LTK mutations responsible for resistance to lorlatinib in non-small cell lung cancer harboring CLIP1-LTK fusion.

The CLIP1-LTK fusion was recently discovered as a novel oncogenic driver in non-small cell lung cancer (NSCLC). Lorlatinib, a third-generation ALK inhibitor, exhibited a dramatic clinical response in a NSCLC patient harboring CLIP1-LTK fusion. However, it is expected that acquired resistance will inevitably develop, particularly by LTK mutations, as observed in NSCLC induced by oncogenic tyrosine kinases treated with corresponding tyrosine kinase inhibitors (TKIs). In this study, we evaluate eight LTK mutations corresponding to ALK mutations that lead to on-target resistance to lorlatinib. All LTK mutations show resistance to lorlatinib with the L650F mutation being the highest. In vitro and in vivo analyses demonstrate that gilteritinib can overcome the L650F-mediated resistance to lorlatinib. In silico analysis suggests that introduction of the L650F mutation may attenuate lorlatinib-LTK binding. Our study provides preclinical evaluations of potential on-target resistance mutations to lorlatinib, and a novel strategy to overcome the resistance.

A macrocyclic kinase inhibitor overcomes triple resistant mutations in EGFR-positive lung cancer.

Brigatinib-based therapy was effective against osimertinib-resistant EGFR C797S mutants and is undergoing clinical studies. However, tumor relapse suggests additional resistance mutations might emerge. Here, we first demonstrated the binding mode of brigatinib to the EGFR-T790M/C797S mutant by crystal structure analysis and predicted brigatinib-resistant mutations through a cell-based assay including N-ethyl-N-nitrosourea (ENU) mutagenesis. We found that clinically reported L718 and G796 compound mutations appeared, consistent with their proximity to the binding site of brigatinib, and brigatinib-resistant quadruple mutants such as EGFR-activating mutation/T790M/C797S/L718M were resistant to all the clinically available EGFR-TKIs. BI-4020, a fourth-generation EGFR inhibitor with a macrocyclic structure, overcomes the quadruple and major EGFR-activating mutants but not the minor mutants, such as L747P or S768I. Molecular dynamics simulation revealed the binding mode and affinity between BI-4020 and EGFR mutants. This study identified potential therapeutic strategies using the new-generation macrocyclic EGFR inhibitor to overcome the emerging ultimate resistance mutants.

Establishment of an MR1 Presentation Reporter Screening System and Identification of Phenylpropanoid Derivatives as MR1 Ligands.

Mucosal-associated invariant T (MAIT) cells are innate-like T cells that are modulated by ligands presented on MHC class I-related proteins (MR1). These cells have attracted attention as potential drug targets because of their involvement in the initial response to infection and various disorders. Herein, we have established the MR1 presentation reporter assay system employing split-luciferase, which enables the efficient exploration of MR1 ligands. Using our screening system, we identified phenylpropanoid derivatives as MR1 ligands, including coniferyl aldehyde, which have an ability to inhibit the MR1-MAIT cell axis. Further, the structure-activity relationship study of coniferyl aldehyde analogs revealed the key structural features of ligands required for MR1 recognition. These results will contribute to identifying a broad range of endogenous and exogenous MR1 ligands and to developing novel MAIT cell modulators.

Mutual induced-fit mechanism drives binding between intrinsically disordered Bim and cryptic binding site of Bcl-xL.

The intrinsically disordered region (IDR) of Bim binds to the flexible cryptic site of Bcl-xL, a pro-survival protein involved in cancer progression that plays an important role in initiating apoptosis. However, their binding mechanism has not yet been elucidated. We have applied our dynamic docking protocol, which correctly reproduced both the IDR properties of Bim and the native bound configuration, as well as suggesting other stable/meta-stable binding configurations and revealed the binding pathway. Although the cryptic site of Bcl-xL is predominantly in a closed conformation, initial binding of Bim in an encounter configuration leads to mutual induced-fit binding, where both molecules adapt to each other; Bcl-xL transitions to an open state as Bim folds from a disordered to an α-helical conformation while the two molecules bind each other. Finally, our data provides new avenues to develop novel drugs by targeting newly discovered stable conformations of Bcl-xL.

Novel Calcium-Binding Ablating Mutations Induce Constitutive RET Activity and Drive Tumorigenesis.

Distinguishing oncogenic mutations from variants of unknown significance (VUS) is critical for precision cancer medicine. Here, computational modeling of 71,756 RET variants for positive selection together with functional assays of 110 representative variants identified a three-dimensional cluster of VUSs carried by multiple human cancers that cause amino acid substitutions in the calmodulin-like motif (CaLM) of RET. Molecular dynamics simulations indicated that CaLM mutations decrease interactions between Ca2+ and its surrounding residues and induce conformational distortion of the RET cysteine-rich domain containing the CaLM. RET-CaLM mutations caused ligand-independent constitutive activation of RET kinase by homodimerization mediated by illegitimate disulfide bond formation. RET-CaLM mutants possessed oncogenic and tumorigenic activities that could be suppressed by tyrosine kinase inhibitors targeting RET. This study identifies calcium-binding ablating mutations as a novel type of oncogenic mutation of RET and indicates that in silico-driven annotation of VUSs of druggable oncogenes is a promising strategy to identify targetable driver mutations. SIGNIFICANCE: Comprehensive proteogenomic and in silico analyses of a vast number of VUSs identify a novel set of oncogenic and druggable mutations in the well-characterized RET oncogene.

Protein-ligand binding affinity prediction of cyclin-dependent kinase-2 inhibitors by dynamically averaged fragment molecular orbital-based interaction energy.

Fragment molecular orbital (FMO) method is a powerful computational tool for structure-based drug design, in which protein-ligand interactions can be described by the inter-fragment interaction energy (IFIE) and its pair interaction energy decomposition analysis (PIEDA). Here, we introduced a dynamically averaged (DA) FMO-based approach in which molecular dynamics simulations were used to generate multiple protein-ligand complex structures for FMO calculations. To assess this approach, we examined the correlation between the experimental binding free energies and DA-IFIEs of six CDK2 inhibitors whose net charges are zero. The correlation between the experimental binding free energies and snapshot IFIEs for X-ray crystal structures was R2  = 0.75. Using the DA-IFIEs, the correlation significantly improved to 0.99. When an additional CDK2 inhibitor with net charge of -1 was added, the DA FMO-based scheme with the dispersion energies still achieved R2  = 0.99, whereas R2 decreased to 0.32 employing all the energy terms of PIEDA.

Sensitivity to dabrafenib and trametinib treatments in patients with non-small-cell cancer harboring BRAF compound mutations: A pooled analysis of BRAF p.V600E-positive advanced non-small-cell lung cancer.

PURPOSE: The present study clarified the sensitivity of the BRAF tyrosine kinase inhibitor mechanism in patients with BRAF compound mutation and predicted the sensitivity using molecular dynamics simulation. METHODS: We examined 16 BRAF tumors with p.V600E-positive non-small-cell lung cancer. RESULTS: One patient (6.2%) had a BRAF p.V600E and p.K601_W604 compound mutation with a good clinical response to dabrafenib and trametinib. Molecular dynamics simulation also complemented the effect. CONCLUSIONS: The combination of a genetic analysis and computational simulation model may help predict the sensitivity for dabrafenib in cases with a rare BRAF compound mutation. The construction of a genomic and simulation fused database is important for the development of personalized medicine in this field.

Integrated approach to functional analysis of an ERBB2 variant of unknown significance detected by a cancer gene panel test.

PURPOSE: Dealing with variants of unknown significance (VUS) is an important issue in the clinical application of NGS-based cancer gene panel tests. We detected a novel ERBB2 extracellular domain VUS, c.1157A > G p.(E401G), in a cancer gene panel test. Since the mechanisms of activation by ERBB2 extracellular domain (ECD) variants are not fully understood, we aimed to clarify those mechanisms and the biological functions of ERBB2 E401G. METHODS: ERBB2 E401G was selected as VUS for analysis because multiple software tools predicted its pathogenicity. We prepared ERBB2 expression vectors with the E401G variant as well as vectors with S310F and E321G, which are known to be activating mutations. On the basis of wild-type ERBB2 or mutant ERBB2 expression in cell lines without ERBB2 amplification or variants, we evaluated the phosphorylation of human epidermal growth factor receptor 2 and related proteins, and investigated with molecular dynamics (MD) simulation the mechanisms conferred by the variants. The biological effects of ERBB2 E401G were also investigated, both in vitro and in vivo. RESULTS: We found that ERBB2 E401G enhances C-terminal phosphorylation in a way similar to S310F. MD simulation analysis revealed that these variants maintain the stability of the EGFR-HER2 heterodimer in a ligand-independent manner. Moreover, ERBB2 E401G-transduced cells showed an increased invasive capacity in vitro and an increased tumor growth capacity in vivo. CONCLUSION: Our results provide important information on the activating mechanisms of ERBB2 extracellular domain (ECD) variants and illustrate a model workflow integrating wet and dry bench processes for the analysis of VUS detected with cancer gene panel tests.

Accurate Binding Configuration Prediction of a G-Protein-Coupled Receptor to Its Antagonist Using Multicanonical Molecular Dynamics-Based Dynamic Docking.

We have performed dynamic docking between a prototypic G-protein-coupled receptor (GPCR) system, the ß2-adrenergic receptor, and its antagonist, alprenolol, using one of the enhanced conformation sampling methods, multicanonical molecular dynamics (McMD), which does not rely on any prior knowledge for the definition of the reaction coordinate. Although we have previously applied our McMD-based dynamic docking protocol to various globular protein systems, its application to GPCR systems would be difficult because of their complicated design, which include a lipid bilayer, and because of the difficulty in sampling the configurational space of a binding site that exists deep inside the GPCR. Our simulations sampled a wide array of ligand-bound and ligand-unbound structures, and we measured 427 binding events during our 48 µs production run. Analysis of the ensemble revealed several stable and meta-stable structures, where the most stable structure at the global free energy minimum matches the experimental one. Additional canonical MD simulations were used for refinement and validation of the structures, revealing that most of the intermediates are sufficiently stable to trap the ligand in these intermediary states and furthermore validated our prediction results. Given the difficulty in reaching the orthosteric binding site, chemical optimization of the compound for the second ranking configuration, which binds near the pocket's entrance, might lead to a high-affinity allosteric inhibitor. Accordingly, we show that the application of our methodology can be used to provide crucial insights for the rational design of drugs that target GPCRs.

Structure-Based de Novo Molecular Generator Combined with Artificial Intelligence and Docking Simulations.

Recently, molecular generation models based on deep learning have attracted significant attention in drug discovery. However, most existing molecular generation models have serious limitations in the context of drug design wherein they do not sufficiently consider the effect of the three-dimensional (3D) structure of the target protein in the generation process. In this study, we developed a new deep learning-based molecular generator, SBMolGen, that integrates a recurrent neural network, a Monte Carlo tree search, and docking simulations. The results of an evaluation using four target proteins (two kinases and two G protein-coupled receptors) showed that the generated molecules had a better binding affinity score (docking score) than the known active compounds, and the generated molecules possessed a broader chemical space distribution. SBMolGen not only generates novel binding active molecules but also presents 3D docking poses with target proteins, which will be useful in subsequent drug design. The code is available at https://github.com/clinfo/SBMolGen.

Oncogenic mutations Q61L and Q61H confer active form-like structural features to the inactive state (state 1) conformation of H-Ras protein.

GTP-bound forms of Ras proteins (Ras•GTP) assume two interconverting conformations, "inactive" state 1 and "active" state 2. Our previous study on the crystal structure of the state 1 conformation of H-Ras in complex with guanosine 5'-(ß, γ-imido)triphosphate (GppNHp) indicated that state 1 is stabilized by intramolecular hydrogen-bonding interactions formed by Gln61. Since Ras are constitutively activated by substitution mutations of Gln61, here we determine crystal structures of the state 1 conformation of H-Ras•GppNHp carrying representative mutations Q61L and Q61H to observe the effect of the mutations. The results show that these mutations alter the mode of hydrogen-bonding interactions of the residue 61 with Switch II residues and induce conformational destabilization of the neighboring regions. In particular, Q61L mutation results in acquirement of state 2-like structural features. Moreover, the mutations are likely to impair an intramolecular structural communication between Switch I and Switch II. Molecular dynamics simulations starting from these structures support the above observations. These findings may give a new insight into the molecular mechanism underlying the aberrant activation of the Gln61 mutants.

Exploring ligand binding pathways on proteins using hypersound-accelerated molecular dynamics.

Capturing the dynamic processes of biomolecular systems in atomistic detail remains difficult despite recent experimental advances. Although molecular dynamics (MD) techniques enable atomic-level observations, simulations of "slow" biomolecular processes (with timescales longer than submilliseconds) are challenging because of current computer speed limitations. Therefore, we developed a method to accelerate MD simulations by high-frequency ultrasound perturbation. The binding events between the protein CDK2 and its small-molecule inhibitors were nearly undetectable in 100-ns conventional MD, but the method successfully accelerated their slow binding rates by up to 10-20 times. Hypersound-accelerated MD simulations revealed a variety of microscopic kinetic features of the inhibitors on the protein surface, such as the existence of different binding pathways to the active site. Moreover, the simulations allowed the estimation of the corresponding kinetic parameters and exploring other druggable pockets. This method can thus provide deeper insight into the microscopic interactions controlling biomolecular processes.

Microsecond-timescale MD simulation of EGFR minor mutation predicts the structural flexibility of EGFR kinase core that reflects EGFR inhibitor sensitivity.

Approximately 15-30% of patients with lung cancer harbor mutations in the EGFR gene. Major EGFR mutations (>90% of EGFR-mutated lung cancer) are highly sensitive to EGFR tyrosine kinase inhibitors (TKIs). Many uncommon EGFR mutations have been identified, but little is known regarding their characteristics, activation, and sensitivity to various EGFR-TKIs, including allosteric inhibitors. We encountered a case harboring an EGFR-L747P mutation, originally misdiagnosed with EGFR-del19 mutation using a routine diagnostic EGFR mutation test, which was resistant to EGFR-TKI gefitinib. Using this minor mutation and common EGFR-activating mutations, we performed the binding free energy calculations and microsecond-timescale molecular dynamic (MD) simulations, revealing that the L747P mutation considerably stabilizes the active conformation through a salt-bridge formation between K745 and E762. We further revealed why several EGFR inhibitors, including the allosteric inhibitor, were ineffective. Our computational structural analysis strategy would be beneficial for future drug development targeting the EGFR minor mutations.

Gilteritinib overcomes lorlatinib resistance in ALK-rearranged cancer.

ALK gene rearrangement was observed in 3%-5% of non-small cell lung cancer patients, and multiple ALK-tyrosine kinase inhibitors (TKIs) have been sequentially used. Multiple ALK-TKI resistance mutations have been identified from the patients, and several compound mutations, such as I1171N + F1174I or I1171N + L1198H are resistant to all the approved ALK-TKIs. In this study, we found that gilteritinib has an inhibitory effect on ALK-TKI-resistant single mutants and I1171N compound mutants in vitro and in vivo. Surprisingly, EML4-ALK I1171N + F1174I compound mutant-expressing tumors were not completely shrunk but regrew within a short period of time after alectinib or lorlatinib treatment. However, the relapsed tumor was markedly shrunk after switching to the gilteritinib in vivo model. In addition, gilteritinib was effective against NTRK-rearranged cancers including entrectinib-resistant NTRK1 G667C-mutant and ROS1 fusion-positive cancer.

Discovery of natural TRPA1 activators through pharmacophore-based virtual screening and a biological assay.

Transient receptor potential cation channel subfamily A member 1 (TRPA1), a member of the transient receptor potential family, detects a wide range of environmental stimuli, such as low temperature, abnormal pH, and reactive irritants. TRPA1 is of great interest as a target protein in fields related to pharmaceuticals and foods. In this study, a library of natural products was explored to identify TRPA1 activators by pharmacophore screening of known TRPA1 agonists and biological assays for agonist activity. The study identified six natural compounds as novel TRPA1 agonists. The discovery of these compounds may prove useful in elucidating the TRPA1 activation mechanism.

Novel Resistance Mechanisms Including L1196Q, P1094H, and R1248_D1249 Insertion in Three Patients With NSCLC After ALK Tyrosine Kinase Inhibitor Treatment.

OBJECTIVES: The purposes of this study are to clarify the details of the ALK tyrosine kinase inhibitor (TKI) resistance mechanism in rebiopsy cases and to predict novel resistance gene alterations using molecular dynamics simulation. METHODS: A total of 21 patients with ALK-positive NSCLC who underwent a rebiopsy after ALK TKI failure were included in this analysis. ALK fluorescence in situ hybridization and reverse transcription polymerase chain reaction were performed with paired initial and rebiopsy tumor specimens. RESULTS: Nine patients had no known ALK resistance mechanisms. Four had ALK amplification. L1196M, I1171N, and G1269A, mutations that are known to indicate resistance to ALK TKIs, were detected in one patient each. Small cell carcinoma and sarcomatoid transition were found in one case each. L1196Q, P1094H, and exon 24 76-base pair insertion were detected after the second-generation ALK TKIs. CONCLUSIONS: The combination of a genetic analysis and a computational simulation model may make a prediction of resistance mechanisms for overcoming ALK TKI resistance, and the construction of a genomic and simulation fused database is important for the development of personalized medicine in this field.

Hydrophobic interactions at subsite S1' of human dipeptidyl peptidase IV contribute significantly to the inhibitory effect of tripeptides.

Functional inhibitory peptides of human dipeptidyl peptidase 4 (hDPP4) have been highly anticipated as the active ingredient of functional food for type II diabetes; however, the molecular mechanism of hDPP4 inhibition remains unclear. In this study, we focused on dipeptides and tripeptides, which display structure-function correlations that are relatively easy to analyze, and examined their interactions with hDPP4 on an atomic level using a combination of docking studies and an hDPP4 inhibition assay. First, we performed comprehensive binding mode analysis of the dipeptide library and demonstrated that the formation of a tight interaction with the S1 subsite composing part of the substrate pocket is essential for dipeptides to compete with the substrate and strongly inhibit hDPP4. Next, we synthesized tripeptides by adding various amino acids to the C-terminus of Ile-Pro and Val-Pro, which have especially high inhibitory activity among compounds in the dipeptide library, and measured the hDPP4 inhibitory activity of the tripeptides. When hydrophobic amino acids (Ile, Met, Val, Trp) were added, the inhibitory activity increased several-fold. This phenomenon could be explained as follows: the C-terminal amino acid of the tripeptide formed hydrophobic interactions with Tyr547 and Trp629, which compose the S1' subsite located relatively outside the substrate pocket, thereby stabilizing the hDPP4-peptide binding. The structural information on the interaction between hDPP4 and peptide inhibitors attained in this study is anticipated to be useful in the development of a more potent hDPP4 competitive inhibitor.

E487K-Induced Disorder in Functionally Relevant Dynamics of Mitochondrial Aldehyde Dehydrogenase 2.

Mitochondrial aldehyde dehydrogenase 2 (ALDH2), which is a homotetramer assembled by two equivalent dimers, is an important enzyme that metabolizes ethanol-derived acetaldehyde to acetate in a coenzyme-dependent manner. The highly reactive acetaldehyde exhibits a toxic effect, indicating that the proper functioning of ALDH2 is essential to counteract aldehyde-associated diseases. It is known that the catalytic activity of ALDH2 is drastically impaired by a frequently observed mutation, E487K, in a dominant fashion. However, the molecular basis of the inactivation mechanism is elusive because of the complex nature of the dynamic behavior. Here, we performed microsecond-timescale molecular dynamics simulations of the proteins complexed with coenzymes. The E487K mutation elevated the conformational heterogeneity of the dimer interfaces, which are relatively distal from the substituted residue. Dynamic network analyses showed that Glu487 and the dimer interface were dynamically communicated, and the dynamic community further spanned throughout all of the subunits in the wild-type; however, this network was completely rearranged by the E487K mutation. The perturbation of the dynamic properties led to alterations of the global conformational motions and destabilization of the coenzyme binding required for receiving a proton from the catalytic nucleophile. The insights into the dynamic behavior of the dominant negative mutant in this work will provide clues to restore its function.

Landscape and function of multiple mutations within individual oncogenes.

Sporadic reports have described cancer cases in which multiple driver mutations (MMs) occur in the same oncogene1,2. However, the overall landscape and relevance of MMs remain elusive. Here we carried out a pan-cancer analysis of 60,954 cancer samples, and identified 14 pan-cancer and 6 cancer-type-specific oncogenes in which MMs occur more frequently than expected: 9% of samples with at least one mutation in these genes harboured MMs. In various oncogenes, MMs are preferentially present in cis and show markedly different mutational patterns compared with single mutations in terms of type (missense mutations versus in-frame indels), position and amino-acid substitution, suggesting a cis-acting effect on mutational selection. MMs show an overrepresentation of functionally weak, infrequent mutations, which confer enhanced oncogenicity in combination. Cells with MMs in the PIK3CA and NOTCH1 genes exhibit stronger dependencies on the mutated genes themselves, enhanced downstream signalling activation and/or greater sensitivity to inhibitory drugs than those with single mutations. Together oncogenic MMs are a relatively common driver event, providing the underlying mechanism for clonal selection of suboptimal mutations that are individually rare but collectively account for a substantial proportion of oncogenic mutations.

Identification of a new class of non-electrophilic TRPA1 agonists by a structure-based virtual screening approach.

Recent work has gradually been clarifying the binding site of non-electrophilic agonists on the transient receptor potential A1 (TRPA1). This study searched for non-electrophilic TRPA1 agonists by means of in silico drug discovery techniques based on three-dimensional (3-D) protein structure. First, agonist-bound pocket structures were explored using an advanced molecular dynamics simulation starting from the cryo-electron microscopic structure of TRPA1, and several pocket structures suitable for virtual screening were extracted by structure evaluation using known non-electrophilic TRPA1 agonists. Next, 49 compounds were selected as new non-electrophilic agonist candidates from a library of natural products comprising 10,555 compounds by molecular docking toward these pocket structures. Measurement of the TRPA1 agonist activity of these compounds showed notable TRPA1 activation with three compounds (decanol, 2-ethyl-1-hexanol, phenethyl butanoate). Decanol and 2-ethyl-1-hexanol, which are categorized as fatty alcohols, in particular have a novel chemical scaffold for TRPA1 activation. The results of this study are expected to be of considerable use in understanding the molecular mechanism of TRPA1 recognition by non-electrophilic agonists.