Diverse Family Of Proteins Research Articles

ABCG Transporters in the Adaptation of Rice to Salt Stresses

The ATP-binding cassette (ABC) proteins are a diverse family of transmembrane transporter proteins widely identified in various organisms. The ABCG transporters belong to the G subfamily of the ABC transporter family. Rarely research on ABCG transporters involved in salt tolerance of rice was found. In this study, the evolutionary relationships, conserved motifs, intra- and inter-species homologous genes, and cis-acting elements of ABCG subfamily members were analyzed, and the expression changes of these genes under salt stress at 0 h, 3 h, and 24 h were detected. Based on these results, the candidate gene OsABCG7, which is induced by salt stress, was selected for further studies. Yeast experiments confirmed that the OsABCG7 gene might be involved in the regulation of salt tolerance. The abcg7 mutant showed a higher degree of leaf wilting and a lower survival rate, exhibiting a salt-sensitive phenotype. Systematic analysis of this family in rice helps design effective functional analysis strategies and provides data support for understanding the role of ABCG transporters under salt stress.

Insights into the structure of NLR family member X1: Paving the way for innovative drug discovery

Nucleotide-binding oligomerization domain, leucine rich repeat containing X1 (NLRX1) is a negative regulator of the nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) pathway, with a significant role in the context of inflammation. Altered expression of NLRX1 is prevalent in inflammatory diseases leading to interest in NLRX1 as a drug target. There is a lack of structural information available for NLRX1 as only the leucine-rich repeat domain of NLRX1 has been crystallised. This lack of structural data limits progress in understanding function and potential druggability of NLRX1. We have modelled full-length NLRX1 by combining experimental, homology modelled and AlphaFold2 structures. The full-length model of NLRX1 was used to explore protein dynamics, mutational tolerance and potential functions. We identified a new RNA binding site in the previously uncharacterized N-terminus, which served as a basis to model protein-RNA complexes. The structure of the adenosine triphosphate (ATP) binding domain revealed a potential catalytic functionality for the protein as a member of the ATPase Associated with Diverse Cellular Activity family of proteins. Finally, we investigated the interactions of NLRX1 with small molecule activators in development, revealing a binding site that has not previously been discussed in literature. The model generated here will help to catalyse efforts towards creating new drug molecules to target NLRX1 and may be used to inform further studies on functionality of NLRX1.

Personalized Medicine Approach to Proteomics and Metabolomics of Cytochrome P450 Enzymes: A Narrative Review.

Cytochrome P450 enzymes (CYPs) represent a diverse family of heme-thiolate proteins involved in the metabolism of a wide range of endogenous compounds and xenobiotics. In recent years, proteomics and metabolomics have been used to obtain a comprehensive insight into the role of CYPs in health and disease aspects. The objective of the present work is to better understand the status of proteomics and metabolomics in CYP research in optimizing therapeutics and patient safety from a personalized medicine approach. The literature used in this narrative review was procured by electronic search of PubMed, Medline, Embase, and Google Scholar databases. The following keywords were used in combination to identify related literature: "proteomics," "metabolomics," "cytochrome P450," "drug metabolism," "disease conditions," "proteome," "liquid chromatography-mass spectrometry," "integration," "metabolites," "pathological conditions." We reviewed studies that utilized proteomics and metabolomics approaches to explore the multifaceted roles of CYPs in identifying disease markers and determining the contribution of CYP enzymes in developing treatment strategies. The applications of various cutting-edge analytical techniques, including liquid chromatography-mass spectrometry, nuclear magnetic resonance, and bioinformatics analyses in CYP proteomics and metabolomics studies, have been highlighted. The identification of CYP enzymes through metabolomics and/or proteomics in various disease conditions provides key information in the diagnostic and therapeutic landscape. Leveraging both proteomics and metabolomics presents a powerful approach for an exhaustive exploration of the multifaceted roles played by CYP enzymes in personalized medicine. Proteomics and metabolomics have enabled researchers to unravel the complex connection between CYP enzymes and metabolic markers associated with specific diseases. As technology and methodologies evolve, an integrated approach promises to further elucidate the role of CYPs in human health and disease, potentially ushering in a new era of personalized medicine.

Revisiting legume lectins: Structural organization and carbohydrate-binding properties

Legume lectins are a diverse family of carbohydrate-binding proteins that share significant similarities in their primary, secondary, and tertiary structures, yet exhibit remarkable variability in their quaternary structures and carbohydrate-binding specificities. The tertiary structure of legume lectins, characterized by a conserved β-sandwich fold, provides the scaffold for the formation of a carbohydrate-recognition domain (CRD) responsible for ligand binding. The structural basis for the binding is similar between members of the family, with key residues interacting with the sugar through hydrogen bonds, hydrophobic interactions, and van der Waals forces. Variability in substructures and residues within the CRD are responsible for the large array of specificities and enable legume lectins to recognize diverse sugar structures, while maintaining a consistent structural fold. Therefore, legume lectins can be classified into several specificity groups based on their preferred ligands, including mannose/glucose-specific, N-acetyl-d-galactosamine/galactose-specific, N-acetyl-d-glucosamine-specific, l-fucose-specific, and α-2,3 sialic acid-specific lectins. In this context, this review examined the structural aspects and carbohydrate-binding properties of representative legume lectins and their specific ligands in detail. Understanding the structure/binding relationships of lectins continues to provide valuable insights into their biological roles, while also assisting in the potential applications of these proteins in glycobiology, diagnostics, and therapeutics.

Rapid protein evolution by few-shot learning with a protein language model.

Directed evolution of proteins is critical for applications in basic biological research, therapeutics, diagnostics, and sustainability. However, directed evolution methods are labor intensive, cannot efficiently optimize over multiple protein properties, and are often trapped by local maxima. In silico- directed evolution methods incorporating protein language models (PLMs) have the potential to accelerate this engineering process, but current approaches fail to generalize across diverse protein families. We introduce EVOLVEpro, a few-shot active learning framework to rapidly improve protein activity using a combination of PLMs and protein activity predictors, achieving improved activity with as few as four rounds of evolution. EVOLVEpro substantially enhances the efficiency and effectiveness of in silico protein evolution, surpassing current state-of-the-art methods and yielding proteins with up to 100-fold improvement of desired properties. We showcase EVOLVEpro for five proteins across three applications: T7 RNA polymerase for RNA production, a miniature CRISPR nuclease, a prime editor, and an integrase for genome editing, and a monoclonal antibody for epitope binding. These results demonstrate the advantages of few-shot active learning with small amounts of experimental data over zero-shot predictions. EVOLVEpro paves the way for broader applications of AI-guided protein engineering in biology and medicine.

RhoMax: Computational Prediction of Rhodopsin Absorption Maxima Using Geometric Deep Learning.

Microbial rhodopsins (MRs) are a diverse and abundant family of photoactive membrane proteins that serve as model systems for biophysical techniques. Optogenetics utilizes genetic engineering to insert specialized proteins into specific neurons or brain regions, allowing for manipulation of their activity through light and enabling the mapping and control of specific brain areas in living organisms. The obstacle of optogenetics lies in the fact that light has a limited ability to penetrate biological tissues, particularly blue light in the visible spectrum. Despite this challenge, most optogenetic systems rely on blue light due to the scarcity of red-shifted opsins. Finding additional red-shifted rhodopsins would represent a major breakthrough in overcoming the challenge of limited light penetration in optogenetics. However, determining the wavelength absorption maxima for rhodopsins based on their protein sequence is a significant hurdle. Current experimental methods are time-consuming, while computational methods lack accuracy. The paper introduces a new computational approach called RhoMax that utilizes structure-based geometric deep learning to predict the absorption wavelength of rhodopsins solely based on their sequences. The method takes advantage of AlphaFold2 for accurate modeling of rhodopsin structures. Once trained on a balanced train set, RhoMax rapidly and precisely predicted the maximum absorption wavelength of more than half of the sequences in our test set with an accuracy of 0.03 eV. By leveraging computational methods for absorption maxima determination, we can drastically reduce the time needed for designing new red-shifted microbial rhodopsins, thereby facilitating advances in the field of optogenetics.

Bioinformatic analysis of type III CRISPR systems reveals key properties and new effector families.

Recognition of RNA from invading mobile genetic elements (MGE) prompts type III CRISPR systems to activate an HD nuclease domain and/or a nucleotide cyclase domain in the Cas10 subunit, eliciting an immune response. The cyclase domain can generate a range of nucleotide second messengers, which in turn activate a diverse family of ancillary effector proteins. These provide immunity by non-specific degradation of host and MGE nucleic acids or proteins, perturbation of membrane potentials, transcriptional responses, or the arrest of translation. The wide range of nucleotide activators and downstream effectors generates a complex picture that is gradually being resolved. Here, we carry out a global bioinformatic analysis of type III CRISPR loci in prokaryotic genomes, defining the relationships of Cas10 proteins and their ancillary effectors. Our study reveals that cyclic tetra-adenylate is by far the most common signalling molecule used and that many loci have multiple effectors. These typically share the same activator and may work synergistically to combat MGE. We propose four new candidate effector protein families and confirm experimentally that the Csm6-2 protein, a highly diverged, fused Csm6 effector, is a ribonuclease activated by cyclic hexa-adenylate.

Identification and Characterization of a Bacterial Periplasmic Solute Binding Protein That Binds l-Amino Acid Amides.

Periplasmic solute-binding proteins (SBPs) are key ligand recognition components of bacterial ATP-binding cassette (ABC) transporters that allow bacteria to import nutrients and metabolic precursors from the environment. Periplasmic SBPs comprise a large and diverse family of proteins, of which only a small number have been empirically characterized. In this work, we identify a set of 610 unique uncharacterized proteins within the SBP_bac_5 family that are found in conserved operons comprising genes encoding (i) ABC transport systems and (ii) putative amidases from the FmdA_AmdA family. From these uncharacterized SBP_bac_5 proteins, we characterize a representative periplasmic SBP from Mesorhizobium sp. A09 (MeAmi_SBP) and show that MeAmi_SBP binds l-amino acid amides but not the corresponding l-amino acids. An X-ray crystal structure of MeAmi_SBP bound to l-serinamide highlights the residues that impart distinct specificity for l-amino acid amides and reveals a structural Ca2+ binding site within one of the lobes of the protein. We show that the residues involved in ligand and Ca2+ binding are conserved among the 610 SBPs from experimentally uncharacterized FmdA_AmdA amidase-associated ABC transporter systems, suggesting these homologous systems are also likely to be involved in the sensing, uptake, and metabolism of l-amino acid amides across many Gram-negative nitrogen-fixing soil bacteria. We propose that MeAmi_SBP is involved in the uptake of such solutes to supplement pathways such as the citric acid cycle and the glutamine synthetase-glutamate synthase pathway. This work expands our currently limited understanding of microbial interactions with l-amino acid amides and bacterial nitrogen utilization.

CUREs for high-level Galectin-3 expression

Galectins are a large and diverse protein family defined by the presence of a carbohydrate recognition domain (CRD) that binds β-galactosides. They play important roles in early development, tissue regeneration, immune homeostasis, pathogen recognition, and cancer. In many cases, studies that examine galectin biology and the effect of manipulating galectins are aided by, or require the ability to express and purify, specific members of the galectin family. In many cases, E. coli is employed as a heterologous expression system, and galectin expression is induced with isopropyl β-galactoside (IPTG). Here, we show that galectin-3 recognizes IPTG with micromolar affinity and that as IPTG induces expression, newly synthesized galectin can bind and sequester cytosolic IPTG, potentially repressing further expression. To circumvent this putative inhibitory feedback loop, we utilized an autoinduction protocol that lacks IPTG, leading to significantly increased yields of galectin-3. Much of this work was done within the context of a course-based undergraduate research experience, indicating the ease and reproducibility of the resulting expression and purification protocols.

Gaining Insights into Key Structural Hotspots within the Allosteric Binding Pockets of Protein Kinases.

Protein kinases are essential regulators of cell function and represent one of the largest and most diverse protein families. They are particularly influential in signal transduction and coordinating complex processes like the cell cycle. Out of the 518 human protein kinases identified, 478 are part of a single superfamily sharing catalytic domains that are related in sequence. The dysregulation of protein kinases due to certain mutations has been associated with various diseases, including cancer. Although most of the protein kinase inhibitors identified as type I or type II primarily target the ATP-binding pockets of kinases, the structural and sequential resemblances among these pockets pose a significant challenge for selective inhibition. Therefore, targeting allosteric pockets that are beside highly conserved ATP pockets has emerged as a promising strategy to prevail current limitations, such as poor selectivity and drug resistance. In this article, we compared the binding pockets of various protein kinases for which allosteric (type III) inhibitors have already been developed. Additionally, understanding the structure and shape of existing ligands could aid in identifying key interaction sites within the allosteric pockets of kinases. This comprehensive review aims to facilitate the design of more effective and selective allosteric inhibitors.

A novel mouse model carrying a gene trap insertion into the Hmgxb4 gene locus to examine Hmgxb4 expression invivo.

HMG (high mobility group) proteins are a diverse family of nonhistone chromosomal proteins that interact with DNA and a wide range of transcriptional regulators to regulate the structural architecture of DNA. HMGXB4 (also known as HMG2L1) is an HMG protein family member that contains a single HMG box domain. Our previous studies have demonstrated that HMGXB4 suppresses smooth muscle differentiation and exacerbates endotoxemia by promoting a systemic inflammatory response in mice. However, the expression of Hmgxb4 invivo has not fully examined. Herein, we generated a mouse model that harbors a gene trap in the form of a lacZ gene insertion into the Hmgxb4 gene. This mouse enables the visualization of endogenous HMGXB4 expression in different tissues via staining for the β-galactosidase activity of LacZ which is under the control of the endogenous Hmgxb4 gene promoter. We found that HMGXB4 is widely expressed in mouse tissues and is a nuclear protein. Furthermore, the Hmgxb4 gene trap mice exhibit normal cardiac function and blood pressure. Measurement of β-galactosidase activity in the Hmgxb4 gene trap mice demonstrated that the arterial injury significantly induces Hmgxb4 expression. In summary, the Hmgxb4 gene trap reporter mouse described here provides a valuable tool to examine the expression level of endogenous Hmgxb4 in both physiological and pathological settings invivo.

Innate programmable DNA binding by CRISPR-Cas12m effectors enable efficient base editing.

Cas9 and Cas12 nucleases of class 2 CRISPR-Cas systems provide immunity in prokaryotes through RNA-guided cleavage of foreign DNA. Here we characterize a set of compact CRISPR-Cas12m (subtype V-M) effector proteins and show that they provide protection against bacteriophages and plasmids through the targeted DNA binding rather than DNA cleavage. Biochemical assays suggest that Cas12m effectors can act as roadblocks inhibiting DNA transcription and/or replication, thereby triggering interference against invaders. Cryo-EM structure of Gordonia otitidis (Go) Cas12m ternary complex provided here reveals the structural mechanism of DNA binding ensuring interference. Harnessing GoCas12m innate ability to bind DNA target we fused it with adenine deaminase TadA-8e and showed an efficient A-to-G editing in Escherichia coli and human cells. Overall, this study expands our understanding of the functionally diverse Cas12 protein family, revealing DNA-binding dependent interference mechanism of Cas12m effectors that could be harnessed for engineering of compact base-editing tools.

A method for the systematic selection of enzyme panel candidates by solving the maximum diversity problem

Enzymes are being increasingly exploited for their potential as industrial biocatalysts. Establishing a portfolio of useful biocatalysts from large and diverse protein family is challenging and a systematic method for candidate selection promises to aid in this task. Moreover, accurate enzyme functional annotation can only be confidently guaranteed through experimental characterisation in the laboratory. The selection of catalytically diverse enzyme panels for experimental characterisation is also an important step for shedding light on the currently unannotated proteins in enzyme families. Current selection methods often lack efficiency and scalability, and are usually non-systematic. We present a novel algorithm for the automatic selection of subsets from enzyme families. A tabu search algorithm solving the maximum diversity problem for sequence identity was designed and implemented, and applied to three diverse enzyme families. We show that this approach automatically selects panels of enzymes that contain high richness and relative abundance of the known catalytic functions, and outperforms other methods such as k-medoids.

Thaumatin-like protein family genes VfTLP4-3 and VfTLP5 are critical for faba bean's response to drought stress at the seedling stage

Thaumatin-like proteins (TLPs) are a diverse family of pathogenesis-related proteins (PR-5) found in various plant species. Faba bean is an economically important crop known for its nutritional value and resilience to harsh environmental conditions, including drought. In this study, we conducted a comprehensive analysis of the gene structure, phylogenetics, and expression patterns of TLP genes in faba bean, with a specific focus on their response to drought stress. A total of 10 TLP genes were identified and characterized from the faba bean transcriptome, which could be classified into four distinct groups based on their evolutionary relationships. Conserved cysteine residues and REDDD motifs, which are characteristic features of TLPs, were found in most of the identified VfTLP members, and these proteins were likely to reside in the cytoplasm. Two genes, VfTLP4-3 and VfTLP5, exhibited significant upregulation under drought conditions. Additionally, ectopically expressing VfTLP4-3 and VfTLP5 in tobacco leaves resulted in enhanced drought tolerance and increased peroxidase (POD) activity. Moreover, the protein VfTLP4-3 was hypothesized to interact with glycoside hydrolase family 18 (GH18), endochitinase, dehydrin, Barwin, and aldolase, all of which are implicated in chitin metabolism. Conversely, VfTLP5 was anticipated to associate with peptidyl-prolyl cis-trans isomerase-like 3, a molecule linked to the synthesis of proline. These findings suggest that these genes may play crucial roles in mediating the drought response in faba bean through the regulation of these metabolic pathways, and serve as a foundation for future genetic improvement strategies targeting enhanced drought resilience in this economically important crop.

ProtWave-VAE: Integrating Autoregressive Sampling with Latent-Based Inference for Data-Driven Protein Design.

Deep generative models (DGMs) have shown great success in the understanding and data-driven design of proteins. Variational autoencoders (VAEs) are a popular DGM approach that can learn the correlated patterns of amino acid mutations within a multiple sequence alignment (MSA) of protein sequences and distill this information into a low-dimensional latent space to expose phylogenetic and functional relationships and guide generative protein design. Autoregressive (AR) models are another popular DGM approach that typically lacks a low-dimensional latent embedding but does not require training sequences to be aligned into an MSA and enable the design of variable length proteins. In this work, we propose ProtWave-VAE as a novel and lightweight DGM, employing an information maximizing VAE with a dilated convolution encoder and an autoregressive WaveNet decoder. This architecture blends the strengths of the VAE and AR paradigms in enabling training over unaligned sequence data and the conditional generative design of variable length sequences from an interpretable, low-dimensional learned latent space. We evaluated the model's ability to infer patterns and design rules within alignment-free homologous protein family sequences and to design novel synthetic proteins in four diverse protein families. We show that our model can infer meaningful functional and phylogenetic embeddings within latent spaces and make highly accurate predictions within semisupervised downstream fitness prediction tasks. In an application to the C-terminal SH3 domain in the Sho1 transmembrane osmosensing receptor in baker's yeast, we subject ProtWave-VAE-designed sequences to experimental gene synthesis and select-seq assays for the osmosensing function to show that the model enables synthetic protein design, conditional C-terminus diversification, and engineering of the osmosensing function into SH3 paralogues.

How AlphaFold2 shaped the structural coverage of the human transmembrane proteome

AlphaFold2 (AF2) provides a 3D structure for every known or predicted protein, opening up new prospects for virtually every field in structural biology. However, working with transmembrane protein molecules pose a notorious challenge for scientists, resulting in a limited number of experimentally determined structures. Consequently, algorithms trained on this finite training set also face difficulties. To address this issue, we recently launched the TmAlphaFold database, where predicted AlphaFold2 structures are embedded into the membrane plane and a quality assessment (plausibility of the membrane-embedded structure) is provided for each prediction using geometrical evaluation. In this paper, we analyze how AF2 has improved the structural coverage of membrane proteins compared to earlier years when only experimental structures were available, and high-throughput structure prediction was greatly limited. We also evaluate how AF2 can be used to search for (distant) homologs in highly diverse protein families. By combining quality assessment and homology search, we can pinpoint protein families where AF2 accuracy is still limited, and experimental structure determination would be desirable.

ABC transporter subfamily B1 as a susceptibility determinant of Bombyx mori larvae to Cry1Ba, Cry1Ia and Cry9Da toxins

ATP binding cassette (ABC) transporters are a diverse family of transmembrane proteins. Specific subfamily members expressed in the lepidopteran midgut can act as susceptibility determinants for several insecticidal Bt Cry proteins. However, the susceptibility determinants to many Cry toxins still remain unclear. Therefore, we knocked out a series of ABC transporters that are highly expressed in the midgut of Bombyx mori larvae by transcription activator-like effector nuclease (TALEN)-mediated gene editing, and the lineages that became resistant to Cry toxins were searched by toxin overlay bioassay. As a result, the B. mori ABC transporter subfamily B1 (BmABCB1) knockout lineage showed 19.17-fold resistance to Cry1Ba, 876.2-fold resistance to Cry1Ia, and 29.1-fold resistance to Cry9Da, suggesting that BmABCB1 is the determinant of susceptibility to these toxins. BmABCC2 and BmABCC3 have been shown to be susceptibility determinants based on their function as receptors. Therefore, we next heterologously expressed these ABC transporters in HEK293T cells and performed a cell swelling assay to examine whether these molecules could exert receptor functions. As a result, BmABCB1-expressing cells showed swelling response to Cry1Ia and Cry9Da, and cells expressing PxABCB1, which is the Plutella xylostella ortholog of BmABCB1, showed swelling for Cry1Ba, suggesting that ABCB1 is a susceptibility determinant by functioning as a receptor to these toxins. Furthermore, in order to clarify how high binding affinity is based on receptor function, we performed surface plasmon resonance analysis and found that each KD of Cry1Ba, Cry1Ia, and Cry9Da to BmABCB1 were 7.69 × 10−8 M, 2.19 × 10−9 M, and 4.17 × 10−6 M respectively.

A marine cryptochrome with an inverse photo-oligomerization mechanism

Cryptochromes (CRYs) are a structurally conserved but functionally diverse family of proteins that can confer unique sensory properties to organisms. In the marine bristle worm Platynereis dumerilii, its light receptive cryptochrome L-CRY (PdLCry) allows the animal to discriminate between sunlight and moonlight, an important requirement for synchronizing its lunar cycle-dependent mass spawning. Using cryo-electron microscopy, we show that in the dark, PdLCry adopts a dimer arrangement observed neither in plant nor insect CRYs. Intense illumination disassembles the dimer into monomers. Structural and functional data suggest a mechanistic coupling between the light-sensing flavin adenine dinucleotide chromophore, the dimer interface, and the C-terminal tail helix, with a likely involvement of the phosphate binding loop. Taken together, our work establishes PdLCry as a CRY protein with inverse photo-oligomerization with respect to plant CRYs, and provides molecular insights into how this protein might help discriminating the different light intensities associated with sunlight and moonlight.

Mutation of the PEBP-like domain of the mitoribosomal MrpL35/mL38 protein results in production of nascent chains with impaired capacity to assemble into OXPHOS complexes.

Located in the central protuberance region of the mitoribosome and mitospecific mL38 proteins display homology to PEBP (Phosphatidylethanolamine Binding Protein) proteins, a diverse family of proteins reported to bind anionic substrates/ligands and implicated in cellular signaling and differentiation pathways. In this study, we have performed a mutational analysis of the yeast mitoribosomal protein MrpL35/mL38 and demonstrate that mutation of the PEBP-invariant ligand binding residues Asp(D)232 and Arg(R)288 impacted MrpL35/mL38's ability to support OXPHOS-based growth of the cell. Furthermore, our data indicate these residues exist in a functionally important charged microenvironment, which also includes Asp(D)167 of MrpL35/mL38 and Arg(R)127 of the neighboring Mrp7/bL27m protein. We report that mutation of each of these charged residues resulted in a strong reduction in OXPHOS complex levels that was not attributed to a corresponding inhibition of the mitochondrial translation process. Rather, our findings indicate that a disconnect exists in these mutants between the processes of mitochondrial protein translation and the events required to ensure the competency and/or availability of the newly synthesized proteins to assemble into OXPHOS enzymes. Based on our findings, we postulate that the PEBP-homology domain of MrpL35/mL38, together with its partner Mrp7/bL27m, form a key regulatory region of the mitoribosome.

Signal-noise metrics for RNA binding protein identification reveal broad spectrum protein-RNA interaction frequencies and dynamics

Recent efforts towards the comprehensive identification of RNA-bound proteomes have revealed a large, surprisingly diverse family of candidate RNA-binding proteins (RBPs). Quantitative metrics for characterization and validation of protein-RNA interactions and their dynamic interactions have, however, proven analytically challenging and prone to error. Here we report a method termed LEAP-RBP (Liquid-Emulsion-Assisted-Purification of RNA-Bound Protein) for the selective, quantitative recovery of UV-crosslinked RNA-protein complexes. By virtue of its high specificity and yield, LEAP-RBP distinguishes RNA-bound and RNA-free protein levels and reveals common sources of experimental noise in RNA-centric RBP enrichment methods. We introduce strategies for accurate RBP identification and signal-based metrics for quantifying protein-RNA complex enrichment, relative RNA occupancy, and method specificity. In this work, the utility of our approach is validated by comprehensive identification of RBPs whose association with mRNA is modulated in response to global mRNA translation state changes and through in-depth benchmark comparisons with current methodologies.