DiffDock
最新标签
latest
文件大小
15.33 GB
多节点支持
多架构支持
最新版本latest安全扫描结果
LINUX/AMD64
AAA
Nspect-9owx-ew8j Drug Discovery Healthcare Life Sciences Nvidia Ai Enterprise Supported Nvidia Nim Cuda Cuda Toolkit Pytorch Pytorch Geometric Rapids Triton Inference Server Ai Inference Nvidia Ai

DiffDock
容器镜像
校验资质

更新2025-05-02

Diffdock predicts the 3D structure of the interaction between a molecule and a protein.

Overview

DiffDock is a generative diffusion model for drug discovery in molecular blind docking.

DiffDock consists of two models: the Score and Confidence models. The Score model generates a series of potential poses for protein-ligand binding by running a reverse diffusion process.

DiffDock does not require any information about a binding pocket. During its diffusion process, the molecule's position relative to the protein, its orientation, and the torsion angles are allowed to change. Running the learned reverse diffusion process transforms a distribution of noisy prior molecule poses to the one learned by the model. As a result, it outputs many sampled poses and ranks them via its confidence model.

Leveraging the same neural-network architecture designed in the original DiffDock by MIT, the model v2.0 is trained by NVIDIA using PLINDER, a state-of-art dataset of well curated and labeled protein-ligand complexes, which therefore, delivers a much higher accuracy for molecular docking tasks.

This model is ready for commercial and non-commercial use.

What Is NVIDIA NIM?

NVIDIA NIM, part of NVIDIA AI Enterprise, is a set of easy-to-use microservices designed to accelerate deployment of generative AI across cloud, data center, and workstations.

Benefits of self-hosted NIMs:

  • Deploy anywhere and maintain control of generative AI applications and data
  • Streamline AI application development with industry standard APIs and tools tailored for enterprise environments
  • Prebuilt containers for the latest generative AI models, offering a diverse range of options and flexibility right out of the gate
  • Industry-leading latency and throughput for cost-effective scaling
  • Support for custom models out of the box so models can be trained on domain specific data
  • Enterprise-grade software with dedicated feature branches, rigorous validation processes, and robust support structures

Getting started

Please visit the DiffDock NIM Documentation for how to get started.

Please review the Security Scanning tab to view the latest security scan results.

For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

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License

This container is licensed under the NVIDIA AI Product Agreement. By pulling and using this container, you accept the terms and conditions of this license.

You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.