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Testing Assumptions and Hypotheses for Rescoring Success in Protein−Ligand Docking

https://doi.org/10.1021/ci900164f
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/1097-4571(2000)9999:9999<::aid-asi1030>3.0.co;2-eopenalex-snapshot
Predicting the effectiveness of na�ve data fusion on the basis of system characteristics
inferredcites →https://doi.org/10.1002/prot.10465openalex-snapshot
Improved protein–ligand docking using GOLD
inferredcites →https://doi.org/10.1002/prot.20497openalex-snapshot
Comparing protein–ligand docking programs is difficult
inferredcites →https://doi.org/10.1002/prot.20588openalex-snapshot
General and targeted statistical potentials for protein–ligand interactions
inferredcites →https://doi.org/10.1002/prot.340170305openalex-snapshot
Orientational sampling and rigid‐body minimization in molecular docking
inferredcites →https://doi.org/10.1002/qsar.200610084openalex-snapshot
Enhancing the Effectiveness of Ligand‐Based Virtual Screening Using Data Fusion
inferredcites →https://doi.org/10.1006/jmbi.1996.0897openalex-snapshot
Development and validation of a genetic algorithm for flexible docking 1 1Edited by F. E. Cohen
inferredcites →https://doi.org/10.1006/jmbi.1999.3371openalex-snapshot
Knowledge-based scoring function to predict protein-ligand interactions
inferredcites →https://doi.org/10.1007/s10791-005-6994-4openalex-snapshot
Comparing Rank and Score Combination Methods for Data Fusion in Information Retrieval
inferredcites →https://doi.org/10.1016/j.drudis.2006.03.009openalex-snapshot
Consensus scoring for protein–ligand interactions
inferredcites →https://doi.org/10.1016/s0022-2836(95)80037-9openalex-snapshot
Molecular recognition of receptor sites using a genetic algorithm with a description of desolvation
inferredcites →https://doi.org/10.1016/s1093-3263(01)00125-5openalex-snapshot
Consensus scoring for ligand/protein interactions
inferredcites →https://doi.org/10.1021/ci010025xopenalex-snapshot
How Does Consensus Scoring Work for Virtual Library Screening? An Idealized Computer Experiment
inferredcites →https://doi.org/10.1021/ci050034wopenalex-snapshot
Consensus Scoring Criteria for Improving Enrichment in Virtual Screening
inferredcites →https://doi.org/10.1021/ci050296yopenalex-snapshot
The Use of Consensus Scoring in Ligand-Based Virtual Screening
inferredcites →https://doi.org/10.1021/ci8000452openalex-snapshot
Using Buriedness To Improve Discrimination between Actives and Inactives in Docking
inferredcites →https://doi.org/10.1021/jm0003992openalex-snapshot
Detailed Analysis of Scoring Functions for Virtual Screening
inferredcites →https://doi.org/10.1021/jm060522aopenalex-snapshot
Accurate Prediction of the Relative Potencies of Members of a Series of Kinase Inhibitors Using Molecular Docking and MM-GBSA Scoring
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/jm061277yopenalex-snapshot
Diverse, High-Quality Test Set for the Validation of Protein−Ligand Docking Performance
inferredcites →https://doi.org/10.1021/jm990352kopenalex-snapshot
Consensus Scoring: A Method for Obtaining Improved Hit Rates from Docking Databases of Three-Dimensional Structures into Proteins
inferredcites →https://doi.org/10.1023/a:1007996124545openalex-snapshot
Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes
inferredcites →https://doi.org/10.1023/b:jcam.0000047812.39758.abopenalex-snapshot
Evaluation and application of multiple scoring functions for a virtual screening experiment
inferredcites →https://doi.org/10.4018/978-1-59140-863-5.ch003openalex-snapshot
Combinatorial Fusion Analysis

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

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Prospects of Modulating Protein–Protein Interactions
inferred← citeshttps://doi.org/10.1002/cmdc.201300204openalex-snapshot
Identification of Hck Inhibitors As Hits for the Development of Antileukemia and Anti‐HIV Agents
inferred← citeshttps://doi.org/10.1002/jmr.1077openalex-snapshot
Challenges and advances in computational docking: 2009 in review
inferred← citeshttps://doi.org/10.1002/pro.2829openalex-snapshot
AB ‐Bind: Antibody binding mutational database for computational affinity predictions
inferred← citeshttps://doi.org/10.1002/wcms.18openalex-snapshot
Outstanding challenges in protein–ligand docking and structure‐based virtual screening
inferred← citeshttps://doi.org/10.1007/978-1-4939-7465-8_12openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-16-3783-4_14openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10822-010-9356-2openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10822-011-9539-5openalex-snapshot
Are predefined decoy sets of ligand poses able to quantify scoring function accuracy?
inferred← citeshttps://doi.org/10.1007/s10822-022-00456-3openalex-snapshot
Consensus scoring evaluated using the GPCR-Bench dataset: Reconsidering the role of MM/GBSA
inferred← citeshttps://doi.org/10.1016/bs.pmch.2021.01.004openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.bmc.2011.11.010openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/acs.jcim.0c01095openalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci100393mopenalex-snapshot
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inferred← citeshttps://doi.org/10.1021/ci200098vopenalex-snapshot
MiniMuDS: A New Optimizer using Knowledge-Based Potentials Improves Scoring of Docking Solutions
inferred← citeshttps://doi.org/10.1021/ci500446sopenalex-snapshot
Performance of Protein–Ligand Docking with Simulated Chemical Shift Perturbations
inferred← citeshttps://doi.org/10.1021/jm101382topenalex-snapshot
Discovery of Potent Inhibitors of Soluble Epoxide Hydrolase by Combinatorial Library Design and Structure-Based Virtual Screening
inferred← citeshttps://doi.org/10.1021/jm2011589openalex-snapshot
Crystal Structure-Based Virtual Screening for Fragment-like Ligands of the Human Histamine H 1 Receptor
inferred← citeshttps://doi.org/10.1038/srep28288openalex-snapshot
Function-specific virtual screening for GPCR ligands using a combined scoring method
inferred← citeshttps://doi.org/10.1039/9781788010139-00001openalex-snapshot
Computational Chemistry and Molecular Modelling Basics
inferred← citeshttps://doi.org/10.1080/07391102.2026.2691863openalex-snapshot
AI-assisted molecular docking and molecular dynamics simulations for predicting off-target effects of AKT1 ATP-competitive inhibitors
inferred← citeshttps://doi.org/10.1111/cbdd.12763openalex-snapshot
Boosting Pose Ranking Performance via Rescoring with MM ‐ GBSA
inferred← citeshttps://doi.org/10.1124/pr.112.007336openalex-snapshot
Computational Methods in Drug Discovery
inferred← citeshttps://doi.org/10.1147/jrd.2018.2888987openalex-snapshot
Potential of quantum computing for drug discovery
inferred← citeshttps://doi.org/10.1371/journal.pone.0134472openalex-snapshot
The Augmenting Effects of Desolvation and Conformational Energy Terms on the Predictions of Docking Programs against mPGES-1
inferred← citeshttps://doi.org/10.15625/2525-2518/59/4/16003openalex-snapshot
VIRTUAL SCREENING STATEGIES IN DRUG DISCOVERY – A BRIEF OVERVIEW
inferred← citeshttps://doi.org/10.2174/09298673113209990001openalex-snapshot
Virtual Screening Strategies in Drug Discovery: A Critical Review
inferred← citeshttps://doi.org/10.2174/1389450119666181022153016openalex-snapshot
Molecular Docking: Challenges, Advances and its Use in Drug Discovery Perspective
inferred← citeshttps://doi.org/10.2174/1389557520666200730161549openalex-snapshot
Virtual Screening of Natural Products Database
inferred← citeshttps://doi.org/10.2174/156802611794863580openalex-snapshot
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inferred← citeshttps://doi.org/10.2174/1568026619666181120142141openalex-snapshot
Application of Computational Techniques to Unravel Structure-Function Relationship and their Role in Therapeutic Development
inferred← citeshttps://doi.org/10.3389/fddsv.2026.1815176openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/molecules24020277openalex-snapshot
PeptoGrid—Rescoring Function for AutoDock Vina to Identify New Bioactive Molecules from Short Peptide Libraries
inferred← citeshttps://doi.org/10.53846/goediss-3829openalex-snapshot
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