4.7 Article

StackCPA: A stacking model for compound-protein binding affinity prediction based on pocket multi-scale features

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Review Biochemical Research Methods

Artificial intelligence in the prediction of protein-ligand interactions: recent advances and future directions

Ashwin Dhakal et al.

Summary: New drug production can take over 12 years and cost around $2.6 billion, with the COVID-19 pandemic emphasizing the need for more powerful computational methods in drug discovery. This review focuses on computational approaches using artificial intelligence (AI) to predict protein-ligand interactions, particularly in deep learning methods. The correlation between protein-ligand interaction aspects and the proposal to study them together could lead to more accurate machine learning-based prediction strategies.

BRIEFINGS IN BIOINFORMATICS (2022)

Article Biochemistry & Molecular Biology

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models

Mihaly Varadi et al.

Summary: AlphaFold DB is an openly accessible database with high-accuracy protein-structure predictions, powered by DeepMind's AlphaFold v2.0. It provides programmatic access to a vast number of predicted structures and is expanding to cover more sequences.

NUCLEIC ACIDS RESEARCH (2022)

Article Chemistry, Medicinal

DeepPocket: Ligand Binding Site Detection and Segmentation using 3D Convolutional Neural Networks

Rishal Aggarwal et al.

Summary: A structure-based drug design pipeline involves the development of drug molecules or ligands that can form stable complexes with a given receptor at its binding site. However, most existing methods fail to accurately identify and rank binding sites. The successful adoption of deep learning algorithms in structural biology is of great significance for accurate binding site detection.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022)

Article Multidisciplinary Sciences

Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning

Maha A. Thafar et al.

Summary: Drug-target interaction (DTI) prediction is crucial for drug repositioning and virtual drug screening. Most methods require 3D structural information of targets, while a few non-structure-based methods have been proposed. In this study, we propose a novel regression-based method, Affinity2Vec, which formulates the task as a graph-based problem and combines computational techniques to predict drug-target binding affinity.

SCIENTIFIC REPORTS (2022)

Article Multidisciplinary Sciences

Highly accurate protein structure prediction with AlphaFold

John Jumper et al.

Summary: Proteins are essential for life, and accurate prediction of their structures is a crucial research problem. Current experimental methods are time-consuming, highlighting the need for accurate computational approaches to address the gap in structural coverage. Despite recent progress, existing methods fall short of atomic accuracy in protein structure prediction.

NATURE (2021)

Article Chemistry, Multidisciplinary

Drug-target affinity prediction using graph neural network and contact maps

Mingjian Jiang et al.

RSC ADVANCES (2020)

Article Biochemical Research Methods

DeepDTA: deep drug-target binding affinity prediction

Hakime Ozturk et al.

BIOINFORMATICS (2018)

Article Chemistry, Medicinal

Mol2vec: Unsupervised Machine Learning Approach with Chemical Intuition

Sabrina Jaeger et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)

Article Chemistry, Medicinal

KDEEP: Protein-Ligand Absolute Binding Affinity Prediction via 3D-Convolutional Neural Networks

Jose Jimenez et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2018)

Article Chemistry, Medicinal

Making Sense of Large-Scale Kinase Inhibitor Bioactivity Data Sets: A Comparative and Integrative Analysis

Jing Tang et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2014)

Article Biochemistry & Molecular Biology

The ChEMBL bioactivity database: an update

A. Patricia Bento et al.

NUCLEIC ACIDS RESEARCH (2014)

Article Biochemistry & Molecular Biology

ChEMBL: a large-scale bioactivity database for drug discovery

Anna Gaulton et al.

NUCLEIC ACIDS RESEARCH (2012)

Article Biochemical Research Methods

Gaussian interaction profile kernels for predicting drug-target interaction

Twan van Laarhoven et al.

BIOINFORMATICS (2011)

Article Biotechnology & Applied Microbiology

Comprehensive analysis of kinase inhibitor selectivity

Mindy I. Davis et al.

NATURE BIOTECHNOLOGY (2011)

Article Chemistry, Multidisciplinary

Open Babel: An open chemical toolbox

Noel M. O'Boyle et al.

JOURNAL OF CHEMINFORMATICS (2011)

Article Biochemical Research Methods

Fpocket: An open source platform for ligand pocket detection

Vincent Le Guilloux et al.

BMC BIOINFORMATICS (2009)

Article Multidisciplinary Sciences

Predictina protein-protein interactions based only on sequences information

Juwen Shen et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2007)

Article Biochemistry & Molecular Biology

Prediction of protein subcellular locations by incorporating quasi-sequence-order effect

KC Chou

BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS (2000)