Predicting inactive conformations of protein kinases using active structures: conformational selection of type-II inhibitors

Validation of ion mobility spectrometry - mass spectrometry as a screening tool to identify type II kinase inhibitors of FGFR1 kinase

RATIONALE

The protein kinase FGFR1 regulates cellular processes in human development. As over-activity of FGFR1 is implicated with cancer, effective inhibitors are in demand. Type I inhibitors, which bind to the active form of FGFR1, are less effective than type II inhibitors, which bind to the inactive form. Screening to distinguish between type I and type II inhibitors is required.

METHODS

X-ray crystallography was used to indicate whether a range of potential inhibitors bind to the active or inactive FGFR1 kinase conformation. The binding affinity of each ligand to FGFR1 was measured using biochemical methods. Electrospray ionisation - ion mobility spectrometry - mass spectrometry (ESI-IMS-MS) in conjunction with collision-induced protein unfolding generated a conformational profile of each FGFR1-ligand complex. The results indicate that the protein's conformational profile depends on whether the inhibitor is type I or type II.

RESULTS

X-ray crystallography confirmed which of the kinase inhibitors bind to the active or inactive form of FGFR1 kinase. Collision-induced unfolding combined with ESI-IMS-MS showed distinct differences in the FGFR1 folding landscape for type I and type II inhibitors. Biochemical studies indicated a similar range of FGFR1 affinities for both types of inhibitors, thus providing confidence that the conformational variations detected using ESI-IMS-MS can be interpretated unequivocally and that this is an effective screening method.

CONCLUSIONS

A robust ESI-IMS-MS method has been implemented to distinguish between the binding mode of type I and type II inhibitors by monitoring the conformational unfolding profile of FGFR1. This rapid method requires low sample concentrations and could be used as a high-throughput screening technique for the characterisation of novel kinase inhibitors.

Probing the Highly Disparate Dual Inhibitory Mechanisms of Novel Quinazoline Derivatives against Mycobacterium tuberculosis Protein Kinases A and B

Mycobacterium tuberculosis (Mtb) serine/threonine (Ser/Thr) Protein kinases A (PknA) and B (PknB) have been identified as highly attractive targets for overcoming drug resistant tuberculosis. A recent lead series optimization study yielded compound 33 which exhibited potencies ~1000 times higher than compound 57. This huge discrepancy left us curious to investigate the mechanistic 'dual' (in)activities of the compound using computational methods, as carried out in this study. Findings revealed that 33 stabilized the PknA and B conformations and reduced their structural activities relative to 57. Optimal stability of 33 in the hydrophobic pockets further induced systemic alterations at the P-loops, catalytic loops, helix Cs and DFG motifs of PknA and B. Comparatively, 57 was more surface-bound with highly unstable motions. Furthermore, 33 demonstrated similar binding patterns in PknA and B, involving conserved residues of their binding pockets. Both π and hydrogen interactions played crucial roles in the binding of 33, which altogether culminated in high ΔGs for both proteins. On the contrary, the binding of 57 was characterized by unfavorable interactions with possible repulsive effects on its optimal dual binding to both proteins, as evidenced by the relatively lowered ΔGs. These findings would significantly contribute to the rational structure-based design of novel and highly selective dual inhibitors of Mtb PknA and B.

The Novel Serine/Threonine Protein Kinase LmjF.22.0810 from Leishmania major may be Involved in the Resistance to Drugs such as Paromomycin

The identification and clarification of the mechanisms of action of drugs used against leishmaniasis may improve their administration regimens and prevent the development of resistant strains. Herein, for the first time, we describe the structure of the putatively essential Ser/Thr kinase LmjF.22.0810 from Leishmania major. Molecular dynamics simulations were performed to assess the stability of the kinase model. The analysis of its sequence and structure revealed two druggable sites on the protein. Furthermore, in silico docking of small molecules showed that aminoglycosides preferentially bind to the phosphorylation site of the protein. Given that transgenic LmjF.22.0810-overexpressing parasites displayed less sensitivity to aminoglycosides such as paromomycin, our predicted models support the idea that the mechanism of drug resistance observed in those transgenic parasites is the tight binding of such compounds to LmjF.22.0810 associated with its overexpression. These results may be helpful to understand the complex machinery of drug response in Leishmania.

Molecular characterization of known and novel ACVR1 variants in phenotypes of aberrant ossification

Diffuse idiopathic skeletal hyperostosis (DISH) is a disorder principally characterized by calcification and ossification of spinal ligaments and entheses. Fibrodysplasia ossificans progressiva (FOP) is a rare autosomal dominant disabling disorder characterized by progressive ossification of skeletal muscle, fascia, tendons, and ligaments. These conditions manifest phenotypic overlap in the ossification of tendons and ligaments. We describe herein a patient with DISH, exhibiting heterotopic ossification of the posterior longitudinal ligament where clinical whole exome sequencing identified a variant within ACVR1, a gene implicated in FOP. This variant, p.K400E, is a novel variant, not identified previously, and occurs in a highly conserved region across orthologs. We used sequence-based predicative algorithms, molecular modeling, and molecular dynamics simulations, to test the potential for p.K400E to alter the structure and dynamics of ACVR1. We applied the same modeling and simulation methods to established FOP variants, to identify the detailed effects that they have on the ACVR1 protein, as well as to act as positive controls against which the effects of p.K400E could be evaluated. Our in silico molecular analyses support p.K400E as altering the behavior of ACVR1. In addition, functional testing to measure the effect of this variant on BMP-pSMAD 1/5/8 target genes was carried out which revealed this variant to cause increased ID1 and Msx2 expression compared with the wild-type receptor. This analysis supports the potential for the variant of uncertain significance to contribute to the patient's phenotype.

Modeling conformational flexibility of kinases in inactive states

Kinase structures in the inactive "DFG-out" state provide a wealth of druggable binding site variants. The conformational plasticity of this state can be mainly described by different conformations of binding site-forming elements such as DFG motif, A-loop, P-loop, and αC-helix. Compared to DFG-in structures, DFG-out structures are largely underrepresented in the Protein Data Bank (PDB). Thus, structure-based drug design efforts for DFG-out inhibitors may benefit from an efficient approach to generate an ensemble of DFG-out structures. Accordingly, the presented modeling pipeline systematically generates homology models of kinases in several DFG-out conformations based on a sophisticated creation of template structures that represent the major states of the flexible structural elements. Eighteen template classes were initially selected from all available kinase structures in the PDB and subsequently employed for modeling the entire kinome in different DFG-out variants by fusing individual structural elements to multiple chimeric template structures. Molecular dynamics simulations revealed that conformational transitions between the different DFG-out states generally do not occur within trajectories of a few hundred nanoseconds length. This underlines the benefits of the presented homology modeling pipeline to generate relevant conformations of "DFG-out" kinase structures for subsequent in silico screening or binding site analysis studies.

Redefining the Protein Kinase Conformational Space with Machine Learning

Protein kinases are dynamic, adopting different conformational states that are critical for their catalytic activity. We assess a range of structural features derived from the conserved αC helix and DFG motif to define the conformational space of the catalytic domain of protein kinases. We then construct Kinformation, a random forest classifier, to annotate the conformation of 3,708 kinase structures in the PDB. Our classification scheme captures known active and inactive kinase conformations and defines an additional conformational state, thereby refining the current understanding of the kinase conformational space. Furthermore, network analysis of the small molecules recognized by each conformation captures chemical substructures that are associated with each conformation type. Our description of the kinase conformational space is expected to improve modeling of protein kinase structures, as well as guide the development of conformation-specific kinase inhibitors with optimal pharmacological profiles.

From Type I to Type II: Design, Synthesis, and Characterization of Potent Pyrazin-2-ones as DFG-Out Inhibitors of PDGFRβ

Reversible protein kinase inhibitors that bind in the ATP cleft can be classified as type I or type II binders. Of these, type I inhibitors address the active form, whereas type II inhibitors typically lock the kinase in an inactive form. At the molecular level, the conformation of the flexible activation loop holding the key DFG motif controls access to the ATP site, thereby determining an active or inactive kinase state. Accordingly, type I and type II kinase inhibitors bind to so-called DFG-in or DFG-out conformations, respectively. Based on our former study on highly selective platelet-derived growth factor receptor β (PDGFRβ) pyrazin-2-one type I inhibitors, we expanded this scaffold toward the deep pocket, yielding the highly potent and effective type II inhibitor 5 (4-[(4-methylpiperazin-1-yl)methyl]-N-[3-[[6-oxo-5-(3,4,5-trimethoxyphenyl)-1H-pyrazin-3-yl]methyl]phenyl]benzamide). In vitro characterization, including selectivity panel data from activity-based assays (300 kinases) and affinity-based assays (97 kinases) of these PDGFRβ type I (1; 5-(4-hydroxy-3-methoxy-phenyl)-3-(3,4,5-trimethoxyphenyl)-1H-pyrazin-2-one) and II (5) inhibitors showing the same pyrazin-2-one chemotype are compared. Implications are discussed regarding the data for selectivity and efficacy of type I and type II ligands.

Recent Progress in the Molecular Recognition and Therapeutic Importance of Interleukin-1 Receptor-Associated Kinase 4

Toll-like receptors (TLRs) are the most upstream pattern recognition receptors in the cell, which detect pathogen associated molecular patterns and initiate signal transduction, culminating in the transcription of pro-inflammatory cytokines and antiviral interferon. Interleukin-1 receptor-associated kinase 4 (IRAK4) is a key mediator in TLR (except for TLR3) and interleukin-1 receptor signaling pathways. The loss of kinase function of IRAK4 is associated with increased susceptibility to various pathogens, while its over-activation causes autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, and cancer. The therapeutic importance of this master kinase has been advocated by a number of recent preclinical studies, where potent inhibitors have been administered to improve various TLR-mediated pathologies. Increasing studies of X-ray crystallographic structures with bound inhibitors have improved our knowledge on the molecular recognition of ligands by IRAK4, which will be crucial for the development of new inhibitors with improved potencies. In this review, we briefly discuss the structural aspect of ligand recognition by IRAK4 and highlight its therapeutic importance in the context of TLR-associated unmet medical needs.

PL-PatchSurfer2: Improved Local Surface Matching-Based Virtual Screening Method That Is Tolerant to Target and Ligand Structure Variation

Virtual screening has become an indispensable procedure in drug discovery. Virtual screening methods can be classified into two categories: ligand-based and structure-based. While the former have advantages, including being quick to compute, in general they are relatively weak at discovering novel active compounds because they use known actives as references. On the other hand, structure-based methods have higher potential to find novel compounds because they directly predict the binding affinity of a ligand in a target binding pocket, albeit with substantially lower speed than ligand-based methods. Here we report a novel structure-based virtual screening method, PL-PatchSurfer2. In PL-PatchSurfer2, protein and ligand surfaces are represented by a set of overlapping local patches, each of which is represented by three-dimensional Zernike descriptors (3DZDs). By means of 3DZDs, the shapes and physicochemical complementarities of local surface regions of a pocket surface and a ligand molecule can be concisely and effectively computed. Compared with the previous version of the program, the performance of PL-PatchSurfer2 is substantially improved by the addition of two more features, atom-based hydrophobicity and hydrogen-bond acceptors and donors. Benchmark studies showed that PL-PatchSurfer2 performed better than or comparable to popular existing methods. Particularly, PL-PatchSurfer2 significantly outperformed existing methods when apo-form or template-based protein models were used for queries. The computational time of PL-PatchSurfer2 is about 20 times shorter than those of conventional structure-based methods. The PL-PatchSurfer2 program is available at http://www.kiharalab.org/plps2/ .

Insights into molecular interactions between CaM and its inhibitors from molecular dynamics simulations and experimental data

In order to contribute to the structural basis for rational design of calmodulin (CaM) inhibitors, we analyzed the interaction of CaM with 14 classic antagonists and two compounds that do not affect CaM, using docking and molecular dynamics (MD) simulations, and the data were compared to available experimental data. The Ca(2+)-CaM-Ligands complexes were simulated 20 ns, with CaM starting in the "open" and "closed" conformations. The analysis of the MD simulations provided insight into the conformational changes undergone by CaM during its interaction with these ligands. These simulations were used to predict the binding free energies (ΔG) from contributions ΔH and ΔS, giving useful information about CaM ligand binding thermodynamics. The ΔG predicted for the CaM's inhibitors correlated well with available experimental data as the r(2) obtained was 0.76 and 0.82 for the group of xanthones. Additionally, valuable information is presented here: I) CaM has two preferred ligand binding sites in the open conformation known as site 1 and 4, II) CaM can bind ligands of diverse structural nature, III) the flexibility of CaM is reduced by the union of its ligands, leading to a reduction in the Ca(2+)-CaM entropy, IV) enthalpy dominates the molecular recognition process in the system Ca(2+)-CaM-Ligand, and V) the ligands making more extensive contact with the protein have higher affinity for Ca(2+)-CaM. Despite their limitations, docking and MD simulations in combination with experimental data continue to be excellent tools for research in pharmacology, toward a rational design of new drugs.

Can structural features of kinase receptors provide clues on selectivity and inhibition? A molecular modeling study

Cancer is a complex disease resulting from the uncontrolled proliferation of cell signaling events. Protein kinases have been identified as central molecules that participate overwhelmingly in oncogenic events, thus becoming key targets for anticancer drugs. A majority of studies converged on the idea that ligand-binding pockets of kinases retain clues to the inhibiting abilities and cross-reacting tendencies of inhibitor drugs. Even though these ideas are critical for drug discovery, validating them using experiments is not only difficult, but also in some cases infeasible. To overcome these limitations and to test these ideas at the molecular level, we present here the results of receptor-focused in-silico docking of nine marketed drugs to 19 different wild-type and mutated kinases chosen from a wide range of families. This investigation highlights the need for using relevant models to explain the correct inhibition trends and the results are used to make predictions that might be able to influence future experiments. Our simulation studies are able to correctly predict the primary targets for each drug studied in majority of cases and our results agree with the existing findings. Our study shows that the conformations a given receptor acquires during kinase activation, and their micro-environment, defines the ligand partners. Type II drugs display high compatibility and selectivity for DFG-out kinase conformations. On the other hand Type I drugs are less selective and show binding preferences for both the open and closed forms of selected kinases. Using this receptor-focused approach, it is possible to capture the observed fold change in binding affinities between the wild-type and disease-centric mutations in ABL kinase for Imatinib and the second-generation ABL drugs. The effects of mutation are also investigated for two other systems, EGFR and B-Raf. Finally, by including pathway information in the design it is possible to model kinase inhibitors with potentially fewer side-effects.

DFGmodel: predicting protein kinase structures in inactive states for structure-based discovery of type-II inhibitors

Protein kinases exist in equilibrium of active and inactive states, in which the aspartate-phenylalanine-glycine motif in the catalytic domain undergoes conformational changes that are required for function. Drugs targeting protein kinases typically bind the primary ATP-binding site of an active state (type-I inhibitors) or utilize an allosteric pocket adjacent to the ATP-binding site in the inactive state (type-II inhibitors). Limited crystallographic data of protein kinases in the inactive state hampers the application of rational drug discovery methods for developing type-II inhibitors. Here, we present a computational approach to generate structural models of protein kinases in the inactive conformation. We first perform a comprehensive analysis of all protein kinase structures deposited in the Protein Data Bank. We then develop DFGmodel, a method that takes either a known structure of a kinase in the active conformation or a sequence of a kinase without a structure, to generate kinase models in the inactive conformation. Evaluation of DFGmodel's performance using various measures indicates that the inactive kinase models are accurate, exhibiting RMSD of 1.5 Å or lower. The kinase models also accurately distinguish type-II kinase inhibitors from likely nonbinders (AUC > 0.70), suggesting that they are useful for virtual screening. Finally, we demonstrate the applicability of our approach with three case studies. For example, the models are able to capture inhibitors with unintended off-target activity. Our computational approach provides a structural framework for chemical biologists to characterize kinases in the inactive state and to explore new chemical spaces with structure-based drug design.

Promiscuous and specific recognition among ephrins and Eph receptors

Eph-ephrin interactions control the signal transduction between cells and play an important role in carcinogenesis and other diseases. The interactions between Eph receptors and ephrins of the same subclass are promiscuous; there are cross-interactions between some subclasses, but not all. To understand how Eph-ephrin interactions can be both promiscuous and specific, we investigated sixteen energy landscapes of four Eph receptors (A2, A4, B2, and B4) interacting with four ephrin ligands (A1, A2, A5, and B2). We generated conformational ensembles and recognition energy landscapes starting from separated Eph and ephrin molecules and proceeding up to the formation of Eph-ephrin complexes. Analysis of the Eph-ephrin recognition trajectories and the co-evolution entropy of 400 ligand binding domains of Eph receptor and 241 ephrin ligands identified conserved residues during the recognition process. Our study correctly predicted the promiscuity and specificity of the interactions and provided insights into their recognition. The dynamic conformational changes during Eph-ephrin recognition can be described by progressive conformational selection and population shift events, with two dynamic salt bridges between EphB4 and ephrin-B2 contributing to the specific recognition. EphA3 cancer-related mutations lowered the binding energies. The specificity is not only controlled by the final stage of the interaction across the protein-protein interface, but also has large contributions from binding kinetics with the help of dynamic intermediates along the pathway from the separated Eph and ephrin to the Eph-ephrin complex.

Exploration of type II binding mode: A privileged approach for kinase inhibitor focused drug discovery?

The ATP site of kinases displays remarkable conformational flexibility when accommodating chemically diverse small molecule inhibitors. The so-called activation segment, whose conformation controls catalytic activity and access to the substrate binding pocket, can undergo a large conformational change with the active state assuming a ‘DFG-in’ and an inactive state assuming a ‘DFG-out’ conformation. Compounds that preferentially bind to the DFG-out conformation are typically called ‘type II’ inhibitors in contrast to ‘type I’ inhibitors that bind to the DFG-in conformation. This review surveys the large number of type II inhibitors that have been developed and provides an analysis of their crystallographically determined binding modes. Using a small library of type II inhibitors, we demonstrate that more than 200 kinases can be targeted, suggesting that type II inhibitors may not be intrinsically more selective than type I inhibitors.

Accurate calculation of mutational effects on the thermodynamics of inhibitor binding to p38α MAP kinase: a combined computational and experimental study

A major current challenge for drug design efforts focused on protein kinases is the development of drug resistance caused by spontaneous mutations in the kinase catalytic domain. The ubiquity of this problem means that it would be advantageous to develop fast, effective computational methods that could be used to determine the effects of potential resistance-causing mutations before they arise in a clinical setting. With this long-term goal in mind, we have conducted a combined experimental and computational study of the thermodynamic effects of active-site mutations on a well-characterized and high-affinity interaction between a protein kinase and a small-molecule inhibitor. Specifically, we developed a fluorescence-based assay to measure the binding free energy of the small-molecule inhibitor, SB203580, to the p38α MAP kinase and used it measure the inhibitor's affinity for five different kinase mutants involving two residues (Val38 and Ala51) that contact the inhibitor in the crystal structure of the inhibitor-kinase complex. We then conducted long, explicit-solvent thermodynamic integration (TI) simulations in an attempt to reproduce the experimental relative binding affinities of the inhibitor for the five mutants; in total, a combined simulation time of 18.5 μs was obtained. Two widely used force fields - OPLS-AA/L and Amber ff99SB-ILDN - were tested in the TI simulations. Both force fields produced excellent agreement with experiment for three of the five mutants; simulations performed with the OPLS-AA/L force field, however, produced qualitatively incorrect results for the constructs that contained an A51V mutation. Interestingly, the discrepancies with the OPLS-AA/L force field could be rectified by the imposition of position restraints on the atoms of the protein backbone and the inhibitor without destroying the agreement for other mutations; the ability to reproduce experiment depended, however, upon the strength of the restraints' force constant. Imposition of position restraints in corresponding simulations that used the Amber ff99SB-ILDN force field had little effect on their ability to match experiment. Overall, the study shows that both force fields can work well for predicting the effects of active-site mutations on small molecule binding affinities and demonstrates how a direct combination of experiment and computation can be a powerful strategy for developing an understanding of protein-inhibitor interactions.

An ire1-phk1 chimera reveals a dispensable role of autokinase activity in endoplasmic reticulum stress response

The endoplasmic reticulum transmembrane receptor Ire1 senses over-accumulation of unfolded proteins in the endoplasmic reticulum and initiates the unfolded protein response (UPR). The cytoplasmic portion of Ire1 has a protein kinase domain (KD) and a kinase extension nuclease (KEN) domain that cleaves an mRNA for encoding the Hac1 transcription factor needed to express UPR genes. During this UPR signaling, Ire1 proteins self-assemble into an oligomer of dimers, which essentially requires autophosphorylation of a constituent activation loop in the KD. However, it is not clear how dimerization, autophosphorylation, and KEN domain function are precisely coordinated. In this study, we uncoupled the KD and KEN domain functions, by removing the activation loop along with an extended region that we called the auto-inhibitory region (AIR), or by swapping the activation loop with a homologous loop from phosphorylase kinase 1 (Ire1(PHK)). Both Ire1(ΔAIR) and Ire1(PHK) activated the UPR even when either protein contained a mutation (D797A) that abolished the ability of Ire1 KD to transfer phosphates to the AIR. Neither protein functioned when containing mutations in key ATP binding residues (E746A and N749A) or in residues that disrupted Ire1 dimer interface (W426A or R697D). We interpret these results as evidence supporting the notion that the primary function of the kinase domain is to autophosphorylate the AIR in order to relieve auto-inhibition and that ADP acts as a switch to activate the KEN domain-catalyzed HAC1 mRNA cleavage.

Structural approaches to obtain kinase selectivity

One of the grand challenges in kinase drug discovery is the design of small-molecule inhibitors with selectivity profiles that will ultimately be efficacious in the clinic. Current medicinal chemistry strategies make heavy use of structural, biophysical and computational approaches to achieve this multi-faceted goal. Here we review structure-based approaches underlying the development of several molecules that are currently in clinical trials, including the cMet inhibitor ARQ197 and the Bcr-Abl inhibitor ponatinib. We highlight the challenge posed by the emergence of resistance mutants and discuss promising lead generation strategies to obtain selective inhibitors of protein and lipid kinases such as targeting of specific sites, the use of fragment-based approaches and new chemical probes based on metal complexes.