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Use of Experimental Design To Optimize Docking Performance: The Case of LiGenDock, the Docking Module of Ligen, a New De Novo Design Program

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

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Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function
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Gaussian docking functions
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AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading
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Evaluation of the performance of four molecular docking programs on a diverse set of protein‐ligand complexes
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Can we trust docking results? Evaluation of seven commonly used programs on PDBbind database
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ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation
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Principles of docking: An overview of search algorithms and a guide to scoring functions
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A new test set for validating predictions of protein–ligand interaction
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Protein–ligand docking: Current status and future challenges
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A Fast Flexible Docking Method using an Incremental Construction Algorithm
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LigBuilder: A Multi-Purpose Program for Structure-Based Drug Design
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Recommendations for evaluation of computational methods
inferredcites →https://doi.org/10.1007/s10822-012-9565-yopenalex-snapshot
Evaluation of DOCK 6 as a pose generation and database enrichment tool
inferredcites →https://doi.org/10.1007/s10822-012-9575-9openalex-snapshot
Docking performance of the glide program as evaluated on the Astex and DUD datasets: a complete set of glide SP results and selected results for a new scoring function integrating WaterMap and glide
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Response surface methodology (RSM) as a tool for optimization in analytical chemistry
inferredcites →https://doi.org/10.1016/s0169-409x(96)00423-1openalex-snapshot
Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings
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Experimental design and optimization
inferredcites →https://doi.org/10.1021/ci050036gopenalex-snapshot
POEM: Parameter Optimization Using Ensemble Methods: Application to Target Specific Scoring Functions
inferredcites →https://doi.org/10.1021/ci200528dopenalex-snapshot
Recognizing Pitfalls in Virtual Screening: A Critical Review
inferredcites →https://doi.org/10.1021/ci400078gopenalex-snapshot
LiGen: A High Performance Workflow for Chemistry Driven de Novo Design
inferredcites →https://doi.org/10.1021/ci600426eopenalex-snapshot
Evaluating Virtual Screening Methods: Good and Bad Metrics for the “Early Recognition” Problem
inferredcites →https://doi.org/10.1021/ci6005596openalex-snapshot
A Multivariate Approach to Investigate Docking Parameters' Effects on Docking Performance
inferredcites →https://doi.org/10.1021/ci7000378openalex-snapshot
Evaluations of Molecular Docking Programs for Virtual Screening
inferredcites →https://doi.org/10.1021/ci900056copenalex-snapshot
Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy
inferredcites →https://doi.org/10.1021/jm020406hopenalex-snapshot
Surflex: Fully Automatic Flexible Molecular Docking Using a Molecular Similarity-Based Search Engine
inferredcites →https://doi.org/10.1021/jm0302997openalex-snapshot
Evaluation of Docking Performance: Comparative Data on Docking Algorithms
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/jm0306430openalex-snapshot
Glide: A New Approach for Rapid, Accurate Docking and Scoring. 1. Method and Assessment of Docking Accuracy
inferredcites →https://doi.org/10.1021/jm048957qopenalex-snapshot
The PDBbind Database: Methodologies and Updates
inferredcites →https://doi.org/10.1021/jm0608356openalex-snapshot
Benchmarking Sets for Molecular Docking
inferredcites →https://doi.org/10.1023/a:1007907728892openalex-snapshot
QXP: Powerful, rapid computer algorithms for structure-based drug design
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/b:jcam.0000017496.76572.6fopenalex-snapshot
Comparative study of several algorithms for flexible ligand docking
inferredcites →https://doi.org/10.1038/nrd1549openalex-snapshot
Docking and scoring in virtual screening for drug discovery: methods and applications
inferredcites →https://doi.org/10.1080/01621459.1951.10500769openalex-snapshot
The Kolmogorov-Smirnov Test for Goodness of Fit
inferredcites →https://doi.org/10.1093/protein/6.7.723openalex-snapshot
Matching chemistry and shape in molecular docking
inferredcites →https://doi.org/10.1111/j.2517-6161.1951.tb00067.xopenalex-snapshot
On the Experimental Attainment of Optimum Conditions
inferredcites →https://doi.org/10.1146/annurev.biophys.32.110601.142532openalex-snapshot
Molecular Recognition and Docking Algorithms
inferredcites →https://doi.org/10.1198/tech.2006.s379openalex-snapshot
Statistics for Experimenters: Design, Innovation and Discovery
inferredcites →https://doi.org/10.1371/journal.pone.0017986openalex-snapshot
Inhibitors of Helicobacter pylori Protease HtrA Found by ‘Virtual Ligand’ Screening Combat Bacterial Invasion of Epithelia
inferredcites →https://doi.org/10.2174/138920306778559412openalex-snapshot
eHiTS: An Innovative Approach to the Docking and Scoring Function Problems
inferredcites →https://doi.org/10.2174/138945008786949432openalex-snapshot
Molecular Docking Algorithms

What points at this work

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

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Improvements, trends, and new ideas in molecular docking: 2012–2013 in review
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Rational design of allosteric modulators: Challenges and successes
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Dynamic Application Autotuning for Self-aware Approximate Computing
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Exploiting OpenMP and OpenACC to accelerate a geometric approach to molecular docking in heterogeneous HPC nodes
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Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App
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Enabling performance portability on the LiGen drug discovery pipeline
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Discovery of Novel TRPM8 Blockers Suitable for the Treatment of Somatic and Ocular Painful Conditions: A Journey through pKa and LogD Modulation
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Paclitaxel binds and activates C5aR1: A new potential therapeutic target for the prevention of chemotherapy-induced peripheral neuropathy and hypersensitivity reactions
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Novel selective, potent naphthyl TRPM8 antagonists identified through a combined ligand- and structure-based virtual screening approach
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ANTAREX -- AutoTuning and Adaptivity appRoach for Energy Efficient eXascale HPC Systems
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Understanding the I/O Impact on the Performance of High-Throughput Molecular Docking
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mARGOt: A Dynamic Autotuning Framework for Self-Aware Approximate Computing
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EXSCALATE: An Extreme-Scale Virtual Screening Platform for Drug Discovery Targeting Polypharmacology to Fight SARS-CoV-2
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The ANTAREX approach to autotuning and adaptivity for energy efficient HPC systems
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Autotuning and adaptivity in energy efficient HPC systems
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Accelerating a Geometric Approach to Molecular Docking with OpenACC
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An hybrid approach to accelerate a molecular docking application for virtual screening in heterogeneous nodes
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Towards a Portable Drug Discovery Pipeline with SYCL 2020
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Revisiting De Novo Drug Design: Receptor Based Pharmacophore Screening
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Yin-yang in drug discovery: rethinking de novo design and development of predictive models
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Binding Mode Exploration of B1 Receptor Antagonists’ by the Use of Molecular Dynamics and Docking Simulation—How Different Target Engagement Can Determine Different Biological Effects
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Combining Different Docking Engines and Consensus Strategies to Design and Validate Optimized Virtual Screening Protocols for the SARS-CoV-2 3CL Protease
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A Review on Parallel Virtual Screening Softwares for High-Performance Computers
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AutoTuning and Adaptivity appRoach for Energy Efficient eXascale HPC Systems: The ANTAREX Approach
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EXSCALATE: An extreme-scale in-silico virtual screening platform to evaluate 1 trillion compounds in 60 hours on 81 PFLOPS supercomputers
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