Biology subjects

Lightstone, F. C.

Publications and source records attributed to Lightstone, F. C..

5 recordsLinked to original sources

bioRxiv2025

An In Vitro BRAF Activation Assay Elucidates Molecular Mechanisms Driving the Disassembly of the Autoinhibited BRAF State

The RAF kinases (ARAF, BRAF and CRAF) are essential components of the RAS-ERK signaling pathway, which controls vital cellular processes and is frequently dysregulated in human disease. Notably, mutations that alter BRAF function are prominent drivers of human cancer and certain RASopathy disorders, making BRAF an important target for therapeutic intervention. Despite extensive research, several aspects of BRAF regulation remain unclear. In this study, we developed an in vitro BRAF activation assay using purified autoinhibited BRAF:14-3-32:MEK complexes. Our results show that fully processed, active-state KRAS alone can promote dimer-dependent BRAF activation. Moreover, we found that phosphatidylserine (PS)-containing liposomes synergized with KRAS to promote BRAF activation, achieving activity levels comparable to those observed with BRAF proteins that constitutively dimerize. In contrast, the SMP phosphatase complex had only a minimal effect on BRAF catalytic activity in this system but mediated the dephosphorylation of the negative regulatory pS365 14-3-3 binding site in a manner that was accelerated by the presence of KRAS alone or KRAS and 30% PS liposomes. Finally, we show that inhibitors blocking the BRAF RBD:KRAS interaction were able to suppress the in vitro activation of BRAF, underscoring the critical role of RAS binding in initiating the disassembly of the BRAF autoinhibited state. Thus, this assay provides valuable insights into the steps required for BRAF activation and can serve as an effective screening tool for identifying compounds that may inhibit this process and have therapeutic potential. Significance StatementBRAF is a central intermediate in RAS pathway signaling, and its activity is often elevated in human cancers and RASopathy disorders. Due to the complexity of BRAF activation, identifying compounds that sustainably inhibit BRAF function has proven difficult, emphasizing the need for a more comprehensive understanding of BRAF regulation. Here, we have developed an in vitro BRAF activation assay that elucidates key steps in this process. Our findings demonstrate that RAS binding not only recruits BRAF to the plasma membrane but initiates the disassembly of the autoinhibited monomer, which in the context of the membrane, facilitates BRAF dimerization and activation. This assay advances our understanding of BRAF regulation and provides a novel platform for drug discovery efforts targeting BRAF.

biochemistry↗

bioRxiv2025

Free energy and flexibility analysis of autoinhibited human BRAF

The RAF serine/threonine protein kinases function as direct effectors of RAS in the intracellular transmission of extracellular growth signals, and they are key targets for drug discovery given the high incidence of oncogenic mutations in RAF and other components of this signaling pathway. In its inactive state, RAF is held in an autoinhibited conformation in the cytosol through a combination of intramolecular interactions and binding to a regulatory 14-3-3 protein dimer. Activation of RAF is initiated by its interaction with membrane-localized, GTP-bound RAS, which induces conformational changes that release RAF from its autoinhibited state. However, the molecular mechanisms governing RAF activation remain incomplete, largely due to the challenges in experimentally capturing intermediate conformational states in this process. To address this gap, we developed a comprehensive all-atom model of BRAF based on existing cryo-EM structures. Using this model, we performed extensive molecular dynamics simulations to evaluate the stability and free energy landscape of autoinhibited BRAF in solution. Our analysis reveals conformational flexibility within the autoinhibited complex, suggesting that this dynamic behavior may play a role in facilitating BRAF activation upon engagement with membrane-bound RAS.

biophysics↗

bioRxiv2023

Clustering Protein Binding Pockets and Identifying Potential Drug Interactions: A Novel Ligand-based Featurization Method

Protein-ligand interactions are essential to drug discovery and drug development efforts. Desirable on-target or multi-target interactions are a first step in finding an effective therapeutic; undesirable off-target interactions are a first step in assessing safety. In this work, we introduce a novel ligand-based featurization and mapping of human protein pockets to identify closely related protein targets, and to project novel drugs into a hybrid protein-ligand feature space to identify their likely protein interactions. Using structure-based template matches from PDB, protein pockets are featurized by the ligands which bind to their best co-complex template matches. The simplicity and interpretability of this approach provides a granular characterization of the human proteome at the protein pocket level instead of the traditional protein-level characterization by family, function, or pathway. We demonstrate the power of this featurization method by clustering a subset of the human proteome and evaluating the predicted cluster associations of over 7,000 compounds.

synthetic biology↗

bioRxiv2022

PDBspheres - a method for finding 3D similarities in local regions in proteins

We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions ("spheres") adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. PDBspheres uses the LGA structure alignment algorithm as the main engine for detecting structure similarities between the protein of interest and template spheres from the library, which currently contains more than 2 million spheres. To assess confidence in structural matches an all-atom-based similarity metric takes sidechain placement into account. Here, we describe the PDBspheres method, demonstrate its ability to detect and characterize binding sites in protein structures, show how PDBspheres - a strictly structure-based method - performs on a curated dataset of 2,528 ligand-bound and ligand-free crystal structures, and use PDBspheres to cluster pockets and assess structural similarities among protein binding sites of 4,876 structures in the "refined set" of the PDBbind 2019 dataset.

bioinformatics↗

bioRxiv2020

Comprehensive characterization of protein-protein interaction network perturbations by human disease mutations

Technological and computational advances in genomics and interactomics have made it possible to identify rapidly how disease mutations perturb interaction networks within human cells. In this study, we investigate at large-scale the effects of network perturbations caused by disease mutations within the human three-dimensional (3D), structurally-resolved macromolecular interactome. We show that disease-associated germline mutations are significantly enriched in sequences encoding protein-protein interfaces compared to mutations identified in healthy subjects from the 1000 Genomes and ExAC projects; these interface mutations correspond to protein-protein interaction (PPI)-perturbing alleles including p.Ser127Arg in PCSK9 at the PCSK9-LDLR interface. In addition, somatic missense mutations are significantly enriched in PPI interfaces compared to non-interfaces in 10,861 human exomes across 33 cancer subtypes/types from The Cancer Genome Atlas. Using a binomial statistical model, we computationally identified 470 PPIs harboring a statistically significant excess number of missense mutations at protein-protein interfaces (termed putative oncoPPIs) in pan-cancer analysis. We demonstrate that the oncoPPIs, including histone H4 complex in individual cancer types, are highly correlated with patient survival and drug resistance/sensitivity in human cancer cell lines and patient-derived xenografts. We experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay. We further showed that ALOX5 p.Met146Lys at the ALOX5-MAD1L1 interface and RXRA p.Ser427Phe at the RXRA-PPARG interface promote significant tumor cell growth using cell line-based functional assays, providing a functional proof-of-concept. In summary, if broadly applied, this human 3D interactome network analysis offers a powerful tool for prioritizing alleles with mutations altering PPIs that may contribute to the pathobiology of human diseases, and may offer disease-specific targets for genotype-informed therapeutic discovery.

systems biology↗