An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes

In Vitro and Computational Response of Differential Catalysis by Phlebia brevispora BAFC 633 Laccase in Interaction with 2,4-D and Chlorpyrifos

Enzymes secreted by white rot fungi (WRF), such as laccase, offer a promising approach for the treatment of hazardous xenobiotic compounds. This study conducted a comprehensive analysis of the impact of the pesticides 2,4-dichlorophenoxyacetic acid (2,4-D) and chlorpyrifos on the laccase of Phlebia brevispora BAFC 633 through in vitro and bioinformatics analyses. The fungal strain was shown to be tolerant to both pesticides, with notable morphological and ultrastructural alterations in the mycelium. Laccase activity and two isoenzymes (53 and 70 kDa) were detected in all initial treatments. The laccase was concentrated for subsequent catalytic evaluation in the presence of both pesticides, showing high stability at a pH of 3.6 and a temperature range of 50-60 °C. The lacI gene, corresponding to this laccase, was modeled, and its structure revealed a defined catalytic pocket validated with a drug score of 0.61. Molecular docking estimated affinity energies of -5.06 and -9.41 Kcal mol-1 for 2,4-D and chlorpyrifos, respectively. Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) analysis through 250 ns of molecular dynamics revealed stronger hydrophobic interactions of laccase with chlorpyrifos and highlighted the importance of residue His460 in stabilizing both complexes. Understanding the impact of these agrochemicals on the catalytic function of laccase is crucial for developing future biotechnological strategies involving this enzyme.

Catalytic function of the laccase enzyme in response to chlorpyrifos and 2,4-dichlorophenoxyacetic acid: behavior in controlled and simulated environments

Enzymes secreted by white-rot fungi, such as laccase, offer a promising solution for treating xenobiotic compounds dangerous to the environment and human health. This study aimed to perform a comprehensive analysis of the tolerance of Pleurotus pulmonarius LBM 105 and its laccase activity toward the pesticides 2,4-D and chlorpyrifos both in vitro and in silico. The fungal strain was able to grow in different concentrations of the pesticides, showing evident morphological alterations. Laccase activity and a 53 kDa electromorph were present in all treatments, showing significant stability with peak activity achieved at a pH of 5.6 and within a temperature range of 50-60 °C. Three laccase genes were mapped, annotated, and characterized from the genome. PplacI obtained better structural validation and affinity energy of - 5.05 and - 7.65 kcal mol-1 with 2,4-D and chlorpyrifos, respectively. The Molecular Mechanics/Poisson-Boltzmann Surface Area analysis at 250 ns confirmed the docking results, revealing the existence of stronger hydrophobic interactions between laccase and chlorpyrifos and highlighting the importance of the Phe341 residue in stabilizing both complexes. Understanding the impact of pesticides on laccase's catalytic function is key to formulating and applying future biotechnological strategies with this enzyme.

Unveiling crucial amino acids in the carbohydrate recognition domain of a viral protein through a structural bioinformatic approach

Carbohydrate binding modules (CBMs) are protein domains that typically reside near catalytic domains, increasing substrate-protein proximity by constraining the conformational space of carbohydrates. Due to the flexibility and variability of glycans, the molecular details of how these protein regions recognize their target molecules are not always fully understood. Computational methods, including molecular docking and molecular dynamics simulations, have been employed to investigate lectin-carbohydrate interactions. In this study, we introduce a novel approach that integrates multiple computational techniques to identify the critical amino acids involved in the interaction between a CBM located at the tip of bacteriophage J-1's tail and its carbohydrate counterparts. Our results highlight three amino acids that play a significant role in binding, a finding we confirmed through in vitro experiments. By presenting this approach, we offer an intriguing alternative for pinpointing amino acids that contribute to protein-sugar interactions, leading to a more thorough comprehension of the molecular determinants of protein-carbohydrate interactions.

The Malaria Box molecules: a source for targeting the RBD and NTD cryptic pocket of the spike glycoprotein in SARS-CoV-2

CONTEXT

SARS-CoV-2, responsible for COVID-19, has led to over 500 million infections and more than 6 million deaths globally. There have been limited effective treatments available. The study aims to find a drug that can prevent the virus from entering host cells by targeting specific sites on the virus's spike protein.

METHOD

We examined 13,397 compounds from the Malaria Box library against two specific sites on the spike protein: the receptor-binding domain (RBD) and a predicted cryptic pocket. Using virtual screening, molecular docking, molecular dynamics, and MMPBSA techniques, they evaluated the stability of two compounds. TCMDC-124223 showed high stability and binding energy in the RBD, while TCMDC-133766 had better binding energy in the cryptic pocket. The study also identified that the interacting residues are conserved, which is crucial for addressing various virus variants. The findings provide insights into the potential of small molecules as drugs against the spike protein.

A quinolin-8-ol sub-millimolar inhibitor of UGGT, the ER glycoprotein folding quality control checkpoint

Misfolded glycoprotein recognition and endoplasmic reticulum (ER) retention are mediated by the ER glycoprotein folding quality control (ERQC) checkpoint enzyme, UDP-glucose glycoprotein glucosyltransferase (UGGT). UGGT modulation is a promising strategy for broad-spectrum antivirals, rescue-of-secretion therapy in rare disease caused by responsive mutations in glycoprotein genes, and many cancers, but to date no selective UGGT inhibitors are known. The small molecule 5-[(morpholin-4-yl)methyl]quinolin-8-ol (5M-8OH-Q) binds a CtUGGTGT24 "WY" conserved surface motif conserved across UGGTs but not present in other GT24 family glycosyltransferases. 5M-8OH-Q has a 47 μM binding affinity for CtUGGTGT24in vitro as measured by ligand-enhanced fluorescence. In cellula, 5M-8OH-Q inhibits both human UGGT isoforms at concentrations higher than 750 μM. 5M-8OH-Q binding to CtUGGTGT24 appears to be mutually exclusive to M5-9 glycan binding in an in vitro competition experiment. A medicinal program based on 5M-8OH-Q will yield the next generation of UGGT inhibitors.

Carbohydrate structure database (CSDB) oligosaccharide conformation tool

Population analysis in terms of glycosidic torsion angles is frequently used to reveal preferred conformers of glycans. However, due to high structural diversity and flexibility of carbohydrates, conformational characterization of complex glycans can be a challenging task. Herein we present a conformation module of oligosaccharide fragments occurring in natural glycan structures developed on the platform of the Carbohydrate Structure Database (CSDB). Currently, this module deposits free energy surface and conformer abundance maps plotted as a function of glycosidic torsions for 194 inter-residue bonds. Data are automatically and continuously derived from explicit-solvent molecular dynamics (MD) simulations. The module was also supplemented with high-temperature MD data of saccharides (2403 maps) provided by GlycoMapsDB (hosted by GLYCOSCIENCES.de project). Conformational data defined by up to four torsional degrees of freedom can be freely explored using a web interface of the module available at http://csdb.glycoscience.ru/database/core/search_conf.html.

Comprehensive virtual screening of 4.8 k flavonoids reveals novel insights into allosteric inhibition of SARS-CoV-2 MPRO

SARS-CoV-2 main protease is a common target for inhibition assays due to its high conservation among coronaviruses. Since flavonoids show antiviral activity, several in silico works have proposed them as potential SARS-CoV-2 main protease inhibitors. Nonetheless, there is reason to doubt certain results given the lack of consideration for flavonoid promiscuity or main protease plasticity, usage of short library sizes, absence of control molecules and/or the limitation of the methodology to a single target site. Here, we report a virtual screening study where dorsilurin E, euchrenone a11, sanggenol O and CHEMBL2171598 are proposed to inhibit main protease through different pathways. Remarkably, novel structural mechanisms were observed after sanggenol O and CHEMBL2171598 bound to experimentally proven allosteric sites. The former drastically affected the active site, while the latter triggered a hinge movement which has been previously reported for an inactive SARS-CoV main protease mutant. The use of a curated database of 4.8 k flavonoids, combining two well-known docking software (AutoDock Vina and AutoDock4.2), molecular dynamics and MMPBSA, guaranteed an adequate analysis and robust interpretation. These criteria can be considered for future screening campaigns against SARS-CoV-2 main protease.

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.

Arylsulfonyl histamine derivatives as powerful and selective α-glucosidase inhibitors

A series of simple N-arylbenzenesulfonyl histamine derivatives were prepared and screened against α-glucosidase. Inhibition was in the micromolar range for several N α,N τ-di-arylsulfonyl compounds, with N α,N τ-di-4-trifluorobenzenesulfonyl histamine (IId) being the best inhibitor. Compound IId is a reversible and competitive α-glucosidase inhibitor, and presented good selectivity with respect to other target enzymes, including β-glucosidase and α-amylase, and interesting predicted physicochemical properties. Docking studies have been run to postulate ligand-enzyme interactions to account for the experimental results. In vivo, compound IId produced a similar hypoglycemic effect to acarbose with half of its dose.

Exploring lectin-like activity of the S-layer protein of Lactobacillus acidophilus ATCC 4356

The surface layer (S-layer) protein of Lactobacillus acidophilus is a crystalline array of self-assembling, proteinaceous subunits non-covalently bound to the outmost bacterial cell wall envelope and is involved in the adherence of bacteria to host cells. We have previously described that the S-layer protein of L. acidophilus possesses anti-viral and anti-bacterial properties. In this work, we extracted and purified S-layer proteins from L. acidophilus ATCC 4356 cells to study their interaction with cell wall components from prokaryotic (i.e., peptidoglycan and lipoteichoic acids) and eukaryotic origin (i.e., mucin and chitin), as well as with viruses, bacteria, yeast, and blood cells. Using chimeric S-layer fused to green fluorescent protein (GFP) from different parts of the protein, we analyzed their binding capacity. Our results show that the C-terminal part of the S-layer protein presents lectin-like activity, interacting with different glycoepitopes. We further demonstrate that lipoteichoic acid (LTA) serves as an anchor for the S-layer protein. Finally, a structure for the C-terminal part of S-layer and possible binding sites were predicted by a homology-based model.