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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  
The Drug Design Data Resource (D3R) ran Grand Challenge 2015 between September 2015 and February 2016.  ...  The challenges for both target datasets were conducted in two stages, with the first stage testing pose predictions and the capacity to rank compounds by affinity with minimal structural data; and the  ...  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

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  
The performance gap between classical and machine-learning SFs was large and has now broadened owing to methodological improvements and the availability of more training data.  ...  These have exhibited excellent predictive accuracy in compelling retrospective tests, outperforming in some cases much more computationally demanding molecular simulation-based methods.  ...  The D3R Grand Challenge 3 28 was a larger blind evaluation and more specific regarding whether methods employ ML or not.  ... 
doi:10.1002/wcms.1465 fatcat:qnrk4qw3h5gjtcxncourqzhkxe

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 fast evaluation of docking poses generated by the search method and the accurate prediction of binding affinity of topranked poses is essential in VS protocols.  ... 
doi:10.3389/fphar.2018.01089 pmid:30319422 pmcid:PMC6165880 fatcat:johy46r7pzfclbpigg6kqpmqza

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.  ...  The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature  ...  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

Recent Advances and Applications of Molecular Docking to G Protein-Coupled Receptors

Damian Bartuzi, Agnieszka Kaczor, Katarzyna Targowska-Duda, Dariusz Matosiuk
2017 Molecules  
A number of improvements and innovative applications of this method were documented recently. In this review, we focus particularly on innovations in docking to GPCRs.  ...  GPCRs are responsible for a vast part of signaling in vertebrates and, as such, invariably remain in the spotlight of medicinal chemistry.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/molecules22020340 pmid:28241450 fatcat:xyytfxpfcvd43dyoefto4qr5pi

Deep Learning in Virtual Screening: Recent Applications and Developments

Talia B Kimber, Yonghui Chen, Andrea Volkamer
2021 International Journal of Molecular Sciences  
Finally, the present state-of-the-art, including the current challenges and emerging problems, are examined and discussed.  ...  For many years, machine learning methods have been successfully applied in the context of computer-aided drug discovery.  ...  Similarly, in other blind challenges for pose and affinity prediction such as the D3R grand challenges, deep learning-based methods increasingly make it to the top ranges ( [149] , Table 1 ).  ... 
doi:10.3390/ijms22094435 pmid:33922714 fatcat:uecx2a7rarb2hdyui6m3kg5vge

Development of an Automatic Pipeline for Participation in the CELPP Challenge

Marina Miñarro-Lleonar, Sergio Ruiz-Carmona, Daniel Alvarez-Garcia, Peter Schmidtke, Xavier Barril
2022
Here, we present a fully automated pipeline for pose prediction validated by participating in the Continuous Evaluation of Ligand Pose Prediction (CELPP) Challenge.  ...  Molecular docking is a standard tool to predict the binding mode of a ligand to its macromolecular receptor and to quantify their mutual complementarity, with multiple applications in drug design.  ...  Besides the annual Grand Challenge, D3R also organises the CELPP Challenge (Continuous Evaluation of Ligand Pose Prediction) [16] .  ... 
doi:10.3390/ijms23094756 pmid:35563148 fatcat:atjht4ojujcm3jhvxjhh3cgaui

Abstracts of the 4th World Parkinson Congress, September 20–23, 2016, Portland, OR, USA

2016 Journal of Parkinson's Disease  
The work of a navigator nurse is varied and addresses many challenges faced by the PLWP.  ...  address care partner concerns and provide education and training to care partners to enable them to support the person with Parkinson disease's daily performance and quality of life.  ...  The APOE e4 allele predicted lower performance across multiple domains including memory, executive function, and verbal fluency.  ... 
doi:10.3233/jpd-169900 pmid:27589541 fatcat:ld522ggsvvceriigc4fi7e5g7q

Maximum entropy Potts Hamiltonian models of protein fitness and applications to HIV-1 proteins Maximum entropy Potts Hamiltonian models of protein fitness and applications to HIV-1 proteins

William Flynn, William Flynn, Ronald Levy
2017 unpublished
We demonstrate that these models are able to predict higher order sequence statistics and the fitness effects of multiple simultaneous mutations.  ...  As Hamiltonian models of sequence covariation is a growing field, we provide a first-order analytic framework to quantify the error in the model's predictions and provide a retrospective error analysis  ...  of New York in the United States of America and each party hereby consents and submits to the personal jurisdiction of such court, waives any objection to venue in such court and consents to service of  ... 
fatcat:gx2s3ohcfbhrfisnw4qz56snm4