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1. Gatekeeper mutations activate FGF receptor tyrosine kinases by destabilizing the autoinhibited state

   https://doi.org/10.1073/pnas.2213090120  

   Besch, Alida ; Marsiglia, William M. ; Mohammadi, Moosa ; Zhang, Yingkai ; Traaseth, Nathaniel J. ( February 2023 , Proceedings of the National Academy of Sciences)

   Many types of human cancers are being treated with small molecule ATP-competitive inhibitors targeting the kinase domain of receptor tyrosine kinases. Despite initial successful remission, long-term treatment almost inevitably leads to the emergence of drug resistance mutations at the gatekeeper residue hindering the access of the inhibitor to a hydrophobic pocket at the back of the ATP-binding cleft. In addition to reducing drug efficacy, gatekeeper mutations elevate the intrinsic activity of the tyrosine kinase domain leading to more aggressive types of cancer. However, the mechanism of gain-of-function by gatekeeper mutations is poorly understood. Here, we characterized fibroblast growth factor receptor (FGFR) tyrosine kinases harboring two distinct gatekeeper mutations using kinase activity assays, NMR spectroscopy, bioinformatic analyses, and MD simulations. Our data show that gatekeeper mutations destabilize the autoinhibitory conformation of the DFG motif locally and of the kinase globally, suggesting they impart gain-of-function by facilitating the kinase's ability to populate the active state. 

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2. Targeting the Id1-Kif11 Axis in Triple-Negative Breast Cancer Using Combination Therapy

   https://doi.org/10.3390/biom10091295  

   Thankamony, Archana P. ; Murali, Reshma ; Karthikeyan, Nitheesh ; Varghese, Binitha Anu ; Teo, Wee S. ; McFarland, Andrea ; Roden, Daniel L. ; Holliday, Holly ; Konrad, Christina Valbirk ; Cazet, Aurelie ; et al ( September 2020 , Biomolecules)

   null (Ed.)

   The basic helix-loop-helix (bHLH) transcription factors inhibitor of differentiation 1 (Id1) and inhibitor of differentiation 3 (Id3) (referred to as Id) have an important role in maintaining the cancer stem cell (CSC) phenotype in the triple-negative breast cancer (TNBC) subtype. In this study, we aimed to understand the molecular mechanism underlying Id control of CSC phenotype and exploit it for therapeutic purposes. We used two different TNBC tumor models marked by either Id depletion or Id1 expression in order to identify Id targets using a combinatorial analysis of RNA sequencing and microarray data. Phenotypically, Id protein depletion leads to cell cycle arrest in the G0/G1 phase, which we demonstrate is reversible. In order to understand the molecular underpinning of Id proteins on the cell cycle phenotype, we carried out a large-scale small interfering RNA (siRNA) screen of 61 putative targets identified by using genomic analysis of two Id TNBC tumor models. Kinesin Family Member 11 (Kif11) and Aurora Kinase A (Aurka), which are critical cell cycle regulators, were further validated as Id targets. Interestingly, unlike in Id depletion conditions, Kif11 and Aurka knockdown leads to a G2/M arrest, suggesting a novel Id cell cycle mechanism, which we will explore in further studies. Therapeutic targeting of Kif11 to block the Id1–Kif11 axis was carried out using small molecular inhibitor ispinesib. We finally leveraged our findings to target the Id/Kif11 pathway using the small molecule inhibitor ispinesib in the Id+ CSC results combined with chemotherapy for better response in TNBC subtypes. This work opens up exciting new possibilities of targeting Id targets such as Kif11 in the TNBC subtype, which is currently refractory to chemotherapy. Targeting the Id1–Kif11 molecular pathway in the Id1+ CSCs in combination with chemotherapy and small molecular inhibitor results in more effective debulking of TNBC. 

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3. RCSB Protein Data Bank: Enabling biomedical research and drug discovery

   https://doi.org/10.1002/pro.3730  

   Goodsell, David S. ; Zardecki, Christine ; Di Costanzo, Luigi ; Duarte, Jose M. ; Hudson, Brian P. ; Persikova, Irina ; Segura, Joan ; Shao, Chenghua ; Voigt, Maria ; Westbrook, John D. ; et al ( November 2019 , Protein Science)

   Analyses of publicly available structural data reveal interesting insights into the impact of the three‐dimensional (3D) structures of protein targets important for discovery of new drugs (e.g., G‐protein‐coupled receptors, voltage‐gated ion channels, ligand‐gated ion channels, transporters, and E3 ubiquitin ligases). The Protein Data Bank (PDB) archive currently holds > 155,000 atomic‐level 3D structures of biomolecules experimentally determined using crystallography, nuclear magnetic resonance spectroscopy, and electron microscopy. The PDB was established in 1971 as the first open‐access, digital‐data resource in biology, and is now managed by the Worldwide PDB partnership (wwPDB;wwPDB.org). US PDB operations are the responsibility of the Research Collaboratory for Structural Bioinformatics PDB (RCSB PDB). The RCSB PDB serves millions ofRCSB.orgusers worldwide by delivering PDB data integrated with ∼40 external biodata resources, providing rich structural views of fundamental biology, biomedicine, and energy sciences. Recently published work showed that the PDB archival holdings facilitated discovery of ∼90% of the 210 new drugs approved by the US Food and Drug Administration 2010–2016. We review user‐driven development of RCSB PDB services, examine growth of the PDB archive in terms of size and complexity, and present examples and opportunities for structure‐guided drug discovery for challenging targets (e.g., integral membrane proteins).

    

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4. RCSB Protein Data Bank tools for 3D structure-guided cancer research: human papillomavirus (HPV) case study

   https://doi.org/10.1038/s41388-020-01461-2  

   Goodsell, David S. ; Burley, Stephen K. ( September 2020 , Oncogene)

   Atomic-level three-dimensional (3D) structure data for biological macromolecules often prove critical to dissecting and understanding the precise mechanisms of action of cancer-related proteins and their diverse roles in oncogenic transformation, proliferation, and metastasis. They are also used extensively to identify potentially druggable targets and facilitate discovery and development of both small-molecule and biologic drugs that are today benefiting individuals diagnosed with cancer around the world. 3D structures of biomolecules (including proteins, DNA, RNA, and their complexes with one another, drugs, and other small molecules) are freely distributed by the open-access Protein Data Bank (PDB). This global data repository is used by millions of scientists and educators working in the areas of drug discovery, vaccine design, and biomedical and biotechnology research. The US Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) provides an integrated portal to the PDB archive that streamlines access for millions of worldwide PDB data consumers worldwide. Herein, we review online resources made available free of charge by the RCSB PDB to basic and applied researchers, healthcare providers, educators and their students, patients and their families, and the curious public. We exemplify the value of understanding cancer-related proteins in 3D with a case study focused on human papillomavirus.

    

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5. Systematic analysis of the interactions driving small molecule–RNA recognition

   https://doi.org/10.1039/D0MD00167H  

   Padroni, G. ; Patwardhan, N. N. ; Schapira, M. ; Hargrove, A. E. ( January 2020 , RSC Medicinal Chemistry)

   RNA molecules are becoming an important target class in drug discovery. However, the principles for designing RNA-binding small molecules are yet to be fully uncovered. In this study, we examined the Protein Data Bank (PDB) to highlight privileged interactions underlying small molecule–RNA recognition. By comparing this analysis with previously determined small molecule–protein interactions, we find that RNA recognition is driven mostly by stacking and hydrogen bonding interactions, while protein recognition is instead driven by hydrophobic effects. Furthermore, we analyze patterns of interactions to highlight potential strategies to tune RNA recognition, such as stacking and cation–π interactions that favor purine and guanine recognition, and note an unexpected paucity of backbone interactions, even for cationic ligands. Collectively, this work provides further understanding of RNA–small molecule interactions that may inform the design of small molecules targeting RNA. 

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