Papers with Code 아카이브

Blind Docking

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

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평가표

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보존된 평가 기록

18

논문

이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.

Seq2Bind Webserver for Decoding Binding Hotspots directly from Sequences using Fine-Tuned Protein Language Models

PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking

SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation

Fast and Accurate Blind Flexible Docking

Accurate Pocket Identification for Binding-Site-Agnostic Docking

Group Ligands Docking to Protein Pockets

FlowDock: Geometric Flow Matching for Generative Protein-Ligand Docking and Affinity Prediction

GNNAS-Dock: Budget Aware Algorithm Selection with Graph Neural Networks for Molecular Docking

DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking

GeoDirDock: Guiding Docking Along Geodesic Paths

FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation

Deep Confident Steps to New Pockets: Strategies for Docking Generalization

Quantum-Inspired Machine Learning for Molecular Docking

Multi-scale Iterative Refinement towards Robust and Versatile Molecular Docking

FABind: Fast and Accurate Protein-Ligand Binding

DSDP: A Blind Docking Strategy Accelerated by GPUs

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking

State-specific protein-ligand complex structure prediction with a multi-scale deep generative model

EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.