A Specialized and Enhanced Deep Generation Model for Active Molecular Design Targeting Kinases Guided by Affinity Prediction Models and Reinforcement Learning
Sign Up to like & getrecommendations! Published in 2025 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.5c00074
Abstract: Kinases are critical regulators in numerous cellular processes, and their dysregulation is linked to various diseases, including cancer. Thus, protein kinases have emerged as major drug targets at present, with approximately a quarter to a… read more here.
Keywords: affinity prediction; generation; drug; specialized enhanced ... See more keywords
SophosQM: Accurate Binding Affinity Prediction in Compound Optimization
Sign Up to like & getrecommendations! Published in 2023 at "ACS Omega"
DOI: 10.1021/acsomega.2c08132
Abstract: The optimization of compounds’ binding affinity for a biological target is a crucial aspect of the drug development process. Being able to accurately predict binding energies in advance of synthesizing compounds would have a massive… read more here.
Keywords: binding affinity; affinity; sophosqm; affinity prediction ... See more keywords
Interformer: an interaction-aware model for protein-ligand docking and affinity prediction
Sign Up to like & getrecommendations! Published in 2024 at "Nature Communications"
DOI: 10.1038/s41467-024-54440-6
Abstract: In recent years, the application of deep learning models to protein-ligand docking and affinity prediction, both vital for structure-based drug design, has garnered increasing interest. However, many of these models overlook the intricate modeling of… read more here.
Keywords: affinity prediction; affinity; protein ligand; model ... See more keywords
A Folding-Docking-Affinity framework for protein-ligand binding affinity prediction
Sign Up to like & getrecommendations! Published in 2025 at "Communications Chemistry"
DOI: 10.1038/s42004-025-01506-1
Abstract: Accurate protein-ligand binding affinity prediction is crucial in drug discovery. Existing methods are predominately docking-free, without explicitly considering atom-level interaction between proteins and ligands in scenarios where crystallized protein-ligand binding conformations are unavailable. Now, with… read more here.
Keywords: binding affinity; affinity prediction; affinity; protein ligand ... See more keywords
SAM-DTA: a sequence-agnostic model for drug-target binding affinity prediction
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac533
Abstract: Drug-target binding affinity prediction is a fundamental task for drug discovery and has been studied for decades. Most methods follow the canonical paradigm that processes the inputs of the protein (target) and the ligand (drug)… read more here.
Keywords: binding affinity; drug target; sequence; target binding ... See more keywords
Improving drug-target affinity prediction via feature fusion and knowledge distillation.
Sign Up to like & getrecommendations! Published in 2023 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbad145
Abstract: Rapid and accurate prediction of drug-target affinity can accelerate and improve the drug discovery process. Recent studies show that deep learning models may have the potential to provide fast and accurate drug-target affinity prediction. However,… read more here.
Keywords: drug target; prediction; drug; affinity prediction ... See more keywords
DeepDTA: deep drug–target binding affinity prediction
Sign Up to like & getrecommendations! Published in 2018 at "Bioinformatics"
DOI: 10.1093/bioinformatics/bty593
Abstract: Motivation The identification of novel drug‐target (DT) interactions is a substantial part of the drug discovery process. Most of the computational methods that have been proposed to predict DT interactions have focused on binary classification,… read more here.
Keywords: affinity prediction; drug target; binding affinity; affinity ... See more keywords
A simple spatial extension to the extended connectivity interaction features for binding affinity prediction
Sign Up to like & getrecommendations! Published in 2022 at "Royal Society Open Science"
DOI: 10.1098/rsos.211745
Abstract: The representation of the protein-ligand complexes used in building machine learning models play an important role in the accuracy of binding affinity prediction. The Extended Connectivity Interaction Features (ECIF) is one such representation. We report… read more here.
Keywords: extended connectivity; binding affinity; affinity prediction; interaction features ... See more keywords
Improving the accuracy of high-throughput protein-protein affinity prediction may require better training data
Sign Up to like & getrecommendations! Published in 2017 at "BMC Bioinformatics"
DOI: 10.1186/s12859-017-1533-z
Abstract: BackgroundOne goal of structural biology is to understand how a protein’s 3-dimensional conformation determines its capacity to interact with potential ligands. In the case of small chemical ligands, deconstructing a static protein-ligand complex into its… read more here.
Keywords: affinity prediction; protein affinity; protein protein; affinity ... See more keywords
Drug-target binding affinity prediction based on power graph and word2vec
Sign Up to like & getrecommendations! Published in 2025 at "BMC Medical Genomics"
DOI: 10.1186/s12920-024-02073-5
Abstract: Drug and protein targets affect the physiological functions and metabolic effects of the body through bonding reactions, and accurate prediction of drug-protein target interactions is crucial for drug development. In order to shorten the drug… read more here.
Keywords: drug; drug target; target; affinity prediction ... See more keywords
Distance plus attention for binding affinity prediction
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Cheminformatics"
DOI: 10.1186/s13321-024-00844-x
Abstract: Protein-ligand binding affinity plays a pivotal role in drug development, particularly in identifying potential ligands for target disease-related proteins. Accurate affinity predictions can significantly reduce both the time and cost involved in drug development. However,… read more here.
Keywords: distance; binding affinity; affinity prediction; attention ... See more keywords