Effects of intrinsically disordered regions in gp120 underlying HIV neutralization phenotypes

HIV envelope protein gp120 is considered a primary molecular determinant of viral neutralization phenotype due to its critical role in viral entry and immune evasion. The intrinsically disordered regions (IDRs) in gp120 are responsible for their extensive sequence variations and significant structural rearrangements. Despite HIV neutralization phenotype and sequence/structural information of gp120 have been experimentally characterized, there remains a gap in our understanding of the correlation between the viral phenotype and IDRs in gp120. Here, we combined machine learning (ML) techniques and molecular dynamics (MD) simulations to gain data-driven and molecule-mechanism insights into relationships between viral sequence, structure, and phenotypes from the perspective of IDRs in gp120. ML models, trained only on the length and disorder score of IDRs, achieved equivalent performance to the best baseline model using amino acid sequences to discriminate HIV neutralization phenotype, indicating that the lengths or disorder of specific IDRs are strongly related to HIV neutralization phenotypes. Comparative MD analysis reveals that gp120 with extreme neutralization phenotypes in multiple conformational states, especially some IDRs, exhibit significantly distinct structural dynamics, conformational flexibility, and thermodynamic distributions. Taken together, our study provided insights into the role of IDRs in gp120 responding to HIV neutralization phenotypes, which will advance the understanding of molecular mechanisms underlying viral function associated with HIV neutralization phenotype and help develop antiviral vaccines or drugs.

Structural flexibility and heterogeneity of recombinant human glial fibrillary acidic protein (GFAP)

Glial fibrillary acidic protein (GFAP) is a promising biomarker for brain and spinal cord disorders. Recent studies have highlighted the differences in the reliability of GFAP measurements in different biological matrices. The reason for these discrepancies is poorly understood as our knowledge of the protein's 3-dimensional conformation, proteoforms, and aggregation remains limited. Here, we investigate the structural properties of GFAP under different conditions. For this, we characterized recombinant GFAP proteins from various suppliers and applied hydrogen-deuterium exchange mass spectrometry (HDX-MS) to provide a snapshot of the conformational dynamics of GFAP in artificial cerebrospinal fluid (aCSF) compared to the phosphate buffer. Our findings indicate that recombinant GFAP exists in various conformational species. Furthermore, we show that GFAP dimers remained intact under denaturing conditions. HDX-MS experiments show an overall decrease in H-bonding and an increase in solvent accessibility of GFAP in aCSF compared to the phosphate buffer, with clear indications of mixed EX2 and EX1 kinetics. To understand possible structural interface regions and the evolutionary conservation profiles, we combined HDX-MS results with the predicted GFAP-dimer structure by AlphaFold-Multimer. We found that deprotected regions with high structural flexibility in aCSF overlap with predicted conserved dimeric 1B and 2B domain interfaces. Structural property predictions combined with the HDX data show an overall deprotection and signatures of aggregation in aCSF. We anticipate that the outcomes of this research will contribute to a deeper understanding of the structural flexibility of GFAP and ultimately shed light on its behavior in different biological matrices.

Sequence-dependent and -independent information in a combined random energy model for protein folding and coding

Random energy models (REMs) provide a simple description of the energy landscapes that guide protein folding and evolution. The requirement of a large energy gap between the native structure and unfolded conformations, considered necessary for cooperative, protein-like, folding behavior, indicates that proteins differ markedly from random heteropolymers. It has been suggested, therefore, that natural selection might have acted to choose nonrandom amino acid sequences satisfying this particular condition, implying that a large fraction of possible, unselected random sequences, would not fold to any structure. From an informational perspective, however, this scenario could indicate that protein structures, regarded as messages to be transmitted through a communication channel, would not be efficiently encoded in amino acid sequences, regarded as the communication channel for this transmission, since a large fraction of possible channel states would not be used. Here, we use a combined REM for conformations and sequences, with previously estimated parameters for natural proteins, to explore an alternative possibility in which the appropriate shape of the landscape results mainly from the deviation from randomness of possible native structures instead of sequences. We observe that this situation emerges naturally if the distribution of conformational energies happens to arise from two independent contributions corresponding to sequence-dependent and -independent terms. This construction is consistent with the hypothesis of a protein burial folding code, with native structures being determined by a modest amount of sequence-dependent atomic burial information with sequence-independent constraints imposed by unspecific hydrogen bond formation. More generally, an appropriate combination of sequence-dependent and -independent information accommodates the possibility of an efficient structural encoding with the main physical requirement for folding, providing possible insight not only on the folding process but also on several aspects sequence evolution such as neutral networks, conformational coverage, and de novo gene emergence.

Investigating direct current potentials that affect native protein conformation during trapped ion mobility spectrometry-mass spectrometry

Trapped ion mobility spectrometry-time-of-flight mass spectrometry (TIMS-TOFMS) has emerged as a tool to study protein conformational states. In TIMS, gas-phase ions are guided across the IM stages by applying direct current (DC) potentials (D1-6), which, however, might induce changes in protein structures through collisional activation. To define conditions for native protein analysis, we evaluated the influence of these DC potentials using the metalloenzyme bovine carbonic anhydrase (BCA) as primary test compound. The variation of DC potentials did not change BCA-ion charge and heme content but affected (relative) charge-state intensities and adduct retention. Constructed extracted-ion mobilograms and corresponding collisional cross-section (CCS) profiles gave useful insights in (alterations of) protein conformational state. For BCA, the D3 and D6 potential (which are applied between the deflection transfer and funnel 1 [F1] and the accumulation exit and the start of the ramp, respectively) had most profound effects, showing multimodal CCS distributions at higher potentials indicating gradual unfolding. The other DC potentials only marginally altered the CCS profiles of BCA. To allow for more general conclusions, five additional proteins of diverse molecular weight and conformational stability were analyzed, and for the main protein charge states, CCS profiles were constructed. Principal component analysis (PCA) of the obtained data showed that D1 and D3 exhibit the highest degree of correlation with the ratio of folded and unfolded protein (F/U) as extracted from the mobilograms obtained per set D potential. The correlation of D6 with F/U and protein charge were similar, and D2, D4, and D5 showed an inverse correlation with F/U but were correlated with protein charge. Although DC boundary values for induced conformational changes appeared protein dependent, a set of DC values could be determined, which assured native analysis of most proteins.

Four-dimensional imaging for cryo-electron microscopy experiments using molecular simulations and manifold learning

Elucidating protein conformational changes is essential because conformational changes are closely related to the functions of proteins. Cryo-electron microscopy (cryo-EM) experiment can be used to reconstruct protein conformational changes via a method that involves using the experimental data (two-dimensional protein images). In this study, a reconstruction method, referred to as the "four-dimensional imaging," was proposed. In our four-dimensional imaging technique, the protein conformational change was obtained using the two-dimensional protein images (the three-dimensional electron density maps used in previously proposed techniques were not used). The protein conformation for each two-dimensional protein image was obtained using our original protocol with molecular dynamics simulations. Using a manifold-learning technique and two-dimensional protein images, the protein conformations were arranged according to the conformational change of the protein. By arranging the protein conformations according to the arrangement of the protein images, four-dimensional imaging is constructed. A simulation for a cryo-EM experiment demonstrated the validity of our four-dimensional imaging technique.

In silico design of misfolding resistant proteins: the role of structural similarity of a competing conformational ensemble in the optimization of frustration

Most state-of-the-art in silico design methods fail due to misfolding of designed sequences to a conformation other than the target. Thus, a method to design misfolding resistant proteins will provide a better understanding of the misfolding phenomenon and will also increase the success rate of in silico design methods. In this work, we optimize the conformational ensemble to be selected for negative design purposes based on the similarity of the conformational ensemble to the target. Five ensembles with different degrees of similarity to the target are created and destabilized and the target is stabilized while designing sequences using mean field theory and Monte Carlo simulation methods. The results suggest that the degree of similarity of the non-native conformations to the target plays a prominent role in designing misfolding resistant protein sequences. The design procedures that destabilize the conformational ensemble with moderate similarity to the target have proven to be more promising. Incorporation of either highly similar or highly dissimilar conformations to the target conformation into the non-native ensemble to be destabilized may lead to sequences with a higher misfolding propensity. This will significantly reduce the conformational space to be considered in any protein design procedure. Interestingly, the results suggest that a sequence with higher frustration in the target structure does not necessarily lead to a misfold prone sequence. A successful design method may purposefully choose a frustrated sequence in the target conformation if that sequence is even more frustrated in the competing non-native conformations.

Conformational free-energy landscapes of a Na+/Ca2+ exchanger explain its alternating-access mechanism and functional specificity

Secondary-active transporters catalyze the movement of myriad substances across all cellular membranes, typically against opposing concentration gradients, and without consuming any ATP. To do so, these proteins employ an intriguing structural mechanism evolved to be activated only upon recognition or release of the transported species. We examine this self-regulated mechanism using a homolog of the cardiac Na+/Ca2+ exchanger as a model system. Using advanced computer simulations, we map out the complete functional cycle of this transporter, including unknown conformations that we validate against existing experimental data. Calculated free-energy landscapes reveal why this transporter functions as an antiporter rather than a symporter, why it specifically exchanges Na+ and Ca2+, and why the stoichiometry of this exchange is exactly 3:1. We also rationalize why the protein does not exchange H+ for either Ca2+ or Na+, despite being able to bind H+ and its high similarity with H+/Ca2+ exchangers. Interestingly, the nature of this transporter is not explained by its primary structural states, known as inward- and outward-open conformations; instead, the defining factor is the feasibility of conformational intermediates between those states, wherein access pathways leading to the substrate binding sites become simultaneously occluded from both sides of the membrane. This analysis offers a physically coherent, broadly transferable route to understand the emergence of function from structure among secondary-active membrane transporters.

Functional protein dynamics in a crystal

Proteins are molecular machines and to understand how they work, we need to understand how they move. New pump-probe time-resolved X-ray diffraction methods open up ways to initiate and observe protein motions with atomistic detail in crystals on biologically relevant timescales. However, practical limitations of these experiments demands parallel development of effective molecular dynamics approaches to accelerate progress and extract meaning. Here, we establish robust and accurate methods for simulating dynamics in protein crystals, a nontrivial process requiring careful attention to equilibration, environmental composition, and choice of force fields. With more than seven milliseconds of sampling of a single chain, we identify critical factors controlling agreement between simulation and experiments and show that simulated motions recapitulate ligand-induced conformational changes. This work enables a virtuous cycle between simulation and experiments for visualizing and understanding the basic functional motions of proteins.

Subatomic structure of orthorhombic thaumatin at 0.89 Å reveals that highly flexible conformations are crucial for thaumatin sweetness

Thaumatin is a sweet-tasting protein that elicits a sweet taste at a threshold of approximately 50 nM. Structure-sweetness relationships in thaumatin suggest that the basicity of two amino acids residues, Arg82 and Lys67, are particularly responsible for sweetness. Using tetragonal crystals, our structural analysis suggested that flexible sidechain conformations of these two residues play an important role in sweetness. However, in tetragonal crystals, Arg82 is adjacent to symmetry-related residues, and its flexibility is relatively restrained by the crystal packing. To reduce and diminish these symmetry-related effects, orthorhombic crystals were prepared, and their structures were successfully determined at a resolution of 0.89 Å. Within the orthorhombic lattice, two alternative conformations were more clearly visible at Lys67 than in a tetragonal system. Interestingly, for the first time, three alternative conformations at Arg82 were only found in an orthorhombic system. These results suggest the importance of flexible conformations in sweetness determinants. Such subtle structural variations might serve to adjust the complementarity of the electrostatic potentials of sweet receptors, thereby eliciting the potent sweet taste of thaumatin.

Protein Ensemble Generation Through Variational Autoencoder Latent Space Sampling

Mapping the ensemble of protein conformations that contribute to function and can be targeted by small molecule drugs remains an outstanding challenge. Here, we explore the use of variational autoencoders for reducing the challenge of dimensionality in the protein structure ensemble generation problem. We convert high-dimensional protein structural data into a continuous, low-dimensional representation, carry out a search in this space guided by a structure quality metric, and then use RoseTTAFold guided by the sampled structural information to generate 3D structures. We use this approach to generate ensembles for the cancer relevant protein K-Ras, train the VAE on a subset of the available K-Ras crystal structures and MD simulation snapshots, and assess the extent of sampling close to crystal structures withheld from training. We find that our latent space sampling procedure rapidly generates ensembles with high structural quality and is able to sample within 1 Å of held-out crystal structures, with a consistency higher than that of MD simulation or AlphaFold2 prediction. The sampled structures sufficiently recapitulate the cryptic pockets in the held-out K-Ras structures to allow for small molecule docking.

Exploring Kinase Asp-Phe-Gly (DFG) Loop Conformational Stability with AlphaFold2-RAVE

Kinases compose one of the largest fractions of the human proteome, and their misfunction is implicated in many diseases, in particular, cancers. The ubiquitousness and structural similarities of kinases make specific and effective drug design difficult. In particular, conformational variability due to the evolutionarily conserved Asp-Phe-Gly (DFG) motif adopting in and out conformations and the relative stabilities thereof are key in structure-based drug design for ATP competitive drugs. These relative conformational stabilities are extremely sensitive to small changes in sequence and provide an important problem for sampling method development. Since the invention of AlphaFold2, the world of structure-based drug design has noticeably changed. In spite of it being limited to crystal-like structure prediction, several methods have also leveraged its underlying architecture to improve dynamics and enhanced sampling of conformational ensembles, including AlphaFold2-RAVE. Here, we extend AlphaFold2-RAVE and apply it to a set of kinases: the wild type DDR1 sequence and three mutants with single point mutations that are known to behave drastically differently. We show that AlphaFold2-RAVE is able to efficiently recover the changes in relative stability using transferable learned order parameters and potentials, thereby supplementing AlphaFold2 as a tool for exploration of Boltzmann-weighted protein conformations (Meller, A.; Bhakat, S.; Solieva, S.; Bowman, G. R. Accelerating Cryptic Pocket Discovery Using AlphaFold. J. Chem. Theory Comput. 2023, 19, 4355-4363).

Accurate and Fast Prediction of Intrinsically Disordered Protein by Multiple Protein Language Models and Ensemble Learning

Intrinsically disordered proteins (IDPs) play a vital role in various biological processes and have attracted increasing attention in the past few decades. Predicting IDPs from the primary structures of proteins offers a rapid and facile means of protein analysis without necessitating crystal structures. In particular, machine learning methods have demonstrated their potential in this field. Recently, protein language models (PLMs) are emerging as a promising approach to extracting essential information from protein sequences and have been employed in protein modeling to utilize their advantages of precision and efficiency. In this article, we developed a novel IDP prediction method named IDP-ELM to predict the intrinsically disordered regions (IDRs) as well as their functions including disordered flexible linkers and disordered protein binding. This method utilizes high-dimensional representations extracted from several state-of-the-art PLMs and predicts IDRs by ensemble learning based on bidirectional recurrent neural networks. The performance of the method was evaluated on two independent test data sets from CAID (critical assessment of protein intrinsic disorder prediction) and CAID2, indicating notable improvements in terms of area under the receiver operating characteristic (AUC), Matthew's correlation coefficient (MCC), and F1 score. Moreover, IDP-ELM requires solely protein sequences as inputs and does not entail a time-consuming process of protein profile generation, which is a prerequisite for most existing state-of-the-art methods, enabling an accurate, fast, and convenient tool for proteome-level analysis. The corresponding reproducible source code and model weights are available at https://github.com/xu-shi-jie/idp-elm.

The series of conformational states adopted by rotorless F1-ATPase during its hydrolysis cycle

F1Fo ATP synthase interchanges phosphate transfer energy and proton motive force via a rotary catalytic mechanism and isolated F1-ATPase subcomplexes can also hydrolyze ATP to generate rotation of their central γ rotor subunit. As ATP is hydrolyzed, the F1-ATPase cycles through a series of conformational states that mediates unidirectional rotation of the rotor. However, even in the absence of a rotor, the α and β subunits are still able to pass through a series of conformations, akin to those that generate rotation. Here, we use cryoelectron microscopy to establish the structures of these rotorless states. These structures indicate that cooperativity in this system is likely mediated by contacts between the β subunit lever domains, irrespective of the presence of the γ rotor subunit. These findings provide insight into how long-range information may be transferred in large biological systems.

Intrinsically disordered regions (IDRs): A vague and confusing concept for protein function

The term "intrinsically disordered region" (IDR) in proteins has been used in numerous publications. However, most proteins contain IDRs, the term refers to very different types of structures and functions, and many IDRs become structured upon interaction with other biomolecules. Thus, IDR is an unnecessary, vague, and ultimately confusing concept.

De novo design of cavity-containing proteins with a backbone-centered neural network energy function

The design of small-molecule-binding proteins requires protein backbones that contain cavities. Previous design efforts were based on naturally occurring cavity-containing backbone architectures. Here, we designed diverse cavity-containing backbones without predefined architectures by introducing tailored restraints into the backbone sampling driven by SCUBA (Side Chain-Unknown Backbone Arrangement), a neural network statistical energy function. For 521 out of 5816 designs, the root-mean-square deviations (RMSDs) of the Cα atoms for the AlphaFold2-predicted structures and our designed structures are within 2.0 Å. We experimentally tested 10 designed proteins and determined the crystal structures of two of them. One closely agrees with the designed model, while the other forms a domain-swapped dimer, where the partial structures are in agreement with the designed structures. Our results indicate that data-driven methods such as SCUBA hold great potential for designing de novo proteins with tailored small-molecule-binding function.

Terms and conditions

Brian Plosky provides some context for a debate over the use of "intrinsically disordered" to describe regions of proteins.

Intrinsic disorder: A term to define the specific physicochemical characteristic of protein conformational heterogeneity

In his commentary in this issue of Molecular Cell,1 Struhl reasons that the term "intrinsically disordered regions" represents a vague and confusing concept for protein function. However, the term "intrinsically disordered" highlights the important physicochemical characteristic of conformational heterogeneity. Thus, "intrinsically disordered" is the counterpart to the term "folded, " with neither term having specific functional implications.

In Vitro and In Silico Explorations of the Protein Conformational Changes of Corynebacterium glutamicum MshA, a Model Retaining GT-B Glycosyltransferase

MshA is a GT-B glycosyltransferase catalyzing the first step in the biosynthesis of mycothiol. While many GT-B enzymes undergo an open-to-closed transition, MshA is unique because its 97° rotation is beyond the usual range of 10-25°. Molecular dynamics (MD) simulations were carried out for MshA in both ligand bound and unbound states to investigate the effect of ligand binding on localized protein dynamics and its conformational free energy landscape. Simulations showed that both the unliganded "opened" and liganded "closed" forms of the enzyme sample a wide degree of dihedral angles and interdomain distances with relatively low overlapping populations. Calculation of the free energy surface using replica exchange MD for the apo "opened" and an artificial generated apo "closed" structure revealed overlaps in the geometries sampled, allowing calculation of a barrier of 2 kcal/mol for the open-to-closed transition in the absence of ligands. MD simulations of fully liganded MshA revealed a smaller sampling of the dihedral angles. The localized protein fluctuation changes suggest that UDP-GlcNAc binding activates the motions of loops in the 1-l-myo-inositol-1-phosphate (I1P)-binding site despite little change in the interactions with UDP-GlcNAc. Circular dichroism, intrinsic fluorescence spectroscopy, and mutagenesis studies were used to confirm the ligand-induced structural changes in MshA. The results support a proposed mechanism where UDP-GlcNAc binds with rigid interactions to the C-terminal domain of MshA and activates flexible loops in the N-terminal domain for binding and positioning of I1P. This model can be used for future structure-based drug development of inhibitors of the mycothiol biosynthetic pathway.

Ligand-induced protein transition state stabilization switches the binding pathway from conformational selection to induced fit

Protein-ligand complex formation is fundamental to biological function. A central question is whether proteins spontaneously adopt binding-competent conformations to which ligands bind conformational selection (CS) or whether ligands induce the binding-competent conformation induced fit (IF). Here, we resolve the CS and IF binding pathways by characterizing protein conformational dynamics over a wide range of ligand concentrations using NMR relaxation dispersion. We determined the relative flux through the two pathways using a four-state binding model that includes both CS and IF. Experiments conducted without ligand show that galectin-3 exchanges between the ground-state conformation and a high-energy conformation similar to the ligand-bound conformation, demonstrating that CS is a plausible pathway. Near-identical crystal structures of the apo and ligand-bound states suggest that the high-energy conformation in solution corresponds to the apo crystal structure. Stepwise additions of the ligand lactose induce progressive changes in the relaxation dispersions that we fit collectively to the four-state model, yielding all microscopic rate constants and binding affinities. The ligand affinity is higher for the bound-like conformation than for the ground state, as expected for CS. Nonetheless, the IF pathway contributes greater than 70% of the total flux even at low ligand concentrations. The higher flux through the IF pathway is explained by considerably higher rates of exchange between the two protein conformations in the ligand-associated state. Thus, the ligand acts to decrease the activation barrier between protein conformations in a manner reciprocal to enzymatic transition-state stabilization of reactions involving ligand transformation.

Calcium mediated static and dynamic allostery in S100A12: Implications for target recognition by S100 proteins

Structure and functions of S100 proteins are regulated by two distinct calcium binding EF hand motifs. In this work, we used solution-state NMR spectroscopy to investigate the cooperativity between the two calcium binding sites and map the allosteric changes at the target binding site. To parse the contribution of the individual calcium binding events, variants of S100A12 were designed to selectively bind calcium to either the EF-I (N63A) or EF-II (E31A) loop, respectively. Detailed analysis of the backbone chemical shifts for wildtype protein and its mutants indicates that calcium binding to the canonical EF-II loop is the principal trigger for the conformational switch between 'closed' apo to the 'open' Ca2+ -bound conformation of the protein. Elimination of binding in S100-specific EF-I loop has limited impact on the calcium binding affinity of the EF-II loop and the concomitant structural rearrangement. In contrast, deletion of binding in the EF-II loop significantly attenuates calcium affinity in the EF-I loop and the structure adopts a 'closed' apo-like conformation. Analysis of experimental amide nitrogen (15 N) relaxation rates (R1 , R2 , and 15 N-{1 H} NOE) and molecular dynamics (MD) simulations demonstrate that the calcium bound state is relatively floppy with pico-nanosecond motions induced in functionally relevant domains responsible for target recognition such as the hinge domain and the C-terminal residues. Experimental relaxation studies combined with MD simulations show that while calcium binding in the EF-I loop alone does not induce significant motions in the polypeptide chain, EF-I regulates fluctuations in the polypeptide in the presence of bound calcium in the EF-II loop. These results offer novel insights into the dynamic regulation of target recognition by calcium binding and unravels the role of cooperativity between the two calcium binding events in S100A12.

Proteasome activation: A novel strategy for targeting undruggable intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are characterized by their inability to adopt well-defined tertiary structures under physiological conditions. Nonetheless, they often play pivotal roles in the progression of various diseases, including cancer, neurodegenerative disorders, and cardiovascular ailments. Owing to their inherent dynamism, conventional drug design approaches based on structural considerations encounter substantial challenges when applied to IDPs. Consequently, the pursuit of therapeutic interventions directed towards IDPs presents a complex endeavor. While there are indeed existing methodologies for targeting IDPs, they are encumbered by noteworthy constrains. Hence, there exists an imminent imperative to investigate more efficacious and universally applicable strategies for modulating IDPs. Here, we present an overview of the latest advancements in the research pertaining to IDPs, along with the indirect regulation approach involving the modulation of IDP degradation through proteasome. By comprehending these advancements in research, novel insights can be generated to facilitate the development of new drugs targeted at addressing the accumulation of IDPs in diverse pathological conditions.

Classifying protein kinase conformations with machine learning

Protein kinases are key actors of signaling networks and important drug targets. They cycle between active and inactive conformations, distinguished by a few elements within the catalytic domain. One is the activation loop, whose conserved DFG motif can occupy DFG-in, DFG-out, and some rarer conformations. Annotation and classification of the structural kinome are important, as different conformations can be targeted by different inhibitors and activators. Valuable resources exist; however, large-scale applications will benefit from increased automation and interpretability of structural annotation. Interpretable machine learning models are described for this purpose, based on ensembles of decision trees. To train them, a set of catalytic domain sequences and structures was collected, somewhat larger and more diverse than existing resources. The structures were clustered based on the DFG conformation and manually annotated. They were then used as training input. Two main models were constructed, which distinguished active/inactive and in/out/other DFG conformations. They considered initially 1692 structural variables, spanning the whole catalytic domain, then identified ("learned") a small subset that sufficed for accurate classification. The first model correctly labeled all but 3 of 3289 structures as active or inactive, while the second assigned the correct DFG label to all but 17 of 8826 structures. The most potent classifying variables were all related to well-known structural elements in or near the activation loop and their ranking gives insights into the conformational preferences. The models were used to automatically annotate 3850 kinase structures predicted recently with the Alphafold2 tool, showing that Alphafold2 reproduced the active/inactive but not the DFG-in proportions seen in the Protein Data Bank. We expect the models will be useful for understanding and engineering kinases.

Xplor-NIH: Better parameters and protocols for NMR protein structure determination

The present work describes an update to the protein covalent geometry and atomic radii parameters in the Xplor-NIH biomolecular structure determination package. In combination with an improved treatment of selected non-bonded interactions between atoms three bonds apart, such as those involving methyl hydrogens, and a previously developed term that affects the system's gyration volume, the new parameters are tested using structure calculations on 30 proteins with restraints derived from nuclear magnetic resonance data. Using modern structure validation criteria, including several formally adopted by the Protein Data Bank, and a clear measure of structural accuracy, the results show superior performance relative to previous Xplor-NIH implementations. Additionally, the Xplor-NIH structures compare favorably against originally determined NMR models.

Connectivity between surface and interior in catalytic subunits of acetylcholinesterases inferred from their X-ray structures

Catalytic activity and function of acetylcholinesterase (AChE; EC 3.1.1.7) have been recognized and studied for over a century and its quaternary and primary structures for about half a century, and its tertiary structure has been known for about 33 years. Clear understanding of relationships between the structure and the function is still pending for this enzyme. Hundreds of crystallographic, static snapshots of AChEs from different sources reveal largely one general backbone conformation with narrow entry into the active center gorge, tightly fit to accept one acetylcholine (ACh) molecule, in contrast to its high catalytic turnover. This short review of available X-ray structures of AChEs from electric ray Torpedo californica, mouse and human, finds some limited, yet consistent deviations in conformations of selected secondary structure elements of AChE relevant for its function. The observed conformational diversity of the acyl pocket loop of AChE, unlike the large Ω-loop, appears consistent with structurally dynamic INS data and solution-based SAXS experiments to explain its dominant role in controlling the size of the active center gorge opening, as well as connectivity between the immediate surroundings of the buried active Ser, and catalytically relevant sites on the AChE surface.

AlphaFold-assisted structure determination of a bacterial protein of unknown function using X-ray and electron crystallography

Macromolecular crystallography generally requires the recovery of missing phase information from diffraction data to reconstruct an electron-density map of the crystallized molecule. Most recent structures have been solved using molecular replacement as a phasing method, requiring an a priori structure that is closely related to the target protein to serve as a search model; when no such search model exists, molecular replacement is not possible. New advances in computational machine-learning methods, however, have resulted in major advances in protein structure predictions from sequence information. Methods that generate predicted structural models of sufficient accuracy provide a powerful approach to molecular replacement. Taking advantage of these advances, AlphaFold predictions were applied to enable structure determination of a bacterial protein of unknown function (UniProtKB Q63NT7, NCBI locus BPSS0212) based on diffraction data that had evaded phasing attempts using MIR and anomalous scattering methods. Using both X-ray and micro-electron (microED) diffraction data, it was possible to solve the structure of the main fragment of the protein using a predicted model of that domain as a starting point. The use of predicted structural models importantly expands the promise of electron diffraction, where structure determination relies critically on molecular replacement.

Exploring biocompatible chemistry to create stapled and photoswitchable variants of the antimicrobial peptide aurein 1.2

Antibiotic resistance is an escalating global health threat. Due to their diverse mechanisms of action and evasion of traditional resistance mechanisms, peptides hold promise as future antibiotics. Their ability to disrupt bacterial membranes presents a potential strategy to combat drug-resistant infections and address the increasing need for effective antimicrobial treatments. Amphipathic α-helical peptides possess a distinctive molecular structure with both charged/hydrophilic and hydrophobic regions that interact with the bacterial cell membrane, disrupting its structural integrity. The α-helical amphipathic peptide aurein 1.2, secreted by the Australian frog Litoria aurea, is one of the shortest known antimicrobial peptides, spanning only 13 amino acids. The primary objective of this study was to investigate stapled and photoswitchable modifications of short helical peptides employing biocompatible chemistry, utilising aurein 1.2 as a model system. We developed various stapled versions of aurein 1.2 using biocompatible conjugation chemistry between dicyanopyridine and 1,2-aminothiols. While the commonly employed stapling pattern for longer staples is i, i + 7, we observed superior helicity in peptides stapled at positions i, i + 8. Molecular dynamics simulations confirmed both stapling patterns to support an α-helical peptide conformation. Additionally, we utilised a cysteine-selective photosensitive staple, perfluoro azobenzene, to explore photoswitchable variants of aurein 1.2. A double-cysteine variant stapled at i, i + 7 indeed exhibited a change in overall helicity induced by light. We further demonstrated the applicability of this staple to attach to cysteine residues in i, i + 7 positions of a helix in a model protein. While some of the stapled variants displayed substantial increase in helicity, minimal inhibitory concentration assays revealed that none of the stapled aurein 1.2 variants exhibited increased antimicrobial activity compared to the wildtype.

Automated model building and protein identification in cryo-EM maps

Interpreting electron cryo-microscopy (cryo-EM) maps with atomic models requires high levels of expertise and labour-intensive manual intervention in three-dimensional computer graphics programs1,2. Here we present ModelAngelo, a machine-learning approach for automated atomic model building in cryo-EM maps. By combining information from the cryo-EM map with information from protein sequence and structure in a single graph neural network, ModelAngelo builds atomic models for proteins that are of similar quality to those generated by human experts. For nucleotides, ModelAngelo builds backbones with similar accuracy to those built by humans. By using its predicted amino acid probabilities for each residue in hidden Markov model sequence searches, ModelAngelo outperforms human experts in the identification of proteins with unknown sequences. ModelAngelo will therefore remove bottlenecks and increase objectivity in cryo-EM structure determination.

Small angle X-ray scattering analysis of thermophilic cytochrome P450 CYP119 and the effects of the N-terminal histidine tag

Combining size exclusion chromatography-small angle X-ray scattering (SEC-SAXS) and molecular dynamics (MD) analysis is a promising approach to investigate protein behavior in solution, particularly for understanding conformational changes due to substrate binding in cytochrome P450s (CYPs). This study investigates conformational changes in CYP119, a thermophilic CYP from Sulfolobus acidocaldarius that exhibits structural flexibility similar to mammalian CYPs. Although the crystal structure of ligand-free (open state) and ligand-bound (closed state) forms of CYP119 is known, the overall structure of the enzyme in solution has not been explored until now. It was found that theoretical scattering profiles from the crystal structures of CYP119 did not align with the SAXS data, but conformers from MD simulations, particularly starting from the open state (46 % of all frames), agreed well. Interestingly, a small percentage of closed-state conformers also fit the data (9 %), suggesting ligand-free CYP119 samples ligand-bound conformations. Ab initio SAXS models for N-His tagged CYP119 revealed a tail-like unfolded structure impacting protein flexibility, which was confirmed by in silico modeling. SEC-SAXS analysis of N-His CYP119 indicated pentameric structures in addition to monomers in solution, affecting the stability and activity of the enzyme. This study adds insights into the conformational dynamics of CYP119 in solution.

Evaluating the effects of graphene nanoparticles combined radio-frequency thawing on the physicochemical quality and protein conformation in hairtail (Trichiurus lepturus) dorsal muscle

BACKGROUND

The thawing process is an essential step for a frozen marine fish. The present study aimed to investigate the effects of graphene magnetic nanoparticles combined radio-frequency thawing methods on frozen hairtail (Trichiurus lepturus) dorsal muscle. Seven thawing methods were used: air thawing, 4 °C cold storage thawing, water thawing, radio-frequency thawing (RT), radio frequency thawing combined with graphene nanoparticles (G-RT), radio frequency thawing combined with graphene oxide nanoparticles (GO-RT) and radio-frequency thawing combined with graphene magnetic nanoparticles (GM-RT). The thawing loss and centrifugal loss, electric conductivity, total volatile basic nitrogen, thiobarbituric acid reactive substances and color of thawed hairtail dorsal muscle were determined. The carbonyl content, total sulfhydryl groups, Ca2+ -ATPase activity, raman spectroscopy measurements and Fourier-transform infrared spectrometry measurements were determined using myofibrillar extracted from the dorsal muscle of hairtail. The water distribution was determined using low-field NMR techniques.

RESULTS

The results demonstrated that the RT, G-RT, GO-RT and GM-RT could significantly shorten the thawing time. Moreover, GO-RT and GM-RT efficiently preserved the color of fish dorsal muscle and reduced the impact of thawing on fish quality by reducing lipid and protein oxidation. Meanwhile, the myofibrillar protein structure thawed by GO-RT and GM-RT were more stable and had a more stable secondary structure, which maintained strong systemic stability at the same time as slowing down protein oxidation.

CONCLUSION

The results showed that GO-RT and GM-RT can significantly improve the thawing efficiency at the same time as effectively maintaining and improving the color and texture of thawed fish, slowing down the oxidation of proteins and lipids, and maintaining a good quality of thawed fish meat. © 2023 Society of Chemical Industry.

Changes in an enzyme ensemble during catalysis observed by high-resolution XFEL crystallography

Enzymes populate ensembles of structures necessary for catalysis that are difficult to experimentally characterize. We use time-resolved mix-and-inject serial crystallography at an x-ray free electron laser to observe catalysis in a designed mutant isocyanide hydratase (ICH) enzyme that enhances sampling of important minor conformations. The active site exists in a mixture of conformations, and formation of the thioimidate intermediate selects for catalytically competent substates. The influence of cysteine ionization on the ICH ensemble is validated by determining structures of the enzyme at multiple pH values. Large molecular dynamics simulations in crystallo and time-resolved electron density maps show that Asp17 ionizes during catalysis and causes conformational changes that propagate across the dimer, permitting water to enter the active site for intermediate hydrolysis. ICH exhibits a tight coupling between ionization of active site residues and catalysis-activated protein motions, exemplifying a mechanism of electrostatic control of enzyme dynamics.

Hairpin trimer transition state of amyloid fibril

Protein fibril self-assembly is a universal transition implicated in neurodegenerative diseases. Although fibril structure/growth are well characterized, fibril nucleation is poorly understood. Here, we use a computational-experimental approach to resolve fibril nucleation. We show that monomer hairpin content quantified from molecular dynamics simulations is predictive of experimental fibril formation kinetics across a tau motif mutant library. Hairpin trimers are predicted to be fibril transition states; one hairpin spontaneously converts into the cross-beta conformation, templating subsequent fibril growth. We designed a disulfide-linked dimer mimicking the transition state that catalyzes fibril formation, measured by ThT fluorescence and TEM, of wild-type motif - which does not normally fibrillize. A dimer compatible with extended conformations but not the transition-state fails to nucleate fibril at any concentration. Tau repeat domain simulations show how long-range interactions sequester this motif in a mutation-dependent manner. This work implies that different fibril morphologies could arise from disease-dependent hairpin seeding from different loci.

Multilevel superposition for deciphering the conformational variability of protein ensembles

The dynamics and variability of protein conformations are directly linked to their functions. Many comparative studies of X-ray protein structures have been conducted to elucidate the relevant conformational changes, dynamics and heterogeneity. The rapid increase in the number of experimentally determined structures has made comparison an effective tool for investigating protein structures. For example, it is now possible to compare structural ensembles formed by enzyme species, variants or the type of ligands bound to them. In this study, the author developed a multilevel model for estimating two covariance matrices that represent inter- and intra-ensemble variability in the Cartesian coordinate space. Principal component analysis using the two estimated covariance matrices identified the inter-/intra-enzyme variabilities, which seemed to be important for the enzyme functions, with the illustrative examples of cytochrome P450 family 2 enzymes and class A $\beta$-lactamases. In P450, in which each enzyme has its own active site of a distinct size, an active-site motion shared universally between the enzymes was captured as the first principal mode of the intra-enzyme covariance matrix. In this case, the method was useful for understanding the conformational variability after adjusting for the differences between enzyme sizes. The developed method is advantageous in small ensemble-size problems and hence promising for use in comparative studies on experimentally determined structures where ensemble sizes are smaller than those generated, for example, by molecular dynamics simulations.

High-throughput prediction of protein conformational distributions with subsampled AlphaFold2

This paper presents an innovative approach for predicting the relative populations of protein conformations using AlphaFold 2, an AI-powered method that has revolutionized biology by enabling the accurate prediction of protein structures. While AlphaFold 2 has shown exceptional accuracy and speed, it is designed to predict proteins' ground state conformations and is limited in its ability to predict conformational landscapes. Here, we demonstrate how AlphaFold 2 can directly predict the relative populations of different protein conformations by subsampling multiple sequence alignments. We tested our method against nuclear magnetic resonance experiments on two proteins with drastically different amounts of available sequence data, Abl1 kinase and the granulocyte-macrophage colony-stimulating factor, and predicted changes in their relative state populations with more than 80% accuracy. Our subsampling approach worked best when used to qualitatively predict the effects of mutations or evolution on the conformational landscape and well-populated states of proteins. It thus offers a fast and cost-effective way to predict the relative populations of protein conformations at even single-point mutation resolution, making it a useful tool for pharmacology, analysis of experimental results, and predicting evolution.

Conformation selection by ATP-competitive inhibitors and allosteric communication in ERK2

Activation of the extracellular signal-regulated kinase-2 (ERK2) by phosphorylation has been shown to involve changes in protein dynamics, as determined by hydrogen-deuterium exchange mass spectrometry (HDX-MS) and NMR relaxation dispersion measurements. These can be described by a global exchange between two conformational states of the active kinase, named 'L' and 'R,' where R is associated with a catalytically productive ATP-binding mode. An ATP-competitive ERK1/2 inhibitor, Vertex-11e, has properties of conformation selection for the R-state, revealing movements of the activation loop that are allosterically coupled to the kinase active site. However, the features of inhibitors important for R-state selection are unknown. Here, we survey a panel of ATP-competitive ERK inhibitors using HDX-MS and NMR and identify 14 new molecules with properties of R-state selection. They reveal effects propagated to distal regions in the P+1 and helix αF segments surrounding the activation loop, as well as helix αL16. Crystal structures of inhibitor complexes with ERK2 reveal systematic shifts in the Gly loop and helix αC, mediated by a Tyr-Tyr ring stacking interaction and the conserved Lys-Glu salt bridge. The findings suggest a model for the R-state involving small movements in the N-lobe that promote compactness within the kinase active site and alter mobility surrounding the activation loop. Such properties of conformation selection might be exploited to modulate the protein docking interface used by ERK substrates and effectors.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Comprehensive Analysis of Coupled Proline Cis-Trans States in Bradykinin Using ωBP-REMD Simulations

It is well-known that proline (Pro) cis-trans isomerization plays a decisive role in the folding and stabilization of proteins. The conformational coupling between isomerization states of different Pro residues in proteins during conformational adaptation processes is not well understood. In the present work, we investigate the coupled cis-trans isomerization of three Pro residues using bradykinin (BK), a partially unstructured nonapeptide hormone, as a model system. We use a recently developed enhanced-sampling molecular dynamics method (ω-bias potential replica exchange molecular dynamics; ωBP-REMD) that allows us to exhaustively sample all combinations of Pro isomer states and obtain converged probability densities of all eight state combinations within 885 ns ωBP-REMD simulations. In agreement with experiment, the all-trans state is seen to be the preferred isomer of zwitterionic aqueous BK. In about a third of its structures, this state presents the characteristic C-terminal β-turn conformation; however, other isomer combinations also contribute significantly to the structural ensemble. Unbiased probabilities can be projected onto the peptide bond dihedral angles of the three Pro residues. This unveils the interdependence of the individual Pro isomerization states, i.e., a possible coupling of the different Pro isomers. The cis/trans equilibrium of a Pro residue can change by up to 2.5 kcal·mol-1, depending on the isomerization state of other Pro residues. For example, for Pro7, the simulations indicate that its cis state becomes favored compared to its trans state when Pro2 is switched from the trans state to the cis state. Our findings demonstrate the efficiency of the ωBP-REMD methodology and suggest that the coupling of Pro isomerization states may play an even more decisive role in larger folded proteins subject to more conformational restraints.

Switching Go̅-Martini for Investigating Protein Conformational Transitions and Associated Protein-Lipid Interactions

Proteins are dynamic biomolecules that can transform between different conformational states when exerting physiological functions, which is difficult to simulate using all-atom methods. Coarse-grained (CG) Go̅-like models are widely used to investigate large-scale conformational transitions, which usually adopt implicit solvent models and therefore cannot explicitly capture the interaction between proteins and surrounding molecules, such as water and lipid molecules. Here, we present a new method, named Switching Go̅-Martini, to simulate large-scale protein conformational transitions between different states, based on the switching Go̅ method and the CG Martini 3 force field. The method is straightforward and efficient, as demonstrated by the benchmarking applications for multiple protein systems, including glutamine binding protein (GlnBP), adenylate kinase (AdK), and β2-adrenergic receptor (β2AR). Moreover, by employing the Switching Go̅-Martini method, we can not only unveil the conformational transition from the E2Pi-PL state to E1 state of the type 4 P-type ATPase (P4-ATPase) flippase ATP8A1-CDC50 but also provide insights into the intricate details of lipid transport.

The Effect of Microwaves on Protein Structure: Molecular Dynamics Approach

The impact of microwave (MW) irradiation on protein folding, potentially inciting misfolding, was investigated by employing molecular dynamics (MD) simulations. Twenty-nine proteins were subjected to MD simulations under equilibrium (300 K) and MW conditions, where the rotational temperature was elevated to 700 K. The utilized replacement model captures the microwave effects of δ- and γ-relaxation processes (frequency range of ∼300 MHz to ∼20 GHz). The results disclosed that MW heating incited a shift toward more compact protein conformations, as indicated by decreased root-mean-square deviations, root-mean-square fluctuations, head-to-tail distances, and radii of gyration. This compaction was attributed to the intensification of intramolecular electrostatic interactions and hydrogen bonds within the protein caused by MW-destabilized hydrogen bonds between the protein and solvent. The solvent-accessible surface area (SASA), particularly that of polar amino-acid residues, shrank under MW conditions, corresponding to a reduced polarity of the water solvent. However, MW irradiation produced no significant alterations in protein secondary structures; hence, MW heating was observed to primarily affect the protein tertiary structures.

Structure and function of the Arabidopsis ABC transporter ABCB19 in brassinosteroid export

Brassinosteroids are steroidal phytohormones that regulate plant development and physiology, including adaptation to environmental stresses. Brassinosteroids are synthesized in the cell interior but bind receptors at the cell surface, necessitating a yet to be identified export mechanism. Here, we show that a member of the ATP-binding cassette (ABC) transporter superfamily, ABCB19, functions as a brassinosteroid exporter. We present its structure in both the substrate-unbound and the brassinosteroid-bound states. Bioactive brassinosteroids are potent activators of ABCB19 ATP hydrolysis activity, and transport assays showed that ABCB19 transports brassinosteroids. In Arabidopsis thaliana, ABCB19 and its close homolog, ABCB1, positively regulate brassinosteroid responses. Our results uncover an elusive export mechanism for bioactive brassinosteroids that is tightly coordinated with brassinosteroid signaling.

Enhanced Sampling for Conformational Changes and Molecular Mechanisms of Human NTHL1

The functionalities of proteins rely on protein conformational changes during many processes. Identification of the protein conformations and capturing transitions among different conformations are important but extremely challenging in both experiments and simulations. In this work, we develop a machine learning based approach to identify a reaction coordinate that accelerates the exploration of protein conformational changes in molecular simulations. We implement our approach to study the conformational changes of human NTHL1 during DNA repair. Our results identified three distinct conformations: open (stable), closed (unstable), and bundle (stable). The existence of the bundle conformation can rationalize recent experimental observations. Comparison with an NTHL1 mutant demonstrates that a closely packed cluster of positively charged residues in the linker could be a factor to search when screening for genetic abnormalities. Results will lead to a better modulation of the DNA repair pathway to protect against carcinogenesis.

How nuclear receptors transition between active and inactive forms: An energetic perspective

Nuclear receptors regulate transcriptional programs in response to the binding of natural and synthetic ligands. These ligands modulate the receptor by inducing dynamic changes in the ligand binding domain that shift the C-terminal helix (H12) between active and inactive conformations. Despite decades of study, many questions persist regarding the nature of the inactive state and how ligands shift receptors between different states. Here, we use molecular dynamics (MD) simulations to investigate the timescale and energetic landscape of the conformational transition between inactive and active forms of progesterone receptor (PR) bound to a partial agonist. We observe that the microsecond timescale is insufficient to observe any transitions; only at millisecond timescales achieved via accelerated MD simulations do we find the inactive PR switches to the active state. Energetic analysis reveals that both active and inactive PR states represent energy minima separated by a barrier that can be traversed. In contrast, little or no transition is observed between active and inactive states when an agonist or antagonist is bound, confirming that ligand identity plays a key role in defining the energy landscape of nuclear receptor conformations.

Synthetic and Computational Design Insights toward Mimicking Protein Binding of Phosphate

The unique and precise capabilities of proteins are renowned for their specificity and range of application. Effective mimicking of protein-binding offers enticing potential to direct their abilities toward useful applications, but it is nevertheless quite difficult to realize this characteristic of protein behavior in a synthetic material. Here, we design, synthesize, and evaluate experimentally and computationally a series of multicomponent phosphate-binding peptide amphiphile micelles to derive design insights into how protein binding behavior translates to synthetic materials. By inserting the Walker A P-loop binding motif into this peptide synthetic material, we successfully implemented the protein-binding design parameters of hydrogen-bonding and electrostatic interaction to bind phosphate completely and selectively in this highly tunable synthetic platform. Moreover, in this densely arrayed peptide environment, we use molecular dynamics simulations to identify an intriguing mechanistic shift of binding that is inaccessible in traditional proteins, introducing two corresponding new design elements─flexibility and minimization of the loss of entropy due to ion binding, in protein-analogous synthetic materials. We then translate these new design factors to de novo peptide sequences that bind phosphate independent of protein-extracted sequence or conformation. Overall, this work reveals that traditional complex conformational restrictions of binding by proteins can be replaced and repurposed in a multicomponent peptide amphiphile synthetic material, opening up opportunities for future enhanced protein-inspired design.

Activation and friction in enzymatic loop opening and closing dynamics

Protein loop dynamics have recently been recognized as central to enzymatic activity, specificity and stability. However, the factors controlling loop opening and closing kinetics have remained elusive. Here, we combine molecular dynamics simulations with string-method determination of complex reaction coordinates to elucidate the molecular mechanism and rate-limiting step for WPD-loop dynamics in the PTP1B enzyme. While protein conformational dynamics is often represented as diffusive motion hindered by solvent viscosity and internal friction, we demonstrate that loop opening and closing is activated. It is governed by torsional rearrangement around a single loop peptide group and by significant friction caused by backbone adjustments, which can dynamically trap the loop. Considering both torsional barrier and time-dependent friction, our calculated rate constants exhibit very good agreement with experimental measurements, reproducing the change in loop opening kinetics between proteins. Furthermore, we demonstrate the applicability of our results to other enzymatic loops, including the M20 DHFR loop, thereby offering prospects for loop engineering potentially leading to enhanced designs.

Multiple retinal isomerizations during the early phase of the bestrhodopsin photoreaction

Bestrhodopsins constitute a class of light-regulated pentameric ion channels that consist of one or two rhodopsins in tandem fused with bestrophin ion channel domains. Here, we report on the isomerization dynamics in the rhodopsin tandem domains of Phaeocystis antarctica bestrhodopsin, which binds all-trans retinal Schiff-base (RSB) absorbing at 661 nm and, upon illumination, converts to the meta-stable P540 state with an unusual 11-cis RSB. The primary photoproduct P682 corresponds to a mixture of highly distorted 11-cis and 13-cis RSB directly formed from the excited state in 1.4 ps. P673 evolves from P682 in 500 ps and contains highly distorted 13-cis RSB, indicating that the 11-cis fraction in P682 converts to 13-cis. Next, P673 establishes an equilibrium with P595 in 1.2 µs, during which RSB converts to 11-cis and then further proceeds to P560 in 48 µs and P540 in 1.0 ms while remaining 11-cis. Hence, extensive isomeric switching occurs on the early ground state potential energy surface (PES) on the hundreds of ps to µs timescale before finally settling on a metastable 11-cis photoproduct. We propose that P682 and P673 are trapped high up on the ground-state PES after passing through either of two closely located conical intersections that result in 11-cis and 13-cis RSB. Co-rotation of C11=C12 and C13=C14 bonds results in a constricted conformational landscape that allows thermal switching between 11-cis and 13-cis species of highly strained RSB chromophores. Protein relaxation may release RSB strain, allowing it to evolve to a stable 11-cis isomeric configuration in microseconds.

Non-fluorescent transient states of tyrosine as a basis for label-free protein conformation and interaction studies

The amino acids tryptophan, tyrosine, and phenylalanine have been extensively used for different label-free protein studies, based on the intensity, lifetime, wavelength and/or polarization of their emitted fluorescence. Similar to most fluorescent organic molecules, these amino acids can undergo transitions into dark meta-stable states, such as triplet and photo-radical states. On the one hand, these transitions limit the fluorescence signal, but they are also highly environment-sensitive and can offer an additional set of parameters, reflecting interactions, folding states, and immediate environments around the proteins. In this work, by analyzing the average intensity of tyrosine emission under different excitation modulations with the transient state monitoring (TRAST) technique, we explored the photo physics of tyrosine as a basis for such environment-sensitive readouts. From how the dark state transitions of tyrosine varied with excitation intensity and solvent conditions we first established a photophysical model for tyrosine. Next, we studied Calmodulin (containing two tyrosines), and how its conformation is changed upon calcium binding. From these TRAST experiments, performed with 280 nm time-modulated excitation, we show that tyrosine dark state transitions clearly change with the calmodulin conformation, and may thus represent a useful source of information for (label-free) analyses of protein conformations and interactions.

Voltage-clamp fluorometry to record flow-activated PIEZO1 currents and fluorometric signals

PIEZO channels sense mechanical forces through conformational rearrangements of a mechanosensory domain called blade. To probe these rearrangements in real time, we have inserted conformational-sensitive cyclic-permuted GFP into several positions of PIEZO1's blade. Here, we describe the step-by-step experimental procedure we developed to simultaneously measure flow-activated ionic currents and fluorometric signals in cells expressing these engineered constructs. We describe steps for performing transfection, seeding cells on coverslips, setting up a perfusion-based fluid shear application system, and performing voltage-clamp fluorometry. For complete details on the use and execution of this protocol, please refer to Ozkan et al. (2023).1.

Cryo-EM Structures of CRAF2/14-3-32 and CRAF2/14-3-32/MEK12 Complexes

RAF protein kinases are essential effectors in the MAPK pathway and are important cancer drug targets. Structural understanding of RAF activation is so far based on cryo-electron microscopy (cryo-EM) and X-ray structures of BRAF in different conformational states as inactive or active complexes with KRAS, 14-3-3 and MEK1. In this study, we have solved the first cryo-EM structures of CRAF2/14-3-32 at 3.4 Å resolution and CRAF2/14-3-32/MEK12 at 4.2 Å resolution using CRAF kinase domain expressed as constitutively active Y340D/Y341D mutant in insect cells. The overall architecture of our CRAF2/14-3-32 and CRAF2/14-3-32/MEK12 cryo-EM structures is highly similar to corresponding BRAF structures in complex with 14-3-3 or 14-3-3/MEK1 and represent the activated dimeric RAF conformation. Our CRAF cryo-EM structures provide additional insights into structural understanding of the activated CRAF2/14-3-32/MEK12 complex.

Assembly of Protein Complexes in and on the Membrane with Predicted Spatial Arrangement Constraints

Membrane proteins play crucial roles in various cellular processes, and their interactions with other proteins in and on the membrane are essential for their proper functioning. While an increasing number of structures of more membrane proteins are being determined, the available structure data is still sparse. To gain insights into the mechanisms of membrane protein complexes, computational docking methods are necessary due to the challenge of experimental determination. Here, we introduce Mem-LZerD, a rigid-body membrane docking algorithm designed to take advantage of modern membrane modeling and protein docking techniques to facilitate the docking of membrane protein complexes. Mem-LZerD is based on the LZerD protein docking algorithm, which has been constantly among the top servers in many rounds of CAPRI protein docking assessment. By employing a combination of geometric hashing, newly constrained by the predicted membrane height and tilt angle, and model scoring accounting for the energy of membrane insertion, we demonstrate the capability of Mem-LZerD to model diverse membrane protein-protein complexes. Mem-LZerD successfully performed unbound docking on 13 of 21 (61.9%) transmembrane complexes in an established benchmark, more than shown by previous approaches. It was additionally tested on new datasets of 44 transmembrane complexes and 92 peripheral membrane protein complexes, of which it successfully modeled 35 (79.5%) and 15 (16.3%) complexes respectively. When non-blind orientations of peripheral targets were included, the number of successes increased to 54 (58.7%). We further demonstrate that Mem-LZerD produces complex models which are suitable for molecular dynamics simulation. Mem-LZerD is made available at https://lzerd.kiharalab.org.

Fork coupling directs DNA replication elongation and termination

DNA replication is initiated at multiple loci to ensure timely duplication of eukaryotic genomes. Sister replication forks progress bidirectionally, and replication terminates when two convergent forks encounter one another. To investigate the coordination of replication forks, we developed a replication-associated in situ HiC method to capture chromatin interactions involving nascent DNA. We identify more than 2000 fountain-like structures of chromatin contacts in human and mouse genomes, indicative of coupling of DNA replication forks. Replication fork interaction not only occurs between sister forks but also involves forks from two distinct origins to predetermine replication termination. Termination-associated chromatin fountains are sensitive to replication stress and lead to coupled forks-associated genomic deletions in cancers. These findings reveal the spatial organization of DNA replication forks within the chromatin context.

Molecular recognition and binding between human plasminogen Kringle 5 and α-chain of human complement component C3b by frontal chromatography and dynamics simulation

The binding and molecular recognition between α-chain of human complement C3b (α-chain of C3b) and human plasminogen Kringle 5 (Kringle 5) were studied and explored by frontal chromatography and dynamics simulation in the combination of bio-specific technologies. The specific interaction between the α-chain of C3b and Kringle 5 was initially confirmed by ligand blot and ELISA (Kd = 4.243×10-6 L/mol). Furthermore, the binding determination conducted via frontal chromatography showed that the presence of a single binding site between them, with the binding constant of 2.98 × 105 L/mol. Then the molecular recognition by dynamics simulation and molecular docking showed that there were 9 and 13 amino acid residues respective in the Kringle 5 and α-chain of C3b directly implicated in the binding and the main stabilizing forces were electrostatic force (-55.99 ± 11.82 kcal/mol) and Van der Waals forces (-42.70 ± 3.45 kcal/mol). Additionally, a loop structure (65-71) in Kringle 5 underwent a conformational change from a random structure to an α-helix and a loop structure (417-425) in α-chain of C3b was closer to the molecular center, both of them were more conducive to the binding between them. Meanwhile, the involvement of the lysine binding site of Kringle 5 played an important role in the binding process. In addition, the erythrocyte-antibody complement rosette assay substantiated that the presence of Kringle 5 hindered the transportation of α-chain of C3b to antigen-antibody complex in a dose-dependent manner. These findings collectively indicated that the α-chain of C3b is very likely a receptor protein for Kringle 5, which provides a methodology for other similar investigations and valuable insights into expansion of the pharmacological effects and potential application of Kringle 5 in immune-related diseases.