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PUResNetV2.0: a deep learning model leveraging sparse representation for improved ligand binding site prediction
Accurate ligand binding site prediction (LBSP) within proteins is essential for drug discovery. We developed ProteinUNetResNetV2.0 (PUResNetV2.0),...
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DeepBindPPI: Protein–Protein Binding Site Prediction Using Attention Based Graph Convolutional Network
Due to the importance of protein-protein interactions in defence mechanism of living body, attempts were made to investigate its attributes,...
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PSnpBind-ML: predicting the effect of binding site mutations on protein-ligand binding affinity
Protein mutations, especially those which occur in the binding site, play an important role in inter-individual drug response and may alter binding...
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Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures
Protein-ligand binding site prediction is a useful tool for understanding the functional behaviour and potential drug-target interactions of a novel...
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Distance plus attention for binding affinity prediction
Protein-ligand binding affinity plays a pivotal role in drug development, particularly in identifying potential ligands for target disease-related...
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Open-ComBind: harnessing unlabeled data for improved binding pose prediction
Determination of the bound pose of a ligand is a critical first step in many in silico drug discovery tasks. Molecular docking is the main tool for...
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Structure-based, deep-learning models for protein-ligand binding affinity prediction
The launch of AlphaFold series has brought deep-learning techniques into the molecular structural science. As another crucial problem,...
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LVPocket: integrated 3D global-local information to protein binding pockets prediction with transfer learning of protein structure classification
BackgroundPrevious deep learning methods for predicting protein binding pockets mainly employed 3D convolution, yet an abundance of convolution...
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Improvement of binding pose prediction of the MR1 covalent ligands by inclusion of simple pharmacophore constraints and structural waters in the docking process
The major histocompatibility complex (MHC) class I-related molecule, MR1, is a key component of the immune system, presenting antigens to T-cell...
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AI-based prediction of protein–ligand binding affinity and discovery of potential natural product inhibitors against ERK2
Determination of protein–ligand binding affinity (PLA) is a key technological tool in hit discovery and lead optimization, which is critical to the...
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Is there a common allosteric binding site for G-protein coupled receptors?
Targeting the allosteric sites on G-protein coupled receptors (GPCRs) for drug discovery is attracting increased interest. Given a GPCR target,...
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Exploiting the Role of Features for Antigens-Antibodies Interaction Site Prediction
Antibodies are a class of proteins that recognize and neutralize pathogens by binding to their antigens. They are the most significant category of...
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Prediction of the Mannose-Binding Site in the Agaricus bisporus Mannose-Binding Protein
Agaricus bisporus mannose-binding protein (Abmb) was discovered as part of mushroom tyrosinase (PPO3) complex. Apart from its presence, nothing is...
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Computational Protein Binding
Why it is important to know this material? The computational approach to protein binding has become a crucial methodology in drug design and...
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Co-evolution-based prediction of metal-binding sites in proteomes by machine learning
Metal ions have various important biological roles in proteins, including structural maintenance, molecular recognition and catalysis. Previous...
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Docking-Based Prediction of Peptide Binding to MHC Proteins
Major histocompatibility complex (MHC) proteins are the most polymorphic and polygenic proteins in humans. They bind peptides, derived from cleavage...
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Software for Predicting Binding Free Energy of Protein–Protein Complexes and Their Mutants
Protein–protein binding affinity prediction is important for understanding complex biochemical pathways and to uncover protein interaction networks....
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Sequence-based prediction of protein binding regions and drug–target interactions
Identifying drug–target interactions (DTIs) is important for drug discovery. However, searching all drug–target spaces poses a major bottleneck....
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PSnpBind: a database of mutated binding site protein–ligand complexes constructed using a multithreaded virtual screening workflow
A key concept in drug design is how natural variants, especially the ones occurring in the binding site of drug targets, affect the inter-individual...
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Proteins and Their Interacting Partners: An Introduction to Protein–Ligand Binding Site Prediction Methods with a Focus on FunFOLD3
Proteins are essential molecules with a diverse range of functions; elucidating their biological and biochemical characteristics can be difficult and...