Calculating Protein-Ligand Residence Times through State Predictive Information Bottleneck Based Enhanced Sampling.

Understanding drug residence times in target proteins is key to improving drug efficacy and understanding target recognition in biochemistry. While drug residence time is just as important as binding affinity, atomic-level understanding of drug residence times through molecular dynamics (MD) simulations has been difficult primarily due to the extremely long time scales. Recent advances in rare event sampling have allowed us to reach these time scales, yet predicting protein-ligand residence times remains a significant challenge. Here we present a semi-automated protocol to calculate the ligand residence times across 12 orders of magnitude of time scales. In our proposed framework, we integrate a deep learning-based method, the state predictive information bottleneck (SPIB), to learn an approximate reaction coordinate (RC) and use it to guide the enhanced sampling method metadynamics. We demonstrate the performance of our algorithm by applying it to six different protein-ligand complexes with available benchmark residence times, including the dissociation of the widely studied anticancer drug Imatinib (Gleevec) from both wild-type Abl kinase and drug-resistant mutants. We show how our protocol can recover quantitatively accurate residence times, potentially opening avenues for deeper insights into drug development possibilities and ligand recognition mechanisms.

The C1q and gC1qR axis as a novel checkpoint inhibitor in cancer.

Understanding at the molecular level of the cell biology of tumors has led to significant treatment advances in the past. Despite such advances however, development of therapy resistance and tumor recurrence are still unresolved major challenges. This therefore underscores the need to identify novel tumor targets and develop corresponding therapies to supplement existing biologic and cytotoxic approaches so that a deeper and more sustained treatment responses could be achieved. The complement system is emerging as a potential novel target for cancer therapy. Data accumulated to date show that complement proteins, and in particular C1q and its receptors cC1qR/CR and gC1qR/p33/HABP1, are overexpressed in most cancer cells and together are involved not only in shaping the inflammatory tumor microenvironment, but also in the regulation of angiogenesis, metastasis, and cell proliferation. In addition to the soluble form of C1q that is found in plasma, the C1q molecule is also found anchored on the cell membrane of monocytes, macrophages, dendritic cells, and cancer cells, via a 22aa long leader peptide found only in the A-chain. This orientation leaves its 6 globular heads exposed outwardly and thus available for high affinity binding to a wide range of molecular ligands that enhance tumor cell survival, migration, and proliferation. Similarly, the gC1qR molecule is not only overexpressed in most cancer types but is also released into the microenvironment where it has been shown to be associated with cancer cell proliferation and metastasis by activation of the complement and kinin systems. Co-culture of either T cells or cancer cells with purified C1q or anti-gC1qR has been shown to induce an anti-proliferative response. It is therefore postulated that in the tumor microenvironment, the interaction between C1q expressing cancer cells and gC1qR bearing cytotoxic T cells results in T cell suppression in a manner akin to the PD-L1 and PD-1 interaction.

Calculating Protein-Ligand Residence Times Through State Predictive Information Bottleneck based Enhanced Sampling.

Understanding drug residence times in target proteins is key to improving drug efficacy and understanding target recognition in biochemistry. While drug residence time is just as important as binding affinity, atomic-level understanding of drug residence times through molecular dynamics (MD) simulations has been difficult primarily due to the extremely long timescales. Recent advances in rare event sampling have allowed us to reach these timescales, yet predicting protein-ligand residence times remains a significant challenge. Here we present a semi-automated protocol to calculate the ligand residence times across 12 orders of magnitudes of timescales. In our proposed framework, we integrate a deep learning-based method, the state predictive information bottleneck (SPIB), to learn an approximate reaction coordinate (RC) and use it to guide the enhanced sampling method metadynamics. We demonstrate the performance of our algorithm by applying it to six different protein-ligand complexes with available benchmark residence times, including the dissociation of the widely studied anti-cancer drug Imatinib (Gleevec) from both wild-type Abl kinase and drug-resistant mutants. We show how our protocol can recover quantitatively accurate residence times, potentially opening avenues for deeper insights into drug development possibilities and ligand recognition mechanisms.

All the mutations that are fit to die.

In this issue of Cell Chemical Biology, Chakraborty et al.1 employ a deep mutational screening analysis of 3,500 single point mutations in every residue in Src kinase's catalytic domain to determine which residues are critical for conferring ATP-competitive inhibitor resistance. They identify a dynamically controlled resistance site.

Allo-targeting of the kinase domain: Insights from in silico studies and comparison with experiments.

The eukaryotic protein kinase domain has been a broadly explored target for drug discovery, despite limitations imposed by its high sequence conservation as a shared modular domain and the development of resistance to drugs. One way of addressing those limitations has been to target its potential allosteric sites, shortly called allo-targeting, in conjunction with, or separately from, its conserved catalytic/orthosteric site that has been widely exploited. Allosteric regulation has gained importance as an alternative to overcome the drawbacks associated with the indiscriminate effect of targeting the active site, and it turned out to be particularly useful for these highly promiscuous and broadly shared kinase domains. Yet, allo-targeting often faces challenges as the allosteric sites are not as clearly defined as its orthosteric sites, and the effect on the protein function may not be unambiguously assessed. A robust understanding of the consequence of site-specific allo-targeting on the conformational dynamics of the target protein is essential to design effective allo-targeting strategies. Recent years have seen important advances in in silico identification of druggable sites and distinguishing among them those sites expected to allosterically mediate conformational switches essential to signal transmission. The present opinion underscores the utility of such computational approaches applied to the kinase domain, with the help of comparison between computational predictions and experimental observations.

Lucanthone, a Potential PPT1 Inhibitor, Perturbs Stemness, Reduces Tumor Microtube Formation, and Slows the Growth of Temozolomide-Resistant Gliomas In Vivo.

Glioblastoma (GBM) is the most frequently diagnosed primary central nervous system tumor in adults. Despite the standard of care therapy, which includes surgical resection, temozolomide chemotherapy, radiation and the newly added tumor-treating fields, median survival remains only ∼20 months. Unfortunately, GBM has a ∼100% recurrence rate, but after recurrence there are no Food and Drug Administration-approved therapies to limit tumor growth and enhance patient survival, as these tumors are resistant to temozolomide (TMZ). Recently, our laboratory reported that lucanthone slows GBM by inhibiting autophagic flux through lysosome targeting and decreases the number of Olig2+ glioma stem-like cells (GSC) in vitro and in vivo. We now additionally report that lucanthone efficiently abates stemness in patient-derived GSC and reduces tumor microtube formation in GSC, an emerging hallmark of treatment resistance in GBM. In glioma tumors derived from cells with acquired resistance to TMZ, lucanthone retains the ability to perturb tumor growth, inhibits autophagy by targeting lysosomes, and reduces Olig2 positivity. We also find that lucanthone may act as an inhibitor of palmitoyl protein thioesterase 1. Our results suggest that lucanthone may function as a potential treatment option for GBM tumors that are not amenable to TMZ treatment. SIGNIFICANCE STATEMENT: We report that the antischistosome agent lucanthone impedes tumor growth in a preclinical model of temozolomide-resistant glioblastoma and reduces the numbers of stem-like glioma cells. In addition, it acts as an autophagy inhibitor, and its mechanism of action may be via inhibition of palmitoyl protein thioesterase 1. As there are no defined therapies approved for recurrent, TMZ-resistant tumor, lucanthone could emerge as a treatment for glioblastoma tumors that may not be amenable to TMZ both in the newly diagnosed and recurrent settings.

Death by a thousand cuts through kinase inhibitor combinations that maximize selectivity and enable rational multitargeting.

Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. However, the high sequence and structural conservation of the catalytic kinase domain complicate the development of selective kinase inhibitors. Inhibition of off-target kinases makes it difficult to study the mechanism of inhibitors in biological systems. Current efforts focus on the development of inhibitors with improved selectivity. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target effects. We develop a multicompound-multitarget scoring (MMS) method that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables optimization of inhibitor combinations for multiple on-targets. Using MMS with published kinase inhibitor datasets we determine potent inhibitor combinations for target kinases with better selectivity than the most selective single inhibitor and validate the predicted effect and selectivity of inhibitor combinations using in vitro and in cellulo techniques. MMS greatly enhances selectivity in rational multitargeting applications. The MMS framework is generalizable to other non-kinase biological targets where compound selectivity is a challenge and diverse compound libraries are available.

Probing conformational dynamics to understand kinase inhibition.

Why do some inhibitors select the on-state in ERK2, a kinase that is involved in many signaling pathways in cells, whereas others bind to more than one conformation?

Structural mechanism of a drug-binding process involving a large conformational change of the protein target.

Proteins often undergo large conformational changes when binding small molecules, but atomic-level descriptions of such events have been elusive. Here, we report unguided molecular dynamics simulations of Abl kinase binding to the cancer drug imatinib. In the simulations, imatinib first selectively engages Abl kinase in its autoinhibitory conformation. Consistent with inferences drawn from previous experimental studies, imatinib then induces a large conformational change of the protein to reach a bound complex that closely resembles published crystal structures. Moreover, the simulations reveal a surprising local structural instability in the C-terminal lobe of Abl kinase during binding. The unstable region includes a number of residues that, when mutated, confer imatinib resistance by an unknown mechanism. Based on the simulations, NMR spectra, hydrogen-deuterium exchange measurements, and thermostability measurements and estimates, we suggest that these mutations confer imatinib resistance by exacerbating structural instability in the C-terminal lobe, rendering the imatinib-bound state energetically unfavorable.

Domain Architecture of the Nonreceptor Tyrosine Kinase Ack1.

The nonreceptor tyrosine kinase (NRTK) Ack1 comprises a distinct arrangement of non-catalytic modules. Its SH3 domain has a C-terminal to the kinase domain (SH1), in contrast to the typical SH3-SH2-SH1 layout in NRTKs. The Ack1 is the only protein that shares a region of high homology to the tumor suppressor protein Mig6, a modulator of EGFR. The vertebrate Acks make up the only tyrosine kinase (TK) family known to carry a UBA domain. The GTPase binding and SAM domains are also uncommon in the NRTKs. In addition to being a downstream effector of receptor tyrosine kinases (RTKs) and integrins, Ack1 can act as an epigenetic regulator, modulate the degradation of the epidermal growth factor receptor (EGFR), confer drug resistance, and mediate the progression of hormone-sensitive tumors. In this review, we discuss the domain architecture of Ack1 in relation to other protein kinases that possess such defined regulatory domains.

Biochemical Studies of Systemic Lupus Erythematosus-Associated Mutations in Nonreceptor Tyrosine Kinases Ack1 and Brk.

Tyrosine kinases (TKs) play essential roles in signaling processes that regulate cell survival, migration, and proliferation. Dysregulation of tyrosine kinases underlies many disorders, including cancer, cardiovascular and developmental diseases, as well as pathologies of the immune system. Ack1 and Brk are nonreceptor tyrosine kinases (NRTKs) best known for their roles in cancer. Here, we have biochemically characterized novel Ack1 and Brk mutations identified in patients with systemic lupus erythematosus (SLE). These mutations are the first SLE-linked polymorphisms found among NRTKs. We show that two of the mutants are catalytically inactive, while the other three have reduced activity. To understand the structural changes associated with the loss-of-function phenotype, we solved the crystal structure of one of the Ack1 kinase mutants, K161Q. Furthermore, two of the mutated residues (Ack1 A156 and K161) critical for catalytic activity are highly conserved among other TKs, and their substitution in other members of the kinase family could have implications in cancer. In contrast to canonical gain-of-function mutations in TKs observed in many cancers, we report loss-of-function mutations in Ack1 and Brk, highlighting the complexity of TK involvement in human diseases.

Allosteric regulation and inhibition of protein kinases.

The human genome encodes more than 500 different protein kinases: signaling enzymes with tightly regulated activity. Enzymatic activity within the conserved kinase domain is influenced by numerous regulatory inputs including the binding of regulatory domains, substrates, and the effect of post-translational modifications such as autophosphorylation. Integration of these diverse inputs occurs via allosteric sites that relate signals via networks of amino acid residues to the active site and ensures controlled phosphorylation of kinase substrates. Here, we review mechanisms of allosteric regulation of protein kinases and recent advances in the field.

Death by a Thousand Cuts â€" Combining Kinase Inhibitors for Selective Target Inhibition and Rational Polypharmacology.

Kinase inhibitors are successful therapeutics in the treatment of cancers and autoimmune diseases and are useful tools in biomedical research. The high sequence and structural conservation of the catalytic kinase domain complicates the development of specific kinase inhibitors. As a consequence, most kinase inhibitors also inhibit off-target kinases which complicates the interpretation of phenotypic responses. Additionally, inhibition of off-targets may cause toxicity in patients. Therefore, highly selective kinase inhibition is a major goal in both biomedical research and clinical practice. Currently, efforts to improve selective kinase inhibition are dominated by the development of new kinase inhibitors. Here, we present an alternative solution to this problem by combining inhibitors with divergent off-target activities. We have developed a multicompound-multitarget scoring (MMS) method framework that combines inhibitors to maximize target inhibition and to minimize off-target inhibition. Additionally, this framework enables rational polypharmacology by allowing optimization of inhibitor combinations against multiple selected on-targets and off-targets. Using MMS with previously published chemogenomic kinase inhibitor datasets we determine inhibitor combinations that achieve potent activity against a target kinase and that are more selective than the most selective single inhibitor against that target. We validate the calculated effect and selectivity of a combination of inhibitors using the in cellulo NanoBRET assay. The MMS framework is generalizable to other pharmacological targets where compound specificity is a challenge and diverse compound libraries are available.

IFITM proteins assist cellular uptake of diverse linked chemotypes.

The search for cell-permeable drugs has conventionally focused on low-molecular weight (MW), nonpolar, rigid chemical structures. However, emerging therapeutic strategies break traditional drug design rules by employing flexibly linked chemical entities composed of more than one ligand. Using complementary genome-scale chemical-genetic approaches we identified an endogenous chemical uptake pathway involving interferon-induced transmembrane proteins (IFITMs) that modulates the cell permeability of a prototypical biopic inhibitor of MTOR (RapaLink-1, MW: 1784 g/mol). We devised additional linked inhibitors targeting BCR-ABL1 (DasatiLink-1, MW: 1518 g/mol) and EIF4A1 (BisRoc-1, MW: 1466 g/mol), uptake of which was facilitated by IFITMs. We also found that IFITMs moderately assisted some proteolysis-targeting chimeras and examined the physicochemical requirements for involvement of this uptake pathway.

Inhibiting ACK1-mediated phosphorylation of C-terminal Src kinase counteracts prostate cancer immune checkpoint blockade resistance.

Solid tumours are highly refractory to immune checkpoint blockade (ICB) therapies due to the functional impairment of effector T cells and their inefficient trafficking to tumours. T-cell activation is negatively regulated by C-terminal Src kinase (CSK); however, the exact mechanism remains unknown. Here we show that the conserved oncogenic tyrosine kinase Activated CDC42 kinase 1 (ACK1) is able to phosphorylate CSK at Tyrosine 18 (pY18), which enhances CSK function, constraining T-cell activation. Mice deficient in the Tnk2 gene encoding Ack1, are characterized by diminished CSK Y18-phosphorylation and spontaneous activation of CD8+ and CD4+ T cells, resulting in inhibited growth of transplanted ICB-resistant tumours. Furthermore, ICB treatment of castration-resistant prostate cancer (CRPC) patients results in re-activation of ACK1/pY18-CSK signalling, confirming the involvement of this pathway in ICB insensitivity. An ACK1 small-molecule inhibitor, (R)-9b, recapitulates inhibition of ICB-resistant tumours, which provides evidence for ACK1 enzymatic activity playing a pivotal role in generating ICB resistance. Overall, our study identifies an important mechanism of ICB resistance and holds potential for expanding the scope of ICB therapy to tumours that are currently unresponsive.

Discovery and molecular basis of subtype-selective cyclophilin inhibitors.

Although cyclophilins are attractive targets for probing biology and therapeutic intervention, no subtype-selective cyclophilin inhibitors have been described. We discovered novel cyclophilin inhibitors from the in vitro selection of a DNA-templated library of 256,000 drug-like macrocycles for cyclophilin D (CypD) affinity. Iterated macrocycle engineering guided by ten X-ray co-crystal structures yielded potent and selective inhibitors (half maximal inhibitory concentration (IC50) = 10 nM) that bind the active site of CypD and also make novel interactions with non-conserved residues in the S2 pocket, an adjacent exo-site. The resulting macrocycles inhibit CypD activity with 21- to >10,000-fold selectivity over other cyclophilins and inhibit mitochondrial permeability transition pore opening in isolated mitochondria. We further exploited S2 pocket interactions to develop the first cyclophilin E (CypE)-selective inhibitor, which forms a reversible covalent bond with a CypE S2 pocket lysine, and exhibits 30- to >4,000-fold selectivity over other cyclophilins. These findings reveal a strategy to generate isoform-selective small-molecule cyclophilin modulators, advancing their suitability as targets for biological investigation and therapeutic development.

Extended DNA-binding interfaces beyond the canonical SAP domain contribute to the function of replication stress regulator SDE2 at DNA replication forks.

Elevated DNA replication stress causes instability of the DNA replication fork and increased DNA mutations, which underlies tumorigenesis. The DNA replication stress regulator silencing-defective 2 (SDE2) is known to bind to TIMELESS (TIM), a protein of the fork protection complex, and enhances its stability, thereby supporting replisome activity at DNA replication forks. However, the DNA-binding activity of SDE2 is not well defined. Here, we structurally and functionally characterize a new conserved DNA-binding motif related to the SAP (SAF-A/B, Acinus, PIAS) domain in human SDE2 and establish its preference for ssDNA. Our NMR solution structure of the SDE2SAP domain reveals a helix-extended loop-helix core with the helices aligned parallel to each other, consistent with known canonical SAP folds. Notably, we have shown that the DNA interaction of this SAP domain extends beyond the core SAP domain and is augmented by two lysine residues in the C-terminal tail, which is uniquely positioned adjacent to the SAP motif and conserved in the pre-mRNA splicing factor SF3A3. Furthermore, we found that mutation in the SAP domain and extended C terminus not only disrupts ssDNA binding but also impairs TIM localization at replication forks, thus inhibiting efficient fork progression. Taken together, our results establish SDE2SAP as an essential element for SDE2 to exert its role in preserving replication fork integrity via fork protection complex regulation and highlight the structural diversity of the DNA-protein interactions achieved by a specialized DNA-binding motif.

Kinases on Double Duty: A Review of UniProtKB Annotated Bifunctionality within the Kinome.

Phosphorylation facilitates the regulation of all fundamental biological processes, which has triggered extensive research of protein kinases and their roles in human health and disease. In addition to their phosphotransferase activity, certain kinases have evolved to adopt additional catalytic functions, while others have completely lost all catalytic activity. We searched the Universal Protein Resource Knowledgebase (UniProtKB) database for bifunctional protein kinases and focused on kinases that are critical for bacterial and human cellular homeostasis. These kinases engage in diverse functional roles, ranging from environmental sensing and metabolic regulation to immune-host defense and cell cycle control. Herein, we describe their dual catalytic activities and how they contribute to disease pathogenesis.