Carbohydrate – Protein aromatic ring interactions beyond CH/π interactions: A Protein Data Bank survey and quantum chemical calculations

Polysaccharide utilization loci encoded DUF1735 likely functions as membrane-bound spacer for carbohydrate active enzymes

Proteins featuring the Domain of Unknown Function 1735 are frequently found in Polysaccharide Utilization Loci, yet their role remains unknown. The domain and vicinity analyzer programs we developed mine the Kyoto Encyclopedia of Genes and Genomes and UniProt to enhance the functional prediction of DUF1735. Our datasets confirmed the exclusive presence of DUF1735 in Bacteroidota genomes, with Bacteroidetes thetaiotaomicron harboring 46 copies. Notably, 97.8% of DUF1735 are encoded in PULs, and 89% are N-termini of multimodular proteins featuring C-termini like Laminin_G_3, F5/8-typeC, and GH18 domains. Predominantly possessing a predicted lipoprotein signal peptide and sharing an immunoglobulin-like β-sandwich fold with the BACON domain and the N-termini of SusE/F, DUF1735 likely functions as N-terminal, membrane-bound spacer for diverse C-termini involved in PUL-mediated carbohydrate utilization.

Genetic and structural basis of the human anti-α-galactosyl antibody response

Humans lack the capacity to produce the Galα1-3Galβ1-4GlcNAc (α-gal) glycan, and produce anti-α-gal antibodies upon exposure to the carbohydrate on a diverse set of immunogens, including commensal gut bacteria, malaria parasites, cetuximab, and tick proteins. Here we use X-ray crystallographic analysis of antibodies from α-gal knockout mice and humans in complex with the glycan to reveal a common binding motif, centered on a germline-encoded tryptophan residue at Kabat position 33 (W33) of the complementarity-determining region of the variable heavy chain (CDRH1). Immunoglobulin sequencing of anti-α-gal B cells in healthy humans and tick-induced mammalian meat anaphylaxis patients revealed preferential use of heavy chain germline IGHV3-7, encoding W33, among an otherwise highly polyclonal antibody response. Antigen binding was critically dependent on the presence of the germline-encoded W33 residue for all of the analyzed antibodies; moreover, introduction of the W33 motif into naive IGHV3-23 antibody phage libraries enabled the rapid selection of α-gal binders. Our results outline structural and genetic factors that shape the human anti-α-galactosyl antibody response, and provide a framework for future therapeutics development.

Small-Basis Set Density-Functional Theory Methods Corrected with Atom-Centered Potentials

Density functional theory (DFT) is currently the most popular method for modeling noncovalent interactions and thermochemistry. The accurate calculation of noncovalent interaction energies, reaction energies, and barrier heights requires choosing an appropriate functional and, typically, a relatively large basis set. Deficiencies of the density-functional approximation and the use of a limited basis set are the leading sources of error in the calculation of noncovalent and thermochemical properties in molecular systems. In this article, we present three new DFT methods based on the BLYP, M06-2X, and CAM-B3LYP functionals in combination with the 6-31G* basis set and corrected with atom-centered potentials (ACPs). ACPs are one-electron potentials that have the same form as effective-core potentials, except they do not replace any electrons. The ACPs developed in this work are used to generate energy corrections to the underlying DFT/basis-set method such that the errors in predicted chemical properties are minimized while maintaining the low computational cost of the parent methods. ACPs were developed for the elements H, B, C, N, O, F, Si, P, S, and Cl. The ACP parameters were determined using an extensive training set of 118655 data points, mostly of complete basis set coupled-cluster level quality. The target molecular properties for the ACP-corrected methods include noncovalent interaction energies, molecular conformational energies, reaction energies, barrier heights, and bond separation energies. The ACPs were tested first on the training set and then on a validation set of 42567 additional data points. We show that the ACP-corrected methods can predict the target molecular properties with accuracy close to complete basis set wavefunction theory methods, but at a computational cost of double-ζ DFT methods. This makes the new BLYP/6-31G*-ACP, M06-2X/6-31G*-ACP, and CAM-B3LYP/6-31G*-ACP methods uniquely suited to the calculation of noncovalent, thermochemical, and kinetic properties in large molecular systems.

Fast and Accurate Quantum Mechanical Modeling of Large Molecular Systems Using Small Basis Set Hartree-Fock Methods Corrected with Atom-Centered Potentials

There has been significant interest in developing fast and accurate quantum mechanical methods for modeling large molecular systems. In this work, by utilizing a machine learning regression technique, we have developed new low-cost quantum mechanical approaches to model large molecular systems. The developed approaches rely on using one-electron Gaussian-type functions called atom-centered potentials (ACPs) to correct for the basis set incompleteness and the lack of correlation effects in the underlying minimal or small basis set Hartree-Fock (HF) methods. In particular, ACPs are proposed for ten elements common in organic and bioorganic chemistry (H, B, C, N, O, F, Si, P, S, and Cl) and four different base methods: two minimal basis sets (MINIs and MINIX) plus a double-ζ basis set (6-31G*) in combination with dispersion-corrected HF (HF-D3/MINIs, HF-D3/MINIX, HF-D3/6-31G*) and the HF-3c method. The new ACPs are trained on a very large set (73 832 data points) of noncovalent properties (interaction and conformational energies) and validated additionally on a set of 32 048 data points. All reference data are of complete basis set coupled-cluster quality, mostly CCSD(T)/CBS. The proposed ACP-corrected methods are shown to give errors in the tenths of a kcal/mol range for noncovalent interaction energies and up to 2 kcal/mol for molecular conformational energies. More importantly, the average errors are similar in the training and validation sets, confirming the robustness and applicability of these methods outside the boundaries of the training set. In addition, the performance of the new ACP-corrected methods is similar to complete basis set density functional theory (DFT) but at a cost that is orders of magnitude lower, and the proposed ACPs can be used in any computational chemistry program that supports effective-core potentials without modification. It is also shown that ACPs improve the description of covalent and noncovalent bond geometries of the underlying methods and that the improvement brought about by the application of the ACPs is directly related to the number of atoms to which they are applied, allowing the treatment of systems containing some atoms for which ACPs are not available. Overall, the ACP-corrected methods proposed in this work constitute an alternative accurate, economical, and reliable quantum mechanical approach to describe the geometries, interaction energies, and conformational energies of systems with hundreds to thousands of atoms.

Structural Determinants of Substrate Recognition and Catalysis by Heparan Sulfate Sulfotransferases

Heparan sulfate (HS) and heparin contain imprinted "sulfation codes", which dictate their diverse physiological and pathological functions. A group of orchestrated biosynthetic enzymes cooperate in polymerizing and modifying HS chains. The biotechnological development of enzymes that can recreate this sulfation pattern on synthetic heparin is challenging, primarily due to the paucity of quantitative data for sulfotransferase enzymes. Herein, we identified critical structural characteristics that determine substrate specificity and shed light on the catalytic mechanism of sugar sulfation of two HS sulfotransferases, 2-O-sulfotransferase (HS2ST) and 6-O-sulfotransferase (HS6ST). Two sets of molecular clamps in HS2ST recognize appropriate substrates; these clamps flank the acceptor binding site on opposite sides. The hexuronic epimers, and not their puckers, have a critical influence on HS2ST selectivity. In contrast, HS6ST recognizes a broader range of substrates. This promiscuity is granted by a conserved tryptophan residue, W210, that positions the acceptor within the active site for catalysis by means of strong electrostatic interactions. Lysines K131 and K132 act in concert with a second tryptophan, W153, shedding water molecules from within the active site, thus providing HS6ST with a binding preference toward 2-O-sulfated substrates. QM/MM calculations provided valuable mechanistic insights into the catalytic process, identifying that the sulfation of both HS2ST and HS6ST follows a SN2-like mechanism. When they are taken together, our findings reveal the molecular basis of how these enzymes recognize different substrates and catalyze sugar sulfation, enabling the generation of enzymes that could create specific heparin epitopes.

Development and Evaluation of GlycanDock: A Protein-Glycoligand Docking Refinement Algorithm in Rosetta

Carbohydrate chains are ubiquitous in the complex molecular processes of life. These highly diverse chains are recognized by a variety of protein receptors, enabling glycans to regulate many biological functions. High-resolution structures of protein-glycoligand complexes reveal the atomic details necessary to understand this level of molecular recognition and inform application-focused scientific and engineering pursuits. When experimental challenges hinder high-throughput determination of quality structures, computational tools can, in principle, fill the gap. In this work, we introduce GlycanDock, a residue-centric protein-glycoligand docking refinement algorithm developed within the Rosetta macromolecular modeling and design software suite. We performed a benchmark docking assessment using a set of 109 experimentally determined protein-glycoligand complexes as well as 62 unbound protein structures. The GlycanDock algorithm can sample and discriminate among protein-glycoligand models of native-like structural accuracy with statistical reliability from starting structures of up to 7 Å root-mean-square deviation in the glycoligand ring atoms. We show that GlycanDock-refined models qualitatively replicated the known binding specificity of a bacterial carbohydrate-binding module. Finally, we present a protein-glycoligand docking pipeline for generating putative protein-glycoligand complexes when only the glycoligand sequence and unbound protein structure are known. In combination with other carbohydrate modeling tools, the GlycanDock docking refinement algorithm will accelerate research in the glycosciences.

Exploring the inhibitory effects of liquiritigenin against tau fibrillation and related neurotoxicity as a model of preventive care in Alzheimer's disease

Aggregation of tau protein into the form of insoluble amyloid fibrils is linked with Alzheimer's disease. The identification of potential small molecules that can inhibit tau protein from undergoing aggregation has received a great deal of interest, recently. In the present study, the possible inhibitory effects of liquiritigenin as a member of chiral flavanone family on tau amyloid fibrils formation and their resulting neurotoxicity were assessed by different biophysical and cellular assays. The inhibitory effect of the liquiritigenin against tau amyloid formation was investigated using thioflavin T (ThT) and 1-Anilino-8-naphthalene sulfonate (ANS) fluorescence spectroscopy, Congo red (CR) binding assays, transmission electron microscopy (TEM) analysis, and circular dichroism (CD) spectroscopy. Neurotoxicity assays were also performed against neuron-like cells (SH-SY5Y) using 3-(4,5-Dimethylthiazol)-2,5-diphenyltetrazolium bromide (MTT) reduction, reactive oxygen species (ROS), catalase (CAT) and caspase-3 activity measurements. We found that liquiritigenin served as an efficient inhibitor of tau amyloid fibrils formation through prevention of structural transition in tau structure, exposure of hydrophobic patches and their associated neurotoxicity mediated by decrease in the production of ROS and caspase-3 activity and elevation of CAT activity. These data may finally find applications in the development of promising inhibitors against amyloid fibril formation and treatment of Alzheimer's disease.

Prebiotic Peptides Based on the Glycocodon Theory Analyzed with FRET

In modern protein–carbohydrate interactions, carbohydrate–aromatic contact with CH–π interactions are used. Currently, they are considered driving forces of this complexation. In these contacts, tryptophan, tyrosine, and histidine are preferred. In this study, we focus on primary prebiotic chemistry when only glycine, alanine, aspartic acid, and valine are available in polypeptides. In this situation, when the aromatic acids are not available, hydrogen-bonding aspartic acid must be used for monosaccharide complexation. It is shown here that (DAA)n polypeptides play important roles in primary “protein”–glucose recognition, that (DGG)n plays an important role in “protein”–ribose recognition, and that (DGA)n plays an important role in “protein”–galactose recognition. Glucose oxidase from Aspergillus niger, which still has some ancient prebiotic sequences, is chosen here as an example for discussion.

Substitution of distal and active site residues reduces product inhibition of E1 from Acidothermus Cellulolyticus

Cellulases are largely afflicted by inhibition from their reaction products, especially at high-substrate loading, which represents a major challenge for biomass processing. This challenge was overcome for endoglucanase 1 (E1) from Acidothermus cellulolyticus by identifying a large conformational change involving distal residues upon binding cellobiose. Having introduced alanine substitutions at each of these residues, we identified several mutations that reduced cellobiose inhibition of E1, including W212A, W213A, Q247A, W249A and F250A. One of the mutations (W212A) resulted in a 47-fold decrease in binding affinity of cellobiose as well as a 5-fold increase in the kcat. The mutation further increased E1 activity on Avicel and dilute-acid treated corn stover and enhanced its productivity at high-substrate loadings. These findings were corroborated by funnel metadynamics, which showed that the W212A substitution led to reduced affinity for cellobiose in the +1 and +2 binding sites due to rearrangement of key cellobiose-binding residues.

Three-Dimensional Structures of Carbohydrates and Where to Find Them

Analysis and systematization of accumulated data on carbohydrate structural diversity is a subject of great interest for structural glycobiology. Despite being a challenging task, development of computational methods for efficient treatment and management of spatial (3D) structural features of carbohydrates breaks new ground in modern glycoscience. This review is dedicated to approaches of chemo- and glyco-informatics towards 3D structural data generation, deposition and processing in regard to carbohydrates and their derivatives. Databases, molecular modeling and experimental data validation services, and structure visualization facilities developed for last five years are reviewed.