Daniel Cappel

Novel Inverse Binding Mode of Indirubin Derivatives Yields Improved Selectivity for DYRK Kinases

DYRK kinases are involved in alternative pre-mRNA splicing as well as in neuropathological states such as Alzheimers disease and Down syndrome. In this study, we present the design, synthesis, and biological evaluation of indirubins as DYRK inhibitors with enhanced selectivity. Modifications of the bis-indole included polar or acidic functionalities at positions 5′ and 6′ and a bromine or a trifluoromethyl group at position 7, affording analogues that possess high activity and pronounced specificity. Compound 6i carrying a 5′-carboxylate moiety demonstrated the best inhibitory profile. A novel inverse binding mode, which forms the basis for the improved selectivity, was suggested by molecular modeling and confirmed by determining the crystal structure of DYRK2 in complex with 6i. Structure–activity relationships were further established, including a thermodynamic analysis of binding site water molecules, offering a structural explanation for the selective DYRK inhibition.

Accurate Binding Free Energy Predictions in Fragment Optimization.

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Probing the Dynamic Nature of Water Molecules and Their Influences on Ligand Binding in a Model Binding Site

The model binding site of the cytochrome c peroxidase (CCP) W191G mutant is used to investigate the structural and dynamic properties of the water network at the buried cavity using computational methods supported by crystallographic analysis. In particular, the differences of the hydration pattern between the uncomplexed state and various complexed forms are analyzed as well as the differences between five complexes of CCP W191G with structurally closely related ligands. The ability of docking programs to correctly handle the water molecules in these systems is studied in detail. It is found that fully automated prediction of water replacement or retention upon docking works well if some additional preselection is carried out but not necessarily if the entire water network in the cavity is used as input. On the other hand, molecular interaction fields for water calculated from static crystal structures and hydration density maps obtained from molecular dynamics simulations agree very well with crystallographically observed water positions. For one complex, the docking and MD results sensitively depend on the quality of the starting structure, and agreement is obtained only after redetermination of the crystal structure and refinement at higher resolution.

Exploring conformational search protocols for ligand-based virtual screening and 3-D QSAR modeling

Abstract3-D ligand conformations are required for most ligand-based drug design methods, such as pharmacophore modeling, shape-based screening, and 3-D QSAR model building. Many studies of conformational search methods have focused on the reproduction of crystal structures (i.e. bioactive conformations); however, for ligand-based modeling the key question is how to generate a ligand alignment that produces the best results for a given query molecule. In this work, we study different conformation generation modes of ConfGen and the impact on virtual screening (Shape Screening and e-Pharmacophore) and QSAR predictions (atom-based and field-based). In addition, we develop a new search method, called common scaffold alignment, that automatically detects the maximum common scaffold between each screening molecule and the query to ensure identical coordinates of the common core, thereby minimizing the noise introduced by analogous parts of the molecules. In general, we find that virtual screening results are relatively insensitive to the conformational search protocol; hence, a conformational search method that generates fewer conformations could be considered “better” because it is more computationally efficient for screening. However, for 3-D QSAR modeling we find that more thorough conformational sampling tends to produce better QSAR predictions. In addition, significant improvements in QSAR predictions are obtained with the common scaffold alignment protocol developed in this work, which focuses conformational sampling on parts of the molecules that are not part of the common scaffold.

Molecular Dynamics Reveal Binding Mode of Glutathionylspermidine by Trypanothione Synthetase

The trypanothione synthetase (TryS) catalyses the two-step biosynthesis of trypanothione from spermidine and glutathione and is an attractive new drug target for the development of trypanocidal and antileishmanial drugs, especially since the structural information of TryS from Leishmania major has become available. Unfortunately, the TryS structure was solved without any of the substrates and lacks loop regions that are mechanistically important. This contribution describes docking and molecular dynamics simulations that led to further insights into trypanothione biosynthesis and, in particular, explains the binding modes of substrates for the second catalytic step. The structural model essentially confirm previously proposed binding sites for glutathione, ATP and two Mg2+ ions, which appear identical for both catalytic steps. The analysis of an unsolved loop region near the proposed spermidine binding site revealed a new pocket that was demonstrated to bind glutathionylspermidine in an inverted orientation. For the second step of trypanothione synthesis glutathionylspermidine is bound in a way that preferentially allows N1-glutathionylation of N8-glutathionylspermidine, classifying N8-glutathionylspermidine as the favoured substrate. By inhibitor docking, the binding site for N8-glutathionylspermidine was characterised as druggable.

Calculating Water Thermodynamics in the Binding Site of Proteins – Applications of WaterMap to Drug Discovery

The ability to accurately characterize the solvation properties (water locations and thermodynamics) of biomolecules is of great importance to drug discovery. While crystallography, NMR, and other experimental techniques can assist in determining the structure of water networks in proteins and protein-ligand complexes, most water molecules are not fully resolved and accurately placed. Furthermore, understanding the energetic effects of solvation and desolvation on binding requires an analysis of the thermodynamic properties of solvent involved in the interaction between ligands and proteins. WaterMap is a molecular dynamics-based computational method that uses statistical mechanics to describe the thermodynamic properties (entropy, enthalpy, and free energy) of water molecules at the surface of proteins. This method can be used to assess the solvent contributions to ligand binding affinity and to guide lead optimization. In this review, we provide a comprehensive summary of published uses of WaterMap, including applications to lead optimization, virtual screening, selectivity analysis, ligand pose prediction, and druggability assessment.

Generation of structure-based pharmacophores using energetic analysis – application on fragment docking

We describe a novel method to develop energetically optimized, structure-based pharmacophores for use in rapid in silico screening. The method combines pharmacophore perception and database screening with protein ligand energetic terms computed by the Glide XP scoring function to rank the importance of pharmacophore features. We derive energy-optimized pharmacophore hypotheses for 30 pharmaceutically relevant crystal structures and screen a database to assess the enrichment of active compounds. The method is compared to three other approaches: (1) pharmacophore hypotheses derived from a systematic assessment of receptor ligand contacts, (2) Glide SP docking, and (3) 2D ligand fingerprint similarity. The method developed here shows better enrichments than the other three methods and yields a greater diversity of actives than the contact-based pharmacophores or the 2D ligand similarity. We then apply this method on fragment docking using fragment-specific settings aimed to generate poses that explore every pocket of a binding site while maintaining the docking accuracy of the top scoring pose. Next, we describe how the energy terms from the Glide XP scoring function are mapped onto pharmacophore sites from the docked fragments in order to rank their importance for binding. We show that the most energetically favourable pharmacophore sites are consistent with features from known tight binding compounds. The derived pharmacophore models are able to recover known active compounds from a database screen and retrieving diverse compounds that are not biased by the co-crystallized ligand.

Virtual screening using structure-based consensus pharmacophore models and ensemble docking based on MD-generated conformations

The protozoan parasites of the genus Trypanosoma sp. and Leishmania sp. are responsible for neglected diseases like Chagas’ disease, African sleeping sickness or Leishmaniasis. The trypanothione synthetase (TryS) is an attractive new drug target for the development of trypanocidal and antileishmanial drugs [1]. In our virtual screening campaign for targeting the trypanothione synthetase (TryS) we used representative protein conformations derived from a computational analysis using molecular dynamics (MD) simulations of this key component of trypanothione biosynthesis. The publicly available crystal structure lacks a variable loop region that is known to be important for trypanothione biosynthesis. MD simulations turned out to be a good tool to model this loop region and obtain a more complete set of protein conformations for subsequent use in virtual screening [2]. For creating a structure-based consensus pharmacophore model, Superstar [3] was deployed to generate favourable non-bonded interaction maps of different functional groups (probes) for all representative protein conformations. The pharmacophore model was then created for the rigid part of the binding pocket based on high- propensity peaks of these maps. The variable loop region was left out since it can not be depicted by this approach. To include also multiple conformations of the variable loop region, the new ensemble docking feature of Gold was used [4]. After a pharmacophore search within the ZINC database the retrieved molecules were simultaneously docked to the different protein conformations to identify the best combination of ligand pose and protein conformer. Finally, several high-scoring molecules were selected for further testing. We will discuss in detail this combined pharmacophore/ensemble docking approach based on MD simulations and will present the results of the compound selection for testing.

Small-molecule targeting of MUSASHI RNA-binding activity in acute myeloid leukemia

The MUSASHI family of RNA binding proteins (MSI1 and MSI2) contribute to a wide spectrum of cancers including acute myeloid leukemia. We found that the small molecule Ro 08–2750 (Ro) directly binds to MSI2 and competes for its RNA binding in biochemical assays. Ro treatment in mouse and human myeloid leukemia cells resulted in an increase in differentiation and apoptosis, inhibition of known MSI-targets, and a shared global gene expression signature similar to shRNA depletion of MSI2. Ro demonstrated in vivo inhibition of c-MYC and reduced disease burden in a murine AML leukemia model. Thus, we have identified a small molecule that targets MSI’s oncogenic activity. Our study provides a framework for targeting RNA binding proteins in cancer.

Impact of binding site waters on inhibitor design: contemplating a novel inverse binding mode of indirubin derivatives in DYRK kinases

DYRK kinases are involved in alternative pre-mRNA splicing as well as in neuropathological states such as Alzheimers disease and Down syndrome. In this study, we present the design, synthesis, and biological evaluation of indirubins as DYRK inhibitors with enhanced selectivity. Modifications of the bis-indole included polar or acidic functionalities at positions 5′ and 6′ and a bromine or a trifluoromethyl group at position 7, affording analogues that possess high activity and pronounced specificity. Compound 6i carrying a 5′- carboxylate moiety demonstrated the best inhibitory profile. A novel inverse binding mode, which forms the basis for the improved selectivity, was suggested by molecular modeling and confirmed by determining the crystal structure of DYRK2 in complex with 6i. Structure–activity relationships were further established, including a thermodynamic analysis of binding site water molecules, offering a structural explanation for the selective DYRK inhibition [1].