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CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes

James B. Dunbar, Richard D. Smith, Chao-Yie Yang, Peter Man-Un Ung, Katrina W. Lexa, Nickolay A. Khazanov, Jeanne A. Stuckey, Shaomeng Wang, Heather A. Carlson
2011 Journal of Chemical Information and Modeling  
Here, we describe our process for creating the 2010 benchmark exercise data set that was used in the studies to follow.  ...  This paper presents the process of developing the data set used in the 2010 CSAR exercise (flowchart in Figure 1 ).  ... 
doi:10.1021/ci200082t pmid:21728306 pmcid:PMC3180202 fatcat:cqd3oezs2bbdrlpz7spd75lxoq

CSAR Benchmark Exercise of 2010: Combined Evaluation Across All Submitted Scoring Functions

Richard D. Smith, James B. Dunbar, Peter Man-Un Ung, Emilio X. Esposito, Chao-Yie Yang, Shaomeng Wang, Heather A. Carlson
2011 Journal of Chemical Information and Modeling  
To learn what features are most important to address first, we devised our 2010 benchmark exercise.  ...  We also thank the Chemical Computing Group and OpenEye Scientific Software for generously donating the use of their software. ' REFERENCES Special Issue: CSAR 2010 Scoring Exercise Received: June 14, 2011  ... 
doi:10.1021/ci200269q pmid:21809884 pmcid:PMC3186041 fatcat:o72lqwmrbbhgbh2pqtkxv6ifyq

Lessons Learned in Empirical Scoring with smina from the CSAR 2011 Benchmarking Exercise

David Ryan Koes, Matthew P. Baumgartner, Carlos J. Camacho
2013 Journal of Chemical Information and Modeling  
scoring function and evaluated it in the context of the CSAR 2011 benchmarking exercise.  ...  Using our general method, the unique capabilities of smina, a set of default interaction terms from AutoDock Vina, and the CSAR (Community Structure-Activity Resource) 2010 dataset, we created a custom  ...  Acknowledgments This work was supported by grant R01GM097082-01 from the National Institutes of Health.  ... 
doi:10.1021/ci300604z pmid:23379370 pmcid:PMC3726561 fatcat:5is3fcqvifbfpbf7ipx5kd2vue

CSAR Benchmark Exercise 2011–2012: Evaluation of Results from Docking and Relative Ranking of Blinded Congeneric Series

Kelly L. Damm-Ganamet, Richard D. Smith, James B. Dunbar, Jeanne A. Stuckey, Heather A. Carlson
2013 Journal of Chemical Information and Modeling  
A total of 20 research groups submitted results for the benchmark exercise where the goal was to compare different improvements for pose prediction, enrichment, and relative ranking of congeneric series  ...  The Community Structure-Activity Resource (CSAR) recently held its first blinded exercise based on data provided by Abbott, Vertex, and colleagues at the University of Michigan, Ann Arbor.  ...  CSAR conducted its first benchmark exercise in 2010 with the goal of (1) evaluating the current ability of the field to predict the free energy of binding for proteinligand complexes and (2) investigating  ... 
doi:10.1021/ci400025f pmid:23548044 pmcid:PMC3753884 fatcat:dxmgxmeerbh4xe4xyg7ynmnagi

CSAR 2014: A Benchmark Exercise Using Unpublished Data from Pharma

Heather A. Carlson, Richard D. Smith, Kelly L. Damm-Ganamet, Jeanne A. Stuckey, Aqeel Ahmed, Maire A. Convery, Donald O. Somers, Michael Kranz, Patricia A. Elkins, Guanglei Cui, Catherine E. Peishoff, Millard H. Lambert (+1 others)
2016 Journal of Chemical Information and Modeling  
In Phase 1 of the CSAR 2014 Exercise, participants were given several protein-ligand complexes and asked to identify the one near-native pose from among 200 decoys provided by CSAR.  ...  The 2014 CSAR Benchmark Exercise was the last community-wide exercise that was conducted by the group at the University of Michigan, Ann Arbor.  ...  The CSAR Center is funded by the National Institute of General Medical Sciences (U01 GM086873).  ... 
doi:10.1021/acs.jcim.5b00523 pmid:27149958 pmcid:PMC5228621 fatcat:5kin36kdjrfndps4w3yhge3tla

Scoring and Lessons Learned with the CSAR Benchmark Using an Improved Iterative Knowledge-Based Scoring Function

Sheng-You Huang, Xiaoqin Zou
2011 Journal of Chemical Information and Modeling  
The resulted scoring function, referred to as ITScore 2.0, has been tested with the CSAR (Community Structure-Activity Resource, 2009 release) benchmark of 345 diverse protein-ligand complexes.  ...  Based on a statistical mechanics-based iterative method, we have extracted a set of distancedependent, all-atom pairwise potentials for protein-ligand interactions from the crystal structures of 1300 protein-ligand  ...  The computations were performed on the HPC resources at the University of Missouri Bioinformatics Consortium (UMBC).  ... 
doi:10.1021/ci2000727 pmid:21830787 pmcid:PMC3190652 fatcat:sy75s3tlgnbo7jfyv4uqrgrzny

Combined Application of Cheminformatics- and Physical Force Field-Based Scoring Functions Improves Binding Affinity Prediction for CSAR Data Sets

Jui-Hua Hsieh, Shuangye Yin, Shubin Liu, Alexander Sedykh, Nikolay V. Dokholyan, Alexander Tropsha
2011 Journal of Chemical Information and Modeling  
Special Issue: CSAR 2010 Scoring Exercise Received: March 28, 2011 Figure 1 . 1 Illustration of the method to derive PL/MCT-Tess descriptors using the tesselated proteinÀligand complex (3ERT, the ER/  ...  In this study, we employ the CSAR-NRC benchmark set to test two scoring functions of very different natures.  ... 
doi:10.1021/ci200146e pmid:21780807 pmcid:PMC3183266 fatcat:a3mpg6litjffxoecillhubxqie

A Diverse Benchmark Based on 3D Matched Molecular Pairs for Validating Scoring Functions

Lena Kalinowsky, Julia Weber, Shantheya Balasupramaniam, Knut Baumann, Ewgenij Proschak
2018 ACS Omega  
The prediction of protein-ligand interactions and their corresponding binding free energy is a challenging task in structure-based drug design and related applications.  ...  This data set was used to study the predictive power of 13 commonly used scoring functions to demonstrate the applicability of the 3D-MMP data set as a valuable tool for benchmarking scoring functions.  ...  Guido Kirsten, Chemical Computing Group, for the adaptation of the KNIME node to the Amber force field.  ... 
doi:10.1021/acsomega.7b01194 pmid:31458770 pmcid:PMC6641919 fatcat:kchkibqqbjaurorpje4u72ubni

Recent improvements to Binding MOAD: a resource for protein–ligand binding affinities and structures

Aqeel Ahmed, Richard D. Smith, Jordan J. Clark, James B. Dunbar, Heather A. Carlson
2014 Nucleic Acids Research  
The improved user interface incorporates current thirdparty plugins for better visualization of protein and ligand molecules, and it provides features like sorting, filtering and filtered downloads.  ...  Binding MOAD has grown at the rate of 1994 complexes per year, on average. Currently, it contains 23 269 complexes and 8156 binding affinities.  ...  ACKNOWLEDGEMENT We thank the many coworkers who have contributed to the Binding MOAD project, particularly Dr Mark Benson, PhD.  ... 
doi:10.1093/nar/gku1088 pmid:25378330 pmcid:PMC4383918 fatcat:vkrhl5ppizc4lnivd6nstpzewy

RosENet: Improving binding affinity prediction by leveraging molecular mechanics energies with a 3D Convolutional Neural Network [article]

Hussein Hassan-Harrirou, Ce Zhang, Thomas Lemmin
2020 bioRxiv   pre-print
absolute binding affinity of protein - ligand complexes.  ...  One key step in these approaches is the need for the rapid and accurate prediction of the binding affinity for potential leads.  ...  This dataset was part of the CSAR 2010 exercise and was composed of two sets: A2.2 FEP The FEP dataset was used for a Free Energy Perturbation study 32 A.2.3 PDBBind 2018 NMR structures Complexes  ... 
doi:10.1101/2020.05.12.090191 fatcat:ktsozvesc5hd7jsrtutrlbsf2q

ABS–Scan: In silico alanine scanning mutagenesis for binding site residues in protein–ligand complex

Praveen Anand, Deepesh Nagarajan, Sumanta Mukherjee, Nagasuma Chandra
2014 F1000Research  
It is well known that the residues present at the binding site of the protein form pockets that provide a conducive environment for recognition of specific ligands.  ...  Understanding the process of ligand recognition by proteins is a vital activity in molecular biology and biochemistry.  ...  Acknowledgements We acknowledge all the members of the NSC lab for useful suggestions during the development of the web-server and visualization of the results.  ... 
doi:10.12688/f1000research.5165.1 pmid:25685322 pmcid:PMC4319546 fatcat:rs4nfm7tgzbz5borueyxw4h3ba

ABS–Scan: In silico alanine scanning mutagenesis for binding site residues in protein–ligand complex

Praveen Anand, Deepesh Nagarajan, Sumanta Mukherjee, Nagasuma Chandra
2014 F1000Research  
It is well known that the residues present at the binding site of the protein form pockets that provide a conducive environment for recognition of specific ligands.  ...  Understanding the process of ligand recognition by proteins is a vital activity in molecular biology and biochemistry.  ...  Acknowledgements We acknowledge all the members of the NSC lab for useful suggestions during the development of the web-server and visualization of the results.  ... 
doi:10.12688/f1000research.5165.2 pmid:25685322 pmcid:PMC4319546 fatcat:chrxsu6jpzeizilkdzrfw4fi5i

Multipose Binding in Molecular Docking

Kalina Atkovska, Sergey Samsonov, Maciej Paszkowski-Rogacz, M. Pisabarro
2014 International Journal of Molecular Sciences  
., the property of certain protein-ligand complexes to exhibit different ligand binding modes, has been shown to occur in nature for a variety of molecules.  ...  Further developments of the selection criteria for docking solutions for each individual complex are still necessary for a general utilization of the multipose binding concept for accurate binding affinity  ...  Conflicts of Interest The authors declare no conflict of interest.  ... 
doi:10.3390/ijms15022622 pmid:24534807 pmcid:PMC3958872 fatcat:nvm46ljofrcddb5won76plkn6u

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

Sergei Grudinin, Maria Kadukova, Andreas Eisenbarth, Simon Marillet, Frédéric Cazals
2016 Journal of Computer-Aided Molecular Design  
provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes.  ...  Predicting binding poses and affinities for protein-ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimationAbstract The 2015 D3R Grand Challenge  ...  Acknowledgments The authors thank Dr. Petr Popov from MIPT Moscow for the initial analysis of the HSP90 targets.  ... 
doi:10.1007/s10822-016-9976-2 pmid:27718029 fatcat:ofyasi7lzbbazl66nyh4e22jku

Machine-learning scoring functions to improve structure-based binding affinity prediction and virtual screening

Qurrat Ul Ain, Antoniya Aleksandrova, Florian D. Roessler, Pedro J. Ballester
2015 Wiley Interdisciplinary Reviews. Computational Molecular Science  
The emerging picture from these studies is that the classical approach of using linear regression with a small number of expert-selected structural features can be strongly improved by a machine-learning  ...  The reliability of docking depends, however, on the accuracy of the adopted scoring function (SF).  ...  the CSAR benchmark by a large margin.  ... 
doi:10.1002/wcms.1225 pmid:27110292 pmcid:PMC4832270 fatcat:6kkpyx7m3bgn5lxunyw7nga56i
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