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Using Buriedness To Improve Discrimination between Actives and Inactives in Docking
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/(sici)1097-0134(19981115)33:3<367::aid-prot6>3.0.co;2-wopenalex-snapshot
Flexible docking using tabu search and an empirical estimate of binding affinity
inferredcites →https://doi.org/10.1002/jcc.20504openalex-snapshot
An iterative knowledge‐based scoring function to predict protein–ligand interactions: I. Derivation of interaction potentials
inferredcites →https://doi.org/10.1002/prot.10465openalex-snapshot
Improved protein–ligand docking using GOLD
inferredcites →https://doi.org/10.1006/jmbi.1996.0477openalex-snapshot
A Fast Flexible Docking Method using an Incremental Construction Algorithm
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/10.1007/bf00124474openalex-snapshot
Scoring noncovalent protein-ligand interactions: A continuous differentiable function tuned to compute binding affinities
inferredcites →https://doi.org/10.1016/j.ddtec.2004.08.004openalex-snapshot
Scoring functions for protein–ligand interactions: a critical perspective
inferredcites →https://doi.org/10.1016/j.jmb.2006.07.022openalex-snapshot
Travel Depth, a New Shape Descriptor for Macromolecules: Application to Ligand Binding
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(03)00125-6openalex-snapshot
Analysis and optimization of structure-based virtual screening protocols
inferredcites →https://doi.org/10.1021/ci00020a039openalex-snapshot
Comparison of Automatic Three-Dimensional Model Builders Using 639 X-ray Structures
inferredcites →https://doi.org/10.1021/ci020055fopenalex-snapshot
Consideration of Molecular Weight during Compound Selection in Virtual Target-Based Database Screening
inferredcites →https://doi.org/10.1021/ci034289qopenalex-snapshot
Virtual Screening Using Protein−Ligand Docking: Avoiding Artificial Enrichment
inferredcites →https://doi.org/10.1021/ci0500381openalex-snapshot
A Stepwise Approach for Defining the Applicability Domain of SAR and QSAR Models
inferredcites →https://doi.org/10.1021/ci700157bopenalex-snapshot
y-Randomization and Its Variants in QSPR/QSAR
inferredcites →https://doi.org/10.1021/jm050040jopenalex-snapshot
Parameter Estimation for Scoring Protein−Ligand Interactions Using Negative Training Data
inferredcites →https://doi.org/10.1021/jm050362nopenalex-snapshot
A Critical Assessment of Docking Programs and Scoring Functions
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/10.1023/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/a:1008724921888openalex-snapshot
Modifications of the scoring function in FlexX for virtual screening applications
inferredcites →https://doi.org/10.1186/1471-2105-7-316openalex-snapshot
CAVER: a new tool to explore routes from protein clefts, pockets and cavities
inferredcites →https://doi.org/10.2174/092986706779026165openalex-snapshot
Towards Predictive Ligand Design With Free-Energy Based Computational Methods?
inferredcites →https://doi.org/10.2174/138920306778559395openalex-snapshot
Scoring Functions for Protein-Ligand Docking
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/9783527633326.ch7openalex-snapshot
The Challenge of Affinity Prediction: Scoring Functions for Structure‐Based Virtual Screening
inferred← citeshttps://doi.org/10.1002/jcc.70470openalex-snapshot
Can Cavity Prediction Algorithms Help in Docking Experiments?
inferred← citeshttps://doi.org/10.1002/minf.201200132openalex-snapshot
Key Structural Features of Azanaphthoquinone Annelated Pyrrole Derivative as Anticancer Agents Based on the Rational Drug Design Approaches
inferred← citeshttps://doi.org/10.1007/s10822-009-9276-1openalex-snapshot
Robust optimization of scoring functions for a target class
inferred← citeshttps://doi.org/10.1007/s10822-010-9356-2openalex-snapshot
Chemical space sampling by different scoring functions and crystal structures
inferred← citeshttps://doi.org/10.1007/s10822-022-00478-xopenalex-snapshot
A high quality, industrial data set for binding affinity prediction: performance comparison in different early drug discovery scenarios
inferred← citeshttps://doi.org/10.1016/j.cellsig.2024.111181openalex-snapshot
Moringin, an isothiocyanate modulates multiple cellular signalling molecules in breast cancer cells
inferred← citeshttps://doi.org/10.1016/j.drudis.2009.03.013openalex-snapshot
Targeted scoring functions for virtual screening
inferred← citeshttps://doi.org/10.1021/ci500299hopenalex-snapshot
Docking Ligands into Flexible and Solvated Macromolecules. 7. Impact of Protein Flexibility and Water Molecules on Docking-Based Virtual Screening Accuracy
inferred← citeshttps://doi.org/10.1021/ci8004176openalex-snapshot
Docking Ligands into Flexible and Solvated Macromolecules. 3. Impact of Input Ligand Conformation, Protein Flexibility, and Water Molecules on the Accuracy of Docking Programs
inferred← citeshttps://doi.org/10.1021/ci900164fopenalex-snapshot
Testing Assumptions and Hypotheses for Rescoring Success in Protein−Ligand Docking
inferred← citeshttps://doi.org/10.1371/journal.pgen.1012163openalex-snapshot
Predicting antifolate resistance in the unculturable fungal pathogen Pneumocystis jirovecii
inferred← citeshttps://doi.org/10.19070/2377-8075-21000276openalex-snapshot
Bioactive Compounds from Clove against Oral Biofilm Drug Targets - An insilico Analysis
inferred← citeshttps://doi.org/10.2174/0109298673284600231230093955openalex-snapshot
Evaluation of Efficacy of Curcumin and Caffeic Acid Phenethyl Ester in Breast Cancer by Preclinical Studies
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