including model architecture, toolchain, in-house weights and scheduling logic--are not disclosed in this report, available under cooperation frameworks as needed.
Core Capability · 3-Step Pipeline
From candidate peptides to conformational validation structure prediction loop · Click steps to view underlying validation
Candidate Peptide Input
✓ 已验证->Receives MHC binding prediction output
Affinity-qualified candidate peptide list
pMHC 3D Structure Prediction
✓ 已验证DiVo in-house structure prediction engine (Protenix)
Full-atom pMHC 3D structure + pLDDT/ipTM
Conformational Stability Cross-Validation
✓ 已验证DiVo in-house validation engine
Eliminates conformationally unstable false positives
Differentiation
Core differences from traditional "affinity-value-only" pipelines
Atomic-Level 3D Structure Replaces Pure Value Judgment
Traditional pipelines stop at affinity values for binding judgment, not knowing the spatial conformation of peptides in the MHC groove. DiVo builds atomic-level pMHC 3D structures for each candidate, validating conformational credibility with confidence metrics--a qualitative change from "may bind" to "confirmed presentation".
Structure Score Participates in Immunogenicity Ranking
Not just visualization; pMHC structure scores directly participate in immunogenicity ranking at 25% weight. False positives with passing affinity but unstable conformations are eliminated at the structural level, reducing downstream无效 experiments.
DiVo In-House Capability Modules
Functional capabilities · All verified
| Capability Module | Underlying Engine | Function Description | Status |
|---|---|---|---|
| pMHC 3D Structure Prediction | DiVo in-house structure prediction engine | Outputs full-atom 3D structure of peptide-MHC complex, with confidence metrics, validating spatial conformational credibility | ✓ 已验证 |
| Conformational Stability Cross-Validation | DiVo in-house validation engine | Cross-validates structure prediction results, eliminating false positives with passing affinity but unstable spatial conformation | ✓ 已验证 |
| Multi-Chain Complex Large-Scale Prediction | DiVo in-house batch prediction scheduler | Supports peptide-receptor, tetramer+substrate and other complex systems batch prediction, validated at scale, not just point demos | ✓ 已验证 |
Three capability modules together form DiVo's complete pMHC structure prediction capability loop: structure prediction gives conformation -> cross-validation eliminates false positives -> large-scale scheduling supports real-world batch delivery. Modules are orchestrated by DiVo's in-house pipeline, not third-party tool stitching.
Evidence · pMHC Structures
Peptide sequences sanitized · Confidence metrics are measured values
| Complex | Antigen Source | Confidence | Complex Overall Score |
|---|---|---|---|
| HLA-A*02:01 + candidate peptide ① | HTLV-1 Tax | 95.4 | 0.977 |
| HLA-A*02:01 + candidate peptide ② | WT1 | 94+ | 0.96+ |
| HLA-A*02:01 + candidate peptide ③ | WT1 | 94+ | 0.96+ |
| HLA-A*02:06 + candidate peptide ④ | MAGE-A1 | 94+ | 0.96+ |
| HLA-A*02:06 + candidate peptide ⑤ | HTLV-1 Tax | 94+ | 0.96+ |
The candidate peptide sequences of the above 5 pMHC structures have been sanitized (numbered ①-⑤), antigen sources retained for credibility cross-reference. Confidence metrics are all measured values, not simulated.
Evidence · Large-Scale Validation
Project-level scale generalized and sanitized
| Metric | Value | Note |
|---|---|---|
| Large-scale real-world projects | 千级突变 × 多版迭代 | Multi-project cross-validation |
| Complex batch prediction | 400+ 复合物 | Highest confidence 95.4 |
| Structure confidence | 95.4 | Approaching X-ray crystallography precision |
| Complex overall score | 0.977 | Atomic-level reliability |
| Cross-validation | 通过 | Conformational stability validation completed |
Honest Boundaries
What we can and cannot do, clearly stated
What We Can Do
What We Don't Do
Glossary
5 core terms in pMHC structure prediction
| Abbr. | Full Name | Translation | Explanation |
|---|---|---|---|
| pMHC | peptide-MHC complex | peptide-MHC Complex | Antigen peptide complex presented by MHC molecules, the target of T cell recognition |
| pLDDT | predicted Local Distance Difference Test | predicted Local Distance Difference Test | Structure prediction confidence metric, >90 is high confidence, 95.4 approaches X-ray crystallography precision |
| ipTM | interface predicted TM-score | interface predicted TM-score | Protein complex interface interaction confidence, >0.75 is high confidence |
| MHC | Major Histocompatibility Complex | Major Histocompatibility Complex | The "display board" on cell surfaces, presenting intracellular protein fragments to T cells |
| 假阳性 | False Positive | False Positive | Candidate peptides with passing affinity values but unstable spatial conformations, not actually stably presented |
CAPACITY TRACE
能力回溯
这项服务由哪些能力支撑——从硅片到你的场景
硅片(L1) → 模型(L2) → Agent(L3) → 管线(L4) → 你的场景