Journal: Journal of Computer-Aided Molecular Design

Abbreviation

J Comput Aided Mol Des

Publisher

Springer

Journal Volumes

ISSN

0920-654X
1573-4951

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2011 - 201952020 - 20223
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Publications 1 - 8 of 8
  • Relative free-energy calculations for scaffold hopping-type transformations with an automated RE-EDS sampling procedure
    Item type: Journal Article
    Ries, Benjamin; Normak, Karl; Weiß, R. Gregor; et al. (2022)
    Journal of Computer-Aided Molecular Design
    The calculation of relative free-energy differences between different compounds plays an important role in drug design to identify potent binders for a given protein target. Most rigorous methods based on molecular dynamics simulations estimate the free-energy difference between pairs of ligands. Thus, the comparison of multiple ligands requires the construction of a "state graph", in which the compounds are connected by alchemical transformations. The computational cost can be optimized by reducing the state graph to a minimal set of transformations. However, this may require individual adaptation of the sampling strategy if a transformation process does not converge in a given simulation time. In contrast, path-free methods like replica-exchange enveloping distribution sampling (RE-EDS) allow the sampling of multiple states within a single simulation without the pre-definition of alchemical transition paths. To optimize sampling and convergence, a set of RE-EDS parameters needs to be estimated in a pre-processing step. Here, we present an automated procedure for this step that determines all required parameters, improving the robustness and ease of use of the methodology. To illustrate the performance, the relative binding free energies are calculated for a series of checkpoint kinase 1 inhibitors containing challenging transformations in ring size, opening/closing, and extension, which reflect changes observed in scaffold hopping. The simulation of such transformations with RE-EDS can be conducted with conventional force fields and, in particular, without soft bond-stretching terms.
  • RestraintMaker: a graph-based approach to select distance restraints in free-energy calculations with dual topology
    Item type: Journal Article
    Ries, Benjamin; Rieder, Salomé; Rhiner, Clemens; et al. (2022)
    Journal of Computer-Aided Molecular Design
    The calculation of relative binding free energies (RBFE) involves the choice of the end-state/system representation, of a sampling approach, and of a free-energy estimator. System representations are usually termed “single topology” or “dual topology”. As the terminology is often used ambiguously in the literature, a systematic categorization of the system representations is proposed here. In the dual-topology approach, the molecules are simulated as separate molecules. Such an approach is relatively easy to automate for high-throughput RBFE calculations compared to the single-topology approach. Distance restraints are commonly applied to prevent the molecules from drifting apart, thereby improving the sampling efficiency. In this study, we introduce the program RestraintMaker, which relies on a greedy algorithm to find (locally) optimal distance restraints between pairs of atoms based on geometric measures. The algorithm is further extended for multi-state methods such as enveloping distribution sampling (EDS) or multi-site λ-dynamics. The performance of RestraintMaker is demonstrated for toy models and for the calculation of relative hydration free energies. The Python program can be used in script form or through an interactive GUI within PyMol. The selected distance restraints can be written out in GROMOS or GROMACS file formats. Additionally, the program provides a human-readable JSON format that can easily be parsed and processed further. The code of RestraintMaker is freely available on GitHub https://github.com/rinikerlab/restraintmaker.
  • Local neighborhood behavior in a combinatorial library context
    Item type: Journal Article
    Horvath, Dragos; Koch, Christian; Schneider, Gisbert; et al. (2011)
    Journal of Computer-Aided Molecular Design
  • Designing the molecular future
    Item type: Journal Article
    Schneider, Gisbert (2012)
    Journal of Computer-Aided Molecular Design
  • Multi-task learning for pK(a) prediction
    Item type: Journal Article
    Skolidis, Grigorios; Hansen, Katja; Sanguinetti, Guido; et al. (2012)
    Journal of Computer-Aided Molecular Design
  • Free energy calculations offer insights into the influence of receptor flexibility on ligand–receptor binding affinities
    Item type: Journal Article
    Dolenc, Jozica; Riniker, Sereina; Gaspari, Roberto; et al. (2011)
    Journal of Computer-Aided Molecular Design
  • Free enthalpies of replacing water molecules in protein binding pockets
    Item type: Journal Article
    Riniker, Sereina; Barandun, Luzi J.; Diederich, François; et al. (2012)
    Journal of Computer-Aided Molecular Design
  • Use of molecular dynamics fingerprints (MDFPs) in SAMPL6 octanol–water log P blind challenge
    Item type: Journal Article
    Wang, Shuzhe; Riniker, Sereina (2020)
    Journal of Computer-Aided Molecular Design
    The in silico prediction of partition coefficients is an important task in computer-aided drug discovery. In particular the octanol–water partition coefficient is used as surrogate for lipophilicity. Various computational approaches have been proposed, ranging from simple group-contribution techniques based on the 2D topology of a molecule to rigorous methods based molecular dynamics (MD) or quantum chemistry. In order to balance accuracy and computational cost, we recently developed the MD fingerprints (MDFPs), where the information in MD simulations is encoded in a floating-point vector, which can be used as input for machine learning (ML). The MDFP-ML approach was shown to perform similarly to rigorous methods while being substantially more efficient. Here, we present the application of MDFP-ML for the prediction of octanol–water partition coefficients in the SAMPL6 blind challenge. The underlying computational pipeline is made freely available in form of the MDFPtools package.
Publications 1 - 8 of 8