A general framework for inhibitor resistance in protein kinases

Protein kinases control virtually every aspect of normal and pathological cell physiology and are considered ideal targets for drug discovery. Most kinase inhibitors target the ATP binding site and interact with residue of a hinge loop connecting the small and large lobes of the kinase scaffold. Resistance to kinase inhibitors emerges during clinical treatment or as a result of in vitro selection approaches. Mutations conferring resistance to ATP site inhibitors often affect residues that line the ATP binding site and therefore contribute to selective inhibitor binding. Here, we show that mutations at two specific positions in the hinge loop, distinct from the previously characterized "gatekeeper," have general adverse effects on inhibitor sensitivity in six distantly related kinases, usually without consequences on kinase activity. Our results uncover a unifying mechanism of inhibitor resistance of protein kinases that might have widespread significance for drug target validation and clinical practice.     

Molecular basis of drug resistance in aurora kinases

Aurora kinases have emerged as potential targets in cancer therapy, and several drugs are currently undergoing preclinical and clinical validation. Whether clinical resistance to these drugs can arise is unclear. We exploited a hypermutagenic cancer cell line to select mutations conferring resistance to a well-studied Aurora inhibitor, ZM447439. All resistant clones contained dominant point mutations in Aurora B. Three mutations map to residues in the ATP-binding pocket that are distinct from the "gatekeeper" residue. The mutants retain wild-type catalytic activity and were resistant to all of the Aurora inhibitors tested. Our studies predict that drug-resistant Aurora B mutants are likely to arise during clinical treatment. Furthermore, because the plasticity of the ATP-binding pocket renders Aurora B insensitive to multiple inhibitors, our observations indicate that the drug-resistant Aurora B mutants should be exploited as novel drug targets.     

The open structure of a multi-drug-resistant HIV-1 protease is stabilized by crystal packing contacts

The introduction of HIV-1 protease (HIV-PR) inhibitors has led to a dramatic increase in patient survival; however, these gains are threatened by the emergence of multi-drug-resistant strains. Design of inhibitors that overcome resistance would be greatly facilitated by deeper insight into the mechanistic events associated with binding of substrates and inhibitors, as well as an understanding of the effects of resistance mutations on the structure and dynamic behavior of HIV-PR. We previously reported a series of simulations that provide a model for HIV-PR dynamics, with spontaneous conversions between the bound and unbound crystal forms upon addition or removal of an inhibitor. Importantly, the unbound protease transiently sampled a third fully open state that permits entry to the active site, unlike both crystallographic forms. Recently, a crystal structure of unbound HIV-PR was reported for the MDR 769 isolate (PDB: 1TW7); unlike all previous experimental structures, the binding pocket is open. It is suggested that drug resistance in this strain arises at least in part from the inability of inhibitors to induce closing. We carried out simulations of the MDR 769 HIV-PR mutant and observed that the reported structure is unstable in solution and rapidly adopts the semi-open conformation observed for the unbound wild-type protease in solution. Further analysis suggests that the wide-open structure observed for MDR 769 arises not from sequence variation, but instead is an artifact from crystal packing. Thus, despite being the first experimental structure to reveal flap opening sufficient for substrate access to the active site, this structure may not be directly relevant to studies of inhibitor entry or to the cause of HIV-PR drug resistance.     

Enhancing protein backbone binding--a fruitful concept for combating drug-resistant HIV

The evolution of drug resistance is one of the most fundamental problems in medicine. In HIV/AIDS, the rapid emergence of drug-resistant HIV-1 variants is a major obstacle to current treatments. HIV-1 protease inhibitors are essential components of present antiretroviral therapies. However, with these protease inhibitors, resistance occurs through viral mutations that alter inhibitor binding, resulting in a loss of efficacy. This loss of potency has raised serious questions with regard to effective long-term antiretroviral therapy for HIV/AIDS. In this context, our research has focused on designing inhibitors that form extensive hydrogen-bonding interactions with the enzyme's backbone in the active site. In doing so, we limit the protease's ability to acquire drug resistance as the geometry of the catalytic site must be conserved to maintain functionality. In this Review, we examine the underlying principles of enzyme structure that support our backbone-binding concept as an effective means to combat drug resistance and highlight their application in our recent work on antiviral HIV-1 protease inhibitors.     

Prospective CCR5 small molecule antagonist compound design using a combined mutagenesis/modeling approach

The viral resistance of marketed antiviral drugs including the emergence of new viral resistance of the only marketed CCR5 entry inhibitor, maraviroc, makes it necessary to develop new CCR5 allosteric inhibitors. A mutagenesis/modeling approach was used (a) to remove the potential hERG liability in an otherwise very promising series of compounds and (b) to design a new class of compounds with an unique mutant fingerprint profile depending on residues in the N-terminus and the extracellular loop 2. On the basis of residues, which were identified by mutagenesis as key interaction sites, binding modes of compounds were derived and utilized for compound design in a prospective manner. The compounds were then synthesized, and in vitro evaluation not only showed that they had good antiviral potency but also fulfilled the requirement of low hERG inhibition, a criterion necessary because a potential approved drug would be administered chronically. This work utilized an interdisciplinary approach including medicinal chemistry, molecular biology, and computational chemistry merging the structural requirements for potency with the requirements of an acceptable in vitro profile for allosteric CCR5 inhibitors. The obtained mutant fingerprint profiles of CCR5 inhibitors were used to translate the CCR5 allosteric binding site into a general pharmacophore, which can be used for discovering new inhibitors.     

Connectivity and binding‐site recognition: Applications relevant to drug design

Here, we describe a family of methods based on residue–residue connectivity for characterizing binding sites and apply variants of the method to various types of protein–ligand complexes including proteases, allosteric‐binding sites, correctly and incorrectly docked poses, and inhibitors of protein–protein interactions. Residues within ligand‐binding sites have about 25% more contact neighbors than surface residues in general; high‐connectivity residues are found in contact with the ligand in 84% of all complexes studied. In addition, a k‐means algorithm was developed that may be useful for identifying potential binding sites with no obvious geometric or connectivity features. The analysis was primarily carried out on 61 protein–ligand structures from the MEROPS protease database, 250 protein–ligand structures from the PDBSelect (25%), and 30 protein–protein complexes. Analysis of four proteases with crystal structures for multiple bound ligands has shown that residues with high connectivity tend to have less variable side‐chain conformation. The relevance to drug design is discussed in terms of identifying allosteric‐binding sites, distinguishing between alternative docked poses and designing protein interface inhibitors. Taken together, this data indicate that residue–residue connectivity is highly relevant to medicinal chemistry. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010     

On the relationship between catalytic residues and their protein contact number

Due to advances in structural biology, an increasing number of protein structures of unknown function have been deposited in Protein Data Bank (PDB). These proteins are usually characterized by novel structures and sequences. Conventional comparative methodology (such as sequence alignment, structure comparison, or template search) is unable to determine their function. Thus, it is important to identify protein's function directly from its structure, but this is not an easy task. One of the strategies used is to analyze whether there are distinctive structure-derived features associated with functional residues. If so, one may be able to identify the functional residues directly from a single structure. Recently, we have shown that protein weighted contact number is related to atomic thermal fluctuations and can be used to derive motional correlations in proteins. In this report, we analyze the weighted contact-number profiles of both catalytic residues and non-catalytic residues for a dataset of 760 structures. We found that catalytic residues have distinct distributions of weighted contact numbers from those of non-catalytic residues. Using this feature, we are able to effectively differentiate catalytic residues from other residues with a single optimized threshold value. Our method is simple to implement and compares favourably with other more sophisticated methods. In addition, we discuss the physics behind the relationship between catalytic residues and their contact numbers as well as other features (such as residue centrality or B-factors) associated with catalytic residues.     

Efficient a priori identification of drug resistant mutations using Dead-End Elimination and MM-PBSA

Active site mutations that disrupt drug binding are an important mechanism of drug resistance. Computational methods capable of predicting resistance a priori are poised to become extremely useful tools in the fields of drug discovery and treatment design. In this paper, we describe an approach to predicting drug resistance on the basis of Dead-End Elimination and MM-PBSA that requires no prior knowledge of resistance. Our method utilizes a two-pass search to identify mutations that impair drug binding while maintaining affinity for the native substrate. We use our method to probe resistance in four drug-target systems: isoniazid-enoyl-ACP reductase (tuberculosis), ritonavir-HIV protease (HIV), methotrexate-dihydrofolate reductase (breast cancer and leukemia), and gleevec-ABL kinase (leukemia). We validate our model using clinically known resistance mutations for all four test systems. In all cases, the model correctly predicts the majority of known resistance mutations.     

Interaction energies between tetrahydrobiopterin analogues and aromatic residues in tyrosine hydroxylase and phenylalanine hydroxylase

The phenylalanine residues 300 and 309 in the enzyme tyrosine hydroxylase are known to aid in the positioning and binding of tetrahydrobiopterin (BH4) to the enzyme active site. The residues phenylalanine 254 and tyrosine 325 similarly aid in binding BH4 in phenylalanine hydroxylase. BH4 is a cofactor necessary for enzyme function, and mutations in these residues have been shown to cause a decrease in enzyme function. We examine the pairwise interactions between each aromatic residue and BH4 using second-order Moller Plesset theory and density functional theory to determine the amount of binding due to these aromatic residues. Further, we perform in silico point mutations of these residues to determine if several likely mutations can cause a decrease in protein function. Our results show that dispersion dominates these interactions, and electrostatics alone is not enough to bind the BH4.     

Molecular Dynamics Simulations in Designing DARPins as Phosphorylation-Specific Protein Binders of ERK2

Extracellular signal-regulated kinases 1 and 2 (ERK1/2) play key roles in promoting cell survival and proliferation through the phosphorylation of various substrates. Remarkable antitumour activity is found in many inhibitors that act upstream of the ERK pathway. However, drug-resistant tumour cells invariably emerge after their use due to the reactivation of ERK1/2 signalling. ERK1/2 inhibitors have shown clinical efficacy as a therapeutic strategy for the treatment of tumours with mitogen-activated protein kinase (MAPK) upstream target mutations. These inhibitors may be used as a possible strategy to overcome acquired resistance to MAPK inhibitors. Here, we report a class of repeat proteins—designed ankyrin repeat protein (DARPin) macromolecules targeting ERK2 as inhibitors. The structural basis of ERK2–DARPin interactions based on molecular dynamics (MD) simulations was studied. The information was then used to predict stabilizing mutations employing a web-based algorithm, MAESTRO. To evaluate whether these design strategies were successfully deployed, we performed all-atom, explicit-solvent molecular dynamics (MD) simulations. Two mutations, Ala → Asp and Ser → Leu, were found to perform better than the original sequence (DARPin E40) based on the associated energy and key residues involved in protein-protein interaction. MD simulations and analysis of the data obtained on these mutations supported our predictions.     

Molecular dynamics simulation directed rational design of inhibitors targeting drug-resistant mutants of influenza A virus M2

Influenza A virus M2 (A/M2) forms a homotetrameric proton selective channel in the viral membrane. It has been the drug target of antiviral drugs such as amantadine and rimantadine. However, most of the current virulent influenza A viruses carry drug-resistant mutations alongside the drug binding site, such as S31N, V27A, and L26F, etc., each of which might be dominant in a given flu season. Among these mutations, the V27A mutation was prevalent among transmissible viruses under drug selection pressure. Until now, V27A has not been successfully targeted by small molecule inhibitors, despite years of extensive medicinal chemistry research efforts and high throughput screening. Guided by molecular dynamics (MD) simulation of drug binding and the influence of drug binding on the dynamics of A/M2 from earlier experimental studies, we designed a series of potent spirane amine inhibitors targeting not only WT, but also both A/M2-27A and L26F mutants with IC(50)s similar to that seen for amantadine's inhibition of the WT channel. The potencies of these inhibitors were further demonstrated in experimental binding and plaque reduction assays. These results demonstrate the power of MD simulations to probe the mechanism of drug binding as well as the ability to guide design of inhibitors of targets that had previously appeared to be undruggable.     

Towards Conformation-Sensitive Inhibition of Gyrase: Implications of Mechanistic Insight for the Identification and Improvement of Inhibitors

Gyrase is a bacterial type IIA topoisomerase that catalyzes negative supercoiling of DNA. The enzyme is essential in bacteria and is a validated drug target in the treatment of bacterial infections. Inhibition of gyrase activity is achieved by competitive inhibitors that interfere with ATP- or DNA-binding, or by gyrase poisons that stabilize cleavage complexes of gyrase covalently bound to the DNA, leading to double-strand breaks and cell death. Many of the current inhibitors suffer from severe side effects, while others rapidly lose their antibiotic activity due to resistance mutations, generating an unmet medical need for novel, improved gyrase inhibitors. DNA supercoiling by gyrase is associated with a series of nucleotide- and DNA-induced conformational changes, yet the full potential of interfering with these conformational changes as a strategy to identify novel, improved gyrase inhibitors has not been explored so far. This review highlights recent insights into the mechanism of DNA supercoiling by gyrase and illustrates the implications for the identification and development of conformation-sensitive and allosteric inhibitors.     

Cross-docking study on InhA inhibitors: a combination of Autodock Vina and PM6-DH2 simulations to retrieve bio-active conformations

InhA, the NADH-dependent enoyl-acyl carrier protein reductase from Mycobacterium tuberculosis (Mtb) is the proposed main target of the first-line antituberculosis drug isoniazid (INH). INH activity is dependent on activation by the catalase peroxidase KatG, a Mtb enzyme whose mutations are linked to clinical resistance to INH. Other inhibitors of InhA that do not require any preliminary activation are known. The design of such direct potent inhibitors represents a promising approach to circumvent this resistance mechanism. An ensemble-docking process with four known InhA X-ray crystal structures and employing the Autodock Vina software was performed. Five InhA inhibitors whose bioactive conformations are known were sequentially docked in the substrate cavity of each protein. The efficiency of the docking was assessed and validated by comparing the calculated conformations to the crystallographic structures. For a same inhibitor, the docking results differed from one InhA conformation to another; however, docking poses that matched correctly or were very close to the expected bioactive conformations could be identified. The expected conformations were not systematically well ranked by the Autodock Vina scoring function. A post-docking optimization was carried out on all the docked conformations with the AMMP force field implemented on the VEGAZZ software, followed by a single point calculation of the interaction energy, using the MOPAC PM6-DH2 semi-empirical quantum chemistry method. The conformations were subsequently submitted to a PM6-DH2 optimization in partially flexible cavities. The resulting interaction energies combined with the multiple receptor conformations approach allowed us to retrieve the bioactive conformation of each ligand.     

Lysine‐Targeting Covalent Inhibitors

Targeted covalent inhibitors have gained widespread attention in drug discovery as a validated method to circumvent acquired resistance in oncology. This strategy exploits small‐molecule/protein crystal structures to design tightly binding ligands with appropriately positioned electrophilic warheads. Whilst most focus has been on targeting binding‐site cysteine residues, targeting nucleophilic lysine residues can also represent a viable approach to irreversible inhibition. However, owing to the basicity of the ϵ ‐amino group in lysine, this strategy generates a number of specific challenges. Herein, we review the key principles for inhibitor design, give historical examples, and present recent developments that demonstrate the potential of lysine targeting for future drug discovery.     

QSAR‐based targeting anaplastic lymphoma kinase (ALK) variants with noncognate inhibitors in pediatric acute lymphoblastic leukemia

Human anaplastic lymphoma kinase (ALK) is a potential target for the treatment of pediatric acute lymphoblastic leukemia. However, a number of residue mutations in ALK kinase domain have been observed to cause drug resistance in pediatric acute lymphoblastic leukemia chemotherapy. Here, a chemometrics quantitative structure‐activity relationship predictor was developed using a structure‐based panel of kinase‐inhibitor activity data. The predictor was validated rigorously through internal cross‐validation and external blind test to ensure its statistical reliability, which was then used to computationally construct a systematic activity profile of 13 noncognate kinase inhibitors against both wild‐type ALK^wt and cancer‐related variants ALK^vt. It is revealed that most noncognate inhibitors exhibit weak potency on ALK^wt, but some of them are able to selectively target ALK^vt over ALK^wt. The chemometrics findings were then evaluated by using a kinase inhibition protocol; results showed that few noncognate inhibitors are 2‐ to 5‐fold higher potent against ALK variant than wild‐type kinase.     

In silico explanation for the causalities of deleterious RNF213 SNPs in Moyamoya disease and insulin resistance

Moyamoya disease (MMD), a cerebrovascular disorder caused by the RNF213 gene, is a cerebrovascular, neurological disorder leading to ischemic strokes. Our previous work suggested that RNF213 might be involved in the pro-inflammatory TNFα-mediated insulin-resistance pathway in adipocytes. Insulin resistance can lead to cerebrovascular diseases and ischemic strokes. Though p. R4810 K has been reported as the founder mutation for Asian population with this disease, there are several mutations continuously reported in clinical diagnosis. We are interested to know whether these mutations can modulate insulin resistance. Also, we are intended to understand the causalities of RNF213 and its associated mutations in MMD. For this, we have adopted a computational approach to characterize RNF213 and its naturally occurring SNPs. Clinically reported SNPs and the predicted SNPs were analyzed for their pathogenicity and effect on the biological function of the protein. To increase accuracy, this was performed through three different analysis software (PROVEAN, SIFT, and SNAP2). The mutations that were found to be deleterious in all the three platforms were further analyzed for their effect on the thermal stability of the protein through I-mutant and iStable. It was found that R4810 K and other mutations decreased the thermodynamic stability of the protein. Loss of function of RNF213 was suggested in some reports. Contrary to this, some studies reported a gain of function state due to the R4810K mutation. To understand this we have measured the ligand-binding ability of this mutated protein through COFACTOR and COACH. An increase in ligand binding is always related to the functional stability of a protein. We have observed that the R4810K mutation might increase the iron-binding efficiency of the amino acid residues. This increase in binding was further validated by analyzing the binding efficiencies by docking. Since RNF213 was previously reported as a target for Protein Tyrosine Phosphatase 1B (PTP1B), we have also analyzed whether PTP1B-binding positions are susceptible to mutations. We have re-analyzed our earlier report on the differential expression pattern of RNF213 in cancer and obese samples. We have provided a detailed analysis of the most deleterious SNPs related to RNF213. Also, we provide a prediction for the loss of function and gain of function attributes of RNF213 and its predicted causalities in MMD and insulin resistance.