Cumulative mechanism of several major imatinib-resistant mutations in Abl kinase

High-throughput prediction of protein conformational distributions with subsampled AlphaFold2

This paper presents an innovative approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins' ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against nuclear magnetic resonance experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, analysis of experimental results, and predicting evolution.

Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability

Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.

Occurrence of Existing BCR-ABL Baseline Mutations and Associated Haplotype (NmR) Among CML Patients with Diverse IM Response: A Hospital-based Study from North-East India

Highly polymorphic BCR-ABL kinase domains have been reported to harbor more than a hundred mutations, and among these, 40-60% have been identified as influencers of imatinib mesylate (IM) resistance. The emergence of IM resistance poses a significant challenge in the management of Chronic Myeloid Leukemia (CML). M351T (rs121913457), E255K (rs387906517), and Y253H (rs121913461) are of particular clinical significance due to their association with high-level imatinib resistance. This study was conducted to investigate the potential role of three significant SNPs in CML progression due to IM resistance. During the study period from 2018 to 2022 (48 months), the blood samples from 219 Reverse transcriptase-PCR-confirmed CML patients following RNA extraction and cDNA preparation were subjected to M351T, E255K, and Y253H mutation analysis by PCR-RFLP. After agarose gel visualization, the samples were subjected to Sanger sequencing to confirm the nucleotide change at the polymorphic loci. The wild-type genotype of all three ABL1 SNPs under investigation exhibits a significant reduction in frequency among IM non-responders compared to the responder group. The CGT haplotype frequency exhibits a significant difference between IM responder (4.2%) and non-responder (11.8%) (p = 0.002 < 0.05). Further, CGC haplotype was observed solely among the imatinib non-responder patients with a frequency percentage of 3.3% (p = 0.004), whereas the said genotype was absent among the responder group. A reduced overall survival rate was observed with deviation from wild-type genotype (M351T loci (T > C) with 1.217 times, E255K (G > A) with 1.485 and Y253H (T > C) with 1.399 times increase in hazard ratio) thereby enhancing mortality risk due to disease progression. The significant increase in the frequency of M351T, E255K, and Y253H loci among the IM non-responder group indicated their probable association with the development of IM resistance among CML patients. A haplotype frequency distribution pattern analysis of ABL1 loci further identified the CGC haplotype as an independent predictor for IM resistance. As such the study highlights the importance of patient characteristics, genotype distribution, and haplotype frequency distribution in predicting the response to IM treatment and clinical outcomes of CML patients.

Predicting Relative Populations of Protein Conformations without a Physics Engine Using AlphaFold 2

This paper presents a novel approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins' ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against NMR experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, NMR analysis, and evolution.

Identification by molecular dynamic simulation and in vitro validation of SISB-A1, N-[1-(4-bromophenyl)-3-methyl-1H-pyrazol-5-yl]-2-[(2-oxo-4-phenyl-2H-chromen-7-yl) oxy], as an inhibitor of the AblT315I mutant kinase to combat imatinib resistance in chronic myeloid leukemia

The discovery of imatinib, a specific inhibitor of Abl kinase, revolutionized the therapeutic approach to chronic myeloid leukemia (CML); however, its efficacy can be impeded by the emergence of novel mutations within the kinase domain, particularly AblT315I, that lead to the development of drug resistance. It therefore remains necessary to identify specific inhibitors that can effectively target imatinib-resistant CML harboring the AblT315I mutation. A natural product library sourced from the ZINC database was screened against the experimental structure of AblT315I kinase to identify compounds that selectively target the mutated kinase. The top-scoring compound was empirically tested for inhibition of AblT315I kinase using a luminescence-based kit and for impact on cellular proliferation using the BaF3-BCR-ABL-T315I stable cell line. Computational docking and molecular dynamic simulations identified the compound SISB-A1, N-[1-(4-bromophenyl)-3-methyl-1H-pyrazol-5-yl]-2-[(2-oxo-4-phenyl-2H-chromen-7-yl)oxy] acetamide, to effectively bind the catalytic domain of the mutant AblT315I kinase. Moreover, SISB-A1 exhibited greater preference than imatinib for amino acid residues of the mutant kinase's active site, including isoleucine 315. MMPBSA-based Gibbs binding free energy estimation predicted SISB-A1 to have a free energy of -51.5 versus -65.0 kcal/mol for the conventional AblT315I inhibitor ponatinib. Cell proliferation assays showed SISB-A1 to have a GI50 of 164.0 nM against the ABL-T315I stable cell line, whereas imatinib had a GI50 of 5035 nM. The IC50 value obtained for SISB-A1 against the AblT315I kinase was 197.9 nM. The results indicate SISB-A1 to have a notable ability to bind the catalytic domain of the AblT315I mutant kinase and effectively suppress its activity, thereby surpassing the associated resistance to imatinib. Continued advancement of this lead compound has the potential to yield innovative therapeutics for imatinib-resistant CML.

Acquired Secondary HER2 Mutations Enhance HER2/MAPK Signaling and Promote Resistance to HER2 Kinase Inhibition in Breast Cancer

HER2 mutations drive the growth of a subset of breast cancers and are targeted with HER2 tyrosine kinase inhibitors (TKI) such as neratinib. However, acquired resistance is common and limits the durability of clinical responses. Most HER2-mutant breast cancers progressing on neratinib-based therapy acquire secondary mutations in HER2. It is unknown whether these secondary HER2 mutations, other than the HER2T798I gatekeeper mutation, are causal to neratinib resistance. Herein, we show that secondary acquired HER2T862A and HER2L755S mutations promote resistance to HER2 TKIs via enhanced HER2 activation and impaired neratinib binding. While cells expressing each acquired HER2 mutation alone were sensitive to neratinib, expression of acquired double mutations enhanced HER2 signaling and reduced neratinib sensitivity. Computational structural modeling suggested that secondary HER2 mutations stabilize the HER2 active state and reduce neratinib binding affinity. Cells expressing double HER2 mutations exhibited resistance to most HER2 TKIs but retained sensitivity to mobocertinib and poziotinib. Double-mutant cells showed enhanced MEK/ERK signaling, which was blocked by combined inhibition of HER2 and MEK. Together, these findings reveal the driver function of secondary HER2 mutations in resistance to HER2 inhibition and provide a potential treatment strategy to overcome acquired resistance to HER2 TKIs in HER2-mutant breast cancer.

SIGNIFICANCE

HER2-mutant breast cancers acquire secondary HER2 mutations that drive resistance to HER2 tyrosine kinase inhibitors, which can be overcome by combined inhibition of HER2 and MEK.

Adaptive therapy to circumvent drug resistance to tyrosine kinase inhibitors in cancer: is it clinically relevant?

INTRODUCTION

Cancer is highly adaptable and is constantly evolving against current targeted therapies such as tyrosine kinase inhibitors. Despite advances in recent decades, the emergence of drug resistance to tyrosine kinase inhibitors constantly hampers therapeutic efficacy of cancer treatment. Continuous therapy versus intermittent clinical regimen has been a debate in drug administration of cancer patients. An ecologically-inspired shift in cancer treatment known as 'adaptive therapy' intends to improve the drug administration of drugs to cancer patients that can delay emergence of drug resistance.

AREAS COVERED

We discuss improved understanding of the concept of drug resistance, the basis of continuous therapy, intermittent clinical regimens, and adaptive therapy will be reviewed. In addition, we discuss how adaptive therapy provides guidance for future cancer treatment.

EXPERT OPINION

The current understanding of drug resistance in cancer leads to poor prognosis and limited treatment options in patients. Fighting drug resistance mutants is constantly followed by new forms of resistance. In most reported cases, continuous therapy leads to drug resistance and an intermittent clinical regimen vaguely delays it. However, adaptive therapy, conceptually, exploits multiple parameters that can suppress the growth of drug resistance and provides safe treatment for cancer patients in the future.

Biochemical and structural basis for differential inhibitor sensitivity of EGFR with distinct exon 19 mutations

Tyrosine kinase inhibitors (TKIs) are used to treat non-small cell lung cancers (NSCLC) driven by epidermal growth factor receptor (EGFR) mutations in the tyrosine kinase domain (TKD). TKI responses vary across tumors driven by the heterogeneous group of exon 19 deletions and mutations, but the molecular basis for these differences is not understood. Using purified TKDs, we compared kinetic properties of several exon 19 variants. Although unaltered for the second generation TKI afatinib, sensitivity varied significantly for both the first and third generation TKIs erlotinib and osimertinib. The most sensitive variants showed reduced ATP-binding affinity, whereas those associated with primary resistance retained wild type ATP-binding characteristics (and low K_{M, ATP}). Through crystallographic and hydrogen-deuterium exchange mass spectrometry (HDX-MS) studies, we identify possible origins for the altered ATP-binding affinity underlying TKI sensitivity and resistance, and propose a basis for classifying uncommon exon 19 variants that may have predictive clinical value.

Protein tyrosine kinase inhibitor resistance in malignant tumors: molecular mechanisms and future perspective

Protein tyrosine kinases (PTKs) are a class of proteins with tyrosine kinase activity that phosphorylate tyrosine residues of critical molecules in signaling pathways. Their basal function is essential for maintaining normal cell growth and differentiation. However, aberrant activation of PTKs caused by various factors can deviate cell function from the expected trajectory to an abnormal growth state, leading to carcinogenesis. Inhibiting the aberrant PTK function could inhibit tumor growth. Therefore, tyrosine kinase inhibitors (TKIs), target-specific inhibitors of PTKs, have been used in treating malignant tumors and play a significant role in targeted therapy of cancer. Currently, drug resistance is the main reason for limiting TKIs efficacy of cancer. The increasing studies indicated that tumor microenvironment, cell death resistance, tumor metabolism, epigenetic modification and abnormal metabolism of TKIs were deeply involved in tumor development and TKI resistance, besides the abnormal activation of PTK-related signaling pathways involved in gene mutations. Accordingly, it is of great significance to study the underlying mechanisms of TKIs resistance and find solutions to reverse TKIs resistance for improving TKIs efficacy of cancer. Herein, we reviewed the drug resistance mechanisms of TKIs and the potential approaches to overcome TKI resistance, aiming to provide a theoretical basis for improving the efficacy of TKIs.

Altiratinib blocks Toxoplasma gondii and Plasmodium falciparum development by selectively targeting a spliceosome kinase

The Apicomplexa comprise a large phylum of single-celled, obligate intracellular protozoa that include Toxoplasma gondii, Plasmodium, and Cryptosporidium spp., which infect humans and animals and cause severe parasitic diseases. Available therapeutics against these diseases are limited by suboptimal efficacy and frequent side effects, as well as the emergence and spread of resistance. We use a drug repurposing strategy and identify altiratinib, a compound originally developed to treat glioblastoma, as a promising drug candidate with broad spectrum activity against apicomplexans. Altiratinib is parasiticidal and blocks the development of intracellular zoites in the nanomolar range and with a high selectivity index when used against T. gondii. We have identified TgPRP4K of T. gondii as the primary target of altiratinib using genetic target deconvolution, which highlighted key residues within the kinase catalytic site that conferred drug resistance when mutated. We have further elucidated the molecular basis of the inhibitory mechanism and species selectivity of altiratinib for TgPRP4K and for its Plasmodium falciparum counterpart, PfCLK3. Our data identified structural features critical for binding of the other PfCLK3 inhibitor, TCMDC-135051. Consistent with the splicing control activity of this kinase family, we have shown that altiratinib can cause global disruption of splicing, primarily through intron retention in both T. gondii and P. falciparum. Thus, our data establish parasitic PRP4K/CLK3 as a potential pan-apicomplexan target whose repertoire of inhibitors can be expanded by the addition of altiratinib.

Protein Flexibility and Dissociation Pathway Differentiation Can Explain Onset of Resistance Mutations in Kinases

Understanding how mutations render a drug ineffective is a problem of immense relevance. Often the mechanism through which mutations cause drug resistance can be explained purely through thermodynamics. However, the more perplexing situation is when two proteins have the same drug binding affinities but different residence times. In this work, we demonstrate how all-atom molecular dynamics simulations using recent developments grounded in statistical mechanics can provide a detailed mechanistic rationale for such variances. We discover dissociation mechanisms for the anti-cancer drug Imatinib (Gleevec) against wild-type and the N368S mutant of Abl kinase. We show how this point mutation triggers far-reaching changes in the protein's flexibility and leads to a different, much faster, drug dissociation pathway. We believe that this work marks an efficient and scalable approach to obtain mechanistic insight into resistance mutations in biomolecular receptors that are hard to explain using a structural perspective.

Evaluation of residue variability in a conformation-specific context and during evolutionary sequence reconstruction narrows drug resistance selection in Abl1 tyrosine kinase

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.

Mapping the conformational energy landscape of Abl kinase using ClyA nanopore tweezers

Protein kinases play central roles in cellular regulation by catalyzing the phosphorylation of target proteins. Kinases have inherent structural flexibility allowing them to switch between active and inactive states. Quantitative characterization of kinase conformational dynamics is challenging. Here, we use nanopore tweezers to assess the conformational dynamics of Abl kinase domain, which is shown to interconvert between two major conformational states where one conformation comprises three sub-states. Analysis of kinase-substrate and kinase-inhibitor interactions uncovers the functional roles of relevant states and enables the elucidation of the mechanism underlying the catalytic deficiency of an inactive Abl mutant G321V. Furthermore, we obtain the energy landscape of Abl kinase by quantifying the population and transition rates of the conformational states. These results extend the view on the dynamic nature of Abl kinase and suggest nanopore tweezers can be used as an efficient tool for other members of the human kinome.

Quantitative characterization of kinase conformational dynamics remains challenging. Here, the authors show that protein nanopore tweezers allow analyzing the conformational energy landscape and ligand binding of the Abl kinase domain.

Conformational adjustment overcomes multiple drug-resistance mutants of tropomyosin receptor kinase

Mutation-induced resistance to targeted drug treatment poses a serious threat to successful chemotherapy. Multiple mutations underlying drug resistance remain a largely unsolved scientific issue. Tropomyosin receptor kinases (TRKs) are promising therapeutic targets for several malignant human cancers, but they have become less effective due to multiple resistance mutations. Thus, TRKs are representative cases to explore the problem of multiple resistance mutations. Here, we proposed a conformational adjustment strategy of drug design to overcome multiple resistance mutations in cancer treatments. A representative inhibitor, TIY-7, exhibited remarkable inhibitory activity against five TRK mutants, showing an IC₅₀ value of 1.1 nM against the most severe mutant TRKA-G595R. Moreover, it displayed superior tumor growth inhibitory activity compared with the clinically used drug selitrectinib. These results validated our strategy to design a new inhibitor structure to overcome multiple resistance mutations.

Reliable Prediction of the Protein-Ligand Binding Affinity Using a Charge Penetration Corrected AMOEBA Force Field: A Case Study of Drug Resistance Mutations in Abl Kinase

Protein mutations that directly impair drug binding are related to therapeutic resistance, and accurate prediction of their impact on drug binding would benefit drug design and clinical practice. Here, we have developed a scoring strategy that predicts the effect of the mutations on the protein-ligand binding affinity. In view of the critical importance of electrostatics in protein-ligand interactions, the charge penetration corrected AMOEBA force field (AMOEBA_CP model) was employed to improve the accuracy of the calculated electrostatic energy. We calculated the electrostatic energy using an energy decomposition analysis scheme based on the generalized Kohn-Sham (GKS-EDA). The AMOEBA_CP model was validated by a protein-fragment-ligand complex data set (Abl236) constructed from the co-crystal structures of the cancer target Abl kinase with six inhibitors. To predict ligand binding affinity changes upon protein mutation of Abl kinase, we used sampling protocol with multistep simulated annealing to search conformations of mutant proteins. The scoring strategy based on AMOEBA_CP model has achieved considerable performance in predicting resistance for 8 kinase inhibitors across 144 clinically identified point mutations. Overall, this study illustrates that the AMOEBA_CP model, which accurately treats electrostatics through penetration correction, enables the accurate prediction of the mutation-induced variation of protein-ligand binding affinity.

A novel imatinib-upregulated long noncoding RNA plays a critical role in inhibition of tumor growth induced by Abl oncogenes

BACKGROUND

Dysregulation of long noncoding RNAs (lncRNAs) has been linked to various human cancers. Bcr-Abl oncogene that results from a reciprocal translocation between human chromosome 9 and 22, is associated with several hematological malignancies. However, the role of lncRNAs in Bcr-Abl-induced leukemia remains largely unexplored.

METHODS

LncRNA cDNA microarray was employed to identify key lncRNAs involved in Bcr-Abl-mediated cellular transformation. Abl-transformed cell survival and xenografted tumor growth in mice were evaluated to dissect the role of imatinib-upregulated lncRNA 1 (IUR1) in Abl-induced tumorigenesis. Primary bone marrow transformation and in vivo leukemia transplant using lncRNA-IUR1 knockout (KO) mice were further conducted to address the functional relevance of lncRNA-IUR1 in Abl-mediated leukemia. Transcriptome RNA-seq and Western blotting were performed to determine the mechanisms by which lncRNA-IUR1 regulates Bcr-Abl-induced tumorigenesis.

RESULTS

We identified lncRNA-IUR1 as a critical negative regulator of Bcr-Abl-induced tumorigenesis. LncRNA-IUR1 expressed in a very low level in Bcr-Abl-positive cells from chronic myeloid leukemia patients. Interestingly, it was significantly induced in Abl-positive leukemic cells treated by imatinib. Depletion of lncRNA-IUR1 promoted survival of Abl-transformed human leukemic cells in experiments in vitro and xenografted tumor growth in mice, whereas ectopic expression of lncRNA-IUR1 sensitized the cells to apoptosis and suppressed tumor growth. In concert, silencing murine lncRNA-IUR1 in Abl-transformed cells accelerated cell survival and the development of leukemia in mice. Furthermore, lncRNA-IUR1 deficient mice were generated, and we observed that knockout of murine lncRNA-IUR1 facilitated Bcr-Abl-mediated primary bone marrow transformation. Moreover, animal leukemia model revealed that lncRNA-IUR1 deficiency promoted Abl-transformed cell survival and development of leukemia in mice. Mechanistically, we demonstrated that lncRNA-IUR1 suppressed Bcr-Abl-induced tumorigenesis through negatively regulating STAT5-mediated GATA3 expression.

CONCLUSIONS

These findings unveil an inhibitory role of lncRNA-IUR1 in Abl-mediated cellular transformation, and provide new insights into molecular mechanisms underlying Abl-induced leukemogenesis.

Activation of Abl1 Kinase Explored Using Well-Tempered Metadynamics Simulations on an Essential Dynamics Sampled Path

Well-tempered metadynamics (wT-metaD) simulations using path collective variables (CVs) have been successfully applied in recent years to explore conformational transitions in protein kinases and other biomolecular systems. While this methodology has the advantage of describing the transitions with a limited number of predefined path CVs, it requires as an input a reference path connecting the initial and target states of the system. It is desirable to automate the path generation using approaches that do not rely on the choice of geometric CVs to describe the transition of interest. To this end, we developed an approach that couples essential dynamics sampling with wT-metaD simulations. We used this newly developed procedure to explore the activation mechanism of Abl1 kinase and compute the associated free energy barriers. Through these simulations, we identified a three-step mechanism for the activation that involved two metastable intermediates that possessed a partially open activation loop and differed primarily in the “in” or “out” conformation of the aspartate residue of the DFG motif. One of these states is similar to a conformation that was detected in previous spectroscopic studies of Abl1 kinase, albeit its mechanistic role in the activation was hitherto not well understood. The present study establishes its intermediary role in the activation and predicts a rate-determining free energy barrier of 13.8 kcal/mol that is in good agreement with previous experimental and computational estimates. Overall, our study demonstrates the usability of essential dynamics sampling as a path CV in wT-metaD to conveniently study conformational transitions and accurately calculate the associated barriers.

Intracellular delivery of anti-BCR/ABL antibody by PLGA nanoparticles suppresses the oncogenesis of chronic myeloid leukemia cells

BACKGROUND

The pathogenesis of chronic myeloid leukemia (CML) is the formation of the BCR/ABL protein, which is encoded by the bcr/abl fusion gene, possessing abnormal tyrosine kinase activity. Despite the wide application of tyrosine kinase inhibitors (TKIs) in CML treatment, TKIs drug resistance or intolerance limits their further usage in a subset of patients. Furthermore, TKIs inhibit the tyrosine kinase activity of the BCR/ABL oncoprotein while failing to eliminate the pathologenic oncoprotein. To develop alternative strategies for CML treatment using therapeutic antibodies, and to address the issue that antibodies cannot pass through cell membranes, we have established a novel intracellular delivery of anti-BCR/ABL antibodies, which serves as a prerequisite for CML therapy.

METHODS

Anti-BCR/ABL antibodies were encapsulated in poly(D, L-lactide-co-glycolide) nanoparticles (PLGA NPs) by a double emulsion method, and transferrin was labeled on the surface of the nanoparticles (Ab@Tf-Cou6-PLGA NPs). The characteristics of nanoparticles were measured by dynamic light scattering (DLS) and transmission electron microscopy (TEM). Cellular uptake of nanoparticles was measured by flow cytometry (FCM). The effect of nanoparticles on the apoptosis and proliferation of CML cells was testified by FCM and CCK-8 assay. In addition, the anti-cancer impact of nanoparticles was evaluated in mouse models of CML.

RESULTS

The results demonstrated that the Ab@Tf-Cou6-PLGA NPs functioned as an intracellular deliverer of antibodies, and exhibited an excellent effect on degrading BCR/ABL oncoprotein in CML cells via the Trim-Away pathway. Treatment with Ab@Tf-Cou6-PLGA NPs inhibited the proliferation and induced the apoptosis of CML cells in vitro as well as impaired the oncogenesis ability of CML cells in vivo.

CONCLUSIONS

In conclusion, our study indicated that this approach achieved safe and efficient intracellular delivery of antibodies and degraded BCR/ABL oncoprotein via the Trim-Away pathway, which provides a promising therapeutic strategy for CML patients, particularly those with TKI resistance.

Making the invisible visible: Toward structural characterization of allosteric states, interaction networks, and allosteric regulatory mechanisms in protein kinases

Despite the established view of protein kinases as dynamic and versatile allosteric regulatory machines, our knowledge of allosteric functional states, allosteric interaction networks, and the intrinsic folding energy landscapes is surprisingly limited. We discuss the latest developments in structural characterization of allosteric molecular events underlying protein kinase dynamics and functions using structural, biophysical, and computational biology approaches. The recent studies highlighted progress in making the invisible aspects of protein kinase 'life' visible, including the determination of hidden allosteric states and mapping of allosteric energy landscapes, discovery of new mechanisms underlying ligand-induced modulation of allosteric activity, evolutionary adaptation of kinase allostery, and characterization of allosteric interaction networks as the intrinsic driver of kinase adaptability and signal transmission in the regulatory assemblies.

Computer Simulations of the Dissociation Mechanism of Gleevec from Abl Kinase with Milestoning

Gleevec (a.k.a., imatinib) is an important anticancer (e.g., chronic myeloid leukemia) chemotherapeutic drug due to its inhibitory interaction with the Abl kinase. Here, we use atomically detailed simulations within the Milestoning framework to study the molecular dissociation mechanism of Gleevec from Abl kinase. We compute the dissociation free energy profile, the mean first passage time for unbinding, and explore the transition state ensemble of conformations. The milestones form a multidimensional network with average connectivity of about 2.93, which is significantly higher than the connectivity for a one-dimensional reaction coordinate. The free energy barrier for Gleevec dissociation is estimated to be ∼10 kcal/mol, and the exit time is ∼55 ms. We examined the transition state conformations using both, the committor and transition function. We show that near the transition state the highly conserved salt bridge K217 and E286 is transiently broken. Together with the calculated free energy profile, these calculations can advance the understanding of the molecular interaction mechanisms between Gleevec and Abl kinase and play a role in future drug design and optimization studies.