The Effect of Mutations on Drug Sensitivity and Kinase Activity of Fibroblast Growth Factor Receptors: A Combined Experimental and Theoretical Study

Discovery and characterization of novel FGFR1 inhibitors in triple-negative breast cancer via hybrid virtual screening and molecular dynamics simulations

The overexpression of FGFR1 is thought to significantly contribute to the progression of triple-negative breast cancer (TNBC), impacting aspects such as tumorigenesis, growth, metastasis, and drug resistance. Consequently, the pursuit of effective inhibitors for FGFR1 is a key area of research interest. In response to this need, our study developed a hybrid virtual screening method. Utilizing KarmaDock, an innovative algorithm that blends deep learning with molecular docking, alongside Schrödinger's Residue Scanning. This strategy led us to identify compound 6, which demonstrated promising FGFR1 inhibitory activity, evidenced by an IC50 value of approximately 0.24 nM in the HTRF bioassay. Further evaluation revealed that this compound also inhibits the FGFR1 V561M variant with an IC50 value around 1.24 nM. Our subsequent investigations demonstrate that Compound 6 robustly suppresses the migration and invasion capacities of TNBC cell lines, through the downregulation of p-FGFR1 and modulation of EMT markers, highlighting its promise as a potent anti-metastatic therapeutic agent. Additionally, our use of molecular dynamics simulations provided a deeper understanding of the compound's specific binding interactions with FGFR1.

Molecular dynamics simulations reveal phosphorylation-induced conformational dynamics of the fibroblast growth factor receptor 1 kinase

The Fibroblast Growth Factor Receptor1 (FGFR1) kinase wields exquisite control on cell fate, proliferation, differentiation, and homeostasis. An imbalance of FGFR1 signaling leads to several pathogeneses of diseases ranging from multiple cancers to allergic and neurodegenerative disorders. In this study, we investigated the phosphorylation-induced conformational dynamics of FGFR1 in apo and ATP-bound states via all-atom molecular dynamics simulations. All simulations were performed for 2 × 2 µs. We have also investigated the energetics of the binding of ATP to FGFR1 using the molecular mechanics Poisson-Boltzmann scheme. Our study reveals that the FGFR1 kinase can reach a fully active configuration through phosphorylation and ATP binding. A 3-10 helix formation in the activation loop signifies its rearrangement leading to stability upon ATP binding. The interaction of phosphorylated tyrosine (pTyr654) with positively charged residues forms strong salt-bridge interactions, driving the compactness of the structure. The dynamic cross-correlation map reveals phosphorylation enhances correlated motions and reduces anti-correlated motions between different domains. We believe that the mechanistic understanding of large-conformational changes upon the activation of the FGFR1 kinase will aid the development of novel targeted therapeutics.Communicated by Ramaswamy H. Sarma.

Receptor-based pharmacophore modeling, molecular docking, synthesis and biological evaluation of novel VEGFR-2, FGFR-1, and BRAF multi-kinase inhibitors

A receptor-based pharmacophore model describing the binding features required for the multi-kinase inhibition of the target kinases (VEGFR-2, FGFR-1, and BRAF) were constructed and validated. It showed a good overall quality in discriminating between the active and the inactive in a compiled test set compounds with F1 score of 0.502 and Mathew's correlation coefficient of 0.513. It described the ligand binding to the hinge region Cys or Ala, the glutamate residue of the Glu-Lys αC helix conserved pair, the DFG motif Asp at the activation loop, and the allosteric back pocket next to the ATP binding site. Moreover, excluded volumes were used to define the steric extent of the binding sites. The application of the developed pharmacophore model in virtual screening of an in-house scaffold dataset resulted in the identification of a benzimidazole-based scaffold as a promising hit within the dataset. Compounds 8a-u were designed through structural optimization of the hit benzimidazole-based scaffold through (un)substituted aryl substitution on 2 and 5 positions of the benzimidazole ring. Molecular docking simulations and ADME properties predictions confirmed the promising characteristics of the designed compounds in terms of binding affinity and pharmacokinetic properties, respectively. The designed compounds 8a-u were synthesized, and they demonstrated moderate to potent VEGFR-2 inhibitory activity at 10 µM. Compound 8u exhibited a potent inhibitory activity against the target kinases (VEGFR-2, FGFR-1, and BRAF) with IC50 values of 0.93, 3.74, 0.25 µM, respectively. The benzimidazole derivatives 8a-u were all selected by the NCI (USA) to conduct their anti-proliferation screening. Compounds 8a and 8d resulted in a potent mean growth inhibition % (GI%) of 97.73% and 92.51%, respectively. Whereas compounds 8h, 8j, 8k, 8o, 8q, 8r, and 8u showed a mean GI% > 100% (lethal effect). The most potent compounds on the NCI panel of 60 different cancer cell lines were progressed further to NCI five-dose testing. The benzimidazole derivatives 8a, 8d, 8h, 8j, 8k, 8o, 8q, 8r and 8u exhibited potent anticancer activity on the tested cell lines reaching sub-micromolar range. Moreover, 8u was found to induce cell cycle arrest of MCF-7 cell line at the G2/M phase and accumulating cells at the sub-G1 phase as a result of cell apoptosis.

Introduction to Computational Biomedicine

The domain of computational biomedicine is a new and burgeoning one. Its areas of concern cover all scales of human biology, physiology, and pathology, commonly referred to as medicine, from the genomic to the whole human and beyond, including epidemiology and population health. Computational biomedicine aims to provide high-fidelity descriptions and predictions of the behavior of biomedical systems of both fundamental scientific and clinical importance. Digital twins and virtual humans aim to reproduce the extremely accurate duplicate of real-world human beings in cyberspace, which can be used to make highly accurate predictions that take complicated conditions into account. When that can be done reliably enough for the predictions to be actionable, such an approach will make an impact in the pharmaceutical industry by reducing or even replacing the extremely laboratory-intensive preclinical process of making and testing compounds in laboratories, and in clinical applications by assisting clinicians to make diagnostic and treatment decisions.

PoSSuM v.3: A Major Expansion of the PoSSuM Database for Finding Similar Binding Sites of Proteins

Information on structures of protein-ligand complexes, including comparisons of known and putative protein-ligand-binding pockets, is valuable for protein annotation and drug discovery and development. To facilitate biomedical and pharmaceutical research, we developed PoSSuM (https://possum.cbrc.pj.aist.go.jp/PoSSuM/), a database for identifying similar binding pockets in proteins. The current PoSSuM database includes 191 million similar pairs among almost 10 million identified pockets. PoSSuM drug search (PoSSuMds) is a resource for investigating ligand and receptor diversity among a set of pockets that can bind to an approved drug compound. The enhanced PoSSuMds covers pockets associated with both approved drugs and drug candidates in clinical trials from the latest release of ChEMBL. Additionally, we developed two new databases: PoSSuMAg for investigating antibody-antigen interactions and PoSSuMAF to simplify exploring putative pockets in AlphaFold human protein models.

Optimization of a Protein-Targeted Medicine into an RNA-Specific Small Molecule

Protein-targeted small molecule medicines often bind RNAs and affect RNA-mediated pathways in cells. Historically, small molecule engagement and modulation of RNA have not been considered in medicine development; however, RNA should be considered both a potential on- and off-target. Kinase inhibitors have emecrged as common RNA binders with dovitinib, a classic receptor tyrosine kinase (RTK) inhibitor, inhibiting RTKs and the biogenesis of oncogenic microRNA-21 through direct engagement. In this study, we use knowledge of the molecular recognition of both protein and RNA targets by dovitinib to design molecules that specifically inhibit the RNA target but lack activity against canonical protein targets in cells. As it is now becoming apparent that RNA can be both an on- and off-target for small molecule medicines, this study lays a foundation to use design principles to maximize desired compound activity while minimizing off-target effects.

Elucidating the potential effects of point mutations on FGFR3 inhibitor resistance via combined molecular dynamics simulation and community network analysis

FGFR3 kinase mutations are associated with a variety of malignancies, but FGFR3 mutant inhibitors have rarely been studied. Furthermore, the mechanism of pan-FGFR inhibitors resistance caused by kinase domain mutations is still unclear. In this study, we try to explain the mechanism of drug resistance to FGFR3 mutation through global analysis and local analysis based on molecular dynamics simulation, binding free energy analysis, umbrella sampling and community network analysis. The results showed that FGFR3 mutations caused a decrease in the affinity between drugs and FGFR3 kinase, which was consistent with the reported experimental results. Possible mechanisms are that mutations affect drug-protein affinity by altering the environment of residues near the hinge region where the protein binds to the drug, or by affecting the A-loop and interfering with the allosteric communication networks. In conclusion, we systematically elucidated the underlying mechanism of pan-FGFR inhibitor resistance caused by FGFR3 mutation based on molecular dynamics simulation strategy, which provided theoretical guidance for the development of FGFR3 mutant kinase inhibitors.

The FGF/FGFR signalling mediated anti-cancer drug resistance and therapeutic intervention

ABSTRACT Fibroblast Growth Factor (FGF) ligands and their receptors are crucial factors driving chemoresistance in several malignancies, challenging the efficacy of currently available anti-cancer drugs. The Fibroblast growth factor/receptor (FGF/FGFR) signalling malfunctions in tumor cells, resulting in a range of molecular pathways that may impact its drug effectiveness. Deregulation of cell signalling is critical since it can enhance tumor growth and metastasis. Overexpression and mutation of FGF/FGFR induce regulatory changes in the signalling pathways. Chromosomal translocation facilitating FGFR fusion production aggravates drug resistance. Apoptosis is inhibited by FGFR-activated signalling pathways, reducing multiple anti-cancer medications' destructive impacts. Angiogenesis and epithelial-mesenchymal transition (EMT) are facilitated by FGFRs-dependent signalling, which correlates with drug resistance and enhances metastasis. Further, lysosome-mediated drug sequestration is another prominent method of resistance. Inhibition of FGF/FGFR by following a plethora of therapeutic approaches such as covalent and multitarget inhibitors, ligand traps, monoclonal antibodies, recombinant FGFs, combination therapy, and targeting lysosomes and micro RNAs would be helpful. As a result, FGF/FGFR suppression treatment options are evolving nowadays. To increase positive impacts, the processes underpinning the FGF/FGFR axis' role in developing drug resistance need to be clarified, emphasizing the need for more studies to develop novel therapeutic options to address this significant problem. Communicated by Ramaswamy H. Sarma.

Role of FGFR3 in bladder cancer: Treatment landscape and future challenges

Bladder cancer is a heterogeneous malignancy and is responsible for approximately 3.2% of new diagnoses of cancer per year (Sung et al., 2021). Fibroblast Growth Factor Receptors (FGFRs) have recently emerged as a novel therapeutic target in cancer. In particular, FGFR3 genomic alterations are potent oncogenic drivers in bladder cancer and represent predictive biomarkers of response to FGFR inhibitors. Indeed, overall ∼50% of bladder cancers have somatic mutations in the FGFR3 -coding sequence (Cappellen et al., 1999; Turner and Grose, 2010). FGFR3 gene rearrangements are typical alterations in bladder cancer (Nelson et al., 2016; Parker et al., 2014). In this review, we summarize the most relevant evidence on the role of FGFR3 and the state-of-art of anti-FGFR3 treatment in bladder cancer. Furthermore, we interrogated the AACR Project GENIE to investigate clinical and molecular features of FGFR3-altered bladder cancers. We found that FGFR3 rearrangements and missense mutations were associated with a lower fraction of mutated genome, compared to the FGFR3 wild-type tumors, as also observed in other oncogene-addicted cancers. Moreover, we observed that FGFR3 genomic alterations are mutually exclusive with other genomic aberrations of canonical bladder cancer oncogenes, such as TP53 and RB1. Finally, we provide an overview of the treatment landscape of FGFR3-altered bladder cancer, discussing future perspectives for the management of this disease.

Signaling Pathway and Small-Molecule Drug Discovery of FGFR: A Comprehensive Review

Targeted therapy is a groundbreaking innovation for cancer treatment. Among the receptor tyrosine kinases, the fibroblast growth factor receptors (FGFRs) garnered substantial attention as promising therapeutic targets due to their fundamental biological functions and frequently observed abnormality in tumors. In the past 2 decades, several generations of FGFR kinase inhibitors have been developed. This review starts by introducing the biological basis of FGF/FGFR signaling. It then gives a detailed description of different types of small-molecule FGFR inhibitors according to modes of action, followed by a systematic overview of small-molecule-based therapies of different modalities. It ends with our perspectives for the development of novel FGFR inhibitors.

Development of a degrader against oncogenic fusion protein FGFR3-TACC3

Fibroblast growth factor receptor 3-transforming acidic coiled-coil containing protein 3 (FGFR3-TACC3), which has been identified in many cancers such as glioblastoma and bladder cancer, is a potent oncogenic fusion protein that induces constitutive activation of FGFR signaling, resulting in uncontrolled cell proliferation. Although several tyrosine kinase inhibitors against FGFR are currently under development, resistance to such types of inhibitors in patients has become a concern. In this study, a chimeric molecule SNIPER(TACC3)-11 (5a) was developed and found to reduce FGFR3-TACC3 levels effectively. Compound 5a conjugated KHS108 (a TACC3 ligand) to an LCL161 derivative (11) (an inhibitor of apoptosis protein [IAP] ligand) with a PEG linker (n = 2). Mechanistical analysis showed that cellular IAP1 was required for the reduction of FGFR3-TACC3 levels. Consistent with the decrease in FGFR3-TACC3 levels, compound 5a suppressed the growth of FGFR3-TACC3 positive cells. Thus, compound 5a is a candidate therapeutic with a novel drug modality against cancers that exhibit FGFR3-TACC3-dependent proliferation and exerts pharmacological effects distinct from FGFR3 kinase inhibitors because it lacks substructures crucial for kinase inhibition.

Unmet needs in the treatment of intrahepatic cholangiocarcinoma harboring FGFR2 gene rearrangements

Intrahepatic cholangiocarcinoma, a malignancy of the intrahepatic bile ducts, is the second most common primary liver malignancy and has been rising in incidence over the past several decades. Given its poor prognosis and diagnosis at a late stage, novel therapies are urgently needed to improve outcomes. Intrahepatic cholangiocarcinoma harbors a high rate of targetable mutations, spurring an increased interest in drug development in this disease. FGFR2 gene rearrangements occur in approximately 10-16% of these tumors and this underscores the importance of next generation sequencing in this population. There are now several FGFR inhibitors in development, and these agents may help improve outcomes for these patients. However, both primary and secondary resistance remain a challenge.

Biological Significance and Targeting of the FGFR Axis in Cancer

Simple Summary

All cells within tissues and organ systems must communicate with each other to ensure they function in a coordinated manner. One form of communication is signalling mediated by small proteins (for example fibroblast growth factors; FGFs) that are secreted by one cell and bind to specialised receptors (for example FGF receptors) on nearby cells. These receptors propagate the signal to the nucleus of the receiving cell, which in turn dictates to the cell how it should react. FGFR signalling is versatile, tightly controlled and important for normal body homeostasis, facilitating growth, healing and replacing old cells. However, cancer cells can take command of this pathway and use it to their advantage. This review will first explain the biology of FGFR signalling and then describe how it can be corrupted, the implications in cancer, and how it can be targeted to improve cancer therapy.

Abstract

The pleiotropic effects of fibroblast growth factors (FGFs), the widespread expression of all seven signalling FGF receptors (FGFRs) throughout the body, and the dramatic phenotypes shown by many FGF/R knockout mice, highlight the diversity, complexity and functional importance of FGFR signalling. The FGF/R axis is critical during normal tissue development, homeostasis and repair. Therefore, it is not surprising that substantial evidence also pinpoints the involvement of aberrant FGFR signalling in disease, including tumourigenesis. FGFR aberrations in cancer include mutations, gene fusions, and amplifications as well as corrupted autocrine/paracrine loops. Indeed, many clinical trials on cancer are focusing on targeting the FGF/FGFR axis, using selective FGFR inhibitors, nonselective FGFR tyrosine kinase inhibitors, ligand traps, and monoclonal antibodies and some have already been approved for the treatment of cancer patients. The heterogeneous tumour microenvironment and complexity of FGFR signalling may be some of the factors responsible for the resistance or poor response to therapy with FGFR axis-directed therapeutic agents. In the present review we will focus on the structure and function of FGF(R)s, their common irregularities in cancer and the therapeutic value of targeting their function in cancer.

The effect of protein mutations on drug binding suggests ensuing personalised drug selection

The advent of personalised medicine promises a deeper understanding of mechanisms and therefore therapies. However, the connection between genomic sequences and clinical treatments is often unclear. We studied 50 breast cancer patients belonging to a population-cohort in the state of Qatar. From Sanger sequencing, we identified several new deleterious mutations in the estrogen receptor 1 gene (ESR1). The effect of these mutations on drug treatment in the protein target encoded by ESR1, namely the estrogen receptor, was achieved via rapid and accurate protein-ligand binding affinity interaction studies which were performed for the selected drugs and the natural ligand estrogen. Four nonsynonymous mutations in the ligand-binding domain were subjected to molecular dynamics simulation using absolute and relative binding free energy methods, leading to the ranking of the efficacy of six selected drugs for patients with the mutations. Our study shows that a personalised clinical decision system can be created by integrating an individual patient's genomic data at the molecular level within a computational pipeline which ranks the efficacy of binding of particular drugs to variant proteins.

Artificial intelligence in drug design: algorithms, applications, challenges and ethics

The discovery paradigm of drugs is rapidly growing due to advances in machine learning (ML) and artificial intelligence (AI). This review covers myriad faces of AI and ML in drug design. There is a plethora of AI algorithms, the most common of which are summarized in this review. In addition, AI is fraught with challenges that are highlighted along with plausible solutions to them. Examples are provided to illustrate the use of AI and ML in drug discovery and in predicting drug properties such as binding affinities and interactions, solubility, toxicology, blood–brain barrier permeability and chemical properties. The review also includes examples depicting the implementation of AI and ML in tackling intractable diseases such as COVID-19, cancer and Alzheimer’s disease. Ethical considerations and future perspectives of AI are also covered in this review.

FGFR-TKI resistance in cancer: current status and perspectives

Fibroblast growth factor receptors (FGFRs) play key roles in promoting the proliferation, differentiation, and migration of cancer cell. Inactivation of FGFRs by tyrosine kinase inhibitors (TKI) has achieved great success in tumor-targeted therapy. However, resistance to FGFR-TKI has become a concern. Here, we review the mechanisms of FGFR-TKI resistance in cancer, including gatekeeper mutations, alternative signaling pathway activation, lysosome-mediated TKI sequestration, and gene fusion. In addition, we summarize strategies to overcome resistance, including developing covalent inhibitors, developing dual-target inhibitors, adopting combination therapy, and targeting lysosomes, which will facilitate the transition to precision medicine and individualized treatment.

How Far Are We from the Rapid Prediction of Drug Resistance Arising Due to Kinase Mutations?

In all living organisms, protein kinases regulate various cell signaling events through phosphorylation. The phosphorylation occurs upon transferring an ATP's terminal phosphate to a target residue. Because of the central role of protein kinases in several proliferative pathways, point mutations occurring within the kinase's ATP-binding site can lead to a constitutively active enzyme, and ultimately, to cancer. A select set of these point mutations can also make the enzyme drug resistant toward the available kinase inhibitors. Because of technical and economical limitations, rapid experimental exploration of the impact of these mutations remains to be a challenge. This underscores the importance of kinase-ligand binding affinity prediction tools that are poised to measure the efficacy of inhibitors in the presence of kinase mutations. To this end, here, we compare the performances of six web-based scoring tools (DSX-ONLINE, KDEEP, HADDOCK2.2, PDBePISA, Pose&Rank, and PRODIGY-LIG) in assessing the impact of kinase mutations on their interactions with their inhibitors. This assessment is carried out on a new structure-based BINDKIN benchmark we compiled. BINDKIN contains wild-type and mutant structure pairs of kinase-inhibitor complexes, together with their corresponding experimental binding affinities (in the form of IC₅₀, K _d, and K _i). The performance of various web servers over BINDKIN shows that they cannot predict the binding affinities (ΔGs) of wild-type and mutant cases directly. Still, they could catch whether a mutation improves or worsens the ligand binding (ΔΔGs) where the highest Pearson's R correlation coefficient is reached by DSX-ONLINE over the K _i dataset. When homology models are used instead of K _i-associated crystal structures, DSX-ONLINE loses its predictive capacity. These results highlight that there is room to improve the available scoring functions to estimate the impact of protein kinase point mutations on inhibitor binding. The BINDKIN benchmark with all related results is freely accessible online (https://github.com/CSB-KaracaLab/BINDKIN).

Plexiform Myofibroblastoma: Clinicopathologic Analysis of 36 Cases of a Distinctive Benign Tumor of Soft Tissue Affecting Mainly Children and Young Adults

The spectrum of benign superficial fibroblastic/myofibroblastic tumors continues to expand and includes entities such as plexiform fibrohistiocytic tumor, dermatomyofibroma and fibroblastic connective tissue nevus. Here, we describe a seemingly distinctive group of lesions which we have labeled "plexiform myofibroblastoma" (PM). PM is a rare superficial mesenchymal tumor of fibroblastic/myofibroblastic lineage that predominantly occurs in children and young adults. Thirty-six cases from the consultation archives of one of the authors have been studied to characterize the clinicopathologic characteristics of PM. 19 patients (53%) were female and 17 were male, with age at presentation ranging from congenital (2 cases) to 50 years of age (median: 9.5 y). Three patients had multiple lesions. Males tended to develop tumors during childhood (median: 2 y; range: congenital-37 y), while in females the age distribution was relatively uniform from childhood through adulthood (median age: 25 y; range: 4 mo to 50 y). Most tumors occurred in truncal locations (25/40), including the back (11), anterolateral chest wall (4), axilla (4), abdominal wall (4), perineum (1) and suprapubic region (1). Other tumor sites were the neck (10/40), occiput (2), lower extremity (2) and breast (1). The average greatest dimension was 2.7±1.7 cm (range: 0.6 to 8 cm). Three male patients, 2 of whom were brothers, presented between 6 months and 1 year of age with multiple lesions variably involving the back, occiput and axillae; these lesions spontaneously regressed after being present for about 2 years, with no evidence of recurrence at a mean follow-up of 11.4±3.2 years. Histologically, PM was composed of plexiform fascicles of fibroblastic/myofibroblastic spindle cells that ramify through the subcutis and reticular dermis. The bland neoplastic cells had indistinct cell borders, palely eosinophilic cytoplasm and ovoid or tapered nuclei. There was no histiocytoid component in any case, and no cases contained osteoclast-like giant cells. Twelve of thirty-four (35%) reviewed cases showed at least focal keloidal hyalinization, 6/34 (18%) contained somewhat fasciitis-like areas and 6/34 (18%) contained focal myxoid stroma. Immunohistochemical studies were positive for SMA (27/32 cases), desmin (9/21) and CD34 (13/24) and negative for β-catenin (0/14) and S-100 (0/22). EMA was weakly positive in 2/15 cases. An FGFR2 M535L tyrosine kinase domain variant of unknown significance was detected in 1/7 sequenced cases, and no somatic alterations, copy number alterations or gene fusions were detected in the other 6. Clinical follow-up data were available for 16/36 patients (44%; median duration: 5.5 y). Although most excisions had positive margins (11/16), only 1 patient developed a local recurrence 4 years after initial excision. No tumors metastasized. PM is a benign tumor with characteristic histology, epidemiology and anatomic site distribution. Because PM rarely recurs, a watchful waiting approach would be reasonable for lesions excised with positive margins.

Rapid, accurate, precise and reproducible ligand-protein binding free energy prediction

A central quantity of interest in molecular biology and medicine is the free energy of binding of a molecule to a target biomacromolecule. Until recently, the accurate prediction of binding affinity had been widely regarded as out of reach of theoretical methods owing to the lack of reproducibility of the available methods, not to mention their complexity, computational cost and time-consuming procedures. The lack of reproducibility stems primarily from the chaotic nature of classical molecular dynamics (MD) and the associated extreme sensitivity of trajectories to their initial conditions. Here, we review computational approaches for both relative and absolute binding free energy calculations, and illustrate their application to a diverse set of ligands bound to a range of proteins with immediate relevance in a number of medical domains. We focus on ensemble-based methods which are essential in order to compute statistically robust results, including two we have recently developed, namely thermodynamic integration with enhanced sampling and enhanced sampling of MD with an approximation of continuum solvent. Together, these form a set of rapid, accurate, precise and reproducible free energy methods. They can be used in real-world problems such as hit-to-lead and lead optimization stages in drug discovery, and in personalized medicine. These applications show that individual binding affinities equipped with uncertainty quantification may be computed in a few hours on a massive scale given access to suitable high-end computing resources and workflow automation. A high level of accuracy can be achieved using these approaches.

Targeting the Src Pathway Enhances the Efficacy of Selective FGFR Inhibitors in Urothelial Cancers with FGFR3 Alterations

Selective FGFR inhibitors such as infigratinib (BGJ398) and erdafitinib (JNJ-42756493) have been evaluated in clinical trials for cancers with FGFR3 molecular alterations, particularly in urothelial carcinoma patients. However, a substantial proportion of these patients (up to 50%) display intrinsic resistance to these drugs and receive minimal clinical benefit. There is thus an unmet need for alternative therapeutic strategies to overcome primary resistance to selective FGFR inhibitors. In this study, we demonstrate that cells expressing cancer-associated activating FGFR3 mutants and the FGFR3-TACC3 fusion showed primary resistance to infigratinib in long-term colony formation assays in both NIH-3T3 and urothelial carcinoma models. We find that expression of these FGFR3 molecular alterations resulted in elevated constitutive Src activation compared to wildtype FGFR3 and that cells co-opted this pathway as a means to achieve intrinsic resistance to infigratinib. Targeting the Src pathway with low doses of the kinase inhibitor dasatinib synergistically sensitized multiple urothelial carcinoma lines harbouring endogenous FGFR3 alterations to infigratinib. Our data provide preclinical rationale that supports the use of dasatinib in combination with selective FGFR inhibitors as a means to overcome intrinsic drug resistance in the salvage therapy setting in urothelial cancer patients with FGFR3 molecular alterations.

Accuracy and Precision of Alchemical Relative Free Energy Predictions with and without Replica-Exchange

A systematic and statistically robust protocol is applied for the evaluation of free energy calculations with and without replica-exchange. The protocol is based on ensemble averaging to generate accurate assessments of the uncertainties in the predictions. Comparison is made between FEP+ and TIES-free energy perturbation and thermodynamic integration with enhanced sampling-the latter with and without the so-called "enhanced sampling" based on replica-exchange protocols. Standard TIES performs best for a reference set of targets and compounds; no benefits accrue from replica-exchange methods. Evaluation of FEP+ and TIES with REST-replica-exchange with solute tempering-reveals a systematic and significant underestimation of free energy differences in FEP+, which becomes increasingly large for long duration simulations, is confirmed by extensive analysis of previous publications, and raises a number of questions pertaining to the accuracy of the predictions with the REST technique not hitherto discussed.

A Novel FGFR3 Splice Variant Preferentially Expressed in African American Prostate Cancer Drives Aggressive Phenotypes and Docetaxel Resistance

Alternative splicing (AS) has been shown to participate in prostate cancer development and progression; however, a link between AS and prostate cancer health disparities has been largely unexplored. Here we report on the cloning of a novel splice variant of FGFR3 that is preferentially expressed in African American (AA) prostate cancer. This novel variant (FGFR3-S) omits exon 14, comprising 123 nucleotides that encode the activation loop in the intracellular split kinase domain. Ectopic overexpression of FGFR3-S in European American (EA) prostate cancer cell lines (PC-3 and LNCaP) led to enhanced receptor autophosphorylation and increased activation of the downstream signaling effectors AKT, STAT3, and ribosomal S6 compared with FGFR3-L (retains exon 14). The increased oncogenic signaling imparted by FGFR3-S was associated with a substantial gain in proliferative and antiapoptotic activities, as well as a modest but significant gain in cell motility. Moreover, the FGFR3-S-conferred proliferative and motility gains were highly resistant to the pan-FGFR small-molecule inhibitor dovitinib and the antiapoptotic gain was insensitive to the cytotoxic drug docetaxel, which stands in marked contrast with dovitinib- and docetaxel-sensitive FGFR3-L. In an in vivo xenograft model, mice injected with PC-3 cells overexpressing FGFR3-S exhibited significantly increased tumor growth and resistance to dovitinib treatment compared with cells overexpressing FGFR3-L. In agreement with our in vitro and in vivo findings, a high FGFR3-S/FGFR3-L expression ratio in prostate cancer specimens was associated with poor patient prognosis. IMPLICATIONS: This work identifies a novel FGFR3 splice variant and supports the hypothesis that differential AS participates in prostate cancer health disparities.

Multicenter Phase I Study of Erdafitinib (JNJ-42756493), Oral Pan-Fibroblast Growth Factor Receptor Inhibitor, in Patients with Advanced or Refractory Solid Tumors

PURPOSE

Here, we report results of the first phase I study of erdafitinib, a potent, oral pan-FGFR inhibitor.

PATIENTS AND METHODS

Patients age ≥18 years with advanced solid tumors for which standard antineoplastic therapy was no longer effective were enrolled (NCT01703481). Parts 2 to 4 employed molecular screening for activating FGFR genomic alterations. In patients with such alterations, two selected doses/schedules identified during part 1 dose-escalation [9 mg once daily and 10 mg intermittently (7 days on/7 days off), as previously published (Tabernero JCO 2015;33:3401-8)] were tested.

RESULTS

The study included 187 patients. The most common treatment-related adverse events were hyperphosphatemia (64%), dry mouth (42%), and asthenia (28%), generally grade 1/2 severity. All cases of hyperphosphatemia were grade 1/2 except for 1 grade 3 event. Skin, nail, and eye changes were observed in 43%, 33%, and 28% of patients, respectively (mostly grade 1/2 and reversible after temporary dosing interruption). Urothelial carcinoma and cholangiocarcinoma were most responsive to erdafitinib, with objective response rates (ORR) of 46.2% (12/26) and 27.3% (3/11), respectively, in response-evaluable patients with FGFR mutations or fusions. All patients with urothelial carcinoma and cholangiocarcinoma who responded to erdafitinib carried FGFR mutations or fusions. Median response duration was 5.6 months for urothelial carcinoma and 11.4 months for cholangiocarcinoma. ORRs in other tumor types were <10%.

CONCLUSIONS

Erdafitinib shows tolerability and preliminary clinical activity in advanced solid tumors with genomic changes in the FGFR pathway, at two different dosing schedules and with particularly encouraging responses in urothelial carcinoma and cholangiocarcinoma.

Structure and Dynamics of the EGF Receptor as Revealed by Experiments and Simulations and Its Relevance to Non-Small Cell Lung Cancer

The epidermal growth factor receptor (EGFR) is historically the prototypical receptor tyrosine kinase, being the first cloned and the first where the importance of ligand-induced dimer activation was ascertained. However, many years of structure determination has shown that EGFR is not completely understood. One challenge is that the many structure fragments stored at the PDB only provide a partial view because full-length proteins are flexible entities and dynamics play a key role in their functionality. Another challenge is the shortage of high-resolution data on functionally important higher-order complexes. Still, the interest in the structure/function relationships of EGFR remains unabated because of the crucial role played by oncogenic EGFR mutants in driving non-small cell lung cancer (NSCLC). Despite targeted therapies against EGFR setting a milestone in the treatment of this disease, ubiquitous drug resistance inevitably emerges after one year or so of treatment. The magnitude of the challenge has inspired novel strategies. Among these, the combination of multi-disciplinary experiments and molecular dynamic (MD) simulations have been pivotal in revealing the basic nature of EGFR monomers, dimers and multimers, and the structure-function relationships that underpin the mechanisms by which EGFR dysregulation contributes to the onset of NSCLC and resistance to treatment.

Thalidomide and Its Analogs Differentially Target Fibroblast Growth Factor Receptors: Thalidomide Suppresses FGFR Gene Expression while Pomalidomide Dampens FGFR2 Activity

Thalidomide is an infamous teratogen and it is continuously being explored for its anticancer properties. Fibroblast growth factor receptors (FGFRs) are implicated in embryo development and cancer pathophysiology. With striking similarities observed between FGFR implicated conditions and thalidomide embryopathy, we hypothesized thalidomide targets FGFRs. We utilized three different cell lines and chicken embryo model to investigate the effects of thalidomide and analogs on FGFR expression. We performed molecular docking, KINOMEscan analysis, and kinase activity assays to study the drug-protein interactions. The expression of FGFR1 and FGFR2 was differentially regulated by all the three drugs in cells as well as in developing organs. Transcriptome analysis of thalidomide-treated chick embryo strongly suggests the modulation of FGFR signaling and key transcription factors. Corroboration with previous studies suggests that thalidomide might affect FGFR expression through the transcription factor, E2F1. At the protein level, molecular docking predicted all three analogs to interact with lysine residue at 517th and 508th positions of FGFR2 and FGFR3, respectively. This lysine coordinates the ATP binding site of FGFR, thus hinting at the possible perturbation of FGFR activity by thalidomide. Kinome analysis revealed that kinase activities of FGFR2 and FGFR3 (G697C) reduced by 31% and 65%, respectively, in the presence of 10 μM thalidomide. Further, we checked and confirmed that the analogs inhibited the FGFR2 kinase activity in a dose-dependent manner. This study suggests that FGFRs could be potential targets of thalidomide and the two analogs, and also endorses the link between the teratogenicity and antitumor activities of the drugs.

Ensemble-Based Replica Exchange Alchemical Free Energy Methods: The Effect of Protein Mutations on Inhibitor Binding

The accurate prediction of the binding affinity changes of drugs caused by protein mutations is a major goal in clinical personalized medicine. We have developed an ensemble-based free energy approach called thermodynamic integration with enhanced sampling (TIES), which yields accurate, precise, and reproducible binding affinities. TIES has been shown to perform well for predictions of free energy differences of congeneric ligands to a wide range of target proteins. We have recently introduced variants of TIES, which incorporate the enhanced sampling technique REST2 (replica exchange with solute tempering) and the free energy estimator MBAR (Bennett acceptance ratio). Here we further extend the TIES methodology to study relative binding affinities caused by protein mutations when bound to a ligand, a variant which we call TIES-PM. We apply TIES-PM to fibroblast growth factor receptor 3 (FGFR3) to investigate binding free energy changes upon protein mutations. The results show that TIES-PM with REST2 successfully captures a large conformational change and generates correct free energy differences caused by a gatekeeper mutation located in the binding pocket. Simulations without REST2 fail to overcome the energy barrier between the conformations, and hence the results are highly sensitive to the initial structures. We also discuss situations where REST2 does not improve the accuracy of predictions.

High-throughput binding affinity calculations at extreme scales

Background

Resistance to chemotherapy and molecularly targeted therapies is a major factor in limiting the effectiveness of cancer treatment. In many cases, resistance can be linked to genetic changes in target proteins, either pre-existing or evolutionarily selected during treatment. Key to overcoming this challenge is an understanding of the molecular determinants of drug binding. Using multi-stage pipelines of molecular simulations we can gain insights into the binding free energy and the residence time of a ligand, which can inform both stratified and personal treatment regimes and drug development. To support the scalable, adaptive and automated calculation of the binding free energy on high-performance computing resources, we introduce the High-throughput Binding Affinity Calculator (HTBAC). HTBAC uses a building block approach in order to attain both workflow flexibility and performance.

Results

We demonstrate close to perfect weak scaling to hundreds of concurrent multi-stage binding affinity calculation pipelines. This permits a rapid time-to-solution that is essentially invariant of the calculation protocol, size of candidate ligands and number of ensemble simulations.

Conclusions

As such, HTBAC advances the state of the art of binding affinity calculations and protocols. HTBAC provides the platform to enable scientists to study a wide range of cancer drugs and candidate ligands in order to support personalized clinical decision making based on genome sequencing and drug discovery.

A novel FGFR1-binding peptide attenuates the degeneration of articular cartilage in adult mice

OBJECTIVE

We previously reported that genetic ablation of (Fibroblast Growth Factors Receptors) FGFR1 in knee cartilage attenuates the degeneration of articular cartilage in adult mice, which suggests that FGFR1 is a potential targeting molecule for osteoarthritis (OA). Here, we identified R1-P1, an inhibitory peptide for FGFR1 and investigated its effect on the pathogenesis of OA in mice induced by destabilization of medial meniscus (DMM).

DESIGN

Binding ability between R1-P1 and FGFR1 protein was evaluated by enzyme-linked immuno sorbent assay (ELISA) and molecular docking. Alterations in cartilage were evaluated histologically. The expression levels of molecules associated with articular cartilage homeostasis and FGFR1 signaling were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR), Western blotting and immunohistochemistry (IHC). The chondrocyte apoptosis was detected by terminal-deoxynucleoitidyl transferase mediated nick end labeling (TUNEL) assay.

RESULTS

R1-P1 had highly binding affinities to human FGFR1 protein, and efficiently inhibited extracellular signal-regulated kinase (ERK)1/2 pathway in mouse primary chondrocytes. In addition, R1-P1 attenuated the IL-1β induced significant loss of proteoglycan in full-thickness cartilage tissue from human femur head. Moreover, this peptide can significantly restore the IL-1β mediated loss of proteoglycan and type II collagen (Col II) and attenuate the expression of matrix metalloproteinase-13 (MMP13) in mouse primary chondrocytes. Finally, intra-articular injection of R1-P1 remarkably attenuated the loss of proteoglycan and the destruction of articular cartilage and decreased the expressions of extracellular matrix (ECM) degrading enzymes and apoptosis in articular chondrocytes of mice underwent DMM surgery.

CONCLUSIONS

R1-P1, a novel inhibitory peptide for FGFR1, attenuates the degeneration of articular cartilage in adult mice, which is a potential leading molecule for the treatment of OA.

NMR backbone assignments of the tyrosine kinase domain of human fibroblast growth factor receptor 3 in apo state and in complex with inhibitor PD173074

Fibroblast growth factors receptors (FGFR) are transmembrane protein tyrosine kinases involved in many cellular process, including growth, differentiation and angiogenesis. Dysregulation of FGFR enzymatic activity is associated with developmental disorders and cancers; therefore FGFRs have become attractive targets for drug discovery, with a number of agents in late-stage clinical trials. Here, we present the backbone resonance assignments of FGFR3 tyrosine kinase domain in the ligand-free form and in complex with the canonical FGFR kinase inhibitor PD173074. Analysis of chemical shift changes upon inhibitor binding highlights a characteristic pattern of allosteric network perturbations that is of relevance for future drug discovery activities aimed at development of conformationally-selective FGFR inhibitors.

The FGFR1 V561M Gatekeeper Mutation Drives AZD4547 Resistance through STAT3 Activation and EMT

FGFR1 has been implicated in numerous cancer types including squamous cell lung cancer, a subset of non-small cell lung cancer with a dismal 5-year survival rate. Small-molecule inhibitors targeting FGFR1 are currently in clinical trials, with AZD4547 being one of the furthest along; however, the development of drug resistance is a major challenge for targeted therapies. A prevalent mechanism of drug resistance in kinases occurs through mutation of the gatekeeper residue, V561M in FGFR1; however, mechanisms underlying V561M resistance to AZD4547 are not fully understood. Here, the cellular consequences of the V561M gatekeeper mutation were characterized, and it was found that although AZD4547 maintains nanomolar affinity for V561M FGFR1, based on in vitro binding assays, cells expressing V561M demonstrate dramatic resistance to AZD4547 driven by increased STAT3 activation downstream of V561M FGFR1. The data reveal that the V561M mutation biases cells toward a more mesenchymal phenotype, including increased levels of proliferation, migration, invasion, and anchorage-independent growth, which was confirmed using CyTOF, a novel single-cell analysis tool. Using shRNA knockdown, loss of STAT3 restored sensitivity of cancer cells expressing V561M FGFR1 to AZD4547. Thus, the data demonstrate that combination therapies including FGFR and STAT3 may overcome V561M FGFR1-driven drug resistance in the clinic. IMPLICATIONS: The V561M FGFR1 gatekeeper mutation leads to devastating drug resistance through activation of STAT3 and the epithelial-mesenchymal transition; this study demonstrates that FGFR1 inhibitor sensitivity can be restored upon STAT3 knockdown.

Structural Alterations in Human Fibroblast Growth Factor Receptors in Carcinogenesis

Fibroblast growth factor (FGF) plays an important role in human embryogenesis, angiogenesis, cell proliferation, and differentiation. Carcinogenesis is accompanied by aberrant constitutive activation of FGF receptors (FGFRs) resulting from missense mutation in the FGFR1-4 genes, generation of chimeric oncogenes, FGFR1-4 gene amplification, alternative splicing shift toward formation of mesenchymal FGFR isoforms, and FGFR overexpression. Altogether, these alterations contribute to auto- and paracrine stimulation of cancer cells and neoangiogenesis. Certain missense mutations are found at a high rate in urinary bladder cancer and can be used for non-invasive cancer recurrence diagnostics by analyzing urine cell pellet DNA. Chimeric FGFR1/3 and amplified FGFR1/2 genes can predict cell response to the targeted therapy in various oncological diseases. In recent years, high-throughput sequencing has been used to analyze exomes of virtually all human tumors, which allowed to construct phylogenetic trees of clonal cancer evolution with special emphasis on driver mutations in FGFR1-4 genes. At present, FGFR blockers, such as multi-kinase inhibitors, specific FGFR inhibitors, and FGF ligand traps are being tested in clinical trials. In this review, we discuss current data on the functioning of the FGFR family proteins in both normal and cancer cells, mutations in the FGFR1-4 genes, and mechanisms underlying their oncogenic potential, which might be interesting to a broad range of scientists searching for specific tumor markers and targeted anti-cancer drugs.

Recent advances of RAF (rapidly accelerated fibrosarcoma) inhibitors as anti-cancer agents

Frequent oncogenic mutations have been identified in MAPK (mitogen-activated protein kinase) signaling pathway components. As a result, MAPK pathway is associated with human cancer initiation, in particular RAF (rapidly accelerated fibrosarcoma) component. The mutation in RAF component leads to auto-activation of MAPK signaling pathway, stimulating the uncontrolled cell growth and proliferation. In last few years, diverse chemical scaffolds have been identified as RAF inhibitors. Most of these scaffolds show potent anti-cancer activity. The present review highlights the recent investigations of RAF inhibitors during the last five years.

Uncertainty Quantification in Alchemical Free Energy Methods

Alchemical free energy methods have gained much importance recently from several reports of improved ligand–protein binding affinity predictions based on their implementation using molecular dynamics simulations. A large number of variants of such methods implementing different accelerated sampling techniques and free energy estimators are available, each claimed to be better than the others in its own way. However, the key features of reproducibility and quantification of associated uncertainties in such methods have barely been discussed. Here, we apply a systematic protocol for uncertainty quantification to a number of popular alchemical free energy methods, covering both absolute and relative free energy predictions. We show that a reliable measure of error estimation is provided by ensemble simulation—an ensemble of independent MD simulations—which applies irrespective of the free energy method. The need to use ensemble methods is fundamental and holds regardless of the duration of time of the molecular dynamics simulations performed.

Disease Variants of FGFR3 Reveal Molecular Basis for the Recognition and Additional Roles for Cdc37 in Hsp90 Chaperone System

Receptor tyrosine kinase FGFR3 is involved in many signaling networks and is frequently mutated in developmental disorders and cancer. The Hsp90/Cdc37 chaperone system is essential for function of normal and neoplastic cells. Here we uncover the mechanistic inter-relationships between these proteins by combining approaches including NMR, HDX-MS, and SAXS. We show that several disease-linked mutations convert FGFR3 to a stronger client, where the determinant underpinning client strength involves an allosteric network through the N-lobe and at the lobe interface. We determine the architecture of the client kinase/Cdc37 complex and demonstrate, together with site-specific information, that binding of Cdc37 to unrelated kinases induces a common, extensive conformational remodeling of the kinase N-lobe, beyond localized changes and interactions within the binary complex. As further shown for FGFR3, this processing by Cdc37 deactivates the kinase and presents it, in a specific orientation established in the complex, for direct recognition by Hsp90.

On the calculation of equilibrium thermodynamic properties from molecular dynamics

The purpose of statistical mechanics is to provide a route to the calculation of macroscopic properties of matter from their constituent microscopic components. It is well known that the macrostates emerge as ensemble averages of microstates. However, this is more often stated than implemented in computer simulation studies. Here we consider foundational aspects of statistical mechanics which are overlooked in most textbooks and research articles that purport to compute macroscopic behaviour from microscopic descriptions based on classical mechanics and show how due attention to these issues leads in directions which have not been widely appreciated in the field of molecular dynamics simulation.

Structure of the WipA protein reveals a novel tyrosine protein phosphatase effector from Legionella pneumophila

Legionnaires' disease is a severe form of pneumonia caused by the bacterium Legionella pneumophila. L. pneumophila pathogenicity relies on secretion of more than 300 effector proteins by a type IVb secretion system. Among these Legionella effectors, WipA has been primarily studied because of its dependence on a chaperone complex, IcmSW, for translocation through the secretion system, but its role in pathogenicity has remained unknown. In this study, we present the crystal structure of a large fragment of WipA, WipA435. Surprisingly, this structure revealed a serine/threonine phosphatase fold that unexpectedly targets tyrosine-phosphorylated peptides. The structure also revealed a sequence insertion that folds into an α-helical hairpin, the tip of which adopts a canonical coiled-coil structure. The purified protein was a dimer whose dimer interface involves interactions between the coiled coil of one WipA molecule and the phosphatase domain of another. Given the ubiquity of protein-protein interaction mediated by interactions between coiled-coils, we hypothesize that WipA can thereby transition from a homodimeric state to a heterodimeric state in which the coiled-coil region of WipA is engaged in a protein-protein interaction with a tyrosine-phosphorylated host target. In conclusion, these findings help advance our understanding of the molecular mechanisms of an effector involved in Legionella virulence and may inform approaches to elucidate the function of other effectors.

Evaluation and Characterization of Trk Kinase Inhibitors for the Treatment of Pain: Reliable Binding Affinity Predictions from Theory and Computation

Optimization of ligand binding affinity to the target protein of interest is a primary objective in small-molecule drug discovery. Until now, the prediction of binding affinities by computational methods has not been widely applied in the drug discovery process, mainly because of its lack of accuracy and reproducibility as well as the long turnaround times required to obtain results. Herein we report on a collaborative study that compares tropomyosin receptor kinase A (TrkA) binding affinity predictions using two recently formulated fast computational approaches, namely, Enhanced Sampling of Molecular dynamics with Approximation of Continuum Solvent (ESMACS) and Thermodynamic Integration with Enhanced Sampling (TIES), to experimentally derived TrkA binding affinities for a set of Pfizer pan-Trk compounds. ESMACS gives precise and reproducible results and is applicable to highly diverse sets of compounds. It also provides detailed chemical insight into the nature of ligand-protein binding. TIES can predict and thus optimize more subtle changes in binding affinities between compounds of similar structure. Individual binding affinities were calculated in a few hours, exhibiting good correlations with the experimental data of 0.79 and 0.88 from the ESMACS and TIES approaches, respectively. The speed, level of accuracy, and precision of the calculations are such that the affinity predictions can be used to rapidly explain the effects of compound modifications on TrkA binding affinity. The methods could therefore be used as tools to guide lead optimization efforts across multiple prospective structurally enabled programs in the drug discovery setting for a wide range of compounds and targets.

Insight into resistance mechanisms of AZD4547 and E3810 to FGFR1 gatekeeper mutation via theoretical study

Inhibitors targeting the amplification of the fibroblast growth factor receptor 1 (FGFR1) have found success in the treatment of FGFR1-positive squamous cell lung and breast cancers. A secondary mutation of gatekeeper residue (V561M) in the binding site has been linked to the acquired resistance. Recently, two well-known small molecule inhibitors of FGFR1, AZD4547 and E3810, reported that the V561M mutation confers significant resistance to E3810, while retaining affinity for AZD4547. FGFR1 is widely investigated as potential therapeutic target, while there are few computational studies made to understand the resistance mechanisms about FGFR1 V561M gatekeeper mutation. In this study, molecular docking, classical molecular dynamics simulations, molecular mechanics/generalized born surface area (MM/GBSA) free energy calculations, and umbrella sampling (US) simulations were carried out to make clear the principle of the binding preference of AZD4547 and E3810 toward FGFR1 V561M gatekeeper mutation. The results provided by MM/GBSA reveal that AZD4547 has similar binding affinity to both FGFR1^WT and FGFR1^V561M, whereas E3810 has much higher binding affinity to FGFR1^WT than to FGFR1^V561M. Comparison of individual energy terms indicates that the major variation of E3810 between FGFR1^WT and FGFR1^V561M are van der Waals interactions. In addition, US simulations prove that the potential of mean force (PMF) profile of AZD4547 toward FGFR1^WT and FGFR1^V561M has similar PMF depth. However, the PMF profile of E3810 toward FGFR1^WT and FGFR1^V561M has much higher PMF depth, suggesting that E3810 is more easily dissociated from FGFR1^V561M than from FGFR1^WT. The results not only show the drug-resistance determinants of FGFR1 gatekeeper mutation but also provide valuable implications and provide vital clues for the development of new inhibitors to combat drug resistance.

Rapid and Reliable Binding Affinity Prediction of Bromodomain Inhibitors: A Computational Study

Binding free energies of bromodomain inhibitors are calculated with recently formulated approaches, namely ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling). A set of compounds is provided by GlaxoSmithKline, which represents a range of chemical functionality and binding affinities. The predicted binding free energies exhibit a good Spearman correlation of 0.78 with the experimental data from the 3-trajectory ESMACS, and an excellent correlation of 0.92 from the TIES approach where applicable. Given access to suitable high end computing resources and a high degree of automation, we can compute individual binding affinities in a few hours with precisions no greater than 0.2 kcal/mol for TIES, and no larger than 0.34 and 1.71 kcal/mol for the 1- and 3-trajectory ESMACS approaches.

Conformational transition of FGFR kinase activation revealed by site-specific unnatural amino acid reporter and single molecule FRET

Protein kinases share significant structural similarity; however, structural features alone are insufficient to explain their diverse functions. Thus, bridging the gap between static structure and function requires a more detailed understanding of their dynamic properties. For example, kinase activation may occur via a switch-like mechanism or by shifting a dynamic equilibrium between inactive and active states. Here, we utilize a combination of FRET and molecular dynamics (MD) simulations to probe the activation mechanism of the kinase domain of Fibroblast Growth Factor Receptor (FGFR). Using genetically-encoded, site-specific incorporation of unnatural amino acids in regions essential for activation, followed by specific labeling with fluorescent moieties, we generated a novel class of FRET-based reporter to monitor conformational differences corresponding to states sampled by non phosphorylated/inactive and phosphorylated/active forms of the kinase. Single molecule FRET analysis in vitro, combined with MD simulations, shows that for FGFR kinase, there are populations of inactive and active states separated by a high free energy barrier resulting in switch-like activation. Compared to recent studies, these findings support diversity in features of kinases that impact on their activation mechanisms. The properties of these FRET-based constructs will also allow further studies of kinase dynamics as well as applications in vivo.

Rapid, Accurate, Precise, and Reliable Relative Free Energy Prediction Using Ensemble Based Thermodynamic Integration

The accurate prediction of the binding affinities of ligands to proteins is a major goal in drug discovery and personalized medicine. The time taken to make such predictions is of similar importance to their accuracy, precision, and reliability. In the past few years, an ensemble based molecular dynamics approach has been proposed that provides a route to reliable predictions of free energies based on the molecular mechanics Poisson-Boltzmann surface area method which meets the requirements of speed, accuracy, precision, and reliability. Here, we describe an equivalent methodology based on thermodynamic integration to substantially improve the speed, accuracy, precision, and reliability of calculated relative binding free energies. We report the performance of the method when applied to a diverse set of protein targets and ligands. The results are in very good agreement with experimental data (90% of calculations agree to within 1 kcal/mol), while the method is reproducible by construction. Statistical uncertainties of the order of 0.5 kcal/mol or less are achieved. We present a systematic account of how the uncertainty in the predictions may be estimated.

An overview of the binding models of FGFR tyrosine kinases in complex with small molecule inhibitors

The fibroblast growth factor receptor (FGFR) family receptor tyrosine kinase (RTK) includes four structurally related members, termed as FGFR1, FGFR2, FGFR3, and FGFR4. Given its intimate role in the progression of several solid tumors, excessive FGFR signaling provides an opportunity for anticancer therapy. Along with extensive pharmacological studies validating the therapeutic potential of targeting the FGFRs for cancer treatment, co-crystal structures of FGFRs/inhibitors are continuously coming up to study the mechanism of actions and explore new inhibitors. Herein, we review the reported co-crystals of FGFRs in complex with the corresponding inhibitors, main focusing our attention on the binding models and the pharmacological activities of the inhibitors.

Biophysical characterization of drug-resistant mutants of fibroblast growth factor receptor 1

Over-expression and aberrant activation of tyrosine kinases occur frequently in human cancers. Various tyrosine kinase inhibitors (TKIs) are under clinical use, but acquisition of resistance to these drugs is a major problem. Here, we studied the interaction between two drug-resistant mutants of fibroblast growth factor receptor 1 (FGFR1), N546K and V561M, and four ATP-competitive inhibitors, ponatinib, dovitinib, PD173074 and BGJ-398. Among these protein-drug systems, the only marked reduction in affinity was that of PD173074 for the V561M mutant. We also examined the interaction of these FGFR1 variants to AMP-PNP, a nonhydrolyzable analogue of ATP, and showed that N546K showed increased affinity for the ATP analogue as compared with the wild type. These findings will help to clarify the mechanism of drug resistance in mutant tyrosine kinases.

Insight on Mutation-Induced Resistance from Molecular Dynamics Simulations of the Native and Mutated CSF-1R and KIT

The receptors tyrosine kinases (RTKs) for the colony stimulating factor-1, CSF-1R, and for the stem cell factor, SCFR or KIT, are important mediators of signal transduction. The abnormal function of these receptors, promoted by gain-of-function mutations, leads to their constitutive activation, associated with cancer or other proliferative diseases. A secondary effect of the mutations is the alteration of receptors' sensitivity to tyrosine kinase inhibitors, compromising effectiveness of these molecules in clinical treatment. In particular, the mutation V560G in KIT increases its sensitivity to Imatinib, while the D816V in KIT, and D802V in CSF-1R, triggers resistance to the drug. We analyzed the Imatinib binding affinity to the native and mutated KIT (mutations V560G, S628N and D816V) and CSF-1R (mutation D802V) by using molecular dynamics simulations and energy calculations of Imatinib•target complexes. Further, we evaluated the sensitivity of the studied KIT receptors to Imatinib by measuring the inhibition of KIT phosphorylation. Our study showed that (i) the binding free energy of Imatinib to the targets is highly correlated with their experimentally measured sensitivity; (ii) the electrostatic interactions are a decisive factor affecting the binding energy; (iii) the most deleterious impact to the Imatinib sensitivity is promoted by D802V (CSF-1R) and D816V (KIT) mutations; (iv) the role of the juxtamembrane region, JMR, in the imatinib binding is accessory. These findings contribute to a better description of the mutation-induced effects alternating the targets sensitivity to Imatinib.

A place for precision medicine in bladder cancer: targeting the FGFRs

Bladder tumors show diverse molecular features and clinical outcome. Muscle-invasive bladder cancer has poor prognosis and novel approaches to systemic therapy are urgently required. Non-muscle-invasive bladder cancer has good prognosis, but high recurrence rate and the requirement for life-long disease monitoring places a major burden on patients and healthcare providers. Studies of tumor tissues from both disease groups have identified frequent alterations of FGFRs, including mutations of FGFR3 and dysregulated expression of FGFR1 and FGFR3 that suggest that these may be valid therapeutic targets. We summarize current understanding of the molecular alterations affecting these receptors in bladder tumors, preclinical studies validating them as therapeutic targets, available FGFR-targeted agents and results from early clinical trials in bladder cancer patients.