Functional aspects of protein flexibility

The Role of Flexibility in the Bioactivity of Short α-Helical Antimicrobial Peptides

The formation of aqueous pores through the interaction of amphipathic peptides is a process facilitated by the conformational dynamics typical of these biomolecules. Prior to their insertion with the membrane, these peptides go through several conformational states until they finally reach a stable α-helical structure. The conformational dynamics of these pore-forming peptides, α-PFP, is, thus, encoded in their amino acid sequence, which also predetermines their intrinsic flexibility. However, although the role of flexibility is widely recognized as fundamental in their bioactivity, it is still unclear whether this parameter is indeed decisive, as there are reports favoring the view of highly disruptive flexible peptides and others where relative rigidity also predetermines high rates of permeability across membranes. In this review we discuss in depth all those aspects linked to the conformational dynamics of these small biomolecules and which depend on the composition, sequence and dynamic performance both in aqueous phase and in close interaction with phospholipids. In addition, evidence is provided for the contribution of the known carboxyamidation in some well-studied α-PFPs, which are preferentially associated with sequences intrinsically more rigid than those not amidated and generally more flexible than the former. Taken together, this information is of great relevance for the optimization of new antibiotic peptides.

Computational analysis of polymorphic residues in maltose and maltotriose transporters of a wild Saccharomyces cerevisiae strain

The metabolism of maltose and maltotriose, the primary sugars in brewing wort, depends on an efficient transport system. However, most Saccharomyces cerevisiae strains transport maltotriose inefficiently, leaving residual α-glucosides in the final product. Proteins involved in maltotriose transport exhibit diverse polymorphic sequences linked to sugar transport efficiency. In this study, a wild S. cerevisiae strain was placed under adaptive selection, resulting in a strain with a 65 and 44% increase in maltose and maltotriose transport rates, respectively. Genes encoding maltose and maltotriose transporters, including MALx1, MPHx, and AGT1, were detected in both the native and adapted strains. One variant of Mal31p, carrying a polymorphism at position 371 in transmembrane helix 7, was identified. This helix has been reported to have a high likelihood of undergoing polymorphisms. Bioinformatics analysis revealed structural changes affecting substrate interactions and channel dynamics, with the polymorphism conferring greater protein flexibility and reducing electrostatic interactions. These results suggest that the residue at position 371 in maltose and maltotriose transporters is a key element distinct from those previously reported. Additionally, we propose a significant set of polymorphic residues within these transporters potentially resulting from the evolution of these proteins.

Data-driven evaluation of suitable immunogens for improved antibody selection

Antibodies are indispensable in laboratory and clinical applications due to their high specificity and affinity for protein antigens. However, selecting the right protein fragments as immunogens for antibody production remains challenging. Leveraging the Human Protein Atlas, this study systematically evaluates immunogen properties aiming to identify key factors that influence their suitability. Antibodies were classified as successful or unsuccessful based on standardized validation experiments, and the structural and functional properties of their immunogens were analyzed. Results indicated that longer immunogens often resulted in more successful but less specific antibodies. Shorter immunogens (50 residues or fewer) with disordered or unfolded regions at the N- or C-terminus and long coil stretches were more likely to generate successful antibodies. Conversely, immunogens with high beta sheet content, transmembrane regions, or disulfide bridges were associated with poorer antibody performance. Post-translational modification sites within immunogens appeared to mark beneficial regions for antibody generation. To support antibody selection, a novel R package, immunogenViewer, was developed, enabling researchers to easily apply these insights when immunogen sequences are disclosed. By providing a deeper understanding of immunogen suitability, this study promotes the development of more effective antibodies, ultimately addressing issues of reproducibility and reliability in antibody-based research. The findings are highly relevant to the research community, as end users often lack control over the immunogen selection process in antibody production. The R package is freely available as part of Bioconductor: https://bioconductor.org/packages/release/bioc/html/immunogenViewer.html.

Hyaluronic acid-silybin conjugate for the preparation of multifunctional, biomimetic, vancomycin-loaded self-assembled polymersomes against bacterial sepsis

Sepsis, a life-threatening disruption, remains a significant global healthcare challenge that urgently needs novel strategies to improve management. This study aimed to develop multifunctional vancomycin-loaded polymersomes (VCM-HA-SIL-Ps) using a novel hyaluronic acid-silybin (HA-SIL) conjugate to target the TLR inflammatory pathway and enhance VCM's efficacy against bacterial sepsis. HA-SIL was synthesized and characterized by FT-IR, UV-Vis spectroscopy, and 1H NMR. The biomimetic properties of HA-SIL were confirmed via in silico (-73.35 kcal/mol) and in vitro (dissociation constant = 2.872 μM) binding affinity studies against TLR2. VCM-HA-SIL-Ps exhibited appropriate physicochemical properties, biocompatibility, and stability. VCM-HA-SIL-Ps sustained VCM release for 48 h, achieving 73.38 % cumulative release. In vitro antibacterial studies showed that VCM-HA-SIL-Ps had superior minimum inhibitory concentration against sensitive and resistant Staphylococcus aureus and faster bacterial killing, compared to free VCM. Additionally, VCM-HA-SIL-Ps demonstrated excellent DPPH radicals scavenging and effective anti-inflammatory activity on bacterial toxin-stimulated cells. Finally, in a mouse model of MRSA-induced sepsis, VCM-HA-SIL-Ps achieved 100 % bacterial eradication, significantly reduced pro-inflammatory markers (IL-6, TNF-α, IL-1β by 2.9-, 1.8-, and 5-fold, respectively), and minimized organ damage. Collectively, these findings demonstrate the potential of HA-SIL as a novel multifunctional adjuvant for effective antibiotic delivery against bacterial sepsis.

Multiscale Differential Geometry Learning for Protein Flexibility Analysis

Protein structural fluctuations, measured by Debye-Waller factors or B-factors, are known to be closely associated with protein flexibility and function. Theoretical approaches have also been developed to predict B-factor values, which reflect protein flexibility. Previous models have made significant strides in analyzing B-factors by fitting experimental data. In this study, we propose a novel approach for B-factor prediction using differential geometry theory, based on the assumption that the intrinsic properties of proteins reside on a family of low-dimensional manifolds embedded within the high-dimensional space of protein structures. By analyzing the mean and Gaussian curvatures of a set of low-dimensional manifolds defined by kernel functions, we develop effective and robust multiscale differential geometry (mDG) models. Our mDG model demonstrates a 27% increase in accuracy compared to the classical Gaussian network model (GNM) in predicting B-factors for a dataset of 364 proteins. Additionally, by incorporating both global and local protein features, we construct a highly effective machine-learning model for the blind prediction of B-factors. Extensive least-squares approximations and machine learning-based blind predictions validate the effectiveness of the mDG modeling approach for B-factor predictions.

Pitfalls in measurements of R1 relaxation rates of protein backbone 15N nuclei

The dynamics of the backbone and side-chains of protein are routinely studied by interpreting experimentally determined 15N spin relaxation rates. R1(15N), the longitudinal relaxation rate, reports on fast motions and encodes, together with the transverse relaxation R2, structural information about the shape of the molecule and the orientation of the amide bond vectors in the internal diffusion frame. Determining error-free 15N longitudinal relaxation rates remains a challenge for small, disordered, and medium-sized proteins. Here, we show that mono-exponential fitting is sufficient, with no statistical preference for bi-exponential fitting up to 800 MHz. A detailed comparison of the TROSY and HSQC techniques at medium and high fields showed no statistically significant differences. The least error-prone DD/CSA interference removal technique is the selective inversion of amide signals while avoiding water resonance. The exchange of amide with solvent deuterons appears to affect the rate R1 of solvent-exposed amides in all fields tested and in each DD/CSA interference removal technique in a statistically significant manner. In summary, the most accurate R1(15N) rates in proteins are achieved by selective amide inversion, without the addition of D2O. Importantly, at high magnetic fields stronger than 800 MHz, when non-mono-exponential decay is involved, it is advisable to consider elimination of the shortest delays (typically up to 0.32 s) or bi-exponential fitting.

Flexibility-Induced Collective Behavior Drives Symmetry Breaking in Discrimination of Undesired Ions

Structure flexibility is essential for the biological function of proteins. At the same time, many proteins need to discriminate ligands with subtle differences, with one example being ion selectivity. Investigating the mechanisms by which flexible proteins achieve such precise discrimination is crucial for advancing our understanding of their functions. In this work, we study transporter KCC4, which undergoes continuous conformation changes during ion transport and can realize K+ over Na+ selectivity. Our findings reveal that the center of the binding site no longer represents a stable equilibrium for the undesired Na+, and its binding mode exhibits bifurcation. Interestingly, protein conformation fluctuation can induce collective behavior throughout the entire binding region, which contributes to this bifurcation. Thus, the symmetry of the binding mode decreases from the inherent T d symmetry to a C2v symmetry, and the binding stability of Na+ is largely reduced. A similar phenomenon is observed in a GPCR, β2-AR, where a less favored ligand forms a biased binding mode with reduced stability. The mechanism underlying the selectivity in such flexible regions could be interpreted as spontaneous symmetry breaking, which may represent a general mechanism by which flexible proteins achieve efficient ligand discrimination.

AlphaFold and what is next: bridging functional, systems and structural biology

INTRODUCTION

The DeepMind's AlphaFold (AF) has revolutionized biomedical and biocience research by providing both experts and non-experts with an invaluable tool for predicting protein structures. However, while AF is highly effective for predicting structures of rigid and globular proteins, it is not able to fully capture the dynamics, conformational variability, and interactions of proteins with ligands and other biomacromolecules.

AREAS COVERED

In this review, we present a comprehensive overview of the latest advancements in 3D model predictions for biomacromolecules using AF. We also provide a detailed analysis its of strengths and limitations, and explore more recent iterations, modifications, and practical applications of this strategy. Moreover, we map the path forward for expanding the landscape of AF toward predicting structures of every protein and peptide, and their interactions in the proteome in the most physiologically relevant form. This discussion is based on an extensive literature search performed using PubMed and Google Scholar.

EXPERT OPINION

While significant progress has been made to enhance AF's modeling capabilities, we argue that a combined approach integrating both various in silico and in vitro methods will be most beneficial for the future of structural biology, bridging the gaps between static and dynamic features of proteins and their functions.

Combining Fundamental Kinetics and Standard Alkylation Assays to Prioritize Lead-Like KRAS G12C Inhibitors

We measure the fundamental rate constants of internally discovered KRAS G12C inhibitors to demonstrate how kinetic analyses can be integrated with standard biochemical and cell-based assays for more optimal biophysical compound prioritization. In this proof-of-principle study, we characterize three irreversible covalent inhibitors targeting the mutant cysteine at the switch II binding pocket. We estimate the three fundamental kinetic rate constants (k on , k off , k inact ) that define the contributions of affinity and inactivation to the overall alkylation rate for a more complete biophysical characterization. These parameters are typically unavailable and are generally approximated by a single overall alkylation rate constant (k alk ), where the relative contributions of affinity and inactivation remain unknown. We demonstrate that the alkylation rate constant sacrifices valuable mechanistic information leading to higher risk of suboptimal compound prioritization. Estimation of the three fundamental kinetic rate constants was made possible by developing label-free surface plasmon resonance (SPR) methodologies adapted to measure transient binding using standard SPR equipment. Binding enthalpy was measured by Eyring transition state analysis, which can also benefit compound prioritization. We illustrate how these methodologies can enable more reliable prioritization of lead-like compounds when combined with standard orthogonal assays in a typical lead optimization setting.

Targeting mTOR Kinase with Natural Compounds: Potent ATP-Competitive Inhibition Through Enhanced Binding Mechanisms

Background/Objectives: The mammalian target of the rapamycin (mTOR) signaling pathway is a central regulator of cell growth, proliferation, metabolism, and survival. Dysregulation of mTOR signaling contributes to many human diseases, including cancer, diabetes, and obesity. Therefore, inhibitors against mTOR's catalytic kinase domain (KD) have been developed and have shown significant antitumor activities, making it a promising therapeutic target. The ATP-KD interaction is particularly important for mTOR to exert its cellular functions, and such inhibitors have demonstrated efficient attenuation of overall mTOR activity. Methods: In this study, we screened the Traditional Chinese Medicine (TCM) database, which enlists natural products that capture the relationships between drugs targets and diseases. Our aim was to identify potential ATP-competitive agonists that target the mTOR-KD and compete with ATP to bind the mTOR-KD serving as potential potent mTOR inhibitors. Results: We identified two compounds that demonstrated interatomic interactions similar to those of ATP-mTOR. The conformational stability and dynamic features of the mTOR-KD bound to the selected compounds were tested by subjecting each complex to 200 ns molecular dynamic (MD) simulations and molecular mechanics/generalized Born surface area (MM/GBSA) to extract free binding energies. We show the effectiveness of both compounds in forming stable complexes with the mTOR-KD, which is more effective than the mTOR-KD-ATP complex with more robust binding affinities. Conclusions: This study implies that both compounds could serve as potential therapeutic inhibitors of mTOR, regulating its function and, therefore, mitigating human disease progression.

The synergistic effects of rice bran rancidity and dephenolization on digestive properties of rice bran protein

Both rice bran (RB) rancidity and dephenolization could affect the structural characteristics and phenolics composition of rice bran protein (RBP), thereby affecting RBP digestibility. The synergistic effects of RB rancidity and dephenolization on RBP digestibility were investigated. Excessive RB rancidity (RB stored for 10 d) and non-dephenolization reduced RBP digestibility, while moderate RB rancidity (RB stored for 1 d) combined with dephenolization improved RBP digestibility to a maximum of 74.19%. Dephenolization reduced the antioxidant capacities of RBP digestive products. The digestibility of non-dephenolized RBP (NDRBP) was significantly (P < 0.05) related with its carbonyl content, surface hydrophobicity, and ζ-potential. The digestibility of dephenolized RBP (DRBP) was significantly related with its β-sheet structure content, surface hydrophobicity, ζ-potential, and average particle size. Overall, moderate RB rancidity combined with dephenolization enhanced RBP digestibility by reducing the non-competitive inhibition of endogenous phenolics on protease and regulating the spatial structural characteristics of RBP.

Systematic analysis of the relationship between fold-dependent flexibility and artificial intelligence protein structure prediction

Artificial Intelligence (AI)-based deep learning methods for predicting protein structures are reshaping knowledge development and scientific discovery. Recent large-scale application of AI models for protein structure prediction has changed perceptions about complicated biological problems and empowered a new generation of structure-based hypothesis testing. It is well-recognized that proteins have a modular organization according to archetypal folds. However, it is yet to be determined if predicted structures are tuned to one conformation of flexible proteins or if they represent average conformations. Further, whether or not the answer is protein fold-dependent. Therefore, in this study, we analyzed 2878 proteins with at least ten distinct experimental structures available, from which we can estimate protein topological rigidity verses heterogeneity from experimental measurements. We found that AlphaFold v2 (AF2) predictions consistently return one specific form to high accuracy, with 99.68% of distinct folds (n = 623 out of 628) having an experimental structure within 2.5Å RMSD from a predicted structure. Yet, 27.70% and 10.82% of folds (174 and 68 out of 628 folds) have at least one experimental structure over 2.5Å and 5Å RMSD, respectively, from their AI-predicted structure. This information is important for how researchers apply and interpret the output of AF2 and similar tools. Additionally, it enabled us to score fold types according to how homogeneous versus heterogeneous their conformations are. Importantly, folds with high heterogeneity are enriched among proteins which regulate vital biological processes including immune cell differentiation, immune activation, and metabolism. This result demonstrates that a large amount of protein fold flexibility has already been experimentally measured, is vital for critical cellular processes, and is currently unaccounted for in structure prediction databases. Therefore, the structure-prediction revolution begets the protein dynamics revolution!

Investigating the role of non-synonymous variant D67N of ADGRE2 in chronic myeloid leukemia

BACKGROUND

Chronic myeloid leukaemia (CML) is a type of blood cancer that begins in the hematopoietic stem cells. It is primarily characterized by a specific chromosomal aberration, the Philadelphia chromosome. While the fusion gene is a major contributor to CML, several other genes including ADGRE2, that are reported as highly expressed in hematopoietic stem cells and could be utilized as a therapeutic marker in leukemic patients are implicated in the disease's progression. Until recently, little research had been conducted to identify single nucleotide polymorphisms (SNPs) associated with CML. Therefore, this study aims to investigate the influence of non-synonymous variants on the structure and function of the gene encoding adhesion G protein-coupled receptor E2, ADGRE2, and to evaluate their association with CML and its clinical and pathological characteristics.

METHODS

Non-synonymous SNPs of ADGRE2 were retrieved from the ENSEMBL, COSMIC, and gnomAD genome browsers, and the pathogenicity of deleterious variants was assessed using several established computational tools, including SIFT, CADD, REVEL, PolyPhen, and MetaLR.

RESULTS

Various in silico analyses explored the impact of damaging SNP on the function, stability, and structure of EGF-like modules containing mucin-like hormone receptor-like2 (EMR2) protein encoded by the ADGRE2 gene. Genotype analysis was performed on collected blood samples, revealing that altered genotype TT of variant rs765071211 (C/T) was associated significantly with CML patients compared to the control. Further in vitro and in vivo analyses suggest that this SNP holds potential for clinical translation.

Disulfide Bond Engineering of Soluble ACE2 for Thermal Stability Enhancement

Although the primary pandemic of SARS-CoV-2 is over, there are concerns about the resurgence of the next wave of related viruses, including a wide range of variant viruses. The soluble ACE2 (sACE2) inhibits the SARS-CoV-2 spike protein ACE2 interaction and has potential as a variant-independent therapeutic against SARS-CoV-2. Here, we introduce novel disulfide bonds in the wild-type sACE2-Fc by structure-guided mutagenesis, aiming to improve its stability. The stability of each mutant was assessed by a thermal shift assay to screen mutants with increased thermal stability. As a result, we identified a mutant sACE2-Fc with a significantly increased melting temperature. X-ray crystal structure determination of the sACE2 mutant confirmed the correct formation of the designed disulfide bond, and there were no significant structural disturbances. We also proved that the thermostable sACE2-Fc preserved the spike protein binding affinity comparable to the wild-type sACE2-Fc in both molecular and cellular environments, suggesting its therapeutic potential.

A Critical Review of Short Antimicrobial Peptides from Scorpion Venoms, Their Physicochemical Attributes, and Potential for the Development of New Drugs

Scorpion venoms have proven to be excellent sources of antimicrobial agents. However, although many of them have been functionally characterized, they remain underutilized as pharmacological agents, despite their evident therapeutic potential. In this review, we discuss the physicochemical properties of short scorpion venom antimicrobial peptides (ssAMPs). Being generally short (13-25 aa) and amidated, their proven antimicrobial activity is generally explained by parameters such as their net charge, the hydrophobic moment, or the degree of helicity. However, for a complete understanding of their biological activities, also considering the properties of the target membranes is of great relevance. Here, with an extensive analysis of the physicochemical, structural, and thermodynamic parameters associated with these biomolecules, we propose a theoretical framework for the rational design of new antimicrobial drugs. Through a comparison of these physicochemical properties with the bioactivity of ssAMPs in pathogenic bacteria such as Staphylococcus aureus or Acinetobacter baumannii, it is evident that in addition to the net charge, the hydrophobic moment, electrostatic energy, or intrinsic flexibility are determining parameters to understand their performance. Although the correlation between these parameters is very complex, the consensus of our analysis suggests that there is a delicate balance between them and that modifying one affects the rest. Understanding the contribution of lipid composition to their bioactivities is also underestimated, which suggests that for each peptide, there is a physiological context to consider for the rational design of new drugs.

Binding Affinity Determination in Drug Design: Insights from Lock and Key, Induced Fit, Conformational Selection, and Inhibitor Trapping Models

Binding affinity is a fundamental parameter in drug design, describing the strength of the interaction between a molecule and its target protein. Accurately predicting binding affinity is crucial for the rapid development of novel therapeutics, the prioritization of promising candidates, and the optimization of their properties through rational design strategies. Binding affinity is determined by the mechanism of recognition between proteins and ligands. Various models, including the lock and key, induced fit, and conformational selection, have been proposed to explain this recognition process. However, current computational strategies to predict binding affinity, which are based on these models, have yet to produce satisfactory results. This article explores the connection between binding affinity and these protein-ligand interaction models, highlighting that they offer an incomplete picture of the mechanism governing binding affinity. Specifically, current models primarily center on the binding of the ligand and do not address its dissociation. In this context, the concept of ligand trapping is introduced, which models the mechanisms of dissociation. When combined with the current models, this concept can provide a unified theoretical framework that may allow for the accurate determination of the ligands' binding affinity.

Analysis of the SARS-CoV-2 nsp12 P323L/A529V mutations: coeffect in the transiently peaking lineage C.36.3 on protein structure and response to treatment in Egyptian records

SARS-CoV-2 nsp12, the RNA-dependent RNA-polymerase plays a crucial role in virus replication. Monitoring the effect of its emerging mutants on viral replication and response to antiviral drugs is important. Nsp12 of two Egyptian isolates circulating in 2020 and 2021 were sequenced. Both isolates included P323L, one included the A529V. Tracking A529V mutant frequency, it relates to the transience peaked C.36.3 variant and its parent C.36, both peaked worldwide on February-August 2021, enlisted as high transmissible variants under investigation (VUI) on May 2021. Both Mutants were reported to originate from Egypt and showed an abrupt low frequency upon screening, we analyzed all 1104 nsp12 Egyptian sequences. A529V mutation was in 36 records with an abrupt low frequency on June 2021. As its possible reappearance might obligate actions for a candidate VUI, we analyzed the predicted co-effect of P323L and A529V mutations on protein stability and dynamics through protein structure simulations. Three available structures for drug-nsp12 interaction were used representing remdesivir, suramin and favipiravir drugs. Remdesivir and suramin showed an increase in structure stability and considerable change in flexibility while favipiravir showed an extreme interaction. Results predict a favored efficiency of the drugs except for favipiravir in case of the reported mutations.

ATLAS: protein flexibility description from atomistic molecular dynamics simulations

Dynamical behaviour is one of the most crucial protein characteristics. Despite the advances in the field of protein structure resolution and prediction, analysis and prediction of protein dynamic properties remains a major challenge, mostly due to the low accessibility of data and its diversity and heterogeneity. To address this issue, we present ATLAS, a database of standardised all-atom molecular dynamics simulations, accompanied by their analysis in the form of interactive diagrams and trajectory visualisation. ATLAS offers a large-scale view and valuable insights on protein dynamics for a large and representative set of proteins, by combining data obtained through molecular dynamics simulations with information extracted from experimental structures. Users can easily analyse dynamic properties of functional protein regions, such as domain limits (hinge positions) and residues involved in interaction with other biological molecules. Additionally, the database enables exploration of proteins with uncommon dynamic properties conditioned by their environment such as chameleon subsequences and Dual Personality Fragments. The ATLAS database is freely available at https://www.dsimb.inserm.fr/ATLAS.

Revealing the Role of the Arg and Lys in Shifting Paradigm from BTK Selective Inhibition to the BTK/HCK Dual Inhibition - Delving into the Inhibitory Activity of KIN-8194 against BTK, and HCK in the Treatment of Mutated BTKCys481 Waldenström Macroglobulinemia: A Computational Approach

BACKGROUND

Despite the early success of Bruton's tyrosine kinase (BTK) inhibitors in the treatment of Waldenström macroglobulinemia (WM), these single-target drug therapies have limitations in their clinical applications, such as drug resistance. Several alternative strategies have been developed, including the use of dual inhibitors, to maximize the therapeutic potential of these drugs.

OBJECTIVE

Recently, the pharmacological activity of KIN-8194 was repurposed to serve as a 'dual-target' inhibitor of BTK and Hematopoietic Cell Kinase (HCK). However, the structural dual inhibitory mechanism remains unexplored, hence the aim of this study.

METHODS

Conducting predictive pharmacokinetic profiling of KIN-8194, as well as demonstrating a comparative structural mechanism of inhibition against the above-mentioned enzymes.

RESULTS

Our results revealed favourable binding affinities of -20.17 kcal/mol, and -35.82 kcal/mol for KIN-8194 towards HCK and BTK, respectively. Catalytic residues Arg137/174 and Lys42/170 in BTK and Arg303 and Lys75/173/244/247 in HCK were identified as crucial mediators of the dual binding mechanism of KIN-8194, corroborated by high per-residue energy contributions and consistent high-affinity interactions of these residues. Prediction of the pharmacokinetics and physicochemical properties of KIN-8194 further established its inhibitory potential, evidenced by the favourable absorption, metabolism, excretion, and minimal toxicity properties. Structurally, KIN-8194 impacted the stability, flexibility, solvent-accessible surface area, and rigidity of BTK and HCK, characterized by various alterations observed in the bound and unbound structures, which proved enough to disrupt their biological function.

CONCLUSION

These structural insights provided a baseline for the understanding of the dual inhibitory activity of KIN- 8194. Establishing the cruciality of the interactions between the KIN-8194 and Arg and Lys residues could guide the structure-based design of novel dual BTK/HCK inhibitors with improved therapeutic activities.

Therapeutic Path to Triple Knockout: Investigating the Pan-inhibitory Mechanisms of AKT, CDK9, and TNKS2 by a Novel 2-phenylquinazolinone Derivative in Cancer Therapy- An In-silico Investigation Therapy

BACKGROUND

Blocking the oncogenic Wnt//β-catenin pathway has of late been investigated as a viable therapeutic approach in the treatment of cancer. This involves the multi-targeting of certain members of the tankyrase-kinase family; Tankyrase 2 (TNKS2), Protein Kinase B (AKT), and Cyclin- Dependent Kinase 9 (CDK9), which propagate the oncogenic Wnt/β-catenin signalling pathway.

METHODS

During a recent investigation, the pharmacological activity of 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one was repurposed to serve as a 'triple-target' inhibitor of TNKS2, AKT and CDK9. Yet, the molecular mechanism that surrounds its multi-targeting activity remains unanswered. As such, this study aims to explore the pan-inhibitory mechanism of 2-(4-aminophenyl)-7-chloro-3H-quinazolin- 4-one towards AKT, CDK9, and TNKS2, using in silico techniques.

RESULTS

Results revealed favourable binding affinities of -34.17 kcal/mol, -28.74 kcal/mol, and -27.30 kcal/mol for 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one towards TNKS2, CDK9, and AKT, respectively. Pan-inhibitory binding of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one is illustrated by close interaction with specific residues on tankyrase-kinase. Structurally, 2-(4-aminophenyl)-7-chloro- 3H-quinazolin-4-one had an impact on the flexibility, solvent-accessible surface area, and stability of all three proteins, which was illustrated by numerous modifications observed in the unbound as well as the bound states of the structures, which evidenced the disruption of their biological function. Prediction of the pharmacokinetics and physicochemical properties of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4- one further established its inhibitory potential, evidenced by the favourable absorption, metabolism, excretion, and minimal toxicity properties.

CONCLUSION

The following structural insights provide a starting point for understanding the paninhibitory activity of 2-(4-aminophenyl)-7-chloro-3H-quinazolin-4-one. Determining the criticality of the interactions that exist between the pyrimidine ring and catalytic residues could offer insight into the structure-based design of innovative tankyrase-kinase inhibitors with enhanced therapeutic effects.

Targeting structural flexibility in low density lipoprotein by integrating cryo-electron microscopy and high-speed atomic force microscopy

Low-density lipoprotein (LDL) plays a crucial role in cholesterol metabolism. Responsible for cholesterol transport from the liver to the organs, LDL accumulation in the arteries is a primary cause of cardiovascular diseases, such as atherosclerosis. This work focuses on the fundamental question of the LDL molecular structure, as well as the topology and molecular motions of apolipoprotein B-100 (apo B-100), which is addressed by single-particle cryo-electron microscopy (cryo-EM) and high-speed atomic force microscopy (HS-AFM). Our results suggest a revised model of the LDL core organization with respect to the cholesterol ester (CE) arrangement. In addition, a high-density region close to the flattened poles could be identified, likely enriched in free cholesterol. The most remarkable new details are two protrusions on the LDL surface, attributed to the protein apo B-100. HS-AFM adds the dimension of time and reveals for the first time a highly dynamic direct description of LDL, where we could follow large domain fluctuations of the protrusions in real time. To tackle the inherent flexibility and heterogeneity of LDL, the cryo-EM maps are further assessed by 3D variability analysis. Our study gives a detailed explanation how to approach the intrinsic flexibility of a complex system comprising lipids and protein.

Structure and dynamics of pteridine reductase 1: the key phenomena relevant to enzyme function and drug design

Pteridine reductase 1 (PTR1) is a folate and pterin pathway enzyme unique for pathogenic trypanosomatids. As a validated drug target, PTR1 has been the focus of recent research efforts aimed at finding more effective treatments against human parasitic diseases such as leishmaniasis or sleeping sickness. Previous PTR1-centered structural studies highlighted the enzyme characteristics, such as flexible regions around the active site, highly conserved structural waters, and species-specific differences in pocket properties and dynamics, which likely impacts the binding of natural substrates and inhibitors. Furthermore, several aspects of the PTR1 function, such as the substrate inhibition phenomenon and the level of ligand binding cooperativity in the enzyme homotetramer, likely related to the global enzyme dynamics, are poorly known at the molecular level. We postulate that future drug design efforts could greatly benefit from a better understanding of these phenomena through studying both the local and global PTR1 dynamics. This review highlights the key aspects of the PTR1 structure and dynamics relevant to structure-based drug design that could be effectively investigated by modeling approaches. Particular emphasis is given to the perspective of molecular dynamics, what has been accomplished in this area to date, and how modeling could impact the PTR1-targeted drug design in the future.

Different aspects in explaining how mutations could affect the binding mechanism of receptor binding domain of SARS-CoV-2 spike protein in interaction with ACE2

During replication, some mutations occur in SARS-CoV-2, the causal agent of COVID-19, leading to the emergence of different variants of the virus. The mutations that accrue in different variants of the virus, influence the virus' ability to bind to human cell receptors and ability to evade the human immune system, the rate of viral transmission, and effectiveness of vaccines. Some of these mutations occur in the receptor binding domain (RBD) of the spike protein that may change the affinity of the virus for the ACE2 receptor. In this study, several in silico techniques, such as MD and SMD simulations, were used to perform comparative studies to deeply understand the effect of mutation on structural and functional details of the interaction of the spike glycoprotein of SARS-CoV-2, with the ACE2 receptor. According to our results, the mutation in the RBD associated with the Omicron variant increase binding affinity of the virus to ACE2 when compared to wild type and Delta variants. We also observed that the flexibility of the spike protein of the Omicron variant was lower than in comparison to other variants. In summary, different mutations in variants of the virus can have an effect on the binding mechanism of the receptor binding domain of the virus with ACE2.

Engineering gain-of-function mutants of a WW domain by dynamics and structural analysis

Proteins gain optimal fitness such as foldability and function through evolutionary selection. However, classical studies have found that evolutionarily designed protein sequences alone cannot guarantee foldability, or at least not without considering local contacts associated with the initial folding steps. We previously showed that foldability and function can be restored by removing frustration in the folding energy landscape of a model WW domain protein, CC16, which was designed based on Statistical Coupling Analysis (SCA). Substitutions ensuring the formation of five local contacts identified as "on-path" were selected using the closest homolog native folded sequence, N21. Surprisingly, the resulting sequence, CC16-N21, bound to Group I peptides, while N21 did not. Here, we identified single-point mutations that enable N21 to bind a Group I peptide ligand through structure and dynamic-based computational design. Comparison of the docked position of the CC16-N21/ligand complex with the N21 structure showed that residues at positions 9 and 19 are important for peptide binding, whereas the dynamic profiles identified position 10 as allosterically coupled to the binding site and exhibiting different dynamics between N21 and CC16-N21. We found that swapping these positions in N21 with matched residues from CC16-N21 recovers nature-like binding affinity to N21. This study validates the use of dynamic profiles as guiding principles for affecting the binding affinity of small proteins.

Experimentally Observed Conformational Changes in Antibodies Due to Binding and Paratope-epitope Asymmetries

Understanding binding related changes in antibody conformations is important for epitope prediction and antibody refinement. The increase of available data in the PDB allowed a more detailed investigation of the conformational landscape for free and bound antibodies. A dataset containing a total of 835 unique PDB entries of antibodies that were crystallized in complex with their antigen and in a free state was constructed. It was examined for binding related conformation changes. We present further evidence supporting the theory of a pre-existing-equilibrium in experimental data. Multiple sequence alignments did not show binding induced tendencies in the solvent accessibility of residues in any specific position. Evaluating the changes in solvent accessibility per residue revealed a certain binding induced increase for several amino acids. Antibody-antigen interaction statistics were established and quantify a significant directional asymmetry between many interacting antibody and antigen residue pairs, especially a richness in tyrosine in the antibody epitope compared to its paratope. This asymmetry could potentially facilitate an increase in the success rate of computationally guided antibody refinement.

Substitution of Coxsackievirus A16 VP1 BC and EF Loop Altered the Protective Immune Responses in Chimera Enterovirus A71

Hand, foot and mouth disease (HFMD) is a childhood disease caused by enterovirus A71 (EV-A71) and coxsackievirus A16 (CV-A16). Capsid loops are important epitopes for EV-A71 and CV-A16. Seven chimeric EV-A71 (ChiE71) involving VP1 BC (45.5% similarity), DE, EF, GH and HI loops, VP2 EF loop and VP3 GH loop (91.3% similarity) were substituted with corresponding CV-A16 loops. Only ChiE71-1-BC, ChiE71-1-EF, ChiE71-1-GH and ChiE71-3-GH were viable. EV-A71 and CV-A16 antiserum neutralized ChiE71-1-BC and ChiE71-1-EF. Mice immunized with inactivated ChiE71 elicited high IgG, IFN-γ, IL-2, IL-4 and IL-10. Neonatal mice receiving passive transfer of WT EV-A71, ChiE71-1-EF and ChiE71-1-BC immune sera had 100%, 80.0% and no survival, respectively, against lethal challenges with EV-A71, suggesting that the substituted CV-A16 loops disrupted EV-A71 immunogenicity. Passive transfer of CV-A16, ChiE71-1-EF and ChiE71-1-BC immune sera provided 40.0%, 20.0% and 42.9% survival, respectively, against CV-A16. One-day-old neonatal mice immunized with WT EV-A71, ChiE71-1-BC, ChiE71-1-EF and CV-A16 achieved 62.5%, 60.0%, 57.1%, and no survival, respectively, after the EV-A71 challenge. Active immunization using CV-A16 provided full protection while WT EV-A71, ChiE71-1-BC and ChiE71-1-EF immunization showed partial cross-protection in CV-A16 lethal challenge with survival rates of 50.0%, 20.0% and 40%, respectively. Disruption of a capsid loop could affect virus immunogenicity, and future vaccine design should include conservation of the enterovirus capsid loops.

Model of ligand-triggered information transmission in G-protein coupled receptor complexes

We present a model for the effects of ligands on information transmission in G-Protein Coupled Receptor (GPCR) complexes. The model is built ab initio entirely on principles of statistical mechanics and tenets of information transmission theory and was validated in part using agonist-induced effector activity and signaling bias for the angiotensin- and adrenergic-mediated signaling pathways, with in vitro observations of phosphorylation sites on the C tail of the GPCR complex, and single-cell information-transmission experiments. The model extends traditional kinetic models that form the basis for many existing models of GPCR signaling. It is based on maximizing the rates of entropy production and information transmission through the GPCR complex. The model predicts that (1) phosphatase-catalyzed reactions, as opposed to kinase-catalyzed reactions, on the C-tail and internal loops of the GPCR are responsible for controlling the signaling activity, (2) signaling favors the statistical balance of the number of switches in the ON state and the number in the OFF state, and (3) biased-signaling response depends discontinuously on ligand concentration.

Nanoparticle Targeting with Antibodies in the Central Nervous System

Treatments for disease in the central nervous system (CNS) are limited because of difficulties in agent penetration through the blood-brain barrier, achieving optimal dosing, and mitigating off-target effects. The prospect of precision medicine in CNS treatment suggests an opportunity for therapeutic nanotechnology, which offers tunability and adaptability to address specific diseases as well as targetability when combined with antibodies (Abs). Here, we review the strategies to attach Abs to nanoparticles (NPs), including conventional approaches of chemisorption and physisorption as well as attempts to combine irreversible Ab immobilization with controlled orientation. We also summarize trends that have been observed through studies of systemically delivered Ab-NP conjugates in animals. Finally, we discuss the future outlook for Ab-NPs to deliver therapeutics into the CNS.

Insights into receptor structure and dynamics at the surface of living cells

Evaluating protein structures in living cells remains a challenge. Here, we investigate Interleukin-4 receptor alpha (IL-4Rα) into which the non-canonical amino acid bicyclo[6.1.0]nonyne-lysine (BCNK) is incorporated by genetic code expansion. Bioorthogonal click labeling is performed with tetrazine-conjugated dyes. To quantify the reaction yield in situ, we develop brightness-calibrated ratiometric imaging, a protocol where fluorescent signals in confocal multi-color images are ascribed to local concentrations. Screening receptor mutants bearing BCNK in the extracellular domain uncovered site-specific variations of both click efficiency and Interleukin-4 binding affinity, indicating subtle well-defined structural perturbations. Molecular dynamics and continuum electrostatics calculations suggest solvent polarization to determine site-specific variations of BCNK reactivity. Strikingly, signatures of differential click efficiency, measured for IL-4Rα in ligand-bound and free form, mirror sub-angstrom deformations of the protein backbone at corresponding locations. Thus, click efficiency by itself represents a remarkably informative readout linked to protein structure and dynamics in the native plasma membrane.

Slow conformational changes in the rigid and highly stable chymotrypsin inhibitor 2

Slow conformational changes are often directly linked to protein function. It is however less clear how such processes may perturb the overall folding stability of a protein. We previously found that the stabilizing double mutant L49I/I57V in the small protein chymotrypsin inhibitor 2 from barley led to distributed increased nanosecond and faster dynamics. Here we asked what effects the L49I and I57V substitutions, either individually or together, have on the slow conformational dynamics of CI2. We used ¹⁵ N CPMG spin relaxation dispersion experiments to measure the kinetics, thermodynamics and structural changes associated with slow conformational change in CI2. These changes result in an excited state that is populated to 4.3% at 1 °C. As the temperature is increased the population of the excited state decreases. Structural changes in the excited state are associated with residues that interact with water molecules that have well defined positions and are found at these positions in all crystal structures of CI2. The substitutions in CI2 have only little effect on the structure of the excited state whereas the stability of the excited state to some extent follows the stability of the main state. The minor state is thus most populated for the most stable CI2 variant and least populated for the least stable variant. We hypothesize that the interactions between the substituted residues and the well-ordered water molecules links subtle structural changes around the substituted residues to the region in the protein that experience slow conformational changes. This article is protected by copyright. All rights reserved.

Proteins turn "Proteans" - The over 40-year delayed paradigm shift in structural biology: From "native proteins in uniquely defined configurations" to "intrinsically disordered proteins"

The current millennium brought up a revolutionary paradigm shift in molecular biology: many operative proteins, rather than being quasi-rigid polypeptide chains folded into unique configurations - as believed throughout most of the past century - are now known to be intrinsically disordered, dynamic, pleomorphic, and multifunctional structures with stochastic behaviors. Yet, part of this knowledge, including suggestions about possible mechanisms and plenty of evidence for the same, became available by the 1950s and 1960s to remain then nearly forgotten for over 40 years. Here, we review the main steps toward the classic notions about protein structures, as well as the neglected precedents of present views, discuss possible explanations for such long oblivion, and offer a sketch of the current panorama in this field.

Structural Flexibility of Proteins Dramatically Alters Membrane Stability─A Novel Aspect of Lipid-Protein Interaction

Protein isoforms are structural variants with changes in the overall flexibility predominantly at the tertiary level. For membrane associated proteins, such structural flexibility or rigidity affects membrane stability by playing modulatory roles in lipid-protein interaction. Herein, we investigate the protein chain flexibility mediated changes in the mechanistic behavior of phospholipid model membranes in the presence of two well-known isoforms, erythroid (ER) and nonerythroid (NER) spectrin. We show dramatic alterations of membrane elasticity and stability induced by spectrin in the Langmuir monolayers of phosphatidylocholine (PC) and phosphatidylethanolamine (PE) by a combination of isobaric relaxation, surface pressure-area isotherm, X-ray scattering, and microscopy measurements. The NER spectrin drives all monolayers to possess an approximately equal stability, and that required 25-fold increase and 5-fold decrease of stability in PC and PE monolayers, respectively. The untilting transition of the PC membrane in the presence of NER spectrin observed in X-ray measurements can explain better membrane packing and stability.

Toward Accurate Coarse-Grained Simulations of Disordered Proteins and Their Dynamic Interactions

Intrinsically disordered proteins (IDPs) play crucial roles in cellular regulatory networks and are now recognized to often remain highly dynamic even in specific interactions and assemblies. Accurate description of these dynamic interactions is extremely challenging using atomistic simulations because of the prohibitive computational cost. Efficient coarse-grained approaches could offer an effective solution to overcome this bottleneck if they could provide an accurate description of key local and global properties of IDPs in both unbound and bound states. The recently developed hybrid-resolution (HyRes) protein model has been shown to be capable of providing a semiquantitative description of the secondary structure propensities of IDPs. Here, we show that greatly improved description of global structures and transient interactions can be achieved by introducing a solvent-accessible surface area-based implicit solvent term followed by reoptimization of effective interaction strengths. The new model, termed HyRes II, can semiquantitatively reproduce a wide range of local and global structural properties of a set of IDPs of various lengths and complexities. It can also distinguish the level of compaction between folded proteins and IDPs. In particular, applied to the disordered N-terminal transactivation domain (TAD) of tumor suppressor p53, HyRes II is able to recapitulate various nontrivial structural properties compared to experimental results, some of them to a level of accuracy that is almost comparable to results from atomistic explicit solvent simulations. Furthermore, we demonstrate that HyRes II can be used to simulate the dynamic interactions of TAD with the DNA-binding domain of p53, generating structural ensembles that are highly consistent with existing NMR data. We anticipate that HyRes II will provide an efficient and relatively reliable tool toward accurate coarse-grained simulations of dynamic protein interactions.

What Makes GPCRs from Different Families Bind to the Same Ligand?

G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. In this work, we set out to computationally uncover and understand the binding of a single ligand to GPCRs from several different families. Three-dimensional structural comparisons of the GPCRs that bind to the same ligand revealed local 3D structural similarities and often these regions overlap with locations of binding pockets. These pockets were found to be similar (based on backbone geometry and side-chain orientation using APoc), and they correlate positively with electrostatic properties of the pockets. Moreover, the more similar the pockets, the more likely a ligand binding to the pockets will interact with similar residues, have similar conformations, and produce similar binding affinities across the pockets. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs.

Can DyeCycling break the photobleaching limit in single-molecule FRET?

Biomolecular systems, such as proteins, crucially rely on dynamic processes at the nanoscale. Detecting biomolecular nanodynamics is therefore key to obtaining a mechanistic understanding of the energies and molecular driving forces that control biomolecular systems. Single-molecule fluorescence resonance energy transfer (smFRET) is a powerful technique to observe in real-time how a single biomolecule proceeds through its functional cycle involving a sequence of distinct structural states. Currently, this technique is fundamentally limited by irreversible photobleaching, causing the untimely end of the experiment and thus, a narrow temporal bandwidth of ≤ 3 orders of magnitude. Here, we introduce "DyeCycling", a measurement scheme with which we aim to break the photobleaching limit in smFRET. We introduce the concept of spontaneous dye replacement by simulations, and as an experimental proof-of-concept, we demonstrate the intermittent observation of a single biomolecule for one hour with a time resolution of milliseconds. Theoretically, DyeCycling can provide > 100-fold more information per single molecule than conventional smFRET. We discuss the experimental implementation of DyeCycling, its current and fundamental limitations, and specific biological use cases. Given its general simplicity and versatility, DyeCycling has the potential to revolutionize the field of time-resolved smFRET, where it may serve to unravel a wealth of biomolecular dynamics by bridging from milliseconds to the hour range.

Electronic Supplementary Material

Supplementary material is available for this article at 10.1007/s12274-022-4420-5 and is accessible for authorized users.

Protein Fluctuations in Response to Random External Forces

Elastic network models (ENMs) have been widely used in the last decades to investigate protein motions and dynamics. There the intrinsic fluctuations based on the isolated structures are obtained from the normal modes of these elastic networks, and they generally show good agreement with the B-factors extracted from X-ray crystallographic experiments, which are commonly considered to be indicators of protein flexibility. In this paper, we propose a new approach to analyze protein fluctuations and flexibility, which has a more appropriate physical basis. It is based on the application of random forces to the protein ENM to simulate the effects of collisions of solvent on a protein structure. For this purpose, we consider both the Cα-atom coarse-grained anisotropic network model (ANM) and an elastic network augmented with points included for the crystallized waters. We apply random forces to these protein networks everywhere, as well as only on the protein surface alone. Despite the randomness of the directions of the applied perturbations, the computed average displacements of the protein network show a remarkably good agreement with the experimental B-factors. In particular, for our set of 919 protein structures, we find that the highest correlation with the B-factors is obtained when applying forces to the external surface of the water-augmented ANM (an overall gain of 3% in the Pearson’s coefficient for the entire dataset, with improvements up to 30% for individual proteins), rather than when evaluating the fluctuations obtained from the normal modes of a standard Cα-atom coarse-grained ANM. It follows that protein fluctuations should be considered not just as the intrinsic fluctuations of the internal dynamics, but also equally well as responses to external solvent forces, or as a combination of both.

Conformational ensembles of intrinsically disordered proteins and flexible multidomain proteins

Intrinsically disordered proteins (IDPs) and multidomain proteins with flexible linkers show a high level of structural heterogeneity and are best described by ensembles consisting of multiple conformations with associated thermodynamic weights. Determining conformational ensembles usually involves the integration of biophysical experiments and computational models. In this review, we discuss current approaches to determine conformational ensembles of IDPs and multidomain proteins, including the choice of biophysical experiments, computational models used to sample protein conformations, models to calculate experimental observables from protein structure, and methods to refine ensembles against experimental data. We also provide examples of recent applications of integrative conformational ensemble determination to study IDPs and multidomain proteins and suggest future directions for research in the field.

Molecular Simulations of Intrinsically Disordered Proteins and Their Binding Mechanisms

Intrinsically disordered proteins (IDPs) lack well-defined secondary or tertiary structures in solution but are found to be involved in a wide range of critical cellular processes that highlight their functional importance. IDPs usually undergo folding upon binding to their targets. Such binding coupled to folding behavior has widened our perspective on the protein structure-dynamics-function paradigm in molecular biology. However, characterizing the folding upon binding mechanism of IDPs experimentally remains quite challenging. Molecular simulations emerge as a potentially powerful tool that offers information complementary to experiments. Here we present a general computational framework for the molecular simulations of IDP folding upon binding processes that combines all-atom molecular dynamics (MD) and coarse-grained simulations. The classical all-atom molecular dynamics approach using GPU acceleration allows the researcher to explore the properties of the IDP conformational ensemble, whereas coarse-grained structure-based models implemented with parameters carefully calibrated to available experimental measurements can be used to simulate the entire folding upon binding process. We also discuss a set of tools for the analysis of MD trajectories and describe the details of the computational protocol to follow so that it can be adapted by the user to study any IDP in isolation and in complex with partners.

Protein Chemistry Combined with Mass Spectrometry for Protein Structure Determination

The advent of soft-ionization mass spectrometry for biomolecules has opened up new possibilities for the structural analysis of proteins. Combining protein chemistry methods with modern mass spectrometry has led to the emergence of the distinct field of structural proteomics. Multiple protein chemistry approaches, such as surface modification, limited proteolysis, hydrogen-deuterium exchange, and cross-linking, provide diverse and often orthogonal structural information on the protein systems studied. Combining experimental data from these various structural proteomics techniques provides a more comprehensive examination of the protein structure and increases confidence in the ultimate findings. Here, we review various types of experimental data from structural proteomics approaches with an emphasis on the use of multiple complementary mass spectrometric approaches to provide experimental constraints for the solving of protein structures.

Molecular dynamics and protein frustration analysis of human fused in Sarcoma protein variants in Amyotrophic Lateral Sclerosis type 6: An In Silico approach

Amyotrophic lateral sclerosis (ALS) is the most frequent adult-onset motor neuron disorder. The disease is characterized by degeneration of upper and lower motor neurons, leading to death usually within five years after the onset of symptoms. While most cases are sporadic, 5%-10% of cases can be associated with familial inheritance, including ALS type 6, which is associated with mutations in the Fused in Sarcoma (FUS) gene. This work aimed to evaluate how the most frequent ALS-related mutations in FUS, R521C, R521H, and P525L affect the protein structure and function. We used prediction algorithms to analyze the effects of the non-synonymous single nucleotide polymorphisms and performed evolutionary conservation analysis, protein frustration analysis, and molecular dynamics simulations. Most of the prediction algorithms classified the three mutations as deleterious. All three mutations were predicted to reduce protein stability, especially the mutation R521C, which was also predicted to increase chaperone binding tendency. The protein frustration analysis showed an increase in frustration in the interactions involving the mutated residue 521C. Evolutionary conservation analysis showed that residues 521 and 525 of human FUS are highly conserved sites. The molecular dynamics results indicate that protein stability could be compromised in all three mutations. They also affected the exposed surface area and protein compactness. The analyzed mutations also displayed high flexibility in most residues in all variants, most notably in the interaction site with the nuclear import protein of FUS.

Mycobacterium tuberculosis ferritin: a suitable workhorse protein for cryo-EM development

The use of cryo-EM continues to expand worldwide and calls for good-quality standard proteins with simple protocols for their production. Here, a straightforward expression and purification protocol is presented that provides an apoferritin, bacterioferritin B (BfrB), from Mycobacterium tuberculosis with high yield and purity. A 2.12 Å resolution cryo-EM structure of BfrB is reported, showing the typical cage-like oligomer constituting of 24 monomers related by 432 symmetry. However, it also contains a unique C-terminal extension (164-181), which loops into the cage region of the shell and provides extra stability to the protein. Part of this region was ambiguous in previous crystal structures but could be built within the cryo-EM map. These findings and this protocol could serve the growing cryo-EM community in characterizing and pushing the limits of their electron microscopes and workflows.

Fundamentals to function: Quantitative and scalable approaches for measuring protein stability

Folding a linear chain of amino acids into a three-dimensional protein is a complex physical process that ultimately confers an impressive range of diverse functions. Although recent advances have driven significant progress in predicting three-dimensional protein structures from sequence, proteins are not static molecules. Rather, they exist as complex conformational ensembles defined by energy landscapes spanning the space of sequence and conditions. Quantitatively mapping the physical parameters that dictate these landscapes and protein stability is therefore critical to develop models that are capable of predicting how mutations alter function of proteins in disease and informing the design of proteins with desired functions. Here, we review the approaches that are used to quantify protein stability at a variety of scales, from returning multiple thermodynamic and kinetic measurements for a single protein sequence to yielding indirect insights into folding across a vast sequence space. The physical parameters derived from these approaches will provide a foundation for models that extend beyond the structural prediction to capture the complexity of conformational ensembles and, ultimately, their function.

Estimating the Influence of Physicochemical and Biochemical Property Indexes on Selection for Amino Acids Usage in Eukaryotic Cells

Proteins can evolve by accumulating changes on amino acid sequences. These changes are mainly caused by missense mutations on its DNA coding sequences. Mutations with neutral or positive effects on fitness can be maintained while deleterious mutations tend to be eliminated by natural selection. Amino acid changes are influenced by the biophysical, chemical, and biological properties of amino acids. There is a multiplicity of amino acid properties that can influence the function and expression of proteins. Amino acid properties can be expressed into numerical indexes, which can help to predict functional and structural aspects of proteins and allow statistical inferences of selection pressure on amino acid usage. The accuracy of these analyses may be compromised by the existence of several numerical indexes that measure the same amino acid property, and the lack of objective parameters to determine the most accurate and biologically relevant index. In the present study, the gradient consistency test was used in order to estimate the magnitude of directional selection imparted by amino acid biochemical and biophysical properties on protein evolution.

Novel RyR2 Mutation (G3118R) Is Associated With Autosomal Recessive Ventricular Fibrillation and Sudden Death: Clinical, Functional, and Computational Analysis

Background

The cardiac ryanodine receptor type 2 (RyR2) is a large homotetramer, located in the sarcoplasmic reticulum (SR), which releases Ca²⁺ from the SR during systole. The molecular mechanism underlying Ca²⁺ sensing and gating of the RyR2 channel in health and disease is only partially elucidated. Catecholaminergic Polymorphic Ventricular Tachycardia (CPVT1) is the most prevalent syndrome caused by RyR2 mutations.

Methods and Results

This study involves investigation of a family with 4 cases of ventricular fibrillation and sudden death and physiological tests in HEK 293 cells and normal mode analysis (NMA) computation. We found 4 clinically affected members who were homozygous for a novel RyR2 mutation, G3118R, whereas their heterozygous relatives are asymptomatic. G3118R is located in the periphery of the protein, far from the mutation hotspot regions. HEK293 cells harboring G3118R mutation inhibited Ca²⁺ release in response to increasing doses of caffeine, but decreased the termination threshold for store‐overload‐induced Ca²⁺ release, thus increasing the fractional Ca²⁺ release in response to increasing extracellular Ca²⁺. NMA showed that G3118 affects RyR2 tetramer in a dose‐dependent manner, whereas in the model of homozygous mutant RyR2, the highest entropic values are assigned to the pore and the central regions of the protein.

Conclusions

RyR2 G3118R is related to ventricular fibrillation and sudden death in recessive mode of inheritance and has an effect of gain of function on the protein. Despite a peripheral location, it has an allosteric effect on the stability of central and pore regions in a dose‐effect manner.

Comparison of Huggins Coefficients and Osmotic Second Virial Coefficients of Buffered Solutions of Monoclonal Antibodies

The Huggins coefficient kH is a well-known metric for quantifying the increase in solution viscosity arising from intermolecular interactions in relatively dilute macromolecular solutions, and there has been much interest in this solution property in connection with developing improved antibody therapeutics. While numerous kH measurements have been reported for select monoclonal antibodies (mAbs) solutions, there has been limited study of kH in terms of the fundamental molecular interactions that determine this property. In this paper, we compare measurements of the osmotic second virial coefficient B22, a common metric of intermolecular and interparticle interaction strength, to measurements of kH for model antibody solutions. This comparison is motivated by the seminal work of Russel for hard sphere particles having a short-range "sticky" interparticle interaction, and we also compare our data with known results for uncharged flexible polymers having variable excluded volume interactions because proteins are polypeptide chains. Our observations indicate that neither the adhesive hard sphere model, a common colloidal model of globular proteins, nor the familiar uncharged flexible polymer model, an excellent model of intrinsically disordered proteins, describes the dependence of kH of these antibodies on B22. Clearly, an improved understanding of protein and ion solvation by water as well as dipole-dipole and charge-dipole effects is required to understand the significance of kH from the standpoint of fundamental protein-protein interactions. Despite shortcomings in our theoretical understanding of kH for antibody solutions, this quantity provides a useful practical measure of the strength of interprotein interactions at elevated protein concentrations that is of direct significance for the development of antibody formulations that minimize the solution viscosity.