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D3R grand challenge 2015: Evaluation of protein–ligand pose and affinity predictions

Symon Gathiaka, Shuai Liu, Michael Chiu, Huanwang Yang, Jeanne A. Stuckey, You Na Kang, Jim Delproposto, Ginger Kubish, James B. Dunbar, Heather A. Carlson, Stephen K. Burley, W. Patrick Walters (+3 others)
2016 Journal of Computer-Aided Molecular Design  
An additional sub-challenge provided small groups of chemically similar HSP90 compounds amenable to alchemical calculations of relative binding free energy.  ...  second stage testing methods for ranking compounds with knowledge of at least a subset of the ligand-protein poses.  ...  Acknowledgments We thank the National Institutes of Health (NIH) for grant 1U01GM111528 for the Drug Design Data Resource (D3R) and U01 GM086873 to the Community Structure Activity Resource (CSAR).  ... 
doi:10.1007/s10822-016-9946-8 pmid:27696240 pmcid:PMC5562487 fatcat:akvv3ttra5d65msjn62jwntsqm

Deep neural network affinity model for BACE inhibitors in D3R Grand Challenge 4 [article]

Bo Wang, Ho Leung Ng
2019 bioRxiv   pre-print
Drug Design Data Resource (D3R) Grand Challenge 4 (GC4) offered a unique opportunity for designing and testing novel methodology for accurate docking and affinity prediction of ligands in an open and blinded  ...  According to the results released by D3R, we achieved a Spearman's rank correlation coefficient of 0.43(7) for predicting the affinity of 154 ligands.  ...  Introduction The Drug Design Data Resource (D3R) has organized four Grand Challenges (GC) for docking, affinity, and free energy predictions for protein-ligand complexes.  ... 
doi:10.1101/680306 fatcat:k5pjjlo4avfibbqqbwdtjifika

Blinded predictions of binding modes and energies of HSP90-α ligands for the 2015 D3R grand challenge

Antonia S.J.S. Mey, Jordi Juárez-Jiménez, Alexis Hennessy, Julien Michel
2016 Bioorganic & Medicinal Chemistry  
Abstract In the framework of the 2015 D3R inaugural grand challenge, blind binding pose and affinity predictions were performed for a set of 180 ligands of the Heat Shock Protein HSP 90- protein, a relevant  ...  Structured as a two-stage contest, the first D3R grand challenge aimed to put different computational approaches to the test to predict binding modes and binding affinities.  ... 
doi:10.1016/j.bmc.2016.07.044 pmid:27485604 fatcat:fjwhzhvypnhjxktorsckpwrksi

Optimal strategies for virtual screening of induced-fit and flexible target in the 2015 D3R Grand Challenge

Zhaofeng Ye, Matthew P. Baumgartner, Bentley M. Wingert, Carlos J. Camacho
2016 Journal of Computer-Aided Molecular Design  
Pose prediction using our "close" models resulted in average ligand RMSDs of 0.32 Å and 1.6 Å for HSP90 and MAP4K4, respectively, the most accurate models of the community-wide challenge.  ...  In addition, "close" methods that leverage the co-crystals of the different binding modes of HSP90 also predicted the best affinity ranking.  ...  Acknowledgement The authors thank D3R for organizing and evaluating the 2015 Grand Challenge. We are grateful to the OpenEye Scientific for providing an academic license for their software.  ... 
doi:10.1007/s10822-016-9941-0 pmid:27573981 pmcid:PMC5079819 fatcat:65dh5fjdsvah7pe6qrfy7qw5qi

Large scale free energy calculations for blind predictions of protein–ligand binding: the D3R Grand Challenge 2015

Nanjie Deng, William F. Flynn, Junchao Xia, R. S. K. Vijayan, Baofeng Zhang, Peng He, Ahmet Mentes, Emilio Gallicchio, Ronald M. Levy
2016 Journal of Computer-Aided Molecular Design  
We describe binding free energy calculations in the D3R Grand Challenge 2015 for blind prediction of the binding affinities of 180 ligands to Hsp90.  ...  , the BEDAM binding free energy scoring has resulted in a moderate enrichment of ligand screening against this challenging drug target.  ...  We have participated in the SAMPL3, SAMPL4, SAMPL5 and D3R Grand Challenge 2015 challenges, using the in-house developed BEDAM method for absolute binding free energy calculations [8] [9] [10] .  ... 
doi:10.1007/s10822-016-9952-x pmid:27562018 pmcid:PMC5869689 fatcat:flkyagqv5fgzlezomzplgntdb4

Performance evaluation of molecular docking and free energy calculations protocols using the D3R Grand Challenge 4 dataset

Eddy Elisée, Vytautas Gapsys, Nawel Mele, Ludovic Chaput, Edithe Selwa, Bert L. de Groot, Bogdan I. Iorga
2019 Journal of Computer-Aided Molecular Design  
to predict the binding modes and ranking of ligands.  ...  After the end of the challenge, we also carried out free energy calculations (i.e. in a non-blinded manner) for CatS using the pmx software and several force fields (AMBER, Charmm).  ...  In Phase 2, organizers released the complexes from the pose prediction subset and the participants were required to repeat the affinity predictions for the subset of 154 ligands and the relative free energy  ... 
doi:10.1007/s10822-019-00232-w pmid:31677003 fatcat:h57locrhsnbg3o7cyivy73auee

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  
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  ...  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.  ...  Petr Popov from MIPT Moscow for the initial analysis of the HSP90 targets.  ... 
doi:10.1007/s10822-016-9976-2 pmid:27718029 fatcat:ofyasi7lzbbazl66nyh4e22jku

Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations

Majda Misini Ignjatović, Octav Caldararu, Geng Dong, Camila Muñoz-Gutierrez, Francisco Adasme-Carreño, Ulf Ryde
2016 Journal of Computer-Aided Molecular Design  
Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations. Journal of Computer-Aided Molecular Design, 30(9), 707-730.  ...  Binding-affinity predictions of HSP90 in the D3R Grand Challenge 2015 with docking, MM/GBSA, QM/MM, and free-energy simulations Misini Ignjatović, Majda; Caldararu, Octav; Dong, Geng; Muñoz-Gutierrez,  ... 
doi:10.1007/s10822-016-9942-z pmid:27565797 pmcid:PMC5078160 fatcat:5zhysvqf4vesvemorjrsyw4gti

Coupling enhanced sampling of the apo-receptor with template-based ligand conformers selection: performance in pose prediction in the D3R Grand Challenge 4

Andrea Basciu, Panagiotis I. Koukos, Giuliano Malloci, Alexandre M. J. J. Bonvin, Attilio V. Vargiu
2019 Journal of Computer-Aided Molecular Design  
in the 2019 iteration of the Grand Challenge (GC4) organized by the D3R consortium.  ...  conformation of the binding site within ~ 1 Å RMSD; (ii) as already shown by some of us in GC3, even in the presence of near-native protein structures, a proper selection of ligand conformers is crucial  ...  and to rank them and/or estimate their free energies of binding.  ... 
doi:10.1007/s10822-019-00244-6 pmid:31720895 fatcat:nvfaqtryxvgnhdsu4mdw333ove

Blinded evaluation of cathepsin S inhibitors from the D3RGC3 dataset using molecular docking and free energy calculations

Ludovic Chaput, Edithe Selwa, Eddy Elisée, Bogdan I. Iorga
2018 Journal of Computer-Aided Molecular Design  
functional information available in public databases (PDB, ChEMBL, PubChem Assay, BindingDB, etc.); (ii) the docking of ligand dataset to provide a prediction for the binding modes and ranking of ligands  ...  As expected, the correct ranking of docking poses is still challenging.  ...  This work was supported by the Laboratory of Excellence in Research on Medication and Innovative Therapeutics (LER-MIT) (Agence Nationale de la Recherche, Grant Number ANR-10-LABX-33), by the JPIAMR transnational  ... 
doi:10.1007/s10822-018-0161-7 pmid:30206740 fatcat:6pp7u2pk75gutnej5njlnyvm5e

Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations

Antonia S. J. S. Mey, Jordi Juárez Jiménez, Julien Michel
2017 Journal of Computer-Aided Molecular Design  
latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations.  ...  Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of FXR inhibitors with a semi-automated alchemical free energy  ...  The D3R Grand challenge 2 was the second blinded prediction challenge organised by the D3R consortium in this case looking at predicting binding poses, binding affinity ranking, and free energies for a  ... 
doi:10.1007/s10822-017-0083-9 pmid:29134431 pmcid:PMC5767197 fatcat:7j2nmdpz65egzmzntdbxov2goi

Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations [article]

Antonia S. J. S. Mey, Jordi Juárez-Jiménez, Julien Michel
2017 bioRxiv   pre-print
The drug design data resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations  ...  Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of FXR inhibitors with a semi-automated alchemical free energy  ...  The D3R Grand challenge 2 was the second blinded prediction challenge organised by the D3R consortium in this case looking at predicting binding poses, binding affinity ranking, and free energies for a  ... 
doi:10.1101/150474 fatcat:dnnynb5e3ffnflveb46owhaq4i

Machine‐learning scoring functions for structure‐based drug lead optimization

Hongjian Li, Kam‐Heung Sze, Gang Lu, Pedro J. Ballester
2020 Wiley Interdisciplinary Reviews. Computational Molecular Science  
A classical SF assumes a predetermined theory-inspired functional form for the relationship between the features characterizing the structure of the protein-ligand complex and its predicted binding affinity  ...  Scoring functions (SFs) are employed to rank these molecules by their predicted binding affinity (potency).  ...  [26] [27] [28] The D3R Grand Challenge 2 27 presented a blind evaluation of methods to predict the affinities of molecules against the nuclear receptor Farnesoid X receptor (FXR).  ... 
doi:10.1002/wcms.1465 fatcat:qnrk4qw3h5gjtcxncourqzhkxe

Benchmarking ensemble docking methods as a scientific outreach project [article]

Jessie L Gan, Dhruv Kumar, Cynthia Chen, Bryn C Taylor, Benjamin R Jagger, Rommie E Amaro, Christopher T Lee
2020 biorxiv/medrxiv   pre-print
challenges seeking to identify the best methods for ligand pose-prediction, ligand affinity ranking, and free energy calculations.  ...  Here, we, a group of high school-aged students and their mentors, present the results of our participation in Grand Challenge 4 where we predicted ligand affinity rankings for the Cathepsin S protease,  ...  "D3R Grand Challenge 3: blind pre-651 diction of proteinligand poses and affinity rankings". 652 In: Journal of Computer-Aided Molecular Design 33.Michael K. Ameriks et al.  ... 
doi:10.1101/2020.10.02.324343 fatcat:nkbbaalbdjg6dnq6siucvjiqmi

Empirical Scoring Functions for Structure-Based Virtual Screening: Applications, Critical Aspects, and Challenges

Isabella A. Guedes, Felipe S. S. Pereira, Laurent E. Dardenne
2018 Frontiers in Pharmacology  
Although pose prediction is performed with satisfactory accuracy, the correct prediction of binding affinity is still a challenging task and crucial for the success of structure-based VS experiments.  ...  Empirical scoring functions are widely used for pose and affinity prediction.  ...  The development of docking methodologies to predict poses and binding affinities of ligands that bind covalently to the receptor is a challenging task.  ... 
doi:10.3389/fphar.2018.01089 pmid:30319422 pmcid:PMC6165880 fatcat:johy46r7pzfclbpigg6kqpmqza
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