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PDBbind database
Known as:
PDBbind
The PDBbind database is a comprehensive collection of experimentally measured binding affinity data (Kd, Ki, and IC50) for the protein-ligand…
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Protein Data Bank
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Predicting drug-target interaction using 3D structure-embedded graph representations from graph neural networks
Jaechang Lim
,
Seongok Ryu
,
Kyubyong Park
,
Yo Joong Choe
,
Jiyeon Ham
,
W. Kim
arXiv.org
2019
Corpus ID: 118714970
Accurate prediction of drug-target interaction (DTI) is essential for in silico drug design. For the purpose, we propose a novel…
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2018
2018
Fast, accurate X-ray density-driven ligand docking on the free energy surface using the MovableType method coupled with Phenix/DivCon
Lance M. Westerhoff
,
O. Borbulevych
,
Zheng Zheng
,
Nupur Bansal
,
R. I. Martin
,
K. Merz
Acta Crystallographica Section A: Foundations and…
2018
Corpus ID: 104463136
X-ray crystallography is the primarily technique used to determine the three-dimensional (3D) structure of protein:ligand and…
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2017
2017
Brendan-A Deep Convolutional Network for Representing Latent Features of Protein-Ligand Binding Poses
Thomas Lau
,
R. Dror
2017
Corpus ID: 186201643
Empirical molecular ”fingerprints” are often used in computational drug discovery (specifically in QSAR methods [3]) to predict…
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2017
2017
DockThor 2 . 0 : a Free Web Server for Protein-Ligand Virtual Screening
I. Guedes
,
Eduardo Krempser
,
E. Dardenne
2017
Corpus ID: 4526238
INTRODUCTION. Receptor-ligand molecular docking is a structure-based approach widely used by the scientific community in…
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2016
2016
VinaSC: Scalable Autodock Vina with fine-grained scheduling on heterogeneous platform
Lang Yu
,
Zhongzhi Luan
,
Xiangzheng Sun
,
Zhe Wang
,
Hailong Yang
IEEE International Conference on Bioinformatics…
2016
Corpus ID: 6052933
In this paper we present VinaSC, an improved version of Autodock Vina, that performs molecular docking simulation efficiently on…
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2016
2016
# 56-Binding affinity prediction using a nonparametric regression model based on physicochemical and structural descriptors of the nano-environment for protein-ligand interactions
L. Borro
,
I. Yano
,
I. Mazoni
,
G. Neshich
2016
Corpus ID: 7355137
We propose a new empirical scoring function for binding affinity prediction modeled based on physicochemical and structural…
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2013
2013
The AtlasCBS Application
C. Abad-Zapatero
2013
Corpus ID: 59746083
2013
2013
Does Accurate Scoring of Ligands against Protein Targets Mean Accurate Ranking?
Hossam M. Ashtawy
,
N. Mahapatra
International Symposium on Bioinformatics…
2013
Corpus ID: 33338310
Accurately predicting the binding affinities of large sets of protein-ligand complexes efficiently is a key challenge in…
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2013
2013
Combining SFCscore with Random Forests leads to improved affinity prediction for protein-ligand complexes
David Zilian
,
C. Sotriffer
Journal of Cheminformatics
2013
Corpus ID: 824696
SFCscore is a collection of emprirical scoring functions derived from a set of over 60 descriptors for protein-ligand complexes…
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2008
2008
KASBi: Knowledge-Based Analysis in Systems Biology
María del Mar Roldán García
,
Ismael Navas-Delgado
,
Amine Kerzazi
,
Othmane Chniber
,
Joaquin J. Molina-Castro
,
J. F. A. Montes
Workshop on Semantic Web Applications and Tools…
2008
Corpus ID: 14081928
The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources…
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