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REINVENT 4 - AI Drug Discovery | aibioatlas | aibioatlas

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REINVENT 4 Scientific Architecture

REINVENT 4 Scientific Architecture · AstraZeneca / MolecularAI contributors

AI Drug Discovery · Molecular Design

REINVENT 4

开发机构 AstraZeneca / MolecularAI contributors →

Generative molecular design and optimization

Generative molecular design and optimization. Scoring objectives can bias outputs; synthesis feasibility and activity need separate testing.

Generative molecular design and optimizationInput: Molecular examples, objectives and scoring configurationOutput: Generated and ranked molecular candidates

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概览介绍

Generative molecular design and optimization. Scoring objectives can bias outputs; synthesis feasibility and activity need separate testing.

信息已比对权威文献或官方白皮书；非实验性跑分。权威出处 · 最后核对: 16/09/2026, 17:33:40 UTC

核心功能特性

Generative molecular design and optimization
Input: Molecular examples, objectives and scoring configuration
Output: Generated and ranked molecular candidates

Interactive 3D Illustration

Biological Architecture (Stylized Ribbon)

Default view is a stylized demonstration ribbon. Enter any 4-letter RCSB PDB accession code above to stream real atomic coordinates.

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Illustrative Confidence Gradient:

>90 High / Low B 70-90 Confident 50-70 Low <50 Very low / High B

Academic Context & Research Evidence

Biological & Workflow Fit

Compute & Hardware: Consult linked installation guidance; workload dependent
Licensing & Academic Use: Review the linked release, model weights, datasets and service terms separately
Documented Evidence: Project or provider documentation; no local performance benchmark

Cite this Tool

Use this citation format when referencing REINVENT 4 in scientific publications and benchmark papers.

@software{reinvent4_2026,
  title = {{REINVENT 4}},
  author = {{AstraZeneca / MolecularAI contributors}},
  year = {2026},
  url = {https://github.com/MolecularAI/REINVENT4},
  note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}

Peer-Reviewed Literature & Preprints

Live scientific citations queried from Europe PMC and PubMed for REINVENT 4.

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技术参数与产品规格

Missing values mean the catalog has no recorded information. They do not mean a feature is absent.

Entry typeResearch software / model

Access modePublic code / project terms

AI roleScientific machine learning

Input dataMolecular examples, objectives and scoring configuration

Output dataGenerated and ranked molecular candidates

Licence conditionsReview the linked release, model weights, datasets and service terms separately

Commercial eligibilityNot independently confirmed

Compute requirementsConsult linked installation guidance; workload dependent

ValidationEvaluate on representative data; no clinical suitability established

TypeNot recorded

Intended useBiological and pharmaceutical research

CompatibilityNot recorded

LimitationsScoring objectives can bias outputs; synthesis feasibility and activity need separate testing.

Evidence levelProject or provider documentation; no local performance benchmark

AvailabilitySee project access and maintenance status

Price / accessSee project terms; compute costs may apply

Research fit & compatibility

No software–hardware integration has been verified for this entry yet. Explore documented research workflows.

Gallery & resources

REINVENT 4 Scientific Architecture

REINVENT 4 Scientific Architecture · Credit: AstraZeneca / MolecularAI contributors · Open original ↗

Research and editorial use Source & attribution ↗ License ↗

Resource: Project documentation and evidence ↗ · github.com

BEFORE YOU CHOOSE

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竞品替代

同一科学领域的同类算法与工具。

MOLECULAR DOCKING • SMILES GRAPH

ADMET-AI

AI Drug Discovery

Research AI Methods

ADMET-AI

Source-scoped research method · Confirm distribution and exact release

ADMET-AI — admet-property-prediction

Research / method authors

学术论文 ↗

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MOLECULAR DOCKING • SMILES GRAPH

ChemFM

AI Drug Discovery

Molecular Property Prediction

ChemFM

Research AI model / method · Research code or publication

Chemical foundation model for learned molecular representations, property prediction and conditional mole

Luo Lab

GitHub ↗学术论文 ↗

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MOLECULAR DOCKING • SMILES GRAPH

DiffPharma

AI Drug Discovery

Molecular Design

DiffPharma

Research AI model / method · Research code or publication

Diffusion-based ligand molecule generation constrained by specified pocket and pharmacophore interactions

Sekijima Lab

GitHub ↗学术论文 ↗

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MOLECULAR DOCKING • SMILES GRAPH

DiffSBDD

AI Drug Discovery

Research AI Methods

DiffSBDD

Source-scoped research method · Confirm distribution and exact release

DiffSBDD — structure-conditioned-molecular-generation

Research / method authors

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最新研究动态

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常见问题解答

该工具在哪些平台或地区可用？

See project access and maintenance status

商业授权与费用如何计算？

费用根据官方最近一次公布的说明整理。请在官方网站确认最新报价与学术折扣。

Peer Reviews & Community Ratings

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