Structural insights into isoform-specific RAS-PI3Kα interactions and the role of RAS in PI3Kα activation.

Mutations in RAS and PI3Kα are major drivers of human cancer. Their interaction plays a crucial role in activating PI3Kα and amplifying the PI3K-AKT-mTOR pathway. Disrupting RAS-PI3Kα interaction enhances survival in lung and skin cancer models and reduces tumor growth and angiogenesis, although the structural details of this interaction remain unclear.

The molecular reach of antibodies crucially underpins their viral neutralisation capacity.

Key functions of antibodies, such as viral neutralisation, depend on high-affinity binding. However, viral neutralisation poorly correlates with antigen affinity for reasons that have been unclear. Here, we use a new mechanistic model of bivalent binding to study  >45 patient-isolated IgG1 antibodies interacting with SARS-CoV-2 RBD surfaces.

Discovery of BBO-8520, a first-in-class direct and covalent dual inhibitor of GTP-bound (ON) and GDP-bound (OFF) KRASG12C.

Approved inhibitors of KRASG12C prevent oncogenic activation by sequestering the inactive, GDP-bound (OFF) form rather than directly binding and inhibiting the active, GTP-bound (ON) form. This approach provides no direct target coverage of the active protein. Expectedly, adaptive resistance to KRASG12C (OFF)-only inhibitors is observed in association with increased expression and activity of KRASG12C(ON).

Comprehensive structure-function analysis reveals gain- and loss-of-function mechanisms impacting oncogenic KRAS activity.

To dissect variant-function relationships in the KRAS oncoprotein, we performed deep mutational scanning (DMS) screens for both wild-type and KRAS mutant alleles. We defined the spectrum of oncogenic potential for nearly all possible variants, identifying several novel transforming alleles and elucidating a model to describe the frequency of mutations in human cancer as a function of transforming potential, mutational probability, and tissue-specific mutational signatures. Biochemical and structural analyses of variants identified in a KRAS second-site suppressor DMS screen revealed that attenuation of oncogenic KRAS can be mediated by protein instability and conformational rigidity, resulting in reduced binding affinity to effector proteins, such as RAF and PI3-kinases, or reduced SOS-mediated nucleotide exchange activity.

The prominent pervasive oncogenic role and tissue specific permissiveness of RAS gene mutations.

In cancer research, RAS biology has been focused on only a handful of tumor types. While RAS genes have long been suspected as common contributors to a wide spectrum of cancer types, robust evidence is required to firmly establish their critical oncogenic significance. We present a data mining study using DepMap genome-wide CRISPR screening data, which provide substantial evidence to support the prominent pervasive oncogenic role and tissue-specific permissiveness of RAS gene mutations.

Generating Protein Structures for Pathway Discovery Using Deep Learning.

Resolving the intricate details of biological phenomena at the molecular level is fundamentally limited by both length- and time scales that can be probed experimentally. Molecular dynamics (MD) simulations at various scales are powerful tools frequently employed to offer valuable biological insights beyond experimental resolution. However, while it is relatively simple to observe long-lived, stable configurations of, for example, proteins, at the required spatial resolution, simulating the more interesting rare transitions between such states often takes orders of magnitude longer than what is feasible even on the largest supercomputers available today.

ABodyBuilder3: improved and scalable antibody structure predictions.

Summary: In this article, we introduce ABodyBuilder3, an improved and scalable antibody structure prediction model based on ABodyBuilder2. We achieve a new state-of-the-art accuracy in the modelling of CDR loops by leveraging language model embeddings, and show how predicted structures can be further improved through careful relaxation strategies. Finally, we incorporate a predicted Local Distance Difference Test into the model output to allow for a more accurate estimation of uncertainties.

Determining KRAS4B-Targeting Compound Specificity by Top-Down Mass Spectrometry.

We present a novel method to determine engagement and specificity of KRAS4B-targeting compounds in vitro. By employing top-down mass spectrometry (MS), which analyzes intact and modified protein molecules (proteoforms), we can directly visualize and confidently characterize each KRAS4B species within compound-treated samples. Moreover, by employing targeted MS2 fragmentation, we can precisely localize each compound molecule to a specific residue on a given KRAS4B proteoform.

Natural Product Graveoline Modulates Kirsten Rat Sarcoma Viral Oncogene Homologue (KRAS) Membrane Association: Insights from Advanced Spectroscopic Studies.

The KRAS gene plays a pivotal role in numerous cancers by encoding a GTPase that upon association with the plasma membrane activates the MAPK pathway, promoting cellular proliferation. In our study, we investigated small molecules that disrupt KRAS's membrane interaction, hypothesizing that such disruption could in turn inhibit mutant RAS signaling. Native mass spectrometry screening of KRAS-FMe identified compounds with a preference for interacting with the hypervariable region (HVR), and surface plasmon resonance (SPR) further refined our selection to graveoline as a compound exhibiting preferential HVR binding.

Progress in Targeting KRAS Directly.

RAS research has entered the world of translational and clinical science. Progress has been based on our appreciation of the role of RAS mutations in different types of cancer and the effects of these mutations on the biochemical, structural, and biophysical properties of the RAS proteins themselves, particularly KRAS, on which most attention has been focused. This knowledge base, while still growing, has enabled creative chemical approaches to targeting KRAS directly.

A Top-Down Proteomic Assay to Evaluate KRAS4B-Compound Engagement.

Development of new targeted inhibitors for oncogenic KRAS mutants may benefit from insight into how a given mutation influences the accessibility of protein residues and how compounds interact with mutant or wild-type KRAS proteins. Targeted proteomic analysis, a key validation step in the KRAS inhibitor development process, typically involves both intact mass- and peptide-based methods to confirm compound localization or quantify binding. However, these methods may not always provide a clear picture of the compound binding affinity for KRAS, how specific the compound is to the target KRAS residue, and how experimental conditions may impact these factors.

Structural dynamics of RAF1-HSP90-CDC37 and HSP90 complexes reveal asymmetric client interactions and key structural elements.

RAF kinases are integral to the RAS-MAPK signaling pathway, and proper RAF1 folding relies on its interaction with the chaperone HSP90 and the cochaperone CDC37. Understanding the intricate molecular interactions governing RAF1 folding is crucial for comprehending this process. Here, we present a cryo-EM structure of the closed-state RAF1-HSP90-CDC37 complex, where the C-lobe of the RAF1 kinase domain binds to one side of the HSP90 dimer, and an unfolded N-lobe segment of the RAF1 kinase domain threads through the center of the HSP90 dimer.

Membrane lipids drive formation of KRAS4b-RAF1 RBDCRD nanoclusters on the membrane.

The oncogene RAS, extensively studied for decades, presents persistent gaps in understanding, hindering the development of effective therapeutic strategies due to a lack of precise details on how RAS initiates MAPK signaling with RAF effector proteins at the plasma membrane. Recent advances in X-ray crystallography, cryo-EM, and super-resolution fluorescence microscopy offer structural and spatial insights, yet the molecular mechanisms involving protein-protein and protein-lipid interactions in RAS-mediated signaling require further characterization. This study utilizes single-molecule experimental techniques, nuclear magnetic resonance spectroscopy, and the computational Machine-Learned Modeling Infrastructure (MuMMI) to examine KRAS4b and RAF1 on a biologically relevant lipid bilayer.

Comparative analysis of KRAS4a and KRAS4b splice variants reveals distinctive structural and functional properties.

, the most frequently mutated oncogene in human cancer, produces two isoforms, KRAS4a and KRAS4b, through alternative splicing. These isoforms differ in exon 4, which encodes the final 15 residues of the G-domain and hypervariable regions (HVRs), vital for trafficking and membrane localization. While KRAS4b has been extensively studied, KRAS4a has been largely overlooked.

Synonymous Mutations Can Alter Protein Dimerization Through Localized Interface Misfolding Involving Self-entanglements.

Synonymous mutations in messenger RNAs (mRNAs) can reduce protein-protein binding substantially without changing the protein's amino acid sequence. Here, we use coarse-grain simulations of protein synthesis, post-translational dynamics, and dimerization to understand how synonymous mutations can influence the dimerization of two E. coli homodimers, oligoribonuclease and ribonuclease T.

Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2.

The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction between RBD and ACE2 at the molecular level is critical for the prevention of COVID-19, as more variants of concern, such as Omicron, appear. Recently, atomic force microscopy has been applied to characterize the free energy landscape of the RBD-ACE2 complex, including estimation of the distance between the transition state and the bound state, xu.

How soluble misfolded proteins bypass chaperones at the molecular level.

Subpopulations of soluble, misfolded proteins can bypass chaperones within cells. The extent of this phenomenon and how it happens at the molecular level are unknown. Through a meta-analysis of the experimental literature we find that in all quantitative protein refolding studies there is always a subpopulation of soluble but misfolded protein that does not fold in the presence of one or more chaperones, and can take days or longer to do so.

Reduced dynamic complexity allows structure elucidation of an excited state of KRAS.

Localized dynamics of RAS, including regions distal to the nucleotide-binding site, is of high interest for elucidating the mechanisms by which RAS proteins interact with effectors and regulators and for designing inhibitors. Among several oncogenic mutants, methyl relaxation dispersion experiments reveal highly synchronized conformational dynamics in the active (GMPPNP-bound) KRAS, which suggests an exchange between two conformational states in solution. Methyl and P NMR spectra of active KRAS in solution confirm a two-state ensemble interconverting on the millisecond timescale, with a major P atom peak corresponding to the dominant State 1 conformation and a secondary peak indicating an intermediate state different from the known State 2 conformation recognized by RAS effectors.

Is Posttranslational Folding More Efficient Than Refolding from a Denatured State: A Computational Study.

The folding of proteins into their native conformation is a complex process that has been extensively studied over the past half-century. The ribosome, the molecular machine responsible for protein synthesis, is known to interact with nascent proteins, adding further complexity to the protein folding landscape. Consequently, it is unclear whether the folding pathways of proteins are conserved on and off the ribosome.

The confluence of machine learning and multiscale simulations.

Multiscale modeling has a long history of use in structural biology, as computational biologists strive to overcome the time- and length-scale limits of atomistic molecular dynamics. Contemporary machine learning techniques, such as deep learning, have promoted advances in virtually every field of science and engineering and are revitalizing the traditional notions of multiscale modeling. Deep learning has found success in various approaches for distilling information from fine-scale models, such as building surrogate models and guiding the development of coarse-grained potentials.

Computationally profiling peptide:MHC recognition by T-cell receptors and T-cell receptor-mimetic antibodies.

T-cell receptor-mimetic antibodies (TCRms) targeting disease-associated peptides presented by Major Histocompatibility Complexes (pMHCs) are set to become a major new drug modality. However, we lack a general understanding of how TCRms engage pMHC targets, which is crucial for predicting their specificity and safety. Several new structures of TCRm:pMHC complexes have become available in the past year, providing sufficient initial data for a holistic analysis of TCRms as a class of pMHC binding agents.

Destabilizing NF1 variants act in a dominant negative manner through neurofibromin dimerization.

The majority of pathogenic mutations in the neurofibromatosis type I () gene reduce total neurofibromin protein expression through premature truncation or microdeletion, but it is less well understood how loss-of-function missense variants drive NF1 disease. We have found that patient variants in codons 844 to 848, which correlate with a severe phenotype, cause protein instability and exert an additional dominant-negative action whereby wild-type neurofibromin also becomes destabilized through protein dimerization. We have used our neurofibromin cryogenic electron microscopy structure to predict and validate other patient variants that act through a similar mechanism.