Abl1, a nonreceptor tyrosine kinase closely related to Src kinase, regulates critical cellular processes like proliferation, differentiation, cytoskeletal dynamics, and response to environmental cues through phosphorylation-driven activation. Dysregulation places it centrally in the oncogenic pathway leading to blood cancers. making it an ideal drug target for small molecule inhibitors. We sought to understand the underlying mechanism of the phosphoryl-transfer step from the ATP molecule to the substrate tyrosine, as carried out by the Abl1 enzyme. By calculating free energy profiles for the reaction using the empirical valence bond representation of the reacting fragments paired with molecular dynamics and free energy perturbation calculations, a combination of several plausible reaction pathways, ATP conformations, and the number of magnesium ion cofactors have been investigated. For the best-catalyzed pathway, which proceeds through a dissociative mechanism with a single magnesium ion situated in Site I, a close agreement was reached with the experimentally determined catalytic rates. We conclude that the catalytic mechanism in Abl1 requires one magnesium ion for efficient catalysis, unlike other kinases, where two ions are utilized. A better overall understanding of the phosphoryl-transfer reactions in Abl1 can be used for type-I inhibitor development and generally contributes to a comprehensive overview of the mechanism for ATP-driven reactions.

Transferrin receptor 1 (TfR) delivers iron across cellular membranes by shuttling the ion carrier protein transferrin. This ability to deliver large protein ligands inside cells is taken advantage of by pathogens to infiltrate human cells. Notably, the receptor's outermost ectodomain, the apical domain, is used as a point of attachment for several viruses including hemorrhagic arenaviruses. To better understand interactions with the receptor it would be advantageous to probe sequence determinants in the apical domain with viral spike proteins. Here, we carried out affinity maturation of our computationally designed apical domain from human TfR to identify underlying driving forces that lead to better binding. The improved variants were confirmed by in vitro surface plasmon resonance measurements with dissociation constants obtained in the lower nanomolar range. It was found that the strong binding affinities for the optimized variants matched the strength of interactions with the native receptor. The structure of the best variant was determined experimentally indicating that the conformational change in the hairpin binding motif at the protein-protein interface plays a crucial role. The experimental methodology can be straightforwardly applied to other arenavirus or pathogens that use the apical domain. It can further be useful to probe host-virus compatibility or therapeutic strategies based on the transferrin receptor decoys.

Diseases with readily available therapies may eventually prevail against the specific treatment by the acquisition of resistance. The constitutively active Abl1 tyrosine kinase known to cause chronic myeloid leukemia is an example, where patients may experience relapse after small inhibitor drug treatment. Mutations in the Abl1 tyrosine kinase domain (Abl1-KD) are a critical source of resistance and their emergence depends on the conformational states that have been observed experimentally: the inactive state, the active state, and the intermediate inactive state that resembles Src kinase. Understanding how resistant positions and amino acid identities are determined by selection pressure during drug treatment is necessary to improve future drug development or treatment decisions. We carry out in silico site-saturation mutagenesis over the Abl1-KD structure in a conformational context to evaluate the in situ and conformational stability energy upon mutation. Out of the 11 studied resistant positions, we determined that 7 of the resistant mutations favored the active conformation of Abl1-KD with respect to the inactive state. When, instead, the sequence optimization was modeled simultaneously at resistant positions, we recovered five known resistant mutations in the active conformation. These results suggested that the Abl1 resistance mechanism targeted substitutions that favored the active conformation. Further sequence variability, explored by ancestral reconstruction in Abl1-KD, showed that neutral genetic drift, with respect to amino acid variability, was specifically diminished in the resistant positions. Since resistant mutations are susceptible to chance with a certain probability of fixation, combining methodologies outlined here may narrow and limit the available sequence space for resistance to emerge, resulting in more robust therapeutic treatments over time.

Human transferrin receptor 1 (TfR) is necessary for the delivery of the iron carrier protein transferrin into cells and can be utilized for targeted delivery across cellular membranes. Binding of transferrin to the receptor is regulated by hereditary hemochromatosis protein (HFE), an iron regulatory protein that partly shares a binding site with transferrin on TfR. Here, we derived essential binding interactions from HFE and computationally grafted these into a library of small protein scaffolds. One of the designed proteins, TB08, was further optimized computationally and experimentally to identify variants with improved binding to TfR. The optimized variant, TB08 S3.1, expressed well in the E. coli expression system and had an affinity to TfR in the low micromolar range, K-d approximate to 1 mu m, as determined by surface plasmon resonance. A binding competition assay with transferrin further confirmed the interaction of the evolved variant to TfR at the shared binding surface. Additionally, the GFP-tagged evolved variant of TB08 demonstrated cellular internalization as determined by fluorescent and confocal microscopy in HeLa cells. The designed protein is small, allows for robust cargo tagging, and interacts specifically with TfR, thus making it a valuable tool for the characterization of TfR-mediated cellular transport mechanisms and for the assessment of engineering strategies for cargo delivery across cell membranes.

Coiled coils represent the simplest form of a complex formed between two interacting protein partners. Their extensive study has led to the development of various methods aimed towards the investigation and design of complex forming interactions. Despite the progress that has been made to predict the binding affinities for protein complexes, and specifically those tailored towards coiled coils, many challenges still remain. In this work, we explore whether the information contained in dimeric coiled coil folding energy landscapes can be used to predict binding interactions. Using the published SYNZIP dataset, we start from the amino acid sequence, to simultaneously fold and dock approximately 1000 coiled coil dimers. Assessment of the folding energy landscapes showed that a model based on the calculated number of clusters for the lowest energy structures displayed a signal that correlates with the experimentally determined protein interactions. Although the revealed correlation is weak, we show that such correlation exists; however, more work remains to establish whether further improvements can be made to the presented model.

Machupo virus, known to cause hemorrhagic fevers, enters human cells via binding with its envelope glycoprotein to transferrin receptor 1 (TfR). Similarly, the receptor interactions have been explored in biotechnological applications as a molecular system to ferry therapeutics across the cellular membranes and through the impenetrable blood-brain barrier that effectively blocks any such delivery into the brain. Study of the experimental structure of Machupo virus glycoprotein 1 (MGP1) in complex with TfR and glycoprotein sequence homology has identified some residues at the interface that influence binding. There are, however, no studies that have attempted to optimize the binding potential between MGP1 and TfR. In pursuits for finding therapeutic solutions for the New World arenaviruses, and to gain a greater understanding of MGP1 interactions with TfR, it is crucial to understand the structure-sequence relationship driving the interface formation. By displaying MGP1 on yeast surface we have examined the contributions of individual residues to the binding of solubilized ectodomain of TfR. We identified MGP1 binding hot spot residues, assessed the importance of posttranslational N-glycan modifications, and used a selection with random mutagenesis for affinity maturation. We show that the optimized MGP1 variants can bind more strongly to TfR than the native MGP1, and there is an MGP1 sequence that retains binding in the absence of glycosylation, but with the addition of further amino acid substitutions. The engineered variants can be used to probe cellular internalization or the blood-brain barrier crossing to achieve greater understanding of TfR mediated internalization.

Supply of iron into human cells is achieved by iron carrier protein transferrin and its receptor that upon complex formation get internalized by endocytosis. Similarly, the iron needs to be delivered into the brain, and necessitates the transport across the blood-brain barrier. While there are still unanswered questions about these mechanisms, extensive efforts have been made to use the system for delivery of therapeutics into biological compartments. The dimeric form of the receptor, where each subunit consists of three domains, further complicates the detailed investigation of molecular determinants responsible for guiding the receptor interactions with other proteins. Especially the apical domain's biological function has been elusive. To further the study of transferrin receptor, we have computationally decoupled the apical domain for soluble expression, and validated the design strategy by structure determination. Besides presenting a methodology for solubilizing domains, the results will allow for study of apical domain's function.

FMS-like tyrosine kinase 3 (FLT3) has been found to be mutated in 30% of acute myeloid leukaemia patients. Small-molecule inhibitors targeting FLT3 that are currently approved or still undergoing clinical trials are subject to drug resistance due to FLT3 mutations. How these mutations lead to drug resistance is hitherto poorly understood. Herein, we studied the molecular mechanism of the drug resistance mutations D835N, Y842S and M664I, which confer resistance against the most advanced inhibitors, quizartinib and PLX3397 (pexidartinib), using enzyme kinetics and computer simulations. In vitro kinase assays were performed to measure the comparative catalytic activity of the native protein and the mutants, using a bacterial expression system developed to this aim. Our results reveal that the differential drug sensitivity profiles can be rationalised by the dynamics of the protein-drug interactions and perturbation of the intraprotein contacts upon mutations. Drug binding induced a single conformation in the native protein, whereas multiple conformations were observed otherwise (in the mutants or in the absence of drugs). The end-point kinetics measurements indicated that the three resistant mutants conferred catalytic activity that is at least as high as that of the reference without such mutations. Overall, our calculations and measurements suggest that the structural dynamics of the drug-resistant mutants that affect the active state and the increased conformational freedom of the remaining inactive drug-bound population are the two major factors that contribute to drug resistance in FLT3 harbouring cancer cells. Our results explain the mechanism of drug resistance mutations and can aid to the design of more effective tyrosine kinase inhibitors.

Protein kinases are enzymes with partially overlapping specificities, many of which are important clinical targets. In this article, we give some background on protein kinases and discuss in more depth four such enzymes that have been studied in our labs using computer simulations. The combination of molecular dynamics simulations and enzyme or cell growth experiments was instrumental to explain why certain mutations lead (or do not lead) to resistance to targeted therapy aimed at these proteins. Stochastic network simulations were used to study protein-protein interactions and suggest points for intervention against tumour growth.

Background

Abl1 is a protein tyrosine kinase whose aberrant activation due to mutations is the culprit of several cancers, most notably chronic myeloid leukaemia. Several Abl1 inhibitors are used as anti-cancer drugs. Unfortunately, drug resistance limits their effectiveness. The main cause for drug resistance is mutations in the kinase domain (KD) of Abl1 that evolve in patients. The T315I mutation confers resistance against all clinically-available inhibitors except ponatinib. Resistance to ponatinib can develop by compound (double) mutations.

Methods

Kinetic measurements of the KD of Abl1 and its mutants were carried out to examine their catalytic activity. Specifically, mutants that lead to drug resistance against ponatinib were considered. Molecular dynamics simulations and multiple sequence analysis were used for explanation of the experimental findings.

Results

The catalytic efficiency of the T315I pan-resistance mutant is more than two times lower than that of the native KD. All ponatinib resistant mutations restore the catalytic efficiency of the enzyme. Two of them (G250E/T315I and Y253H/E255V) have a catalytic efficiency that is more than five times that of the native KD.

Conclusions

The measurements and analysis suggest that resistance is at least partially due to the development of a highly efficient kinase through subsequent mutations. The simulations highlight modifications in two structurally important regions of Abl1, the activation and phosphate binding loops, upon mutations.

General significance

Experimental and computational methods were used together to explain how mutations in the kinase domain of Abl1 lead to resistance against the most advanced drug currently in use to treat chronic myeloid leukaemia.