41 research outputs found
AI is a viable alternative to high throughput screening: a 318-target study
: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery
Recommended from our members
Accounting for apparent deviations between calorimetric and van't Hoff enthalpies
BackgroundIn theory, binding enthalpies directly obtained from calorimetry (such as ITC) and the temperature dependence of the binding free energy (van't Hoff method) should agree. However, previous studies have often found them to be discrepant.MethodsExperimental binding enthalpies (both calorimetric and van't Hoff) are obtained for two host-guest pairs using ITC, and the discrepancy between the two enthalpies is examined. Modeling of artificial ITC data is also used to examine how different sources of error propagate to both types of binding enthalpies.ResultsFor the host-guest pairs examined here, good agreement, to within about 0.4kcal/mol, is obtained between the two enthalpies. Additionally, using artificial data, we find that different sources of error propagate to either enthalpy uniquely, with concentration error and heat error propagating primarily to calorimetric and van't Hoff enthalpies, respectively.ConclusionsWith modern calorimeters, good agreement between van't Hoff and calorimetric enthalpies should be achievable, barring issues due to non-ideality or unanticipated measurement pathologies. Indeed, disagreement between the two can serve as a flag for error-prone datasets. A review of the underlying theory supports the expectation that these two quantities should be in agreement.General significanceWe address and arguably resolve long-standing questions regarding the relationship between calorimetric and van't Hoff enthalpies. In addition, we show that comparison of these two quantities can be used as an internal consistency check of a calorimetry study
Evaluating Force Field Performance in Thermodynamic Calculations of Cyclodextrin Host–Guest Binding: Water Models, Partial Charges, and Host Force Field Parameters
Computational
prediction of noncovalent binding free energies with
methods based on molecular mechanical force fields has become increasingly
routine in drug discovery projects, where they promise to speed the
discovery of small molecule ligands to bind targeted proteins with
high affinity. Because the reliability of free energy methods still
has significant room for improvement, new force fields, or modifications
of existing ones, are regularly introduced with the aim of improving
the accuracy of molecular simulations. However, comparatively little
work has been done to systematically assess how well force fields
perform, particularly in relation to the calculation of binding affinities.
Hardware advances have made these calculations feasible, but comprehensive
force field assessments for protein–ligand sized systems still
remain costly. Here, we turn to cyclodextrin host–guest systems,
which feature many hallmarks of protein–ligand binding interactions
but are generally much more tractable due to their small size. We
present absolute binding free energy and enthalpy calculations, using
the attach-pull-release (APR) approach, on a set of 43 cyclodextrin-guest
pairs for which experimental ITC data are available. The test set
comprises both α- and β-cyclodextrin hosts binding a series
of small organic guests, each with one of three functional groups:
ammonium, alcohol, or carboxylate. Four water models are considered
(TIP3P, TIP4Pew, SPC/E, and OPC), along with two partial charge assignment
procedures (RESP and AM1-BCC) and two cyclodextrin host force fields.
The results suggest a complex set of considerations when choosing
a force field for biomolecular simulations. For example, some force
field combinations clearly outperform others at the binding enthalpy
calculations but not for the binding free energy. Additionally, a
force field combination which we expected to be the worst performer
gave the most accurate binding free energies – but the least
accurate binding enthalpies. The results have implications for the
development of improved force fields, and we propose this test set,
and potential future elaborations of it, as a powerful validation
suite to evaluate new force fields and help guide future force field
development
Recommended from our members
Predicting binding free energies: Frontiers and benchmarks (a perpetual review)
Binding free energy calculations based on molecular simulations provide predicted affinities for biomolecular complexes.These calculations begin with a detailed description of a system, including its chemical composition and the interactions between its components.Simulations of the system are then used to compute thermodynamic information, such as binding affinities.Because of their growing promise for guiding molecular design, these calculations have recently begun to see widespread applications in early stage drug discovery.However, many challenges remain to make them a robust and reliable tool. Here, we highlight key challenges facing these calculations, describe known examples of these challenges, and call for the designation of standard community benchmark test systems that will help the research community generate and evaluate progress.In our view, progress will require careful assessment and evaluation of new methods, force fields, and modeling innovations on well-characterized benchmark systems, and we lay out our vision for how this can be achieved. This repository relates to the perpetual review (definition) paper called "Predicting binding free energies: Frontiers and benchmarks" by David L. Mobley, Germano Heinzelmann and Michael K. Gilson. Its focus is benchmark sets for binding free energy calculations, including the perpetual review paper, but also all things relating to benchmark sets for free energy calculations. This includes discussion, datasets, and standards for datasets and data deposition. This work is posted with permission from the Annual Review of Biophysics, Volume 46 © 2017 by Annual Reviews. Only the Annual Reviews version of the work is peer reviewed; versions posted here are effectively preprints updated at the authors' discretion. The right to create derivative works (exercised here) is also exercised with permission from the Annual Review of Biophysics, Volume 46 © 2017 by Annual Reviews, http://www.annualreviews.org/
Updated versions of this work are maintained at github.com/mobleylab/benchmarksets and this eScholarship archive serves to archive release versions of the work
Bind3P: Optimization of a Water Model with Host-Guest Binding Data
We report a water model, Bind3P (Version 0.1), which was obtained by using sensitivity analysis to readjust the Lennard-Jones parameters of the TIP3P model against experimental binding free energies for six host-guest systems, along with pure liquid properties. Tests of Bind3P against >100 experimental binding free energies and enthalpies for host-guest systems distinct from the training set show a consistent drop in the mean signed error, relative to matched calculations with TIP3P. Importantly, Bind3P also yields some improvement in the hydration free energies of small organic molecules, and preserves the accuracy of bulk water properties, such as density and the heat of vaporization. The same approach can be applied to more sophisticated water models that can better represent pure water properties. These results lend further support to concept of integrating host-guest binding data into force field parameterization
Attach-Pull-Release Calculations of Ligand Binding and Conformational Changes on the First BRD4 Bromodomain
Bromodomains,
protein domains involved in epigenetic regulation,
are able to bind small molecules with high affinity. In the present
study, we report free energy calculations for the binding of seven
ligands to the first BRD4 bromodomain, using the attach-pull-release
(APR) method to compute the reversible work of removing the ligands
from the binding site and then allowing the protein to relax conformationally.
We test three different water models, TIP3P, TIP4PEw, and SPC/E, as
well as the GAFF and GAFF2 parameter sets for the ligands. Our simulations
show that the apo crystal structure of BRD4 is only metastable, with
a structural transition happening in the absence of the ligand typically
after 20 ns of simulation. We compute the free energy change for this
transition with a separate APR calculation on the free protein and
include its contribution to the ligand binding free energies, which
generally causes an underestimation of the affinities. By testing
different water models and ligand parameters, we are also able to
assess their influence in our results and determine which one produces
the best agreement with the experimental data. Both free energies
associated with the conformational change and ligand binding are affected
by the choice of water model, with the two sets of ligand parameters
affecting their binding free energies to a lesser degree. Across all
six combinations of water model and ligand potential function, the
Pearson correlation coefficients between calculated and experimental
binding free energies range from 0.55 to 0.83, and the root-mean-square
errors range from 1.4–3.2 kcal/mol. The current protocol also
yields encouraging preliminary results when used to assess the relative
stability of ligand poses generated by docking or other methods, as
illustrated for two different ligands. Our method takes advantage
of the high performance provided by graphics processing units and
can readily be applied to other ligands as well as other protein systems
Optimized Mapping of Gas-Phase Quantum Calculations to General Force Field Lennard-Jones Parameters Based on Liquid-State Data
We utilize a previously
described Minimal Basis Iterative Stockholder (MBIS) method to carry out an
atoms-in-molecules partitioning of electron densities. Information from these atomic densities is
then mapped to Lennard-Jones parameters using a set of mapping parameters much
smaller than the typical number of atom types in a force field. This approach
is advantageous in two ways: it eliminates atom types by allowing each atom to
have unique Lennard-Jones parameters, and it greatly reduces the number of parameters
to be optimized. We show that this approach yields results comparable to those obtained
with the typed GAFF force field, even when trained on a relatively small amount
of experimental data