Blind prediction of host–guest binding affinities: a new SAMPL3 challenge

  title={Blind prediction of host–guest binding affinities: a new SAMPL3 challenge},
  author={Hari S. Muddana and C. Daniel Varnado and Christopher W. Bielawski and Adam R. Urbach and Lyle D Isaacs and Matthew T. Geballe and Michael K. Gilson},
  journal={Journal of Computer-Aided Molecular Design},
The computational prediction of protein–ligand binding affinities is of central interest in early-stage drug-discovery, and there is a widely recognized need for improved methods. Low molecular weight receptors and their ligands—i.e., host–guest systems—represent valuable test-beds for such affinity prediction methods, because their small size makes for fast calculations and relatively facile numerical convergence. The SAMPL3 community exercise included the first ever blind prediction challenge… 
The SAMPL4 host–guest blind prediction challenge: an overview
While some methods performed fairly consistently across both hosts, no single approach emerged as consistent top performer, and the nonsystematic nature of the various submissions made it impossible to draw definitive conclusions regarding the best choices of energy models or sampling algorithms.
Overview of the SAMPL6 host–guest binding affinity prediction challenge
An overview of the SAMPL6 host–guest binding affinity prediction challenge, which featured three supramolecular hosts and an overall improvement in the correlation obtained by the affinity predictions for OA and TEMOA systems, but a surprising lack of improvement regarding root mean square error over the past several challenge rounds.
Overview of the SAMPL6 host-guest binding affinity prediction challenge
An overview of the SAMPL6 host-guest binding affinity prediction challenge, which featured three supramolecular hosts and an overall improvement in the correlation obtained by the affinity predictions for OA and TEMOA systems, but a surprising lack of improvement regarding root mean square error over the past several challenge rounds.
SAMPL3: blinded prediction of host–guest binding affinities, hydration free energies, and trypsin inhibitors
  • A. Skillman
  • Biology
    Journal of Computer-Aided Molecular Design
  • 2012
This special issue of the Journal of Computer-Aided Molecular Design is the culmination of the 4th Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) challenge and workshop, and SAMPL3 was the first blinded challenge to include prediction of host–guest binding affinities.
Overview of the SAMPL5 host–guest challenge: Are we doing better?
An overview of the host–guest component of SAMPL5, which centers on three different hosts, two octa-acids and a glycoluril-based molecular clip, and two different sets of guest molecules, in aqueous solution, and holds promise for future improvements.
Prediction of SAMPL3 host-guest affinities with the binding energy distribution analysis method (BEDAM)
BEDAM calculations are described to predict the free energies of binding of a series of anaesthetic drugs to a recently characterized acyclic cucurbituril host, offering the prospect of utilizing host-guest binding free energy data for force field validation and development.
Testing automatic methods to predict free binding energy of host–guest complexes in SAMPL7 challenge
This work aims to build a computational tool capable of automatically predicting the binding free energy of any host–guest complex, and has used the SAMPL7 challenge to test several methods and design a specific computational pipeline.
Blind prediction of SAMPL4 cucurbit[7]uril binding affinities with the mining minima method
The mining minima (M2) method is used to predict cucurbit[7]uril binding affinities from the SAMPL4 blind prediction challenge and points to possible inaccuracies in the PM6-DH+ energy model or the COSMO solvation model.
Detailed potential of mean force studies on host–guest systems from the SAMPL6 challenge
Examining a series of small host–guest complexes from the SAMPL6 blind challenge suggests that there are large systematic errors in absolute binding free energy calculations that can be straightforwardly accounted for using a scaling procedure.
Parameterization of an effective potential for protein–ligand binding from host–guest affinity data
This work illustrates how benchmark sets of high quality experimental binding affinity data and physics‐based binding free energy models can be used to evaluate and optimize force fields for protein–ligand systems.


Host-guest complexes with protein-ligand-like affinities: computational analysis and design.
The Mining Minima algorithm is used to computationally test a new series of CB[7] ligands designed to bind with similarly high affinity and reproduce key experimental observations regarding the affinities of ferrocene-based guests with CB[ 7] and beta-cyclodextrin.
Calculation of protein-ligand binding affinities.
This paper reviews physics-based models of binding, beginning with a summary of the changes in potential energy, solvation energy, and configurational entropy that influence affinity, and a theoretical overview to frame the discussion of specific computational approaches.
CSAR Benchmark Exercise of 2010: Selection of the Protein–Ligand Complexes
The details of how the data set was initially selected, and the process by which it matured to better fit the needs of the community are presented, underscores the value of a supportive, collaborative effort in moving the field forward.
The SAMPL2 blind prediction challenge: introduction and overview
The results of this blind assessment of the state of the field for transfer energy and tautomer ratio prediction both indicate where the field is performing well and point out flaws in current methods.
Binding affinities of host-guest, protein-ligand, and protein-transition-state complexes.
The origins of the distributions of association constants observed for the broad range of host-guest systems are explored, and typical approaches to compute and analyze host-GUest binding in solution are discussed.
Calculation of cyclodextrin binding affinities: energy, entropy, and implications for drug design.
The second generation Mining Minima method yields binding affinities accurate to within 0.8 kcal/mol for the associations of alpha-, beta-, and gamma-cyclodextrin with benzene, resorcinol, flurbiprofen, naproxen, and nabumetone and indicates that the computed entropy changes show a near-linear relationship with the changes in mean potential plus solvation energy.
Recent theoretical and computational advances for modeling protein-ligand binding affinities.
Enzyme/non-enzyme discrimination and prediction of enzyme active site location using charge-based methods.
Docking and scoring in virtual screening for drug discovery: methods and applications
Key concepts and specific features of small-molecule–protein docking methods are reviewed, selected applications are highlighted and recent advances that aim to address the acknowledged limitations of established approaches are discussed.
S66: A Well-balanced Database of Benchmark Interaction Energies Relevant to Biomolecular Structures
A large new database of interaction energies calculated using an accurate CCSD(T)/CBS scheme is presented, designed to cover the most common types of noncovalent interactions in biomolecules, while keeping a balanced representation of dispersion and electrostatic contributions.