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ProteinGenerator

Peer-reviewed Prospective flag

Summary card

Поле	Значение
Год / version	2025 / NR
Last verified	2026-08-13
Что генерирует	Coupled sequence–structure proposals
Форматы	Proteins and multistate designs
De novo или optimization	De novo and constrained redesign
DOI	10.1038/s41587-024-02395-w
Paper	https://doi.org/10.1038/s41587-024-02395-w
GitHub / repo	https://github.com/RosettaCommons/protein_generator
Service / docs	NR
Лицензия	MIT
Доступность / commercial-use	Code + checkpoints

Задача и generated object

Used in these tasks: Joint sequence–structure generation, Дизайн функционального сайта

Part of these workflows: Joint / multimodal sequence–structure generation

Поле	Значение
Required input	None or sequence/structure motif; state/functional constraints
Conditioning	Sequence/structure motifs, DSSP/hotspots, multistate potentials
Fixed	NR
Editable	NR
Generated	Coupled sequence–structure proposals
Single mutations	Possible
Combinatorial mutations	Yes
Multi-objective	Supports guided multi-constraint design; not universal Pareto optimization

Architecture and operating principle

Author-reported (matrix)

Поле	Значение
Base architecture	NR
Model type	4 Joint sequence–structure generator
Representation	NR
Generation unit	Coupled sequence–structure proposals
Conditioning	Sequence/structure motifs, DSSP/hotspots, multistate potentials
Output	Coupled sequence–structure proposals
Sampling	NR
Internal scorer	Guidance potentials and RoseTTAFold-derived outputs
Structure generation	Structure prediction is entangled with generation

Input representation

Поле	Значение
Node features	NR
Edge / pair features	NR

Encoder и decoder

Поле	Значение
Encoder	NR
Decoder	NR

Latent or generative state

Conditioning mechanism

Sequence/structure motifs, DSSP/hotspots, multistate potentials

Generation mechanism

RoseTTAFold sequence-space diffusion with structural refinement and guidance potentials

Sampling: NR

Training objectives

Losses: NR

Mathematical details: NR

Integrated evaluation

Guidance potentials and RoseTTAFold-derived outputs

Architectural limitations

RoseTTAFold-derived confidence is not independent validation.
environment is nontrivial.
no antibody-specific proof.

Uses these architecture components: Sequence diffusion, Joint sequence–structure generation

Generator versus evaluation

Component	Role	Architecture class	Integrated or external	Required or optional	Influences generation or post hoc	Runtime included or excluded
ProteinGenerator sequence diffusion	primary_generator	RoseTTAFold sequence-space diffusion with structural refinement and guidance potentials	integrated	required	generation	included
Guidance potentials and RoseTTAFold-derived outputs	integrated_scorer	NR	integrated	optional	post_hoc	unknown
Structure prediction is entangled with generation	integrated_structure_predictor	NR	integrated	optional	post_hoc	included
Independent structure/function validation	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 functional validation
Retrospective	NR
Prospective binding	Prospective general protein evidence
Prospective function	Prospective general protein evidence
Developability	NR
Tested design count	Multiple multistate/functional designs; exact aggregate: NR
Success criterion	Prospective general protein evidence
Independent validation	NR
Summary	Prospective general protein evidence

Limitations and failure modes

RoseTTAFold-derived confidence is not independent validation.
environment is nontrivial.
no antibody-specific proof.

Deployment: Limited internal pilot

Reproducibility, license, commercial use

Поле	Значение
Repo	https://github.com/RosettaCommons/protein_generator
License	MIT
Commercial-use status	Code + checkpoints

Alternative tools: NR

Complementary: NR

Related: NR

Not directly comparable with

Efficient evolution with ESM-1v, Structural evolution (ESM-IF1 complex)

Сравнение допустимо только внутри совместимых категорий. Runtime и quality AntiFold vs RFantibody нельзя читать как одну шкалу: разные starting points и generated objects.

Depends on these external modules

Primary paper и полный список источников

Generalized biomolecular modeling and design with sequence-space diffusion

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: None or sequence/structure motif; state/functional constraints

[MATRIX]Generated object: Coupled sequence–structure proposals

[MATRIX]Фиксируется: NR. Изменяется: NR.

[MATRIX]De novo или parent-based: De novo and constrained redesign.

2. Архитектура в одном абзаце

[MATRIX]RoseTTAFold sequence-space diffusion with structural refinement and guidance potentials

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: Coupled sequence–structure proposals. Structure generation: Structure prediction is entangled with generation.

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): Prospective general protein evidence

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 functional validation. Prospective binding: Prospective general protein evidence. Function: Prospective general protein evidence. Developability: NR.

RoseTTAFold-derived confidence is not independent validation.
environment is nontrivial.
no antibody-specific proof.

15. Reproducibility

NRРепозиторий: https://github.com/RosettaCommons/protein_generator. Лицензия: MIT. Commit: NR, пока страница не имеет отдельного analysis YAML.

Модульная схема

Модуль	Класс модели	Вход	Выход	Обучается или frozen	Generator или evaluator
ProteinGenerator sequence diffusion	RoseTTAFold sequence-space diffusion with structural refinement and guidance potentials	NR	NR	NR	primary_generator
Guidance potentials and RoseTTAFold-derived outputs	NR	NR	NR	NR	integrated_scorer
Structure prediction is entangled with generation	NR	NR	NR	NR	integrated_structure_predictor
Independent structure/function validation	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
ProteinGenerator sequence diffusion	primary_generator	integrated	required	generation
Guidance potentials and RoseTTAFold-derived outputs	integrated_scorer	integrated	optional	post_hoc
Structure prediction is entangled with generation	integrated_structure_predictor	integrated	optional	post_hoc
Independent structure/function validation	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
Prospective general protein evidence	RoseTTAFold sequence-space diffusion with structural refinement and guidance potentials	5. prospective functional validation	Multiple multistate/functional designs; exact aggregate: NR	NR	Prospective general protein evidence	[MATRIX] landscape matrix 2026-08-13	Не читать как полный разбор primary paper.