Prediction of water and metal binding sites and their affinities by using the Fold-X force field

HydraProt: A New Deep Learning Tool for Fast and Accurate Prediction of Water Molecule Positions for Protein Structures

Water molecules are integral to the structural stability of proteins and vital for facilitating molecular interactions. However, accurately predicting their precise position around protein structures remains a significant challenge, making it a vibrant research area. In this paper, we introduce HydraProt (deep Hydration of Proteins), a novel methodology for predicting precise positions of water molecule oxygen atoms around protein structures, leveraging two interconnected deep learning architectures: a 3D U-net and a Multi-Layer Perceptron (MLP). Our approach starts by introducing a coarse voxel-based representation of the protein, which allows for rapid sampling of candidate water positions via the 3D U-net. These water positions are then assessed by embedding the water-protein relationship in the Euclidean space by means of an MLP. Finally, a postprocessing step is applied to further refine the MLP predictions. HydraProt surpasses existing state-of-the-art approaches in terms of precision and recall and has been validated on large data sets of protein structures. Notably, our method offers rapid inference runtime and should constitute the method of choice for protein structure studies and drug discovery applications. Our pretrained models, data, and the source code required to reproduce these results are accessible at https://github.com/azamanos/HydraProt.

Eu3+ detects two functionally distinct luminal Ca2+ binding sites in ryanodine receptors

Ryanodine receptors (RyRs) are Ca2+ release channels, gated by Ca2+ in the cytosol and the sarcoplasmic reticulum lumen. Their regulation is impaired in certain cardiac and muscle diseases. Although a lot of data is available on the luminal Ca2+ regulation of RyR, its interpretation is complicated by the possibility that the divalent ions used to probe the luminal binding sites may contaminate the cytoplasmic sites by crossing the channel pore. In this study, we used Eu3+, an impermeable agonist of Ca2+ binding sites, as a probe to avoid this complication and to gain more specific information about the function of the luminal Ca2+ sensor. Single-channel currents were measured from skeletal muscle and cardiac RyRs (RyR1 and RyR2) using the lipid bilayer technique. We show that RyR2 is activated by the luminal addition of Ca2+, whereas RyR1 is inhibited. These results were qualitatively reproducible using Eu3+. The luminal regulation of RyR1 carrying a mutation associated with malignant hyperthermia was not different from that of the wild-type. RyR1 inhibition by Eu3+ was extremely voltage dependent, whereas RyR2 activation did not depend on the membrane potential. These results suggest that the RyR1 inhibition site is in the membrane's electric field (channel pore), whereas the RyR2 activation site is outside. Using in silico analysis and previous results, we predicted putative Ca2+ binding site sequences. We propose that RyR2 bears an activation site, which is missing in RyR1, but both isoforms share the same inhibitory Ca2+ binding site near the channel gate.

Uncovering the interactions between PME and PMEI at the gene and protein levels: Implications for the design of specific PMEI

CONTEXT

Pectin methylesterase inhibitor (PMEI) can specifically bind and inhibit the activity of pectin methylesterase (PME), which has been widely used in fruit and vegetable juice processing. However, the limited three-dimensional structure, unclear action mechanism, low thermal stability and biological activity of PMEI severely limited its application. In this work, molecular recognition and conformational changes of PME and PMEI were analyzed by various molecular simulation methods. Then suggestions were proposed for improving thermal stability and affinity maturation of PMEI through semi-rational design.

METHODS

Phylogenetic trees of PME and PMEI were established using the Maximum likelihood (ML) method. The results show that PME and PMEI have good sequence and structure conservation in various plants, and the simulated data can be widely adopted. In this work, MD simulations were performed using AMBER20 package and ff14SB force field. Protein interaction analysis indicates that H-bonds, van der Waals forces, and the salt bridge formed of K224 with ID116 are the main driving forces for mutual molecular recognition of PME and PMEI. According to the analyses of free energy landscape (FEL), conformational cluster, and motion, the association with PMEI greatly disrupts PME's dispersed functional motion mode and biological function. By monitoring the changes of residue contact number and binding free energy, IG35M/ IG35R: IT93F and IT113W/ IT113W: ID116W mutations contribute to thermal stability and affinity maturation of the PME-PMEI complex system, respectively. This work reveals the interaction between PME and PMEI at the gene and protein levels and provides options for modifying specific PMEI.

Insight into de-regulation of amino acid feedback inhibition: a focus on structure analysis method

Regulation of amino acid's biosynthetic pathway is of significant importance to maintain homeostasis and cell functions. Amino acids regulate their biosynthetic pathway by end-product feedback inhibition of enzymes catalyzing committed steps of a pathway. Discovery of new feedback resistant enzyme variants to enhance industrial production of amino acids is a key objective in industrial biotechnology. Deregulation of feedback inhibition has been achieved for various enzymes using in vitro and in silico mutagenesis techniques. As enzyme's function, its substrate binding capacity, catalysis activity, regulation and stability are dependent on its structural characteristics, here, we provide detailed structural analysis of all feedback sensitive enzyme targets in amino acid biosynthetic pathways. Current review summarizes information regarding structural characteristics of various enzyme targets and effect of mutations on their structures and functions especially in terms of deregulation of feedback inhibition. Furthermore, applicability of various experimental as well as computational mutagenesis techniques to accomplish feedback resistance has also been discussed in detail to have an insight into various aspects of research work reported in this particular field of study.

The Advances and Limitations of the Determination and Applications of Water Structure in Molecular Engineering

Water is a key actor of various processes of nature and, therefore, molecular engineering has to take the structural and energetic consequences of hydration into account. While the present review focuses on the target-ligand interactions in drug design, with a focus on biomolecules, these methods and applications can be easily adapted to other fields of the molecular engineering of molecular complexes, including solid hydrates. The review starts with the problems and solutions of the determination of water structures. The experimental approaches and theoretical calculations are summarized, including conceptual classifications. The implementations and applications of water models are featured for the calculation of the binding thermodynamics and computational ligand docking. It is concluded that theoretical approaches not only reproduce or complete experimental water structures, but also provide key information on the contribution of individual water molecules and are indispensable tools in molecular engineering.

Improving ethanol tolerance of ethyl carbamate hydrolase by diphasic high pressure molecular dynamic simulations

Ethyl carbamate (EC) is mainly found in fermented foods and fermented alcoholic beverages, which could cause carcinogenic potential to humans. Reducing EC is one of the key research priorities to address security of fermented foods. Enzymatic degradation of EC with EC hydrolase in food is the most reliable and efficient method. However, poor tolerance to ethanol severely hinders application of EC hydrolase. In this study, the mutants of EC hydrolase were screened by diphasic high pressure molecular dynamic simulations (dHP-MD). The best variant with remarkable improvement in specific activity and was H68A/K70R/S325N, whose specific activity was approximately 3.42-fold higher than WT, and relative enzyme activity under 20% (v/v) was 5.02-fold higher than WT. Moreover, the triple mutant increased its stability by acquiring more hydration shell and forming extra hydrogen bonds. Furthermore, the ability of degrading EC of the immobilized triple mutant was both detected in mock wine and under certain reaction conditions. The stability of immobilized triple mutant and WT were both improved, and immobilized triple mutant degraded nearly twice as much EC as that of immobilized WT. Overall, dHP-MD was proved to effectively improve enzyme activity and ethanol tolerance for extent application at industrial scale.

SCAMPER: Accurate Type-Specific Prediction of Calcium-Binding Residues Using Sequence-Derived Features

Understanding molecular mechanisms involved in calcium-protein interactions and modeling corresponding docking rely on the accurate identification of calcium-binding residues (CaBRs). The defects of experimentally annotating protein functions enhances the development of computational approaches that correctly identify calcium-binding interactions. Studies have reported that current methods severely cross-predict residues that interact with other types of molecules (e.g., nucleic acids, proteins, and small ligands) as CaBRs. In this study, a novel predictor named SCAMPER (Selective CAlciuM-binding PrEdictoR) is proposed for the accurate and specific prediction of CaBRs. SCAMPER is designed using newly compiled dataset with complete UniProt sequences and annotations, which include calcium-binding, nucleic acid-binding, protein-binding, and small ligand-binding residues. We use a novel designed two-layer scheme to perform predictions as well as penalize cross-predictions. Empirical tests on an independent test dataset reveals that the proposed method significantly outperforms state-of-the-art predictors. SCAMPER is proved to be capable of distinguishing CaBRs from different types of metal-ion binding residues. We further perform CaBRs predictions on the whole human proteome, and use the results to hypothesize calcium-binding proteins (CaBPs). The latest experimental verified CaBPs and GO analysis prove the accuracy of our predictions. We implement the proposed method and share the data at http://www.inforstation.com/webservers/SCAMPER/.

Flexible biomimetic block copolymer composite for temperature and long-wave infrared sensing

Biological compounds often provide clues to advance material designs. Replicating their molecular structure and functional motifs in artificial materials offers a blueprint for unprecedented functionalities. Here, we report a flexible biomimetic thermal sensing (BTS) polymer that is designed to emulate the ion transport dynamics of a plant cell wall component, pectin. Using a simple yet versatile synthetic procedure, we engineer the physicochemical properties of the polymer by inserting elastic fragments in a block copolymer architecture, making it flexible and stretchable. The thermal response of our flexible polymer outperforms current state-of-the-art temperature sensing materials, including vanadium oxide, by up to two orders of magnitude. Thermal sensors fabricated from these composites exhibit a sensitivity that exceeds 10 mK and operate stably between 15° and 55°C, even under repeated mechanical deformations. We demonstrate the use of our flexible BTS polymer in two-dimensional arrays for spatiotemporal temperature mapping and broadband infrared photodetection.

GPDOCK: highly accurate docking strategy for metalloproteins based on geometric probability

Accurately predicting the interaction modes for metalloproteins remains extremely challenging in structure-based drug design and mechanism analysis of enzymatic catalysis due to the complexity of metal coordination in metalloproteins. Here, we report a docking method for metalloproteins based on geometric probability (GPDOCK) with unprecedented accuracy. The docking tests of 10 common metal ions with 9360 metalloprotein-ligand complexes demonstrate that GPDOCK has an accuracy of 94.3% in predicting binding pose. What is more, it can accurately realize the docking of metalloproteins with ligand when one or two water molecules are engaged in the metal ion coordination. Since GPDOCK only depends on the three-dimensional structure of metalloprotein and ligand, structure-based machine learning model is employed for the scoring of binding poses, which significantly improves computational efficiency. The proposed docking strategy can be an effective and efficient tool for drug design and further study of binding mechanism of metalloproteins. The manual of GPDOCK and the code for the logistical regression model used to re-rank the docking results are available at https://github.com/wangkai-zhku/GPDOCK.git.

Antibody CDR amino acids underlying the functionality of antibody repertoires in recognizing diverse protein antigens

Antibodies recognize protein antigens with exquisite specificity in a complex aqueous environment, where interfacial waters are an integral part of the antibody–protein complex interfaces. In this work, we elucidate, with computational analyses, the principles governing the antibodies’ specificity and affinity towards their cognate protein antigens in the presence of explicit interfacial waters. Experimentally, in four model antibody–protein complexes, we compared the contributions of the interaction types in antibody–protein antigen complex interfaces with the antibody variants selected from phage-displayed synthetic antibody libraries. Evidently, the specific interactions involving a subset of aromatic CDR (complementarity determining region) residues largely form the predominant determinant underlying the specificity of the antibody–protein complexes in nature. The interfacial direct/water-mediated hydrogen bonds accompanying the CDR aromatic interactions are optimized locally but contribute little in determining the epitope location. The results provide insights into the phenomenon that natural antibodies with limited sequence and structural variations in an antibody repertoire can recognize seemingly unlimited protein antigens. Our work suggests guidelines in designing functional artificial antibody repertoires with practical applications in developing novel antibody-based therapeutics and diagnostics for treating and preventing human diseases.

The activity of the RGA5 sensor NLR from rice requires binding of its integrated HMA domain to effectors but not HMA domain self-interaction

The rice nucleotide-binding (NB) and leucine-rich repeat (LRR) domain immune receptors (NLRs) RGA4 and RGA5 form a helper NLR/sensor NLR (hNLR/sNLR) pair that specifically recognizes the effectors AVR-Pia and AVR1-CO39 from the blast fungus Magnaporthe oryzae. While RGA4 contains only canonical NLR domains, RGA5 has an additional unconventional heavy metal-associated (HMA) domain integrated after its LRR domain. This RGA5HMA domain binds the effectors and is crucial for their recognition. Investigation of the three-dimensional structure of the AVR1-CO39/RGA5HMA complex by X-ray crystallography identified a candidate surface for effector binding in the HMA domain and showed that the HMA domain self-interacts in the absence of effector through the same surface. Here, we investigated the relevance of this HMA homodimerization for RGA5 function and the role of the RGA5HMA effector-binding and self-interaction surface in effector recognition. By analysing structure-informed point mutations in the RGA5HMA -binding surface in protein interaction studies and in Nicotiana benthamiana cell death assays, we found that HMA self-interaction does not contribute to RGA5 function. However, the effector-binding surface of RGA5HMA identified by X-ray crystallography is crucial for both in vitro and in vivo effector binding as well as effector recognition. These results support the current hypothesis that noncanonical integrated domains of NLRs act primarily as effector traps and deepen our understanding of the sNLRs' function within NLR pairs.

Heterotropic roles of divalent cations in the establishment of allostery and affinity maturation of integrin αXβ2

Allosteric activation and silencing of leukocyte β2-integrins transpire through cation-dependent structural changes, which mediate integrin biosynthesis and recycling, and are essential to designing leukocyte-specific drugs. Stepwise addition of Mg²⁺ reveals two mutually coupled events for the αXβ2 ligand-binding domain-the αX I-domain-corresponding to allostery establishment and affinity maturation. Electrostatic alterations in the Mg²⁺-binding site establish long-range couplings, leading to both pH- and Mg²⁺-occupancy-dependent biphasic stability change in the αX I-domain fold. The ligand-binding sensorgrams show composite affinity events for the αX I-domain accounting for the multiplicity of the αX I-domain conformational states existing in the solution. On cell surfaces, increasing Mg²⁺ concentration enhanced adhesiveness of αXβ2. This work highlights how intrinsically flexible pH- and cation-sensitive architecture endows a unique dynamic continuum to the αI-domain structure on the intact integrin, thereby revealing the importance of allostery establishment and affinity maturation in both extracellular and intracellular integrin events.

Molecular Modeling and Phenotypic Description of a Patient with a Novel Exonic Deletion of GALNS with Resultant Morquio Syndrome with Two Successful Pregnancies

In this report, we describe phenotypic features of a patient with mucopolysaccharidosis type IVA (Morquio syndrome) harboring a novel exon 1 deletion in GALNS with enzymatic confirmation consistent with Morquio syndrome. To our knowledge, this is the first reported case of this variant. Additionally, we protein modelled wild-type GALNS and the pathogenic variant with an exon 1 deletion for comparative analysis using statistical mechanics methods described herein. We demonstrate that, even when the protein is translated, the mutation would affect protein stability and function via homodimer interaction modifications. Lastly, given the patient's 2 successful pregnancies, data about the management of pregnancies in mucopolysaccharidoses are reviewed, and we discuss the management of pregnancy in patients with Morquio syndrome.

MetBP: A Software Tool for Detection of Interaction between Metal Ion-RNA Base Pairs

MOTIVATION

The role of metals in shaping and functioning of RNA is a well established fact and the understanding of that through the analysis of structural data has biological relevance. Often metal ions bind to one or more atoms of the nucleobase of an RNA. This fact becomes more interesting when such bases form a base pair with any other base. Furthermore, when metal ions bind to any residue of an RNA, the secondary structural features of the residue (helix, loop, unpaired etc) are also biologically important. The available metal binding related software tools cannot address such type specific queries.

RESULTS

To fill this limitation, we have designed a software tool, called MetBP, that meets the goal. This tool is a stand-alone command line based tool and has no dependency on the other existing software. It accepts a structure file in mmCIF or PDB format and computes the base pairs and thereafter reports all metals that bind to one or more nucleotides that form pairs with another. It reports binding distance, angles along with base pair stability. It also reports several other important aspects, e.g. secondary structure of the residue in the RNA. MetBP can be used as a generalized metal binding site detection tool for Proteins and DNA as well.

AVAILABILITY

https://github.com/computational-biology/metbp.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PlaceWaters: Real-time, explicit interface water sampling during Rosetta ligand docking

Water molecules at the protein-small molecule interface often form hydrogen bonds with both the small molecule ligand and the protein, affecting the structural integrity and energetics of a binding event. The inclusion of these 'bridging waters' has been shown to improve the accuracy of predicted docked structures; however, due to increased computational costs, this step is typically omitted in ligand docking simulations. In this study, we introduce a resource-efficient, Rosetta-based protocol named "PlaceWaters" to predict the location of explicit interface bridging waters during a ligand docking simulation. In contrast to other explicit water methods, this protocol is independent of knowledge of number and location of crystallographic waters in homologous structures. We test this method on a diverse protein-small molecule benchmark set in comparison to other Rosetta-based protocols. Our results suggest that this coarse-grained, structure-based approach quickly and accurately predicts the location of bridging waters, improving our ability to computationally screen drug candidates.

Calcium Ion Binding to the Mutants of Calmodulin: A Structure-Based Computational Predictive Model of Binding Affinity Using a Charge Scaling Approach in Molecular Dynamics Simulation

The binding of calcium ions (Ca²⁺) to the calcium-binding proteins (CBPs) controls a plethora of regulatory processes. Among the roles played by CBPs in several diseases, the onset and progress of some cardiovascular diseases are caused by mutations in calmodulin (CaM), an important member of CBPs. Rationalization and prediction of the binding affinity of Ca²⁺ ions to the CaM can play important roles in understanding the origin of cardiovascular diseases. However, there is no robust structure-based computational method for predicting the binding affinity of Ca²⁺ ions to the different forms of CBPs in general and CaM in particular. In the current work, we have devised a fast yet accurate computational technique to accurately calculate the binding affinity of Ca²⁺ to the different forms of CaM. This method combines the well-known molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method and a charge scaling approach developed by previous authors that takes care of the polarization of CaM and Ca²⁺ ions. Our detailed analysis of the different components of binding free energy shows that subtle changes in electrostatics and van der Waals contribute to the difference in the binding affinity of mutants from that of the wild type (WT), and the charge scaling approach is superior in calculating these subtle changes in electrostatics as compared to the nonpolarizable force field used in this work. A statistically significant regression model made from our binding free energy calculations gives a correlation coefficient close to 0.8 to the experimental results. This structure-based predictive model can open up a new strategy to understand and predict the binding of Ca²⁺ to the mutants of CBPs, in general.

Structural insights into collagen binding by platelet receptor glycoprotein VI

Glycoprotein VI (GPVI) mediates collagen-induced platelet activation after vascular damage and is an important contributor to the onset of thrombosis, heart attack, and stroke. Animal models of thrombosis have identified GPVI as a promising target for antithrombotic therapy. Although for many years the crystal structure of GPVI has been known, the essential details of its interaction with collagen have remained elusive. Here, we present crystal structures of the GPVI ectodomain bound to triple-helical collagen peptides, which reveal a collagen-binding site across the β-sheet of the D1 domain. Mutagenesis and binding studies confirm the observed binding site and identify Trp76, Arg38, and Glu40 as essential residues for binding to fibrillar collagens and collagen-related peptides (CRPs). GPVI binds a site on collagen comprising two collagen chains with the core formed by the sequence motif OGPOGP. Potent GPVI-binding peptides from Toolkit-III all contain OGPOGP; weaker binding peptides frequently contain a partial motif varying at either terminus. Alanine-scanning of peptide III-30 also identified two AGPOGP motifs that contribute to GPVI binding, but steric hindrance between GPVI molecules restricts the maximum binding capacity. We further show that no cooperative interactions could occur between two GPVI monomers binding to a stretch of (GPO)5 and that binding of ≥2 GPVI molecules to a fibril-embedded helix requires non-overlapping OGPOGP motifs. Our structure confirms the previously suggested similarity in collagen binding between GPVI and leukocyte-associated immunoglobulin-like receptor 1 (LAIR-1) but also indicates significant differences that may be exploited for the development of receptor-specific therapeutics.

Humanizing plant-derived snakins and their encrypted antimicrobial peptides

Due to safety restrictions, plant-derived antimicrobial peptides (AMPs) need optimization to be consumed beyond preservatives. Herein, 175 GASA-domain-containing snakins were analyzed. Factors including charge, hydrophobicity, helicity, hydrophobic moment (μH), folding enthalpy, folding heat capacity, folding free energy, therapeutic index, allergenicity, and bitterness were considered. The most optimal snakins for oral consumption as preservatives were from Cajanus cajan, Cucumis melo, Durio zibethinus, Glycine soja, Herrania umbratica, and Ziziphus jujuba. Virtual digestion of snakins predicted ACE1 and DPPIV inhibitory as dominant effects upon oral use with antihypertensive and antidiabetic properties. To be applied as a therapeutic in parenteral administration, snakins were browsed for short 20-mer encrypted fragments that were non-toxic or with eliminated toxicity using directed mutagenesis yet retaining the AMP property. The most promising 20-mer AMPs were Mr-SNK2-1a in Morella rubra with BBB permeation, Na-SNK2-2a(C¹⁸W), and Na-SNK2-2b(C¹⁶F) from Nicotiana attenuata. These AMPs were cell-penetrating peptides (CPPs), with a charge of +6, a μH of about 0.40, and a Boman-index higher than 2.48 Kcalmol^-1. Na-SNK2-2a(C¹⁸W) had putative activity against gram-negative bacteria with MIC lower than 25 μgml^-1, and Na-SNK2-2b(C¹⁶F) was a potential anti-HIV with an IC₅₀ of 3.04 μM. Other 20-mer AMPs, such as Cc-SNK1-2a from Cajanus cajan displayed an anti-HCV property with an IC₅₀ of 13.91 μM. While Si-SNK2-3a(C¹⁷P) from Sesamum indicum was a cationic anti-angiogenic CPP targeting the acidic microenvironment of tumors, Cme-SNK2-1a(C¹¹F) from Cucumis melo was an immunomodulator CPP applicable as a vaccine adjuvant. Because of combined mechanisms, investigating cysteine-rich peptides can nominate effective biotherapeutics.

Proteins' Evolution upon Point Mutations

As the reader must be already aware, state-of-the-art protein folding prediction methods have reached a smashing success in their goal of accurately determining the three-dimensional structures of proteins. Yet, a solution to simple problems such as the effects of protein point mutations on their (i) native conformation; (ii) marginal stability; (iii) ensemble of high-energy nativelike conformations; and (iv) metamorphism propensity and, hence, their evolvability, remains as an unsolved problem. As a plausible solution to the latter, some properties of the amide hydrogen-deuterium exchange, a highly sensitive probe of the structure, stability, and folding of proteins, are assessed from a new perspective. The preliminary results indicate that the protein marginal stability change upon point mutations provides the necessary and sufficient information to estimate, through a Boltzmann factor, the evolution of the amide hydrogen exchange protection factors and, consequently, that of the ensemble of folded conformations coexisting with the native state. This work contributes to our general understanding of the effects of point mutations on proteins and may spur significant progress in our efforts to develop methods to determine the appearance of new folds and functions accurately.

Isotype-specific binding patterns of serum antibodies to multiple conformational epitopes of Bet v 1

BACKGROUND

Birch pollen is an important elicitor of respiratory allergy. The major allergen, Bet v 1, binds IgE exclusively via conformational epitopes.

OBJECTIVE

To identify Bet v 1-specific epitope repertoires of IgE and IgG from birch pollen-allergic and non-allergic subjects.

METHODS

Chimeric proteins were created by grafting individual epitope-sized, contiguous surface patches of Bet v 1 onto a non-allergenic structural homologue and expressed in Escherichia coli. Binding of IgE, IgG1 and IgG4 from sera of 30 birch pollen-allergic and 11 non-allergic subjects to Bet v 1, 13 chimeric proteins and four bacterial Bet v 1 homologues were measured by ELISA. The proportion of epitope-specific in total Bet v 1-specific IgE and the cross-reactivity of Bet v 1-specific IgE with bacterial homologues were determined by competitive ELISA.

RESULTS

Thirteen soluble, correctly folded chimeric proteins were produced. IgE from 27/30 birch pollen-allergic patients bound to 1-12 chimeric proteins (median 4.0) with patient-specific patterns. Three chimeras binding IgE from the majority of sera were identified, whose pgrafted patches overlapped with previously published epitopes. Patterns of IgG1 and IgG4 binding to the chimeric proteins did not correspond to the binding patterns of IgE. Sera of 19/30 birch pollen-allergic patients contained low amounts of IgE to bacterial homologues. Bacterial proteins were able to partially inhibit IgE binding to Bet v 1.

CONCLUSION

Epitopes recognized by Bet v 1-specific antibodies from birch pollen-allergic patients are specific to each patient and differ between IgE, IgG1 and IgG4.

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.

Water molecules at protein-drug interfaces: computational prediction and analysis methods

The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.

Characterization of a Stable Form of Carboxypeptidase G2 (Glucarpidase), a Potential Biobetter Variant, From Acinetobacter sp. 263903-1

Carboxypeptidase G2 (CPG2) is a bacterial enzyme widely used to detoxify methotrexate (MTX) and in enzyme/prodrug therapy for cancer treatment. However, several drawbacks, such as instability, have limited its efficiency. Herein, we have evaluated the properties of a putative CPG2 from Acinetobacter sp. 263903-1 (AcCPG2). AcCPG2 is compared with a CPG2 derived from Pseudomonas sp. strain RS-16 (PsCPG2), available as an FDA-approved medication called glucarpidase. After modeling AcCPG2 using the I-TASSER program, the refined model was validated by PROCHECK, VERIFY 3D and according to the Z score of the model. Using computational analyses, AcCPG2 displayed higher thermodynamic stability and a lower aggregation propensity than PsCPG2. AcCPG2 showed an optimum pH of 7.5 against MTX and was stable over a pH range of 5-10. AcCPG2 exhibited optimum activity at 50 °C and higher thermal stability at a temperature range of 20-70 °C compared to PsCPG2. The K_m value of the purified AcCPG2 toward folate and MTX was 31.36 µM and 44.99 µM, respectively. The V_max value of AcCPG2 for folate and MTX was 125.80 µmol/min/mg and 48.90  µmol/min/mg, respectively. Accordingly, thermostability and pH versatility makes AcCPG2 a potential biobetter variant for therapeutic applications.

A single residue deletion in the barley HKT1;5 P189 variant restores plasma membrane localisation but not Na+ conductance

Leaf Na⁺ exclusion, mediated by plasma membrane-localised Class 1 High-affinity potassium (K⁺) Transporters (HKTs), is a key mechanism contributing to salinity tolerance of several major crop plants. We determined previously that the leucine to proline residue substitution at position 189 (L189P) in barley HvHKT1;5 disrupts its characteristic plasma membrane localisation and Na⁺ conductance. Here, we focus on a surprising observation that a single residue deletion of methionine at position 372 (M372del) within the conserved VMMYL motif in plant HKTs, restores plasma membrane localisation but not Na⁺ conductance in HvHKT1;5 P189. To clarify why the singular M372 deletion regains plasma membrane localisation, we built 3D models and defined α-helical assembly pathways of the P189 M372del mutant, and compared these findings to the wild-type protein, and the HvHKT1;5 L189 variant and its M372del mutant. We find that α-helical association and assembly pathways in HvHKT1;5 proteins fall in two contrasting categories. Inspections of structural flexibility through molecular dynamics simulations revealed that the conformational states of HvHKT1;5 P189 diverge from those of the L189 variant and M372del mutants. We propose that M372del in HvHKT1;5 P189 instigates structural rearrangements allowing routing to the plasma membrane, while the restoration of conductance would require further interventions. We integrate the microscopy, electrophysiology, and biocomputational data and discuss how a profound structural change in HvHKT1;5 P189 M372del impacts its α-helical protein association pathway and flexibility, and how these features underlie a delicate balance leading to restoring plasma membrane localisation but not Na⁺ conductance.

Cohesin-dockerin code in cellulosomal dual binding modes and its allosteric regulation by proline isomerization

Cellulose is the most abundant organic molecule on Earth and represents a renewable and practically everlasting feedstock for the production of biofuels and chemicals. Self-assembled owing to the high-affinity cohesin-dockerin interaction, cellulosomes are huge multi-enzyme complexes with unmatched efficiency in the degradation of recalcitrant lignocellulosic substrates. The recruitment of diverse dockerin-borne enzymes into a multicohesin protein scaffold dictates the three-dimensional layout of the complex, and interestingly two alternative binding modes have been proposed. Using single-molecule fluorescence resonance energy transfer and molecular simulations on a range of cohesin-dockerin pairs, we directly detect varying distributions between these binding modes that follow a built-in cohesin-dockerin code. Surprisingly, we uncover a prolyl isomerase-modulated allosteric control mechanism, mediated by the isomerization state of a single proline residue, which regulates the distribution and kinetics of binding modes. Overall, our data provide a novel mechanistic understanding of the structural plasticity and dynamics of cellulosomes.

Generating Informative Sequence Tags from Antigen-Binding Regions of Heavily Glycosylated IgA1 Antibodies by Native Top-Down Electron Capture Dissociation

Immunoglobulins A (IgA) include some of the most abundant human antibodies and play an important role in defending mucosal surfaces against pathogens. The unique structural features of the heavy chain of IgA subclasses (called IgA1 and IgA2) enable them to polymerize via the joining J-chain, resulting in IgA dimers but also higher oligomers. While secretory sIgA oligomers are dominant in milk and saliva, IgAs exist primarily as monomers in serum. No method currently allows disentangling the millions of unique IgAs potentially present in the human antibody repertoire. Obtaining unambiguous sequence reads of their hypervariable antigen-binding regions is a prerequisite for IgA identification. We here report a mass spectrometric method that uses electron capture dissociation (ECD) to produce straightforward-to-read sequence ladders of the variable parts of both the light and heavy chains of IgA1s, in particular, of the functionally critical CDR3 regions. We directly compare the native top-down ECD spectra of a heavily and heterogeneously N- and O-glycosylated anti-CD20 IgA1, the corresponding N-glycosylated anti-CD20 IgG1, and their Fab parts. We show that while featuring very different MS1 spectra, the native top-down ECD MS2 spectra of all four species are nearly identical, with cleavages occurring specifically within the CDR3 and FR4 regions of both the heavy and light chain. From the sequence-informative ECD data of an intact glycosylated IgA1, we foresee that native top-down ECD will become a valuable complementary tool for the de novo sequencing of IgA1s from milk, saliva, or serum.

Attacking COVID-19 Progression Using Multi-Drug Therapy for Synergetic Target Engagement

COVID-19 is a devastating respiratory and inflammatory illness caused by a new coronavirus that is rapidly spreading throughout the human population. Over the past 12 months, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID-19, has already infected over 160 million (>20% located in United States) and killed more than 3.3 million people around the world (>20% deaths in USA). As we face one of the most challenging times in our recent history, there is an urgent need to identify drug candidates that can attack SARS-CoV-2 on multiple fronts. We have therefore initiated a computational dynamics drug pipeline using molecular modeling, structure simulation, docking and machine learning models to predict the inhibitory activity of several million compounds against two essential SARS-CoV-2 viral proteins and their host protein interactors-S/Ace2, Tmprss2, Cathepsins L and K, and Mpro-to prevent binding, membrane fusion and replication of the virus, respectively. All together, we generated an ensemble of structural conformations that increase high-quality docking outcomes to screen over >6 million compounds including all FDA-approved drugs, drugs under clinical trial (>3000) and an additional >30 million selected chemotypes from fragment libraries. Our results yielded an initial set of 350 high-value compounds from both new and FDA-approved compounds that can now be tested experimentally in appropriate biological model systems. We anticipate that our results will initiate screening campaigns and accelerate the discovery of COVID-19 treatments.

Variants in MHY7 Gene Cause Arrhythmogenic Cardiomyopathy

BACKGROUND

Arrhythmogenic Cardiomyopathy (ACM) is a disease of the cardiac muscle, characterized by frequent ventricular arrhythmias and functional/ structural abnormalities, mainly of the right ventricle. To date, 20 different genes have been associated with ACM and the majority of them encode for desmosomal proteins. In this study, we describe the characterization of two novel variants in MHY7 gene, segregating in two ACM families. MYH7 encodes for myosin heavy chain β (MHC-β) isoform, involved in cardiac muscle contractility.

METHOD AND RESULTS

In family A, the autopsy revealed ACM with biventricular involvement in both the proband and his father. In family B, the proband had been diagnosed as affected by ACM and implanted with implantable cardioverter defibrillator (ICD), due to ECG evidence of monomorphic ventricular tachycardia after syncope. After clinical evaluation, a molecular diagnosis was performed using a NGS custom panel. The two novel variants identified predicted damaging, located in a highly conserved domain: c. 2630T>C is not described while c.2609G>A has a frequency of 0.00000398. In silico analyses evaluated the docking characteristics between proteins using the Haddock2.2 webserver.

CONCLUSIONS

Our results reveal two variants in sarcomeric genes to be the molecular cause of ACM, further increasing the genetic heterogeneity of the disease; in fact, sarcomeric variants are usually associated with HCM phenotype. Studies on the role of sarcomere genes in the pathogenesis of ACM are surely recommended in those ACM patients negative for desmosomal mutation screening.

Multiobjective heuristic algorithm for de novo protein design in a quantified continuous sequence space

Protein design usually involves sequence search process and evaluation criteria. Commonly used methods primarily implement the Monte Carlo or simulated annealing algorithm with a single-energy function to obtain ideal solutions, which is often highly time-consuming and limited by the accuracy of the energy function. In this report, we introduce a multiobjective algorithm named Hydra for protein design, which employs two different energy functions to optimize solutions simultaneously and makes use of the latent quantitative relationship between different amino acid types to facilitate the search process. The framework uses two kinds of prior information to transform the original disordered discrete sequence space into a relatively ordered space, and decoy sequences are searched in this ordered space through a multiobjective swarm intelligence algorithm. This algorithm features high accuracy and a high-speed search process. Our method was tested on 40 targets covering different fold classes, which were computationally verified to be well folded, and it experimentally solved the 1UBQ fold by NMR in excellent agreement with the native structure with a backbone RMSD deviation of 1.074 Å. The Hydra software package can be downloaded from: http://www.csbio.sjtu.edu.cn/bioinf/HYDRA/ for academic use.

Inferring metal binding sites in flexible regions of proteins

Metal ions are central to the molecular function of many proteins. Thus their knowledge in experimentally determined structure is important; however, such structures often lose bound metal ions during sample preparation. Identification of these metal-binding site(s) becomes difficult when the receptor is novel and/or their conformations differ in the bound/unbound states. Locating such sites in theoretical models also poses a challenge due to the uncertainties with side-chain modeling. We address the problem by employing the Geometric Hashing algorithm to create a template library of functionally important binding sites and match query structures with the available templates. The matching is done on the structure ensemble obtained from coarse-grained molecular dynamics simulation, where metal-specific amino acids are screened to infer the true site. Test on 1347 non-redundant monomer protein structures show that Ca²⁺ , Zn²⁺ , Mg²⁺ , Cu²⁺ , and Fe³⁺ binding site residues can be classified at 0.92, 0.95, 0.80, 0.90, and 0.92 aggregate performance (out of 1) across all possible thresholds. The performance for Ca²⁺ and Zn²⁺ is notably superior in comparison to state-of-the-art methods like IonCom and MIB. Specific case studies show that additionally predicted metal-binding site residues in proteins have features necessary for ion binding. These include new sites not predicted by other methods. The use of coarse-grained dynamics thus provides a generalized approach to improve metal-binding site prediction. The work is expected to contribute to improving our ability to correctly predict protein molecular function where knowledge of metal binding is a key requirement.

Implementing and Assessing an Alchemical Method for Calculating Protein-Protein Binding Free Energy

Protein-protein binding is fundamental to most biological processes. It is important to be able to use computation to accurately estimate the change in protein-protein binding free energy due to mutations in order to answer biological questions that would be experimentally challenging, laborious, or time-consuming. Although nonrigorous free-energy methods are faster, rigorous alchemical molecular dynamics-based methods are considerably more accurate and are becoming more feasible with the advancement of computer hardware and molecular simulation software. Even with sufficient computational resources, there are still major challenges to using alchemical free-energy methods for protein-protein complexes, such as generating hybrid structures and topologies, maintaining a neutral net charge of the system when there is a charge-changing mutation, and setting up the simulation. In the current study, we have used the pmx package to generate hybrid structures and topologies, and a double-system/single-box approach to maintain the net charge of the system. To test the approach, we predicted relative binding affinities for two protein-protein complexes using a nonequilibrium alchemical method based on the Crooks fluctuation theorem and compared the results with experimental values. The method correctly identified stabilizing from destabilizing mutations for a small protein-protein complex, and a larger, more challenging antibody complex. Strong correlations were obtained between predicted and experimental relative binding affinities for both protein-protein systems.

Comprehensive in silico analysis and molecular dynamics of the superoxide dismutase 1 (SOD1) variants related to amyotrophic lateral sclerosis

Amyotrophic Lateral Sclerosis (ALS) is the most frequent motor neuron disorder, with a significant social and economic burden. ALS remains incurable, and the only drugs approved for its treatments confers a survival benefit of a few months for the patients. Missense mutations in superoxide dismutase 1 (SOD1), a major cytoplasmic antioxidant enzyme, has been associated with ALS development, accounting for 23% of its familial cases and 7% of all sporadic cases. This work aims to characterize in silico the structural and functional effects of SOD1 protein variants. Missense mutations in SOD1 were compiled from the literature and databases. Twelve algorithms were used to predict the functional and stability effects of these mutations. ConSurf was used to estimate the evolutionary conservation of SOD1 amino-acids. GROMACS was used to perform molecular dynamics (MD) simulations of SOD1 wild-type and variants A4V, D90A, H46R, and I113T, which account for approximately half of all ALS-SOD1 cases in the United States, Europe, Japan, and United Kingdom, respectively. 233 missense mutations in SOD1 protein were compiled from the databases and literature consulted. The predictive analyses pointed to an elevated rate of deleterious and destabilizing predictions for the analyzed variants, indicating their harmful effects. The ConSurf analysis suggested that mutations in SOD1 mainly affect conserved and possibly functionally essential amino acids. The MD analyses pointed to flexibility and essential dynamics alterations at the electrostatic and metal-binding loops of variants A4V, D90A, H46R, and I113T that could lead to aberrant interactions triggering toxic protein aggregation. These alterations may have harmful implications for SOD1 and explain their association with ALS. Understanding the effects of SOD1 mutations on protein structure and function facilitates the design of further experiments and provides relevant information on the molecular mechanism of pathology, which may contribute to improvements in existing treatments for ALS.

A novel, germline, deactivating CBL variant p.L493F alters domain orientation and is associated with multiple childhood cancers

CBL is a mammalian gene encoding the protein CBL, which is an E3 ubiquitin-protein ligase involved in cell signaling and protein ubiquitination. Pathogenic variants in this gene have been implicated in a number of human cancers, particularly acute myeloid leukemia (AML). Here, we present a 5-year-old male patient with a history of AML, diffuse midline glioma, and left brain lesion with histiocytic features. A variant of uncertain significance (VUS): p.L493F was detected in his CBL gene via clinical evaluation. Protein modeling predicts this variant to be pathogenic. Details of the clinical evaluation and modeling assay are discussed.

Clinical description & molecular modeling of novel MAX pathogenic variant causing pheochromocytoma in family, supports paternal parent-of-origin effect

The titular member of the MAX network of proteins, MYC-associated factor X (MAX), serves an important regulatory function in transcription of E-box genes associated with cell proliferation, differentiation, and apoptosis. Wild type MAX dimerizes with both MYC and MAD, both of which are members of the MAX network, and can promote or repress cell functions as needed. However, pathogenic variants in MAX are known to upset this balance, leading to uncontrolled oncogenic activity and disease phenotypes such as paragangliomas and pheochromocytomas. We report a 58-year-old male and his 32-year-old daughter, both of which have a history of pheochromocytoma and the unique nonsense MAX variant c.271C>T (p.Q91X). These individuals were diagnosed with pheochromocytomas in their early twenties that were later removed through corrective surgery. The father now presents with recurrent symptoms of hypertension, hyperhidrosis, and headaches, which accompany new pheochromocytomas of his remaining adrenal gland. Pathogenicity of this MAX variant is proven through molecular modeling. The case of this father-daughter pair supports both heritability of pheochromocytoma and the paternal parent-of-origin effect for MAX pathogenic variants.

GridSolvate: A Web Server for the Prediction of Biomolecular Hydration Properties

We present a novel web server, named gridSolvate, dedicated to the prediction of biomolecular hydration properties. Given a solute in atomic representation, such as a protein or protein–ligand complex, the server determines positions and excess chemical potential of buried and first hydration shell water molecules. Calculations are based on our semiexplicit hydration model that provides computational efficiency close to implicit solvent approaches, yet captures a number of physical effects unique to explicit solvent representation. The model was introduced and validated before in the context of bulk hydration of drug-like solutes and determination of protein hydration sites. Current methodological developments merge those two avenues into a single, easily accessible tool. Here, we focus on the server’s ability to predict water distribution and affinity within protein–ligand interfaces. We demonstrate that with possibly minimal user intervention the server correctly predicts the locations of 77% of interface water molecules in an external set of test structures. The server is freely available at https://gsolvate.biomod.cent.uw.edu.pl.

Epidemiology, evolutionary origin, and malaria-induced positive selection effects of G6PD-deficient alleles in Chinese populations

BACKGROUND

Although glucose-6-phosphate dehydrogenase (G6PD) deficiency is the most common inherited disorder in the Chinese population, there is scarce evidence regarding the epidemiology, evolutionary origin, and malaria-induced positive selection effects of G6PD-deficient alleles in various Chinese ethnic populations.

METHODS

We performed a large population-based screening (n = 15,690) to examine the impact of selection on human nucleotide diversity and to infer the evolutionary history of the most common deficiency alleles in Chinese populations.

RESULTS

The frequencies of G6PD deficiency ranged from 0% to 11.6% in 12 Chinese ethnic populations. A frequency map based on geographic information showed that G6PD deficiency was highly correlated with historical malaria prevalence in China and was affected by altitude and latitude. The five most frequently occurring G6PD gene variants were NM_001042351.3:c.1376G>T, NM_001042351.3:c.1388G>A, NM_001042351.3:c.95A>G, NM_001042351.3:c.1311T>C, and NM_001042351.3:c.1024C>T, which were distributed with ethnic features. A pathogenic but rarely reported variant site (NM_001042351.3:c.448G>A) was identified in this study. Bioinformatic analysis revealed a strong and recent positive selection targeting the NM_001042351.3:c.1376G>T allele that originated in the past 3125 to 3750 years and another selection targeting the NM_001042351.3:c.1388G>A allele that originated in the past 5000 to 6000 years. Additionally, both alleles originated from a single ancestor.

CONCLUSION

These results indicate that malaria has had a major impact on the Chinese genome since the introduction of rice agriculture.

In silico mutagenesis of human ACE2 with S protein and translational efficiency explain SARS-CoV-2 infectivity in different species

The coronavirus disease COVID-19 constitutes the most severe pandemic of the last decades having caused more than 1 million deaths worldwide. The SARS-CoV-2 virus recognizes the angiotensin converting enzyme 2 (ACE2) on the surface of human cells through its spike protein. It has been reported that the coronavirus can mildly infect cats, and ferrets, and perhaps dogs while not pigs, mice, chicken and ducks. Differences in viral infectivity among different species or individuals could be due to amino acid differences at key positions of the host proteins that interact with the virus, the immune response, expression levels of host proteins and translation efficiency of the viral proteins among other factors. Here, first we have addressed the importance that sequence variants of different animal species, human individuals and virus isolates have on the interaction between the RBD domain of the SARS-CoV-2 spike S protein and human angiotensin converting enzyme 2 (ACE2). Second, we have looked at viral translation efficiency by using the tRNA adaptation index. We find that integration of both interaction energy with ACE2 and translational efficiency explains animal infectivity. Humans are the top species in which SARS-CoV-2 is both efficiently translated as well as optimally interacting with ACE2. We have found some viral mutations that increase affinity for hACE and some hACE2 variants affecting ACE2 stability and virus binding. These variants suggest that different sensitivities to coronavirus infection in humans could arise in some cases from allelic variability affecting ACE2 stability and virus binding.

Genomics combined with a protein informatics platform to assess a novel pathogenic variant c.1024 A>G (p.K342E) in OPA1 in a patient with autosomal dominant optic atrophy

BACKGROUND

Autosomal Dominant Optic Atrophy (ADOA) is caused by mutations in the Optic Atrophy 1 Gene which disrupts the OPA1 protein. This disruption affects the normal function of the protein; impairs fusion of the mitochondrial inner membrane; and prevents normal OPA1 protein degradation. These events cause damage in retinal ganglion cells that could affect the patients with symptoms ranging from none to legally blind.

MATERIALS AND METHODS

Our study identifies a missense variant mutation, c.1024 A > G (p.K342E), in OPA1 gene causing ADOA. Diagnosed clinically in three family members and the presence of this mutation was confirmed in two members by genetic testing. Pathogenic variants in OPA1 impact the secondary protein structure and function by causing non-conservative amino acid substitutions. We also modeled this mutation and compared it to the wild type using statistical mechanics.

RESULTS AND CONCLUSIONS

The proband's pathogenic variant, c.1024 A > G (p.K342E), is located in the GTPase domain of OPA1 and causes changes in the protein structure by affecting the oligomerization pattern thus resulting in ADOA. Identifying the pathogenic potential of the missense mutations in the OPA1 gene using neoteric protein modeling techniques would help in the early detection of ADOA in patients who have family history of blindness. This action would help in providing early follow up, possible treatment in the future, and genetic counseling. Abbreviations: ADOA: Autosomal Dominant Optic Atrophy; CYCS: Caspase Activator Cytochrome C; OPA1: Optic Atrophy Gene 1; RGC: Retinal Ganglion Cells; VUS: Variant of Uncertain Significance.

A single nucleotide substitution in TaHKT1;5-D controls shoot Na+ accumulation in bread wheat

Improving salinity tolerance in the most widely cultivated cereal, bread wheat (Triticum aestivum L.), is essential to increase grain yields on saline agricultural lands. A Portuguese landrace, Mocho de Espiga Branca accumulates up to sixfold greater leaf and sheath sodium (Na+ ) than two Australian cultivars, Gladius and Scout, under salt stress in hydroponics. Despite high leaf and sheath Na+ concentrations, Mocho de Espiga Branca maintained similar salinity tolerance compared to Gladius and Scout. A naturally occurring single nucleotide substitution was identified in the gene encoding a major Na+ transporter TaHKT1;5-D in Mocho de Espiga Branca, which resulted in a L190P amino acid residue variation. This variant prevents Mocho de Espiga Branca from retrieving Na+ from the root xylem leading to a high shoot Na+ concentration. The identification of the tissue-tolerant Mocho de Espiga Branca will accelerate the development of more elite salt-tolerant bread wheat cultivars.

A single nucleotide substitution in TaHKT1;5-D controls shoot Na+ accumulation in bread wheat

Improving salinity tolerance in the most widely cultivated cereal, bread wheat (Triticum aestivum L.), is essential to increase grain yields on saline agricultural lands. A Portuguese landrace, Mocho de Espiga Branca accumulates up to sixfold greater leaf and sheath sodium (Na⁺ ) than two Australian cultivars, Gladius and Scout, under salt stress in hydroponics. Despite high leaf and sheath Na⁺ concentrations, Mocho de Espiga Branca maintained similar salinity tolerance compared to Gladius and Scout. A naturally occurring single nucleotide substitution was identified in the gene encoding a major Na⁺ transporter TaHKT1;5-D in Mocho de Espiga Branca, which resulted in a L190P amino acid residue variation. This variant prevents Mocho de Espiga Branca from retrieving Na⁺ from the root xylem leading to a high shoot Na⁺ concentration. The identification of the tissue-tolerant Mocho de Espiga Branca will accelerate the development of more elite salt-tolerant bread wheat cultivars.

Examination of Molecular Effects of MYLK Deletion in a Patient with Extensive Aortic, Carotid, and Abdominal Dissections That Underlie the Genetic Dysfunction

We describe the phenotype of a patient with extensive aortic, carotid, and abdominal dissections. The proband was found to have a heterozygous deletion of exons 21-34 in MYLK, which is a rare finding, as deletions in this gene have been infrequently reported. We describe this finding following detection in a proband with an extensive history of aortic, carotid, and abdominal dissections. Neoteric molecular modeling techniques to help determine the impact of this deletion on protein function indicated loss of function due to lack of any kinase domain. We also provide the electrostatics calculations from the wild type and mutant variant. Through a combined multiomic approach of clinical, functional, and protein informatics, we arrive at a data fusion for determination of pathogenicity embedded within the genetic code for this particular genetic variant, which, as a platform, continues to broaden its scope across the field of variants of uncertain significance classification.

Recent advances suggest increased influence of selective pressure in allostery

Allosteric regulation of protein functions is ubiquitous in organismal biology, but the principles governing its evolution are not well understood. Here we discuss recent studies supporting the large-scale existence of latent allostery in ancestor proteins of superfamilies. As suggested, the evolution of allostery could be driven by the need for specificity in paralogs of slow evolving protein complexes with conserved active sites. The same slow evolution is displayed by purifying selection exhibited in allosteric proteins with somatic mutations involved in cancer, where disease-associated mutations are enriched in both orthosteric and allosteric sites. Consequently, disease-associated variants can be used to identify druggable allosteric sites that are specific for paralogs in protein superfamilies with otherwise similar functions.

The Ca2+ permeation mechanism of the ryanodine receptor revealed by a multi-site ion model

Ryanodine receptors (RyR) are ion channels responsible for the release of Ca²⁺ from the sarco/endoplasmic reticulum and play a crucial role in the precise control of Ca²⁺ concentration in the cytosol. The detailed permeation mechanism of Ca²⁺ through RyR is still elusive. By using molecular dynamics simulations with a specially designed Ca²⁺ model, we show that multiple Ca²⁺ ions accumulate in the upper selectivity filter of RyR1, but only one Ca²⁺ can occupy and translocate in the narrow pore at a time, assisted by electrostatic repulsion from the Ca²⁺ within the upper selectivity filter. The Ca²⁺ is nearly fully hydrated with the first solvation shell intact during the whole permeation process. These results suggest a remote knock-on permeation mechanism and one-at-a-time occupation pattern for the hydrated Ca²⁺ within the narrow pore, uncovering the basis underlying the high permeability and low selectivity of the RyR channels.

Characterization of a Pathogenic Variant in the ABCD1 Gene Through Protein Molecular Modeling

Background

The ATP-binding cassette, subfamily D, member 1 (ABCD1) protein is a peroxisomal half-transporter that allows for very long chain fatty acid (VLCFA) degradation. Pathogenic variants of ABCD1 cause VLCFAs to build up in various tissues and bodily fluids, resulting in a disorder called X-linked adrenoleukodystrophy (X-ALD). This disorder is most commonly marked by adrenocortical insufficiency and high VLCFA concentration, and has varying levels of neurological involvement depending on phenotype. For example, the Addison-only form of X-ALD has no neurological impact, while the cerebral form of X-ALD often causes severe sensory loss, motor function impairment, cognitive decline, and death.

Methods

A newly characterized and suspected pathogenic variant in ABCD1 cause VLCFAs to build up in various tissues and bodily fluids, resulting in a disorder called X-linked adrenoleukodystrophy (X-ALD). This disorder is most commonly marked by adrenocortical insufficiency and high VLCFA concentration, and has varying levels of neurological involvement depending on phenotype. For example, the Addison-only form of X-ALD has no neurological impact, while the cerebral form of X-ALD often causes severe sensory loss, motor function impairment, cognitive decline, and death.

Results

A case of adult onset adrenomyeloneuropathy (AMN) and a novel ABCD1 cause VLCFAs to build up in various tissues and bodily fluids, resulting in a disorder called X-linked adrenoleukodystrophy (X-ALD). This disorder is most commonly marked by adrenocortical insufficiency and high VLCFA concentration, and has varying levels of neurological involvement depending on phenotype. For example, the Addison-only form of X-ALD has no neurological impact, while the cerebral form of X-ALD often causes severe sensory loss, motor function impairment, cognitive decline, and death.

Conclusions

Data fusion from multiple sources was combined in a comprehensive approach yielding an enriched assessment of the patient's disease and prognosis. Molecular modeling was performed on the variant to better characterize its clinical significance and confirm pathogenicity.

Intrinsically disordered protein domains in flavivirus infection

Intrinsically disordered protein regions are at the core of biological processes and involved in key protein-ligand interactions. The Flavivirus proteins, of viruses of great biomedical importance such as Zika and dengue viruses, exemplify this. Several proteins of these viruses have disordered regions that are of the utmost importance for biological activity. Disordered proteins can adopt several conformations, each able to interact with and/or bind to different ligands. In fact, such interactions can help stabilize a particular fold. Moreover, by being promiscuous in the number of target molecules they can bind to, these protein regions increase the number of functions that their small proteome (10 proteins) can achieve. A folding energy waterfall better describes the protein folding landscape of these proteins. A disordered protein can be thought as rolling down the folding energy cascade, in order "to fall, fold and function". This is the case of many viral protein regions, as seen in the flaviviruses proteome. Given their small size, flaviviruses are a good model system for understanding the role of intrinsically disordered protein regions in viral function. Finally, studying these viruses disordered protein regions will certainly contribute to the development of therapeutic approaches against such promising (yet challenging) targets.

Matching whole genomes to rare genetic disorders: Identification of potential causative variants using phenotype-weighted knowledge in the CAGI SickKids5 clinical genomes challenge

Precise identification of causative variants from whole-genome sequencing data, including both coding and noncoding variants, is challenging. The Critical Assessment of Genome Interpretation 5 SickKids clinical genome challenge provided an opportunity to assess our ability to extract such information. Participants in the challenge were required to match each of the 24 whole-genome sequences to the correct phenotypic profile and to identify the disease class of each genome. These are all rare disease cases that have resisted genetic diagnosis in a state-of-the-art pipeline. The patients have a range of eye, neurological, and connective-tissue disorders. We used a gene-centric approach to address this problem, assigning each gene a multiphenotype-matching score. Mutations in the top-scoring genes for each phenotype profile were ranked on a 6-point scale of pathogenicity probability, resulting in an approximately equal number of top-ranked coding and noncoding candidate variants overall. We were able to assign the correct disease class for 12 cases and the correct genome to a clinical profile for five cases. The challenge assessor found genes in three of these five cases as likely appropriate. In the postsubmission phase, after careful screening of the genes in the correct genome, we identified additional potential diagnostic variants, a high proportion of which are noncoding.

Variation among S-locus haplotypes and among stylar RNases in almond

In many plant species, self-incompatibility systems limit self-pollination and mating among relatives. This helps maintain genetic diversity in natural populations but imposes constraints in agriculture and plant breeding. In almond [Prunus dulcis (Mill.) D.A. Webb], the specificity of self-incompatibility is mainly determined by stylar ribonuclease (S-RNase) and S-haplotype-specific F-box (SFB) proteins, both encoded within a complex locus, S. Prior to this research, a nearly complete sequence was available for one S-locus haplotype. Here, we report complete sequences for four haplotypes and partial sequences for 11 haplotypes. Haplotypes vary in sequences of genes (particularly S-RNase and SFB), distances between genes and numbers and positions of long terminal repeat transposons. Haplotype variation outside of the S-RNase and SFB genes may help maintain functionally important associations between S-RNase and SFB alleles. Fluorescence-based assays were developed to distinguish among some S-RNase alleles. With three-dimensional modelling of five S-RNase proteins, conserved active sites were identified and variation was observed in electrostatic potential and in the numbers, characteristics and positions of secondary structural elements, loop anchoring points and glycosylation sites. A hypervariable region on the protein surface and differences in the number, location and types of glycosylation sites may contribute to determining S-RNase specificity.

B-SIDER: Computational Algorithm for the Design of Complementary β-Sheet Sequences

The β-sheet is an element of protein secondary structure, and intra-/intermolecular β-sheet interactions play pivotal roles in biological regulatory processes including scaffolding, transporting, and oligomerization. In nature, a β-sheet formation is tightly regulated because dysregulated β-stacking often leads to severe diseases such as Alzheimer's, Parkinson's, systemic amyloidosis, or diabetes. Thus, the identification of intrinsic β-sheet-forming propensities can provide valuable insight into protein designs for the development of novel therapeutics. However, structure-based design methods may not be generally applicable to such amyloidogenic peptides mainly owing to high structural plasticity and complexity. Therefore, an alternative design strategy based on complementary sequence information is of significant importance. Herein, we developed a database search method called β-Stacking Interaction DEsign for Reciprocity (B-SIDER) for the design of complementary β-strands. This method makes use of the structural database information and generates target-specific score matrices. The discriminatory power of the B-SIDER score function was tested on representative amyloidogenic peptide substructures against a sequence-based score matrix (PASTA 2.0) and two popular ab initio protein design score functions (Rosetta and FoldX). B-SIDER is able to distinguish wild-type amyloidogenic β-strands as favored interactions in a more consistent manner than other methods. B-SIDER was prospectively applied to the design of complementary β-strands for a splitGFP scaffold. Three variants were identified to have stronger interactions than the original sequence selected through a directed evolution, emitting higher fluorescence intensities. Our results indicate that B-SIDER can be applicable to the design of other β-strands, assisting in the development of therapeutics against disease-related amyloidogenic peptides.

Analysis of Procollagen C-Proteinase Enhancer-1/Glycosaminoglycan Binding Sites and of the Potential Role of Calcium Ions in the Interaction

In this study, we characterize the interactions between the extracellular matrix protein, procollagen C-proteinase enhancer-1 (PCPE-1), and glycosaminoglycans (GAGs), which are linear anionic periodic polysaccharides. We applied molecular modeling approaches to build a structural model of full-length PCPE-1, which is not experimentally available, to predict GAG binding poses for various GAG lengths, types and sulfation patterns, and to determine the effect of calcium ions on the binding. The computational data are analyzed and discussed in the context of the experimental results previously obtained using surface plasmon resonance binding assays. We also provide experimental data on PCPE-1/GAG interactions obtained using inhibition assays with GAG oligosaccharides ranging from disaccharides to octadecasaccharides. Our results predict the localization of GAG-binding sites at the amino acid residue level onto PCPE-1 and is the first attempt to describe the effects of ions on protein-GAG binding using modeling approaches. In addition, this study allows us to get deeper insights into the in silico methodology challenges and limitations when applied to GAG-protein interactions.