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CSAR Scoring Challenge Reveals the Need for New Concepts in Estimating Protein–Ligand Binding Affinity
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1096-987x(19981115)19:14<1639::aid-jcc10>3.0.co;2-bopenalex-snapshot
Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
inferredcites →https://doi.org/10.1002/jcc.20634openalex-snapshot
A semiempirical free energy force field with charge‐based desolvation
inferredcites →https://doi.org/10.1002/jcc.20893openalex-snapshot
Assessment of programs for ligand binding affinity prediction
inferredcites →https://doi.org/10.1002/prot.20512openalex-snapshot
Binding MOAD (Mother Of All Databases)
inferredcites →https://doi.org/10.1002/prot.23099openalex-snapshot
TSAR, a new graph–theoretical approach to computational modeling of protein side‐chain flexibility: Modeling of ionization properties of proteins
inferredcites →https://doi.org/10.1016/s0006-3495(99)76868-2openalex-snapshot
A Self-Consistent, Microenvironment Modulated Screened Coulomb Potential Approximation to Calculate pH-Dependent Electrostatic Effects in Proteins
inferredcites →https://doi.org/10.1021/ci800166popenalex-snapshot
Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening
inferredcites →https://doi.org/10.1021/jm030489hopenalex-snapshot
Assessing Scoring Functions for Protein−Ligand Interactions
inferredcites →https://doi.org/10.1021/jm030580lopenalex-snapshot
The PDBbind Database: Collection of Binding Affinities for Protein−Ligand Complexes with Known Three-Dimensional Structures
inferredcites →https://doi.org/10.1021/jm048957qopenalex-snapshot
The PDBbind Database: Methodologies and Updates
inferredcites →https://doi.org/10.1021/jm050362nopenalex-snapshot
A Critical Assessment of Docking Programs and Scoring Functions
inferredcites →https://doi.org/10.1021/jm051256oopenalex-snapshot
Extra Precision Glide: Docking and Scoring Incorporating a Model of Hydrophobic Enclosure for Protein−Ligand Complexes
inferredcites →https://doi.org/10.1021/jm100112jopenalex-snapshot
A Medicinal Chemist’s Guide to Molecular Interactions
inferredcites →https://doi.org/10.1073/pnas.0407607101openalex-snapshot
Halogen bonds in biological molecules
inferredcites →https://doi.org/10.1093/nar/gkj039openalex-snapshot
AffinDB: a freely accessible database of affinities for protein-ligand complexes from the PDB
inferredcites →https://doi.org/10.1093/nar/gkl999openalex-snapshot
BindingDB: a web-accessible database of experimentally determined protein-ligand binding affinities
inferredcites →https://doi.org/10.1108/03684920410534506openalex-snapshot
Information Theory, Inference, and Learning Algorithms
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Latest developments in molecular docking: 2010–2011 in review
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Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets
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Docking pose selection by interaction pattern graph similarity: application to the D3R grand challenge 2015
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Predicting Ligand Binding Modes from Neural Networks Trained on Protein–Ligand Interaction Fingerprints
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Does a More Precise Chemical Description of Protein–Ligand Complexes Lead to More Accurate Prediction of Binding Affinity?
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