PBEQ-Solver for online visualization of electrostatic potential of biomolecules

Intermolecular Electrostatic Interactions in Cytochrome c Protein Monolayer on Montmorillonite Alumosilicate Surface: A Positive Cooperative Effect

Montmorillonite (MM) crystal nanoplates acquire anticancer properties when coated with the mitochondrial protein cytochrome c (cytC) due to the cancer cells' capability to phagocytize cytC-MM colloid particles. The introduced exogenous cytC initiates apoptosis: an irreversible cascade of biochemical reactions leading to cell death. In the present research, we investigate the organization of the cytC layer on the MM surface by employing physicochemical and computer methods-microelectrophoresis, static, and electric light scattering-to study cytC adsorption on the MM surface, and protein electrostatics and docking to calculate the local electric potential and Gibbs free energy of interacting protein globules. The found protein concentration dependence of the adsorbed cytC quantity is nonlinear, manifesting a positive cooperative effect that emerges when the adsorbed cytC globules occupy more than one-third of the MM surface. Computer analysis reveals that the cooperative effect is caused by the formation of protein associates in which the cytC globules are oriented with oppositely charged surfaces. The formation of dimers and trimers is accompanied by a strong reduction in the electrostatic component of the Gibbs free energy of protein association, while the van der Waals component plays a secondary role.

Identification of the modulatory Ca2+-binding sites of acid-sensing ion channel 1a

Acid-sensing ion channels (ASICs) are neuronal Na+-permeable ion channels activated by extracellular acidification. ASICs are involved in learning, fear sensing, pain sensation and neurodegeneration. Increasing the extracellular Ca2+ concentration decreases the H+ sensitivity of ASIC1a, suggesting a competition for binding sites between H+ and Ca2+ ions. Here, we predicted candidate residues for Ca2+ binding on ASIC1a, based on available structural information and our molecular dynamics simulations. With functional measurements, we identified several residues in cavities previously associated with pH-dependent gating, whose mutation reduced the modulation by extracellular Ca2+ of the ASIC1a pH dependence of activation and desensitization. This occurred likely owing to a disruption of Ca2+ binding. Our results link one of the two predicted Ca2+-binding sites in each ASIC1a acidic pocket to the modulation of channel activation. Mg2+ regulates ASICs in a similar way as does Ca2+. We show that Mg2+ shares some of the binding sites with Ca2+. Finally, we provide evidence that some of the ASIC1a Ca2+-binding sites are functionally conserved in the splice variant ASIC1b. Our identification of divalent cation-binding sites in ASIC1a shows how Ca2+ affects ASIC1a gating, elucidating a regulatory mechanism present in many ion channels.

The molecular basis for hydrodynamic properties of PEGylated human serum albumin

Polyethylene glycol (PEG) conjugation provides a protective modification that enhances the pharmacokinetics and solubility of proteins for therapeutic use. A knowledge of the structural ensemble of these PEGylated proteins is necessary to understand the molecular details that contribute to their hydrodynamic and colligative properties. Because of the large size and dynamic flexibility of pharmaceutically important PEGylated proteins, the determination of structure is challenging. In addition, the hydration of these conjugates that contain large polymers is difficult to determine with traditional methods that identify only first shell hydration water, which does not account for the complete hydrodynamic volume of a macromolecule. Here, we demonstrate that structural ensembles, generated by coarse-grained simulations, can be analyzed with HullRad and used to predict sedimentation coefficients and concentration-dependent hydrodynamic and diffusion nonideality coefficients of PEGylated proteins. A knowledge of these concentration-dependent properties enhances the ability to design and analyze new modified protein therapeutics. HullRad accomplishes this analysis by effectively accounting for the complete hydration of a macromolecule, including that of flexible polymers.

Heliorhodopsin-mediated light-modulation of ABC transporter

Heliorhodopsins (HeRs) have been hypothesized to have widespread functions. Recently, the functions for few HeRs have been revealed; however, the hypothetical functions remain largely unknown. Herein, we investigate light-modulation of heterodimeric multidrug resistance ATP-binding cassette transporters (OmrDE) mediated by Omithinimicrobium cerasi HeR. In this study, we classifiy genes flanking the HeR-encoding genes and identify highly conservative residues for protein-protein interactions. Our results reveal that the interaction between OcHeR and OmrDE shows positive cooperatively sequential binding through thermodynamic parameters. Moreover, light-induced OcHeR upregulates OmrDE drug transportation. Hence, the binding may be crucial to drug resistance in O. cerasi as it survives in a drug-containing habitat. Overall, we unveil a function of HeR as regulatory rhodopsin for multidrug resistance. Our findings suggest potential applications in optogenetic technology.

Computational Insights into the Conformational Dynamics of HIV-1 Vpr in a Lipid Bilayer for Ion Channel Modeling

HIV-1 Vpr is a multifunctional accessory protein consisting of 96 amino acids that play a critical role in viral pathogenesis. Among its diverse range of activities, Vpr can create a cation-selective ion channel within the plasma membrane. However, the oligomeric state of this channel has not yet been elucidated. In this study, we investigated the conformational dynamics of Vpr helices to model the ion channel topology. First, we employed a series of multiscale simulations to investigate the specific structure of monomeric Vpr in a membrane model. During the lipid bilayer self-assembly coarse grain simulation, the C-terminal helix (residues 56-77) effectively formed the transmembrane region, while the N-terminal helix exhibited an amphipathic nature by associating horizontally with a single leaflet. All-atom molecular dynamics (MD) simulations of full-length Vpr inside a phospholipid bilayer show that the C-terminal helix remains very stable inside the bilayer core in a vertical orientation. Subsequently, using the predicted C-terminal helix orientation and conformation, various oligomeric states (ranging from tetramer to heptamer) possibly forming the Vpr ion channel were built and further evaluated. Among these models, the pentameric form exhibited consistent stability in MD simulations and displayed a compatible conformation for a water-assisted ion transport mechanism. This study provides structural insights into the ion channel activity of the Vpr protein and the foundation for developing therapeutics against HIV-1 Vpr-related conditions.

Calculation of solvation force in molecular dynamics simulation by deep-learning method

Electrostatic calculations are generally used in studying the thermodynamics and kinetics of biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann equation on a large grid system, a process known to be time consuming. In this study, we developed a deep neural network to predict the decomposed solvation free energies and forces of all atoms in a molecule. To train the network, the internal coordinates of the molecule were used as the input data, and the solvation free energies along with transformed atomic forces from the Poisson-Boltzmann equation were used as labels. Both the training and prediction tasks were accelerated on GPU. Formal tests demonstrated that our method can provide reasonable predictions for small molecules when the network is well-trained with its simulation data. This method is suitable for processing lots of snapshots of molecules in a long trajectory. Moreover, we applied this method in the molecular dynamics simulation with enhanced sampling. The calculated free energy landscape closely resembled that obtained from explicit solvent simulations.

Poisson-Boltzmann-based machine learning model for electrostatic analysis

Electrostatics is of paramount importance to chemistry, physics, biology, and medicine. The Poisson-Boltzmann (PB) theory is a primary model for electrostatic analysis. However, it is highly challenging to compute accurate PB electrostatic solvation free energies for macromolecules due to the nonlinearity, dielectric jumps, charge singularity, and geometric complexity associated with the PB equation. The present work introduces a PB-based machine learning (PBML) model for biomolecular electrostatic analysis. Trained with the second-order accurate MIBPB solver, the proposed PBML model is found to be more accurate and faster than several eminent PB solvers in electrostatic analysis. The proposed PBML model can provide highly accurate PB electrostatic solvation free energy of new biomolecules or new conformations generated by molecular dynamics with much reduced computational cost.

Three-Dimensional Structural Stability and Local Electrostatic Potential at Point Mutations in Spike Protein of SARS-CoV-2 Coronavirus

The contagiousness of SARS-CoV-2 β-coronavirus is determined by the virus-receptor electrostatic association of its positively charged spike (S) protein with the negatively charged angiotensin converting enzyme-2 (ACE2 receptor) of the epithelial cells. If some mutations occur, the electrostatic potential on the surface of the receptor-binding domain (RBD) could be altered, and the S-ACE2 association could become stronger or weaker. The aim of the current research is to investigate whether point mutations can noticeably alter the electrostatic potential on the RBD and the 3D stability of the S1-subunit of the S-protein. For this purpose, 15 mutants with different hydrophilicity and electric charge (positive, negative, or uncharged) of the substituted and substituting amino acid residues, located on the RBD at the S1-ACE2 interface, are selected, and the 3D structure of the S1-subunit is reconstructed on the base of the crystallographic structure of the S-protein of the wild-type strain and the amino acid sequence of the unfolded polypeptide chain of the mutants. Then, the Gibbs free energy of folding, isoelectric point, and pH-dependent surface electrostatic potential of the S1-subunit are computed using programs for protein electrostatics. The results show alterations in the local electrostatic potential in the vicinity of the mutant amino acid residue, which can influence the S-ACE2 association. This approach allows prediction of the relative infectivity, transmissibility, and contagiousness (at equal social immune status) of new SARS-CoV-2 mutants by reconstruction of the 3D structure of the S1-subunit and calculation of the surface electrostatic potential.

Omicron Coronavirus: pH-Dependent Electrostatic Potential and Energy of Association of Spike Protein to ACE2 Receptor

The association of the S-protein of the SARS-CoV-2 beta coronavirus to ACE2 receptors of the human epithelial cells determines its contagiousness and pathogenicity. We computed the pH-dependent electric potential on the surface of the interacting globular proteins and pH-dependent Gibbs free energy at the association of the wild-type strain and the omicron variant. The calculated isoelectric points of the ACE2 receptor (pI 5.4) and the S-protein in trimeric form (pI 7.3, wild type), (pI 7.8, omicron variant), experimentally verified by isoelectric focusing, show that at pH 6-7, the S1-ACE2 association is conditioned by electrostatic attraction of the oppositely charged receptor and viral protein. The comparison of the local electrostatic potentials of the omicron variant and the wild-type strain shows that the point mutations alter the electrostatic potential in a relatively small area on the surface of the receptor-binding domain (RBD) of the S1 subunit. The appearance of seven charge-changing point mutations in RBD (equivalent to three additional positive charges) leads to a stronger S1-ACE2 association at pH 5.5 (typical for the respiratory tract) and a weaker one at pH 7.4 (characteristic of the blood plasma); this reveals the reason for the higher contagiousness but lower pathogenicity of the omicron variant in comparison to the wild-type strain.

SurfPB: A GPU-Accelerated Electrostatic Calculation and Visualization Tool for Biomolecules

In this work, we present SurfPB as a useful tool for the study of biomolecules. It can do many typical calculations, including the molecular surface, electrostatic potential, solvation free energy, entropy, and binding free energy. Among all of the calculations, the entropy calculation is the most time-consuming one. In SurfPB, the calculation can be performed in a vacuum or implicit solvent and accelerated on GPU. The Poisson-Boltzmann equation solver is accelerated on GPU as well. Moreover, we developed a graphical user interface for SurfPB. It allows users to input the parameters and complete the whole calculation in a visual way. The calculated electrostatic potentials are shown on the molecular surface in a three-dimensional scene.

Time-resolved absorption measurements quantify the competition of energy and electron transfer between quantum dots and cytochrome c

We applied transient absorption spectroscopy to study the early photodynamics in a system composed of CdTe quantum dots (QDs) and cytochrome c (Cyt c) protein. In the QDs and Cyt c mixtures, about 25 % of the excited QD electrons quickly relax (∼23 ps) to the ground state and roughly 75 % decay on slower time scale - mostly due to quenching by Cyt c. On the basis of the assumed model, we estimated the contribution of electron transfer and other mechanisms to this quenching. The primary quenching mechanism is probably energy transfer but electron transfer makes a significant contribution (∼8 %), resulting in photoreduction of Cyt c. The lifetime of one fraction of reduced Cyt c (35-90 %) is ∼ 1 ms and the lifetime of the remaining fraction was longer than the ∼ 50-ms time window of the experiment. We speculate that, in the former fraction, the back electron transfer from the reduced Cyt c to QDs occurs and the latter fraction of Cyt c is stably reduced.

Site Identification by Ligand Competitive Saturation-Biologics Approach for Structure-Based Protein Charge Prediction

Protein-based therapeutics typically require high concentrations of the active protein, which can lead to protein aggregation and high solution viscosity. Such solution behaviors can limit the stability, bioavailability, and manufacturability of protein-based therapeutics and are directly influenced by the charge of a protein. Protein charge is a system property affected by its environment, including the buffer composition, pH, and temperature. Thus, the charge calculated by summing the charges of each residue in a protein, as is commonly done in computational methods, may significantly differ from the effective charge of the protein as these calculations do not account for contributions from bound ions. Here, we present an extension of the structure-based approach termed site identification by ligand competitive saturation-biologics (SILCS-Biologics) to predict the effective charge of proteins. The SILCS-Biologics approach was applied on a range of protein targets in different salt environments for which membrane-confined electrophoresis-determined charges were previously reported. SILCS-Biologics maps the 3D distribution and predicted occupancy of ions, buffer molecules, and excipient molecules bound to the protein surface in a given salt environment. Using this information, the effective charge of the protein is predicted such that the concentrations of the ions and the presence of excipients or buffers are accounted for. Additionally, SILCS-Biologics also produces 3D structures of the binding sites of ions on the proteins, which enable further analyses such as the characterization of protein surface charge distribution and dipole moments in different environments. Notable is the capability of the method to account for competition between salts, excipients, and buffers on the calculated electrostatic properties in different protein formulations. Our study demonstrates the ability of the SILCS-Biologics approach to predict the effective charge of proteins and its applicability in uncovering protein-ion interactions and their contributions to protein solubility and function.

Overlooked KCNQ4 variants augment the risk of hearing loss

Pathogenic variants of KCNQ4 cause symmetrical, late-onset, progressive, high-frequency-affected hearing loss, which eventually involves all frequencies with age. To understand the contribution of KCNQ4 variants to hearing loss, we analyzed whole-exome and genome sequencing data from patients with hearing loss and individuals whose hearing phenotypes were unknown. In KCNQ4, we identified seven missense variants and one deletion variant in 9 hearing loss patients and 14 missense variants in the Korean population with an unknown hearing loss phenotype. The p.R420W and p.R447W variants were found in both cohorts. To investigate the effects of these variants on KCNQ4 function, we performed whole-cell patch clamping and examined their expression levels. Except for p.G435Afs*61, all KCNQ4 variants exhibited normal expression patterns similar to those of wild-type KCNQ4. The p.R331Q, p.R331W, p.G435Afs*61, and p.S691G variants, which were identified in patients with hearing loss, showed a potassium (K+) current density lower than or similar to that of p.L47P, a previously reported pathogenic variant. The p.S185W and p.R216H variants shifted the activation voltage to hyperpolarized voltages. The channel activity of the p.S185W, p.R216H, p.V672M, and p.S691G KCNQ4 proteins was rescued by the KCNQ activators retigabine or zinc pyrithione, whereas p.G435Afs*61 KCNQ4 proteins were partially rescued by sodium butyrate, a chemical chaperone. Additionally, the structure of the variants predicted using AlphaFold2 showed impaired pore configurations, as did the patch-clamp data. Our findings suggest that KCNQ4 variants may be overlooked in hearing loss that starts in adulthood. Some of these variants are medically treatable; hence, genetic screening for KCNQ4 is important.

Computational refinement identifies functional destructive single nucleotide polymorphisms associated with human retinoid X receptor gene

Alterations in the nuclear retinoid X receptor (RXRs) signalling have been implicated in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, stroke, multiple sclerosis and glaucoma. Single nucleotide polymorphisms (SNPs) are the main cause underlying single nucleic acid variations which in turn determine heterogeneity within various populations. These genetic polymorphisms have been suggested to associate with various degenerative disorders in population-wide analysis. This bioinformatics study was designed to investigate, search, retrieve and identify deleterious SNPs which may affect the structure and function of various RXR isoforms through a computational and molecular modelling approach. Amongst the 1,813 retrieved SNPs several were found to be deleterious with rs140464195_G139R, rs368400425_R358W and rs368586400_L383F RXRα mutant variants being the most detrimental ones causing changes in the interatomic interactions and decreasing the flexibility of the mutant proteins. Molecular genetics analysis identified seven missense mutations in RXRα/β/γ isoforms. Two novel mutations SNP IDs (rs1588299621 and rs1057519958) were identified in RXRα isoform. We used several in silico prediction tools such as SIFT, PolyPhen, I-Mutant, Protein Variation Effect Analyzer (PROVEAN), PANTHER, SNP&Go, PhD-SNP and SNPeffect to predict pathogenicity and protein stability associated with RXR mutations. The structural assessment by DynaMut tool revealed that hydrogen bonds were affected along with hydrophobic and carbonyl interactions resulting in reduced flexibility at the mutated residue positions but ultimately stabilizing the molecule as a whole. Summarizing, analysis of the missense mutations in RXR isoforms showed a mix of conclusive and inconclusive genotype-phenotype correlations suggesting the use of sophisticated computational analysis tools for studying RXR variants.Communicated by Ramaswamy H. Sarma.

Electrostatic Surface Potential as a Key Parameter in Virus Transmission and Evolution: How to Manage Future Virus Pandemics in the Post-COVID-19 Era

Virus-cell interactions involve fundamental parameters that need to be considered in strategies implemented to control viral outbreaks. Among these, the surface electrostatic potential can give valuable information to deal with new epidemics. In this article, we describe the role of this key parameter in the hemagglutination of red blood cells and in the co-evolution of synaptic receptors and neurotransmitters. We then establish the functional link between lipid rafts and the electrostatic potential of viruses, with special emphasis on gangliosides, which are sialic-acid-containing, electronegatively charged plasma membrane components. We describe the common features of ganglioside binding domains, which include a wide variety of structures with little sequence homology but that possess key amino acids controlling ganglioside recognition. We analyze the role of the electrostatic potential in the transmission and intra-individual evolution of HIV-1 infections, including gatekeeper and co-receptor switch mechanisms. We show how to organize the epidemic surveillance of influenza viruses by focusing on mutations affecting the hemagglutinin surface potential. We demonstrate that the electrostatic surface potential, by modulating spike-ganglioside interactions, controls the hemagglutination properties of coronaviruses (SARS-CoV-1, MERS-CoV, and SARS-CoV-2) as well as the structural dynamics of SARS-CoV-2 evolution. We relate the broad-spectrum antiviral activity of repositioned molecules to their ability to disrupt virus-raft interactions, challenging the old concept that an antibiotic or anti-parasitic cannot also be an antiviral. We propose a new concept based on the analysis of the electrostatic surface potential to develop, in real time, therapeutic and vaccine strategies adapted to each new viral epidemic.

Characterisation and substrate binding modes of exopolygalacturonase PGQ1 from Saccharobesus litoralis

Among the enzymes required for the efficient utilisation of pectin is polygalacturonase. Saccharobesus litoralis harbours two polygalacturonases belonging to glycoside hydrolase family 28 (GH28). One of them, PGQ1, cleaved polygalacturonate exolytically at the non-reducing end into monomeric units. It was most active at 60 °C and pH 8, with Km and kcat values of 2.3 mg/ml and 6.4 s-1 respectively. Its homology model of a right-handed parallel β-helix core consisted of Asp297 as the general acid and either Asp276 or Asp298 as the general base. By inferring the substrate binding modes at the -1 and +1 subsites from known crystal structures, a hexagalacturonate could be docked into the highly electropositive binding cleft. Interestingly, while no residues were present in the vicinity to make up the +2 and +4 subsites, Arg361 and Arg430 could readily bind to the carboxyl groups of the galacturonates at the +3 and +5 subsites respectively. Structural comparison suggested that this binding pattern with missing subsites might be unique to closely related exopolygalacturonases. As S. litoralis grew much more slowly on extracellular galacturonate due to the lack of a transporter for the monosaccharide, PGQ1 probably functioned in the periplasm to help degrade oligopectates completely.Communicated by Ramaswamy H. Sarma.

Enhanced neuronal differentiation by dynamic piezoelectric stimulation

Electroactive smart materials play an important role for tissue regenerative applications. Poly(vinylidene fluoride) (PVDF) is a specific subtype of piezoelectric electroactive material that generates electrical potential upon mechanical stimulation. This work focuses on the application of piezoelectric PVDF films for neural differentiation. Human neural precursor cells (hNPCs) are cultured on piezoelectric poled and non-poled β-PVDF films with or without a pre-coating step of poly-d-lysine and laminin (PDL/L). Subsequently, hNPCs differentiation into the neuronal lineage is assessed (MAP2⁺ and DCX⁺ ) under static or dynamic (piezoelectric stimulation) culture conditions. The results demonstrate that poled and coated β-PVDF films induce neuronal differentiation under static culture conditions which is further enhanced with mechanical stimulation. In silico calculations of the electrostatic potential of different domains of laminin, highlight the high polarity of those domains, which shows a clear preference to interact with the varying surface electric field of the piezoelectric material under mechanical stimulation. These interactions might explain the higher neuronal differentiation induced by poled β-PVDF films pre-coated with PDL/L under dynamic conditions. Our results suggest that electromechanical stimuli, such as the ones induced by piezoelectric β-PVDF films, are suitable to promote neuronal differentiation and hold great promise for the development of neuroregenerative therapies.

Deciphering the structural and functional impact of missense mutations in Egr1-DNA interacting interface: an integrative computational approach

Early growth response-1 (Egr1) is a zinc-finger transcription factor that plays a critical role in controlling cell growth, proliferation, differentiation, angiogenesis, and apoptosis. Egr1 is induced by many growth factors, cytokines, and stress signals and is also known to be involved in several pathological conditions like cancer, neurological and ocular disorders. The DNA binding domain of Egr1 is a highly conserved Cys2His2 (C2H2) zinc finger (ZNF) domain which specifically binds to GC-rich consensus sequence GcG (G/T) GGGCG and activates transcription. As the C2H2 domain specifically recognizes its DNA target, the mutations spanning this region shall perturb DNA recognition and may hinder transcription of target genes. Therefore, in this study, the missense mutations occurring specifically at the DNA binding domain (DBD) of Egr1 were probed by computational approaches involving in silico screening of pathogenic and functional mutants coupled with extensive molecular dynamics simulations, to determine the mutants that affect its structural stability and interactions with DNA. From the pathogenicity analysis of 38 missense mutations spanning Egr1-DBD, 17 were predicted as pathogenic, and 7 amongst these were found to have functional impact on Egr1. On combined analysis of molecular dynamics simulation, Residue interaction analysis and Egr1-DNA interaction analysis results, the mutants R371C and R375C showed least impact, whilst, H382R tend to increase the structural stability, whereas R360H, H390R, E393V, and H414Y conferred greater impact by altering the structural stability and DNA interactions. Hence, this study exposes the prospects of considering these 4 deleterious mutations for clinical significance, but needs further experimental validation.HighlightsEgr1's DNA binding domain is a highly conserved Cys2His2 (C2H2) zinc finger domain that specifically recognizes its DNA target.Mutations spanning in the DNA binding domain shall perturb DNA recognition and may hinder transcription.Among the missense mutations, mutants R360H, H390R, E393V, and H414Y were inferred to have a greater impact on Egr1 by altering the structural stability and DNA interactions.

Structure and thermodynamics of a UGG motif interacting with Ba2+ and other metal ions: accommodating changes in the RNA structure and the presence of a G(syn)-G(syn) pair

The self-complementary triplet 5'UGG3'/5'UGG3' is a particular structural motif containing noncanonical G-G pair and two U·G wobble pairs. It constitutes a specific structural and electrostatic environment attracting metal ions, particularly Ba2+ ions. Crystallographic research has shown that two Ba2+ cations are located in the major groove of the helix and interact directly with the UGG triplet. A comparison with the unliganded structure has revealed global changes in the RNA structure in the presence of metal ions, whereas thermodynamic measurements have shown increased stability. Moreover, in the structure with Ba2+, an unusual noncanonical G(syn)-G(syn) pair is observed instead of the common G(anti)-G(syn). We further elucidate the metal binding properties of the UGG/UGG triplet by performing crystallographic and thermodynamic studies using DSC and UV melting with other metal ions. The results explain the preferences of the UGG sequence for Ba2+ cations and point to possible applications of this metal-binding propensity.

Predicted Structure and Functions of the Prototypic Alphaherpesvirus Herpes Simplex Virus Type-1 UL37 Tegument Protein

The alphaherpesvirus UL37 tegument protein is a highly conserved, multi-functional protein. Mutagenesis analysis delineated the UL37 domains necessary for retrograde transport and viral replication. Specifically, the amino-terminal 480 amino acids are dispensable for virus replication in epithelial cell culture, but it is unknown whether this amino-terminal deletion affects UL37 structure and intracellular transport in epithelial cells and neurons. To investigate the structure and function of UL37, we utilized multiple computational approaches to predict and characterize the secondary and tertiary structure and other functional features. The structure of HSV-1 UL37 and Δ481N were deduced using publicly available predictive algorithms. The predicted model of HSV-1 UL37 is a stable, multi-functional, globular monomer, rich in alpha helices, with unfolded regions within the linker and the C-tail domains. The highly flexible C-tail contains predicted binding sites to the dynein intermediate chain, as well as DNA and RNA. Predicted interactions with the cytoplasmic surface of the lipid membrane suggest UL37 is a peripheral membrane protein. The Δ481N truncation did not alter the predicted structure of the UL37 C-terminus protein and its predicted interaction with dynein. We validated these models by examining the replication kinetics and transport of the Δ481N virus toward the nuclei of infected epithelial and neuronal cells. The Δ481N virus had substantial defects in virus spread; however, it exhibited no apparent defects in virus entry and intracellular transport. Using computational analyses, we identified several key features of UL37, particularly the flexible unstructured tail; we then demonstrated that the UL37 C-terminus alone is sufficient to effectively transport the virus towards the nucleus of infected epithelial and neuronal cells.

Heliorhodopsin binds and regulates glutamine synthetase activity

Photoreceptors are light-sensitive proteins found in various organisms that respond to light and relay signals into the cells. Heliorhodopsin, a retinal-binding membrane protein, has been recently discovered, however its function remains unknown. Herein, we investigated the relationship between Actinobacteria bacterium IMCC26103 heliorhodopsin (AbHeR) and an adjacent glutamine synthetase (AbGS) in the same operon. We demonstrate that AbHeR binds to AbGS and regulates AbGS activity. More specifically, the dissociation constant (K_d) value of the binding between AbHeR and AbGS is 6.06 μM. Moreover, the absence of positively charged residues within the intracellular loop of AbHeR impacted K_d value as they serve as critical binding sites for AbGS. We also confirm that AbHeR up-regulates the biosynthetic enzyme activity of AbGS both in vitro and in vivo in the presence of light. GS is a key enzyme involved in nitrogen assimilation that catalyzes the conversion of glutamate and ammonia to glutamine. Hence, the interaction between AbHeR and AbGS may be critical for nitrogen assimilation in Actinobacteria bacterium IMCC26103 as it survives in low-nutrient environments. Overall, the findings of our study describe, for the first time, to the best of our knowledge, a novel function of heliorhodopsin as a regulatory rhodopsin with the capacity to bind and regulate enzyme activity required for nitrogen assimilation.

A study of heliorhodopsin, an actinobacterial photoreceptor of unknown function, reveals that it interacts with glutamine synthetase, an enzyme involved in nitrogen assimilation, and regulates its activity in the presence of light, highlighting the diverse functions of rhodopsins in different organisms.

Structure of the hypothetical protein TTHA1873 from Thermus thermophilus

The crystal structure of an uncharacterized hypothetical protein, TTHA1873 from Thermus thermophilus, has been determined by X-ray crystallography to a resolution of 1.78 Å using the single-wavelength anomalous dispersion method. The protein crystallized as a dimer in two space groups: P43212 and P6122. Structural analysis of the hypothetical protein revealed that the overall fold of TTHA1873 has a β-sandwich jelly-roll topology with nine β-strands. TTHA1873 is a dimeric metal-binding protein that binds to two Ca2+ ions per chain, with one on the surface and the other stabilizing the dimeric interface of the two chains. A structural homology search indicates that the protein has moderate structural similarity to one domain of cell-surface proteins or agglutinin receptor proteins. Red blood cells showed visible agglutination at high concentrations of the hypothetical protein.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

The structural conformation of the tachykinin domain drives the anti-tumoral activity of an octopus peptide in melanoma BRAFV600E

BACKGROUND AND PURPOSE

Over the past decades, targeted therapies and immunotherapy have vastly improved survival and reduced the morbidity of patients with BRAF-mutated melanoma. However, drug resistance and relapse hinder overall success. Therefore, there is an urgent need for novel compounds with therapeutic efficacy against BRAF- melanoma. This prompted us to investigate the antiproliferative profile of a tachykinin-peptide from the Octopus kaurna, Octpep-1 in melanoma.

EXPERIMENTAL APPROACH

We evaluated the cytotoxicity of Octpep-1 by MTT assay. Mechanistic insights on viability and cellular damage caused by Octpep-1 were gained via flow cytometry and bioenergetics. Structural and pharmacological characterization was conducted by molecular modelling, molecular biology, CRISPR/Cas9 technology, high-throughput mRNA and calcium flux analysis. In-vivo efficacy was validated in two independent xerograph animal models (mice and zebrafish).

KEY RESULTS

Octpep-1 selectively reduced the proliferative capacity of human melanoma BRAF^V600E -mutated cells with minimal effects on fibroblasts. In melanoma-treated cells, Octpep-1 increased ROS with unaltered mitochondrial membrane potential and promoted non-mitochondrial and mitochondrial respiration with inefficient ATP coupling. Despite similarities with tachykinin peptides, knock-out or pharmacological blockade of tachykinin receptors suggested that Octpep-1 acts via a tachykinin-independent mechanism. Molecular modelling revealed that the cytotoxicity of Octpep-1 depends upon the α-helix and polyproline conformation in the C-terminal region of the peptide. Indeed, a truncated form of the C-terminal end of Octpep-1 displayed enhanced potency and efficacy against melanoma. Octpep-1 reduced the progression of tumors in xenograft melanoma mice and zebrafish, confirming its therapeutic potential in human BRAF-mutated melanoma.

CONCLUSION AND IMPLICATIONS

We unravel the intrinsic anti-tumoral properties of a tachykinin peptide, possessing a pharmacology independent of tachykinin-receptors. This peptide mediates the selective cytotoxicity in BRAF-mutated melanoma in-vitro and prevents tumor progression in-vivo, providing the foundation for a potential therapy against melanoma.

Gating and anion selectivity are reciprocally regulated in TMEM16A (ANO1)

Numerous essential physiological processes depend on the TMEM16A-mediated Ca2+-activated chloride fluxes. Extensive structure-function studies have helped to elucidate the Ca2+ gating mechanism of TMEM16A, revealing a Ca2+-sensing element close to the anion pore that alters conduction. However, substrate selection and the substrate-gating relationship in TMEM16A remain less explored. Here, we study the gating-permeant anion relationship on mouse TMEM16A expressed in HEK 293 cells using electrophysiological recordings coupled with site-directed mutagenesis. We show that the apparent Ca2+ sensitivity of TMEM16A increased with highly permeant anions and SCN- mole fractions, likely by stabilizing bound Ca2+. Conversely, mutations at crucial gating elements, including the Ca2+-binding site 1, the transmembrane helix 6 (TM6), and the hydrophobic gate, impaired the anion permeability and selectivity of TMEM16A. Finally, we found that, unlike anion-selective wild-type channels, the voltage dependence of unselective TMEM16A mutant channels was less sensitive to SCN-. Therefore, our work identifies structural determinants of selectivity at the Ca2+ site, TM6, and hydrophobic gate and reveals a reciprocal regulation of gating and selectivity. We suggest that this regulation is essential to set ionic selectivity and the Ca2+ and voltage sensitivities in TMEM16A.

Protein pKa Prediction by Tree-Based Machine Learning

Protonation states of ionizable protein residues modulate many essential biological processes. For correct modeling and understanding of these processes, it is crucial to accurately determine their pKa values. Here, we present four tree-based machine learning models for protein pKa prediction. The four models, Random Forest, Extra Trees, eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM), were trained on three experimental PDB and pKa datasets, two of which included a notable portion of internal residues. We observed similar performance among the four machine learning algorithms. The best model trained on the largest dataset performs 37% better than the widely used empirical pKa prediction tool PROPKA and 15% better than the published result from the pKa prediction method DelPhiPKa. The overall root-mean-square error (RMSE) for this model is 0.69, with surface and buried RMSE values being 0.56 and 0.78, respectively, considering six residue types (Asp, Glu, His, Lys, Cys, and Tyr), and 0.63 when considering Asp, Glu, His, and Lys only. We provide pKa predictions for proteins in human proteome from the AlphaFold Protein Structure Database and observed that 1% of Asp/Glu/Lys residues have highly shifted pKa values close to the physiological pH.

Structure and activity of the DHNA Coenzyme-A Thioesterase from Staphylococcus aureus providing insights for innovative drug development

Humanity is facing an increasing health threat caused by a variety of multidrug resistant bacteria. Within this scenario, Staphylococcus aureus, in particular methicillin resistant S. aureus (MRSA), is responsible for a number of hospital-acquired bacterial infections. The emergence of microbial antibiotic resistance urgently requires the identification of new and innovative strategies to treat antibiotic resistant microorganisms. In this context, structure and function analysis of potential drug targets in metabolic pathways vital for bacteria endurance, such as the vitamin K₂ synthesis pathway, becomes interesting. We have solved and refined the crystal structure of the S. aureus DHNA thioesterase (SaDHNA), a key enzyme in the vitamin K₂ pathway. The crystallographic structure in combination with small angle X-ray solution scattering data revealed a functional tetramer of SaDHNA. Complementary activity assays of SaDHNA indicated a preference for hydrolysing long acyl chains. Site-directed mutagenesis of SaDHNA confirmed the functional importance of Asp16 and Glu31 for thioesterase activity and substrate binding at the putative active site, respectively. Docking studies were performed and rational designed peptides were synthesized and tested for SaDHNA inhibition activity. The high-resolution structure of SaDHNA and complementary information about substrate binding will support future drug discovery and design investigations to inhibit the vitamin K₂ synthesis pathway.

Prediction of protein pK a with representation learning

The behavior of proteins is closely related to the protonation states of the residues. Therefore, prediction and measurement of pK a are essential to understand the basic functions of proteins. In this work, we develop a new empirical scheme for protein pK a prediction that is based on deep representation learning. It combines machine learning with atomic environment vector (AEV) and learned quantum mechanical representation from ANI-2x neural network potential (J. Chem. Theory Comput. 2020, 16, 4192). The scheme requires only the coordinate information of a protein as the input and separately estimates the pK a for all five titratable amino acid types. The accuracy of the approach was analyzed with both cross-validation and an external test set of proteins. Obtained results were compared with the widely used empirical approach PROPKA. The new empirical model provides accuracy with MAEs below 0.5 for all amino acid types. It surpasses the accuracy of PROPKA and performs significantly better than the null model. Our model is also sensitive to the local conformational changes and molecular interactions.

MLIMC: Machine Learning-Based Implicit-Solvent Monte Carlo

Monte Carlo (MC) methods are important computational tools for molecular structure optimizations and predictions. When solvent effects are explicitly considered, MC methods become very expensive due to the large degree of freedom associated with the water molecules and mobile ions. Alternatively implicit-solvent MC can largely reduce the computational cost by applying a mean field approximation to solvent effects and meanwhile maintains the atomic detail of the target molecule. The two most popular implicit-solvent models are the Poisson-Boltzmann (PB) model and the Generalized Born (GB) model in a way such that the GB model is an approximation to the PB model but is much faster in simulation time. In this work, we develop a machine learning-based implicit-solvent Monte Carlo (MLIMC) method by combining the advantages of both implicit solvent models in accuracy and efficiency. Specifically, the MLIMC method uses a fast and accurate PB-based machine learning (PBML) scheme to compute the electrostatic solvation free energy at each step. We validate our MLIMC method by using a benzene-water system and a protein-water system. We show that the proposed MLIMC method has great advantages in speed and accuracy for molecular structure optimization and prediction.

Functional conservation and divergence of the helix-turn-helix motif of E2 ubiquitin-conjugating enzymes

Polyubiquitination by E2 and E3 enzymes is crucial to cell cycle control, epigenetic regulation, and development. The hallmark of the E2 family is the ubiquitin (Ub)-conjugating (UBC) domain that forms a dynamic thioester conjugate with ubiquitin (E2~Ub). Numerous studies have focused on E2 surfaces, such as the N-terminal and crossover helices, that directly interact with an E3 or the conjugated ubiquitin to stabilize the active, "closed" state of the E2~Ub. However, it remains unclear how other E2 surfaces regulate ubiquitin transfer. Here, we demonstrate the helix-turn-helix (HTH) motif of the UBC tunes the intrinsic polyubiquitination activity through distinct functions in different E2s. Interestingly, the E2^HTH motif is repurposed in UBE2S and UBE2R2 to interact with the conjugated or acceptor ubiquitin, respectively, modulating ubiquitin transfer. Furthermore, we propose that Anaphase-Promoting Complex/Cyclosome binding to the UBE2S^HTH reduces the conformational space of the flexible E2~Ub, demonstrating an atypical E3-dependent activation mechanism. Altogether, we postulate the E2^HTH motif evolved to provide new functionalities that can be harnessed by E3s and permits additional regulation to facilitate specific E2-E3-mediated polyubiquitination.

Whole exome sequencing identifies deleterious rare variants in CCDC141 in familial self-limited delayed puberty

Developmental abnormalities of the gonadotropin-releasing hormone (GnRH) neuronal network result in a range of conditions from idiopathic hypogonadotropic hypogonadism to self-limited delayed puberty. We aimed to discover important underlying regulators of self-limited delayed puberty through interrogation of GnRH pathways. Whole exome sequencing (WES) data consisting of 193 individuals, from 100 families with self-limited delayed puberty, was analysed using a virtual panel of genes related to GnRH development and function (n = 12). Five rare predicted deleterious variants in Coiled-Coil Domain Containing 141 (CCDC141) were identified in 21 individuals from 6 families (6% of the tested cohort). Homology modeling predicted all five variants to be deleterious. CCDC141 mutant proteins showed atypical subcellular localization associated with abnormal distribution of acetylated tubulin, and expression of mutants resulted in a significantly delayed cell migration, demonstrated in transfected HEK293 cells. These data identify mutations in CCDC141 as a frequent finding in patients with self-limited delayed puberty. The mis-localization of acetylated tubulin and reduced cell migration seen with mutant CCDC141 suggests a role of the CCDC141-microtubule axis in GnRH neuronal migration, with heterozygous defects potentially impacting the timing of puberty.

BTK operates a phospho-tyrosine switch to regulate NLRP3 inflammasome activity

Activity of the NLRP3 inflammasome, a critical mediator of inflammation, is controlled by accessory proteins, posttranslational modifications, cellular localization, and oligomerization. How these factors relate is unclear. We show that a well-established drug target, Bruton’s tyrosine kinase (BTK), affects several levels of NLRP3 regulation. BTK directly interacts with NLRP3 in immune cells and phosphorylates four conserved tyrosine residues upon inflammasome activation, in vitro and in vivo. Furthermore, BTK promotes NLRP3 relocalization, oligomerization, ASC polymerization, and full inflammasome assembly, probably by charge neutralization, upon modification of a polybasic linker known to direct NLRP3 Golgi association and inflammasome nucleation. As NLRP3 tyrosine modification by BTK also positively regulates IL-1β release, we propose BTK as a multifunctional positive regulator of NLRP3 regulation and BTK phosphorylation of NLRP3 as a novel and therapeutically tractable step in the control of inflammation.

Computational insights into the membrane fusion mechanism of SARS-CoV-2 at the cellular level

The membrane fusion mechanism of SARS-CoV-2 offers an attractive target for the development of small molecule antiviral inhibitors. Fusion involves an initial binding of the crown-like trimeric spike glycoproteins of SARS-CoV-2 to the receptor angiotensin II-converting enzyme 2 (ACE2) on the permissive host cellular membrane and a prefusion to post-fusion conversion of the spike trimer. During this conversion, the fusion peptides of the spike trimer are inserted into the host membrane to bring together the host and viral membranes for membrane fusion in highly choreographic events. However, geometric constraints due to interactions with the membranes remain poorly understood. In this study, we build structural models of super-complexes of spike trimer/ACE2 dimers based on the molecular structures of the ACE2/neutral amino acid transporter B(0)AT heterodimer. We determine the conformational constraints due to the membrane geometry on the enzymatic activity of ACE2 and on the viral fusion process. Furthermore, we find that binding three ACE2 dimers per spike trimer is essential to open the central pore as necessary for triggering productive membrane fusion through an elongation of the central stalk. The reported findings thus provide valuable insights for targeting the membrane fusion mechanism for drug design at the molecular level.

ARGOS: An adaptive refinement goal-oriented solver for the linearized Poisson-Boltzmann equation

An adaptive finite element solver for the numerical calculation of the electrostatic coupling between molecules in a solvent environment is developed and tested. At the heart of the solver is a goal-oriented a posteriori error estimate for the electrostatic coupling, derived and implemented in the present work, that gives rise to an orders of magnitude improved precision and a shorter computational time as compared to standard finite difference solvers. The accuracy of the new solver ARGOS is evaluated by numerical experiments on a series of problems with analytically known solutions. In addition, the solver is used to calculate electrostatic couplings between two chromophores, linked to polyproline helices of different lengths and between the spike protein of SARS-CoV-2 and the ACE2 receptor. All the calculations are repeated by using the well-known finite difference solvers MEAD and APBS, revealing the advantages of the present finite element solver.

Structural basis of complex formation between mitochondrial anion channel VDAC1 and Hexokinase-II

Complex formation between hexokinase-II (HKII) and the mitochondrial VDAC1 is crucial to cell growth and survival. We hypothesize that HKII first inserts into the outer membrane of mitochondria (OMM) and then interacts with VDAC1 on the cytosolic leaflet of OMM to form a binary complex. To systematically investigate this process, we devised a hybrid approach. First, we describe membrane binding of HKII with molecular dynamics (MD) simulations employing a membrane mimetic model with enhanced lipid diffusion capturing membrane insertion of its H-anchor. The insertion depth of the H-anchor was then used to derive positional restraints in subsequent millisecond-scale Brownian dynamics (BD) simulations to preserve the membrane-bound pose of HKII during the formation of the HKII/VDAC1 binary complex. Multiple BD-derived structural models for the complex were further refined and their structural stability probed with additional MD simulations, resulting in one stable complex. A major feature in the complex is the partial (not complete) blockade of VDAC1's permeation pathway, a result supported by our comparative electrophysiological measurements of the channel in the presence and absence of HKII. We also show how VDAC1 phosphorylation disrupts HKII binding, a feature that is verified by our electrophysiology recordings and has implications in mitochondria-mediated cell death.

Multilevel proteomics reveals host perturbations by SARS-CoV-2 and SARS-CoV

The emergence and global spread of SARS-CoV-2 has resulted in the urgent need for an in-depth understanding of molecular functions of viral proteins and their interactions with the host proteome. Several individual omics studies have extended our knowledge of COVID-19 pathophysiology^1-10. Integration of such datasets to obtain a holistic view of virus-host interactions and to define the pathogenic properties of SARS-CoV-2 is limited by the heterogeneity of the experimental systems. Here we report a concurrent multi-omics study of SARS-CoV-2 and SARS-CoV. Using state-of-the-art proteomics, we profiled the interactomes of both viruses, as well as their influence on the transcriptome, proteome, ubiquitinome and phosphoproteome of a lung-derived human cell line. Projecting these data onto the global network of cellular interactions revealed crosstalk between the perturbations taking place upon infection with SARS-CoV-2 and SARS-CoV at different levels and enabled identification of distinct and common molecular mechanisms of these closely related coronaviruses. The TGF-β pathway, known for its involvement in tissue fibrosis, was specifically dysregulated by SARS-CoV-2 ORF8 and autophagy was specifically dysregulated by SARS-CoV-2 ORF3. The extensive dataset (available at https://covinet.innatelab.org ) highlights many hotspots that could be targeted by existing drugs and may be used to guide rational design of virus- and host-directed therapies, which we exemplify by identifying inhibitors of kinases and matrix metalloproteases with potent antiviral effects against SARS-CoV-2.

Selective Nonmethylated CpG DNA Recognition Mechanism of Cysteine Clamp Domains

Methylation of DNA at CpG sites is a major mark for epigenetic regulation, but how transcription factors are influenced by CpG methylation is not well understood. Here, we report the molecular mechanisms of how the TCF (T-cell factor) and GEF (glucose transporter 4 enhancer factor) families of proteins selectively target unmethylated DNA sequences with a C-clamp type zinc finger domain. The structure of the C-clamp domain from human GEF family protein HDBP1 (C-clamp^HDBP1) in complex with DNA was determined using NMR spectroscopy, which adopts a unique zinc finger fold and selectively binds RCCGG (R = A/G) DNA sequences with an "Arg···Trp-Lys-Lys" DNA recognition motif inserted in the major groove. The CpG base pairs are central to the binding due to multiple hydrogen bonds formed with the backbone carbonyl groups of Trp378 and Lys379, as well as the side chain ε-amino groups of Lys379 and Lys380 from C-clamp^HDBP1. Consequently, methylation of the CpG dinucleotide almost abolishes the binding. Homology modeling reveals that the C-clamp domain from human TCF1E (C-clamp^TCF1E) binds DNA through essentially the same mechanism, with a similar "Arg···Arg-Lys-Lys" DNA recognition motif. The substitution of tryptophan by arginine makes C-clamp^HDBP1 prefer RCCGC DNA sequences. The two signature DNA recognition motifs are invariant in the GEF and TCF families of proteins, respectively, from fly to human. The recognition of the CpG dinucleotide through two consecutive backbone carbonyl groups is the same as that of the CXXC type unmethylated CpG DNA binding domains, suggesting a common mechanism shared by unmethylated CpG binding proteins.

Effects of Curcumin and Ferulic Acid on the Folding of Amyloid-β Peptide

The polyphenols curcumin (CU) and ferulic acid (FA) are able to inhibit the aggregation of amyloid-β (Aβ) peptide with different strengths. CU is a strong inhibitor while FA is a weaker one. In the present study, we examine the effects of CU and FA on the folding process of an Aβ monomer by 1 µs molecular dynamics (MD) simulations. We found that both inhibitors increase the helical propensity and decrease the non-helical propensity of Aβ peptide. They prevent the formation of a dense bulk core and shorten the average lifetime of intramolecular hydrogen bonds in Aβ. CU makes more and longer-lived hydrogen bonds, hydrophobic, π–π, and cation–π interactions with Aβ peptide than FA does, which is in a good agreement with the observed stronger inhibitory activity of CU on Aβ aggregation.

Identification of multiple substrate binding sites in SLC4 transporters in the outward-facing conformation: Insights into the transport mechanism

Solute carrier family 4 (SLC4) transporters mediate the transmembrane transport of HCO₃^-, CO₃^2-, and Cl^- necessary for pH regulation, transepithelial H⁺/base transport, and ion homeostasis. Substrate transport with varying stoichiometry and specificity is achieved through an exchange mechanism and/or through coupling of the uptake of anionic substrates to typically co-transported Na⁺. Recently solved outward-facing structures of two SLC4 members (human anion exchanger 1 [hAE1] and human electrogenic sodium bicarbonate cotransporter 1 [hNBCe1]) with different transport modes (Cl^-/HCO₃^- exchange versus Na⁺-CO₃^2- symport) revealed highly conserved three-dimensional organization of their transmembrane domains. However, the exact location of the ion binding sites and their protein-ion coordination motifs are still unclear. In the present work, we combined site identification by ligand competitive saturation mapping and extensive molecular dynamics sampling with functional mutagenesis studies which led to the identification of two substrate binding sites (entry and central) in the outward-facing states of hAE1 and hNBCe1. Mutation of residues in the identified binding sites led to impaired transport in both proteins. We also showed that R730 in hAE1 is crucial for anion binding in both entry and central sites, whereas in hNBCe1, a Na⁺ acts as an anchor for CO₃^2- binding to the central site. Additionally, protonation of the central acidic residues (E681 in hAE1 and D754 in hNBCe1) alters the ion dynamics in the permeation cavity and may contribute to the transport mode differences in SLC4 proteins. These results provide a basis for understanding the functional differences between hAE1 and hNBCe1 and may facilitate potential drug development for diseases such as proximal and distal renal tubular acidosis.

Phenotypic characterization and predictive analysis of p.Asp47Asn LDL receptor mutation associated with Familial Hypercholesterolemia in a Chilean population

BACKGROUND

Familial hypercholesterolemia (FH) is an inherited disorder mainly caused by mutations in the LDL receptor (LDL-R) and characterized by elevation of low-density lipoprotein cholesterol (LDL-C) levels and premature cardiovascular disease.

OBJECTIVE

In this study, we evaluated the clinical phenotype of the p.Asp47Asn, described as an uncertain pathogenic variant, and its effect on the structure of LDL-R and ligand interactions with apolipoproteins.

METHODS

27 children and adolescents with suspected FH diagnosis were recruited from a pediatric endocrinology outpatient clinic. Blood samples were collected after 12 h fasting for lipid profile analysis. DNA sequencing was performed for six FH-related genes by Ion Torrent PGM platform and copy number variation by MLPA. For index cases, a familial cascade screening was done restricted to the same mutation found in the index case. In silico analysis were developed to evaluate the binding capacity of LDL-R to apolipoproteins B100 and E.

RESULTS

Lipid profile in children and adolescents demonstrated higher LDL-C levels in p.Asp47Asn carriers compared to the wild type genotype. In silico analysis predicted a reduction in the binding capacity of the ligand-binding modules LA1-2 of p.Asp47Asn LDL-R for ApoB100 and ApoE, which was not produced by local structural changes or folding defects but as a consequence of a decreased apparent affinity for both apolipoproteins.

CONCLUSION

The clinical phenotype and the structural effects of p.Asp47Asn LDL-R mutation suggest that this variant associates to FH.

Microcanonical insights into the physicochemical stability of the coformulation of insulin with amylin analogues

Injections of insulin are the main treatment for diabetes, but in the long run this therapy can induce serious drawbacks. This has inspired new drugs able to decrease insulin requirements. For instance, human amylin (hIAPP) is a small hormone cosecreted by pancreatic β-cells with insulin to which is a synergistic partner. However, the high amyloidogenicity of hIAPP precluded it as a therapeutics and led to the design of pramlintide (sIAPP), a chimeric analogue with substitutions (A25P, S28P, and S29P) inherited from the aggregation-resistant rat isoform (rIAPP). Despite sIAPP advantages, it still shares with hIAPP a poorly soluble profile at physiological pH that hampers its mixture with insulin. Recent improvements, as charge-enhanced mutants, have been proposed. For instance, sIAPP⁺ was screened in silico by purely microcanonical thermostatistical methods and adds to sIAPP an S20R mutation to uplift its solubility. This suggests that such physically inspired computational approach may also be auspicious on devising effective coformulations of insulin with amylin analogues. In this seminal attempt, we make comparative multicanonical simulations of regular acting human insulin coformulated with hIAPP, sIAPP, or sIAPP⁺. To assess the respective physicochemical stabilities against aggregation, we characterize the structural-phase transitions through the microcanonical thermodynamic formalism and evaluate their time lags using the classical nucleation theory. These results are then correlated with estimates of solvation free energies, modeled by the Poisson-Boltzmann equation, and structural propensities. Experimental essays are compared to our simulations and support our methodology.

Guardians of the Cell: State-of-the-Art of Membrane Proteins from a Computational Point-of-View

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures

The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF_1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.

Identification of a novel umami peptide in tempeh (Indonesian fermented soybean) and its binding mechanism to the umami receptor T1R

Tempeh, a traditional Indonesian soybean product produced by fermentation, is especially popular because of its umami taste. In this study, a novel umami peptide GENEEEDSGAIVTVK (GK-15) was identified in the small peptide (<3 kDa) fraction of the water extract of tempeh using LC-MS/MS analysis and database-assisted identification. The umami taste of GK-15 was further validated using sensory evaluation, which suggested that GK-15 may be one of the key components contributing to the umami taste in tempeh. To rationalize the biological effect of GK-15, molecular docking of GK-15 into the N-terminal extracellular ligand-binding domain of the umami (T1R) receptor was performed. ZDOCK data showed that GK-15 could perfectly bind either to the open or closed conformation of T1R3. To the best of our knowledge, the present work is the first study to focus on the screening of umami peptides from tempeh.

Mg2+ Sensing by an RNA Fragment: Role of Mg2+-Coordinated Water Molecules

RNA molecules selectively bind to specific metal ions to populate their functional active states, making it important to understand their source of ion selectivity. In large RNA systems, metal ions interact with the RNA at multiple locations, making it difficult to decipher the precise role of ions in folding. To overcome this complexity, we studied the role of different metal ions (Mg²⁺, Ca²⁺, and K⁺) in the folding of a small RNA hairpin motif (5'-ucCAAAga-3') using unbiased all-atom molecular dynamics simulations. The advantage of studying this system is that it requires specific binding of a single metal ion to fold to its native state. We find that even for this small RNA, the folding free energy surface (FES) is multidimensional as different metal ions present in the solution can simultaneously facilitate folding. The FES shows that specific binding of a metal ion is indispensable for its folding. We further show that in addition to the negatively charged phosphate groups, the spatial organization of electronegative nucleobase atoms drives the site-specific binding of the metal ions. Even though the binding site cannot discriminate between different metal ions, RNA folds efficiently only in a Mg²⁺ solution. We show that the rigid network of Mg²⁺-coordinated water molecules facilitates the formation of important interactions in the transition state. The other metal ions such as K⁺ and Ca²⁺ cannot facilitate the formation of such interactions. These results allow us to hypothesize possible metal-sensing mechanisms in large metalloriboswitches and also provide useful insights into the design of appropriate collective variables for studying large RNA molecules using enhanced sampling methods.

Computational evaluation of modified peptides from human neutrophil peptide 1 (HNP-1)

The development of bacterial resistance toward antibiotics has been led to pay attention to the antimicrobial peptides (AMPs). The common mechanism of AMPs is disrupting the integrity of the bacterial membrane. One of the most accessible targets for α-defensins human neutrophil peptide-1 (HNP-1) is lipid II. In the present study, we performed homology modeling and geometrical validation of human neutrophil defensin 1. Then, the conformational and physicochemical properties of HNP-1 derived peptides 2Abz¹⁴S²⁹, 2Abz²³S²⁹, and HNP1ΔC18A, as well as their interaction with lipid II were studied computationally. The overall quality of the predicted model of full protein was -5.14, where over 90% of residues were in the most favored and allowed regions in the Ramachandran plot. Although HNP-1 and HNP1ΔC18A were classified as unstable peptides, 2Abz¹⁴S²⁹ and 2Abz²³S²⁹ were stable, based on the instability index values. Molecular docking showed similar interaction pattern of peptides and HNP-1 to lipid II. Molecular dynamic simulations revealed the overall stability of conformations, though the fluctuations of amino acids in the modified peptides were relatively higher than HNP-1. Further, the binding affinity constant (Kd) of HNP-1 and 2Abz²³S²⁹ in complex with lipid II was 10 times stronger than 2Abz¹⁴S²⁹ and HNP1ΔC18A. Overall, computational studies of conformational and interaction patterns have signified how derived peptides could have displayed relatively similar antimicrobial results compared to HNP-1 in the reported experimental studies. Chemical modifications not only have improved the physicochemical properties of derived peptides compared to HNP-1, but also they have retained the similar pattern and binding affinity of peptides. Communicated by Ramaswamy H. Sarma.

Calcium and hydroxyapatite binding site of human vitronectin provides insights to abnormal deposit formation

The human blood protein vitronectin (Vn) is a major component of the abnormal deposits associated with age-related macular degeneration, Alzheimer's disease, and many other age-related disorders. Its accumulation with lipids and hydroxyapatite (HAP) has been demonstrated, but the precise mechanism for deposit formation remains unknown. Using a combination of solution and solid-state NMR experiments, cosedimentation assays, differential scanning fluorimetry (DSF), and binding energy calculations, we demonstrate that Vn is capable of binding both soluble ionic calcium and crystalline HAP, with high affinity and chemical specificity. Calcium ions bind preferentially at an external site, at the top of the hemopexin-like (HX) domain, with a group of four Asp carboxylate groups. The same external site is also implicated in HAP binding. Moreover, Vn acquires thermal stability upon association with either calcium ions or crystalline HAP. The data point to a mechanism whereby Vn plays an active role in orchestrating calcified deposit formation. They provide a platform for understanding the pathogenesis of macular degeneration and other related degenerative disorders, and the normal functions of Vn, especially those related to bone resorption.

Pattern and Dynamics of FLT3 Duplications

FMS-like tyrosine kinase 3 (FLT3) is mutated in ∼30% of patients that suffer from acute myeloid leukemia (AML). In about 25% of all AML patients, in-frame insertions are observed in the sequence. Most of those insertions are internal tandem duplications (ITDs) of a sequence from the protein. The characteristics of such mutations in terms of length, sequence, and location were hitherto studied in different populations, but not in a comprehensive mutation database. Here, in-frame insertions into the FLT3 gene were extracted from the Catalogue of Somatic Mutations in Cancer (COSMIC) database. These were analyzed with respect to the length, location, and sequence of the mutations. Furthermore, characteristic strings (sequences) of different lengths were identified. Mutations were shown to occur most often in the juxtamembrane zipper (JM-Z) domain of FLT3, followed by the hinge domain and first tyrosine kinase domain (TKD1), upstream of the phosphate-binding loop (P-loop). Interestingly, there are specific hot spot residues where insertions are more likely to occur. The insertions vary in length between one and 67 amino acids, with the largest insertions spanning the phosphate binding loop. Insertions that occur downstream of the P-loop are shorter. Our analysis further shows that acidic and aromatic residues are enriched in the insertions. Finally, molecular dynamics simulations were run for FLT3 with ITD insertions in the hinge and tyrosine kinase domains. On the basis of the findings, a mechanism is proposed for activation by ITDs, according to which there is no direct coupling between the length of the insertion and the activity of the mutated protein. The effect of insertions on the sensitivity of FLT3 to kinase inhibitors is discussed based on our findings.

Protein electrostatics: From computational and structural analysis to discovery of functional fingerprints and biotechnological design

Computationally driven engineering of proteins aims to allow them to withstand an extended range of conditions and to mediate modified or novel functions. Therefore, it is crucial to the biotechnological industry, to biomedicine and to afford new challenges in environmental sciences, such as biocatalysis for green chemistry and bioremediation. In order to achieve these goals, it is important to clarify molecular mechanisms underlying proteins stability and modulating their interactions. So far, much attention has been given to hydrophobic and polar packing interactions and stability of the protein core. In contrast, the role of electrostatics and, in particular, of surface interactions has received less attention. However, electrostatics plays a pivotal role along the whole life cycle of a protein, since early folding steps to maturation, and it is involved in the regulation of protein localization and interactions with other cellular or artificial molecules. Short- and long-range electrostatic interactions, together with other forces, provide essential guidance cues in molecular and macromolecular assembly. We report here on methods for computing protein electrostatics and for individual or comparative analysis able to sort proteins by electrostatic similarity. Then, we provide examples of electrostatic analysis and fingerprints in natural protein evolution and in biotechnological design, in fields as diverse as biocatalysis, antibody and nanobody engineering, drug design and delivery, molecular virology, nanotechnology and regenerative medicine.