PALM-H3
PALM-H3 PALM
Peer-reviewed Prospective flag Direct antibody flagSummary card
| Поле | Значение |
|---|---|
| Год / version | 2024 / NR |
| Last verified | 2026-08-13 |
| Что генерирует | CDR-H3 sequence; grafted antibody candidates |
| Форматы | Antibody variable region candidates; validated on SARS-CoV-2 antibodies |
| De novo или optimization | De novo CDR-H3 on existing framework |
| DOI | 10.1038/s41467-024-50903-y |
| Paper | https://doi.org/10.1038/s41467-024-50903-y |
| GitHub / repo | https://github.com/TencentAILabHealthcare/PALM |
| Service / docs | NR |
| Лицензия | Custom repository license; verify commercial use |
| Доступность / commercial-use | Code + Zenodo models/data |
Задача и generated object
Used in these tasks: Генерация CDR sequence, Antigen-conditioned antibody design
Part of these workflows: Antigen-conditioned CDR-H3 generation (PALM-H3)
| Поле | Значение |
|---|---|
| Required input | Antigen/epitope sequence and antibody context/framework |
| Conditioning | CDR-H3 length/context; antigen epitope sequence |
| Fixed | NR |
| Editable | NR |
| Generated | CDR-H3 sequence; grafted antibody candidates |
| Single mutations | No |
| Combinatorial mutations | Full CDR-H3 |
| Multi-objective | No explicit multi-objective optimizer |
Architecture and operating principle
Author-reported (matrix)| Поле | Значение |
|---|---|
| Base architecture | NR |
| Model type | 1 + 5 Antibody sequence and target-conditioned generator |
| Representation | NR |
| Generation unit | CDR-H3 sequence; grafted antibody candidates |
| Conditioning | CDR-H3 length/context; antigen epitope sequence |
| Output | CDR-H3 sequence; grafted antibody candidates |
| Sampling | NR |
| Internal scorer | A2binder specificity/affinity predictor |
| Structure generation | No native 3D generator; structure modeled downstream |
Input representation
NR
| Поле | Значение |
|---|---|
| Node features | NR |
| Edge / pair features | NR |
Encoder и decoder
NR
| Поле | Значение |
|---|---|
| Encoder | NR |
| Decoder | NR |
Latent or generative state
NR
Conditioning mechanism
CDR-H3 length/context; antigen epitope sequence
Generation mechanism
Antigen encoder + autoregressive antibody decoder; A2binder predictor for ranking
Sampling: NR
Training objectives
NR
Losses: NR
Mathematical details: NR
Integrated evaluation
A2binder specificity/affinity predictor
Architectural limitations
- Single antigen family in prospective validation.
- sequence-only CDR generation.
- internal affinity predictor is not affinity improvement.
Uses these architecture components: Protein language models, Autoregressive generation
Generator versus evaluation
| Component | Role | Architecture class | Integrated or external | Required or optional | Influences generation or post hoc | Runtime included or excluded |
|---|---|---|---|---|---|---|
| PALM-H3 | primary_generator | Antigen encoder + autoregressive antibody decoder; A2binder predictor for ranking | integrated | required | generation | included |
| A2binder specificity/affinity predictor | integrated_scorer | NR | integrated | optional | post_hoc | unknown |
| Structure prediction/docking and binding/neutralization assays | mandatory_external_dependency | NR | external | required | post_hoc | excluded |
| Experimental binding/function assays | experimental_validation | NR | external | required | post_hoc | excluded |
Training data и biases
| Поле | Значение |
|---|---|
| Training data | NR |
| Preprocessing | NR |
| Negative examples | NR |
| Fine-tuning | NR |
| Label requirements | NR |
| Training hardware | NR |
| Training time | NR |
Inference hardware и runtime
| Поле | Значение |
|---|---|
| Candidate count | NR |
| Batch size | NR |
| Generation steps | NR |
| Recycles | NR |
| Size | NR |
| Reported runtime | NR |
| Runtime boundary | NR |
| CPU | NR |
| GPU | NR |
| VRAM | NR |
| RAM | NR |
| Disk | NR |
| Databases | NR |
Experimental evidence
| Поле | Значение |
|---|---|
| Evidence class | 3–4 prospective binding and functional validation |
| Retrospective | NR |
| Prospective binding | Binding and neutralization reported; predicted affinity outputs are not the experimental result |
| Prospective function | Binding and neutralization reported; predicted affinity outputs are not the experimental result |
| Developability | NR |
| Tested design count | Generated antibodies tested against SARS-CoV-2 variants; exact final count: NR here |
| Success criterion | Binding and neutralization reported; predicted affinity outputs are not the experimental result |
| Independent validation | NR |
| Summary | Binding and neutralization reported; predicted affinity outputs are not the experimental result |
Limitations and failure modes
- Single antigen family in prospective validation.
- sequence-only CDR generation.
- internal affinity predictor is not affinity improvement.
Deployment: Limited antibody pilot
Reproducibility, license, commercial use
| Поле | Значение |
|---|---|
| Repo | https://github.com/TencentAILabHealthcare/PALM |
| License | Custom repository license; verify commercial use |
| Commercial-use status | Code + Zenodo models/data |
Related tools
Alternative tools: NR
Complementary: NR
Related: NR
Not directly comparable with
AlphaProteo, BindCraft, BoltzGen, FrameDiff, RFdiffusion, RFdiffusion All-Atom (RFdiffusionAA)Depends on these external modules
NR
Related glossary terms
NRPrimary paper и полный список источников
xTrimoPGLM-based antigen-specific antibody CDR-H3 design (PALM-H3)Source matrix: landscape xlsx, last verified 2026-08-13.
Review queue
- Bibliographic title must be verified against the PDF.
Детальный source-grounded разбор
1. Что именно делает инструмент
[MATRIX]Вход: Antigen/epitope sequence and antibody context/framework
[MATRIX]Generated object: CDR-H3 sequence; grafted antibody candidates
[MATRIX]Фиксируется: NR. Изменяется: NR.
[MATRIX]De novo или parent-based: De novo CDR-H3 on existing framework.
2. Архитектура в одном абзаце
[MATRIX]Antigen encoder + autoregressive antibody decoder; A2binder predictor for ranking
4. Математическая модель
NRТочные уравнения, losses и sampling solver будут внесены после чтения paper/code. Не подставляйте родовой UCB/transformer/diffusion, если он не подтверждён для этого инструмента.
Поля NR: conditional probability, update equations, sampling algorithm
5. Физическое устройство состояния
[MATRIX]Seed generated state / output: CDR-H3 sequence; grafted antibody candidates. Structure generation: No native 3D generator; structure modeled downstream.
6. Физико-химическая интерпретация
[INTERPRETATION]Координаты, frames, PLM embeddings или residue tokens не являются расчётом ΔG, электростатики или растворителя, пока это не сделано внешней energy function. Likelihood / pLDDT / docking score ≠ экспериментальный binding.
7. Training
[MATRIX]Данные: NR. Fine-tuning: NR. Negative examples: NR.
8. Inference
[MATRIX]Sampling: NR. Generation steps: NR. Runtime boundary: NR.
10. Почему, по мнению авторов, метод эффективен
[MATRIX]Author-reported summary (матрица): Binding and neutralization reported; predicted affinity outputs are not the experimental result
NRCausal support не классифицирован, пока не прочитаны ablation и experimental sections.
12. Ablation analysis
NRAblation в этом выпуске не разобрана.
13. What the model does not represent
- Явный растворитель и ионная сила — обычно отсутствуют в генераторе.
- Протонирование, гликозилирование, кофакторы — обычно отсутствуют, если не оговорено.
- Конформационная энтропия и долгая динамика — не моделируются одним forward pass.
- Экспрессия, агрегация, иммуногенность — не равны likelihood генератора.
- Истинная binding free energy — не равна internal score.
14. Evidence and limitations
[MATRIX]Evidence class (матрица): 3–4 prospective binding and functional validation. Prospective binding: Binding and neutralization reported; predicted affinity outputs are not the experimental result. Function: Binding and neutralization reported; predicted affinity outputs are not the experimental result. Developability: NR.
- Single antigen family in prospective validation.
- sequence-only CDR generation.
- internal affinity predictor is not affinity improvement.
15. Reproducibility
NRРепозиторий: https://github.com/TencentAILabHealthcare/PALM. Лицензия: Custom repository license; verify commercial use. Commit: NR, пока страница не имеет отдельного analysis YAML.
Модульная схема
| Модуль | Класс модели | Вход | Выход | Обучается или frozen | Generator или evaluator |
|---|---|---|---|---|---|
| PALM-H3 | Antigen encoder + autoregressive antibody decoder; A2binder predictor for ranking | NR | NR | NR | primary_generator |
| A2binder specificity/affinity predictor | NR | NR | NR | NR | integrated_scorer |
| Structure prediction/docking and binding/neutralization assays | NR | NR | NR | NR | mandatory_external_dependency |
| Experimental binding/function assays | NR | NR | NR | NR | experimental_validation |
Generator versus evaluator
| Компонент | Роль | Integrated или external | Required или optional | Влияет на generation или только ранжирует после |
|---|---|---|---|---|
| PALM-H3 | primary_generator | integrated | required | generation |
| A2binder specificity/affinity predictor | integrated_scorer | integrated | optional | post_hoc |
| Structure prediction/docking and binding/neutralization assays | mandatory_external_dependency | external | required | post_hoc |
| Experimental binding/function assays | experimental_validation | external | required | post_hoc |
Claim–evidence matrix
| Утверждение | Предполагаемый механизм | Тип evidence | Датасет / эксперимент | Comparator | Метрика / результат | Источник | Оговорка |
|---|---|---|---|---|---|---|---|
| Binding and neutralization reported; predicted affinity outputs are not the experimental result | Antigen encoder + autoregressive antibody decoder; A2binder predictor for ranking | 5. prospective functional validation | Generated antibodies tested against SARS-CoV-2 variants; exact final count: NR here | NR | Binding and neutralization reported; predicted affinity outputs are not the experimental result | [MATRIX] landscape matrix 2026-08-13 | Не читать как полный разбор primary paper. |