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The SAMPL project, initiated in 2008, has traditionally included not only protein-ligand modeling, but also challenges based on smaller molecular systems, such as the hydration free energies of small molecules and the binding thermodynamics of host-guest systems. Compact model systems like these embody critical elements of the physical chemistry of protein-ligand binding, while making it far easier to probe the accuracy of computational tools used to model protein-ligand interactions, and to identify and correct sources of error.

The D3R project is coordinating with the organizers of SAMPL to continue these exercises. In particular, while the D3R Grand Challenges will exclusively use traditional datasets comprising a protein target with multiple drug-like ligands, SAMPL will bring in other types of data to drive the evaluation and improvement of computational models intended for ultimate use in computer-aided drug design, with a particular focus on model systems amenable to study with detailed simulations and/or quantum chemical methodologies.

The NIH has funded the SAMPL project and a tentative roadmap for SAMPL's future activities is available, but will be updated in the near future based on the actual scope of funding. Results of the 2017 SAMPL Community Survey are also available, and indicate the community overwhelmingly supports these plans for SAMPL.


The first part of SAMPL6 involved two major categories of challenges, as detailed on the SAMPL6 page: Host-guest binding and pKa  prediction. Host-guest binding and pKa challenge input and submission forms are available.

The SAMPL6 Part I culminated with a workshop joint with D3R in La Jolla in February, 2017, and results have just been published in JCAMD.

SAMPL6 Part II, active now, includes an octanol-water log P prediction challenge which is currently open for participation and predictions from many different methods will be accepted until the submission deadline on March 15, 2019. The Log P prediction challenge will be followed by a joint D3R/SAMPL workshop in San Diego, Aug 22-23, 2019, immediately before the San Diego ACS National Meeting; a virtual workshop will precede this closer to the submission deadline. A special issue or special section of JCAMD will be organized to disseminate the results of this challenge. Join our email list by signing up here to receive announcements of all new SAMPL related news, and here to receive all announcements specific to SAMPL6 and the current log P prediction challenge.

SAMPL Organizers

Prof. John Chodera, Memorial Sloan Kettering Cancer Center, New York, NY
Prof. Michael K. Gilson, UC San Diego, La Jolla, CA
Prof. David Mobley, UC Irvine, Irvine, CA
Prof. Michael Shirts, U. of Colorado, Boulder, CO

SAMPL Committee of Consultants

Dr. Robert Abel, Schrodinger, Inc.
Prof. Bruce Gibb, Tulane University
Prof. Lyle Isaacs, University of Maryland, College Park
Dr. Paul Labute, Chemical Computing Group
Dr. Anthony Nicholls, OpenEye Scientific Software
Prof Vijay Pande, Stanford University


A full list of the 100 SAMPL references we have identified is also available in the SAMPL proposal. Please contact Danielle Bergazin (bergazin ‘at’ uci.edu) if you are aware of any additional references which should be included.

(Dates shown below are currently subject to adjustment.)


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