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Global Free Energy Scoring Functions Based on Distance-Dependent Atom-Type Pair Descriptors

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Converging free energy estimates: MM‐PB(GB)SA studies on the protein–protein complex Ras–Raf
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Assessment of programs for ligand binding affinity prediction
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λ‐Dynamics free energy simulation methods
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Improved protein–ligand docking using GOLD
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General and targeted statistical potentials for protein–ligand interactions
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SFCscore: Scoring functions for affinity prediction of protein–ligand complexes
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Docking and scoring with alternative side‐chain conformations
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Knowledge-based scoring function to predict protein-ligand interactions
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The Elements of Statistical Learning: Data Mining, Inference, and Prediction
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Development and validation of a modular, extensible docking program: DOCK 5
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Customizing scoring functions for docking
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A geometric approach to macromolecule-ligand interactions
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Target-biased scoring approaches and expert systems in structure-based virtual screening
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The role of quantum mechanics in structure-based drug design
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Order Changes within Receptor Systems upon Ligand Binding: Receptor Tightening/Oligomerisation and the Interpretation of Binding Parameters
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Cooperative biotin binding by streptavidin. Electrophoretic behavior and subunit association of streptavidin in the presence of 6 M urea.
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Progress in Medicinal Chemistry
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Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings 1PII of original article: S0169-409X(96)00423-1. The article was originally published in Advanced Drug Delivery Reviews 23 (1997) 3–25. 1
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Development of proteo-chemometrics: a novel technology for the analysis of drug-receptor interactions
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Ligand efficiency: a useful metric for lead selection
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Ligand efficiency indices as guideposts for drug discovery
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Efficient Drug Lead Discovery and Optimization
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Atomic physicochemical parameters for three-dimensional-structure-directed quantitative structure-activity relationships. 2. Modeling dispersive and hydrophobic interactions
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Predicting Protein−Ligand Binding Affinities Using Novel Geometrical Descriptors and Machine-Learning Methods
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QSAR − How Good Is It in Practice? Comparison of Descriptor Sets on an Unbiased Cross Section of Corporate Data Sets
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Test MM-PB/SA on True Conformational Ensembles of Protein−Ligand Complexes
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Leave-Cluster-Out Cross-Validation Is Appropriate for Scoring Functions Derived from Diverse Protein Data Sets
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Novel, Customizable Scoring Functions, Parameterized Using N-PLS, for Structure-Based Drug Discovery
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Distance Dependent Scoring Function for Describing Protein−Ligand Intermolecular Interactions
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Lead Finder: An Approach To Improve Accuracy of Protein−Ligand Docking, Binding Energy Estimation, and Virtual Screening
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Sharpening the Toolbox of Computational Chemistry: A New Approximation of CriticalF-Values for Multiple Linear Regression
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Comparative Assessment of Scoring Functions on a Diverse Test Set
inferredcites →https://doi.org/10.1021/ci900251kopenalex-snapshot
Docking Ligands into Flexible and Solvated Macromolecules. 5. Force-Field-Based Prediction of Binding Affinities of Ligands to Proteins
inferredcites →https://doi.org/10.1021/ci9004139openalex-snapshot
Binding Affinity Prediction with Property-Encoded Shape Distribution Signatures
inferredcites →https://doi.org/10.1021/ja9621760openalex-snapshot
Development and Testing of the OPLS All-Atom Force Field on Conformational Energetics and Properties of Organic Liquids
inferredcites →https://doi.org/10.1021/ja970798vopenalex-snapshot
Molecular Dynamics Studies of the Hydration of α,α-Trehalose
inferredcites →https://doi.org/10.1021/jm0200299openalex-snapshot
Simple, Intuitive Calculations of Free Energy of Binding for Protein−Ligand Complexes. 1. Models without Explicit Constrained Water
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/jm048973nopenalex-snapshot
Large-Scale Validation of a Quantum Mechanics Based Scoring Function: Predicting the Binding Affinity and the Binding Mode of a Diverse Set of Protein−Ligand Complexes
inferredcites →https://doi.org/10.1021/jm049314dopenalex-snapshot
A Knowledge-Based Energy Function for Protein−Ligand, Protein−Protein, and Protein−DNA Complexes
inferredcites →https://doi.org/10.1021/jm050038sopenalex-snapshot
PMF Scoring Revisited
inferredcites →https://doi.org/10.1021/jm050260xopenalex-snapshot
Development of Quantitative Structure−Binding Affinity Relationship Models Based on Novel Geometrical Chemical Descriptors of the Protein−Ligand Interfaces
inferredcites →https://doi.org/10.1021/jm050362nopenalex-snapshot
A Critical Assessment of Docking Programs and Scoring Functions
inferredcites →https://doi.org/10.1021/jm050436vopenalex-snapshot
DrugScore CSD Knowledge-Based Scoring Function Derived from Small Molecule Crystal Data with Superior Recognition Rate of Near-Native Ligand Poses and Better Affinity Prediction
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/jm060999mopenalex-snapshot
Prediction of Protein−Ligand Interactions. Docking and Scoring: Successes and Gaps
inferredcites →https://doi.org/10.1021/jm100112jopenalex-snapshot
A Medicinal Chemist’s Guide to Molecular Interactions
inferredcites →https://doi.org/10.1021/jm701255bopenalex-snapshot
Ligand Binding Efficiency: Trends, Physical Basis, and Implications
inferredcites →https://doi.org/10.1021/jm801444xopenalex-snapshot
Large-Scale Application of High-Throughput Molecular Mechanics with Poisson−Boltzmann Surface Area for Routine Physics-Based Scoring of Protein−Ligand Complexes
inferredcites →https://doi.org/10.1023/a:1016357811882openalex-snapshot
Further development and validation of empirical scoring functions for structure-based binding affinity prediction
inferredcites →https://doi.org/10.1023/a:1020155510718openalex-snapshot
A review of protein-small molecule docking methods
inferredcites →https://doi.org/10.1063/1.2378907openalex-snapshot
Comparison of free energy methods for molecular systems
inferredcites →https://doi.org/10.1093/bioinformatics/btq112openalex-snapshot
A machine learning approach to predicting protein–ligand binding affinity with applications to molecular docking
inferredcites →https://doi.org/10.1110/ps.051970306openalex-snapshot
Cooperative hydrogen bond interactions in the streptavidin–biotin system
inferredcites →https://doi.org/10.1146/annurev.biophys.36.040306.132550openalex-snapshot
Calculation of Protein-Ligand Binding Affinities
inferredcites →https://doi.org/10.1146/annurev.pharmtox.37.1.71openalex-snapshot
STRUCTURE-BASED DRUG DESIGN:Computational Advances
inferredcites →https://doi.org/10.2174/092986706778521797openalex-snapshot
Docking and Scoring - Theoretically Easy, Practically Impossible?
inferredcites →https://doi.org/10.2174/138920306778559395openalex-snapshot
Scoring Functions for Protein-Ligand Docking
inferredcites →https://doi.org/10.2174/138920306778559412openalex-snapshot
eHiTS: An Innovative Approach to the Docking and Scoring Function Problems
inferredcites →https://doi.org/10.2174/138920307781369382openalex-snapshot
Structure-Based Drug Design: Docking and Scoring
inferredcites →https://doi.org/10.2174/156802609789207091openalex-snapshot
Docking Screens: Right for the Right Reasons?
inferredcites →https://doi.org/10.2174/157340909787580863openalex-snapshot
Computational Intelligence Methods for Docking Scores

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Scoring Functions for Protein–Ligand Interactions
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CPIScore: A Deep Learning Approach for Rapid Scoring and Interpretation of Protein–Ligand Binding Interactions
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Three Descriptor Model Sets a High Standard for the CSAR-NRC HiQ Benchmark
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Robust Scoring Functions for Protein–Ligand Interactions with Quantum Chemical Charge Models
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CSAR Benchmark Exercise of 2010: Combined Evaluation Across All Submitted Scoring Functions
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MM/GBSA Binding Energy Prediction on the PDBbind Data Set: Successes, Failures, and Directions for Further Improvement
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ID-Score: A New Empirical Scoring Function Based on a Comprehensive Set of Descriptors Related to Protein–Ligand Interactions
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Binding Affinity Prediction for Protein–Ligand Complexes Based on β Contacts and B Factor
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Comparative Assessment of Scoring Functions on an Updated Benchmark: 2. Evaluation Methods and General Results
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The Experimental Uncertainty of Heterogeneous Public Ki Data
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Docking accuracy enhanced by QM-derived protein charges
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TS ‐Chemscore, a Target‐Specific Scoring Function, Significantly Improves the Performance of Scoring in Virtual Screening
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CSCORE: A SIMPLE YET EFFECTIVE SCORING FUNCTION FOR PROTEIN–LIGAND BINDING AFFINITY PREDICTION USING MODIFIED CMAC LEARNING ARCHITECTURE
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Substituting random forest for multiple linear regression improves binding affinity prediction of scoring functions: Cyscore as a case study
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