Structure-Based Discovery of Mouse Trace Amine-Associated Receptor 5 Antagonists.

Trace amine-associated receptors (TAARs) were discovered in 2001 as new members of class A G protein-coupled receptors (GPCRs). With the only exception of TAAR1, TAAR members (TAAR2-9, also known as noncanonical olfactory receptors) were originally described exclusively in the olfactory epithelium and believed to mediate the innate perception of volatile amines. However, most noncanonical olfactory receptors are still orphan receptors. Given its recently discovered nonolfactory expression and therapeutic potential, TAAR5 has been the focus of deorphanization campaigns that led to the discovery of a few druglike antagonists. Here, we report four novel TAAR5 antagonists identified through high-throughput screening, which, along with the four ligands published in the literature, constituted our starting point to design a computational strategy for the identification of TAAR5 ligands. We developed a structure-based virtual screening protocol that allowed us to identify three new TAAR5 antagonists with a hit rate of 10%. Despite lacking an experimental structure, we accurately modeled the TAAR5 binding site by integrating comparative sequence- and structure-based analyses of serotonin receptors with homology modeling and side-chain optimization. In summary, we have identified seven new TAAR5 antagonists that could serve as lead candidates for the development of new treatments for depression, anxiety, and neurodegenerative diseases.

Modeling the Orthosteric Binding Site of the G Protein-Coupled Odorant Receptor OR5K1.

With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here, we report two additional agonists and functional data of the most potent compound on two mutants, L1043.32 and L2556.51. Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.

Classification Model for the Second Extracellular Loop of Class A GPCRs.

The extracellular loop 2 (ECL2) is the longest and the most diverse loop among class A G protein-coupled receptors (GPCRs). It connects the transmembrane (TM) helices 4 and 5 and contains a highly conserved cysteine through which it is bridged with TM3. In this paper, experimental ECL2 structures were analyzed based on their sequences, shapes, and intramolecular contacts. To take into account the flexibility, we incorporated into our analyses information from the molecular dynamics trajectories available on the GPCRmd website. Despite the high sequence variability, shapes of the analyzed structures, defined by the backbone volume overlaps, can be clustered into seven main groups. Conformational differences within the clusters can be then identified by intramolecular interactions with other GPCR structural domains. Overall, our work provides a reorganization of the structural information of the ECL2 of class A GPCR subfamilies, highlighting differences and similarities on sequence and conformation levels.

In Silico Molecular Study of Tryptophan Bitterness.

Tryptophan is an essential amino acid, required for the production of serotonin. It is the most bitter amino acid and its bitterness was found to be mediated by the bitter taste receptor TAS2R4. Di-tryptophan has a different selectivity profile and was found to activate three bitter taste receptors, whereas tri-tryptophan activated five TAS2Rs. In this work, the selectivity/promiscuity profiles of the mono-to-tri-tryptophans were explored using molecular modeling simulations to provide new insights into the molecular recognition of the bitter tryptophan. Tryptophan epitopes were found in all five peptide-sensitive TAS2Rs and the best tryptophan epitope was identified and characterized at the core of the orthosteric binding site of TAS2R4.

Bitter peptide prediction using graph neural networks.

Bitter taste is an unpleasant taste modality that affects food consumption. Bitter peptides are generated during enzymatic processes that produce functional, bioactive protein hydrolysates or during the aging process of fermented products such as cheese, soybean protein, and wine. Understanding the underlying peptide sequences responsible for bitter taste can pave the way for more efficient identification of these peptides. This paper presents BitterPep-GCN, a feature-agnostic graph convolution network for bitter peptide prediction. The graph-based model learns the embedding of amino acids in the bitter peptide sequences and uses mixed pooling for bitter classification. BitterPep-GCN was benchmarked using BTP640, a publicly available bitter peptide dataset. The latent peptide embeddings generated by the trained model were used to analyze the activity of sequence motifs responsible for the bitter taste of the peptides. Particularly, we calculated the activity for individual amino acids and dipeptide, tripeptide, and tetrapeptide sequence motifs present in the peptides. Our analyses pinpoint specific amino acids, such as F, G, P, and R, as well as sequence motifs, notably tripeptide and tetrapeptide motifs containing FF, as key bitter signatures in peptides. This work not only provides a new predictor of bitter taste for a more efficient identification of bitter peptides in various food products but also gives a hint into the molecular basis of bitterness.Scientific ContributionOur work provides the first application of Graph Neural Networks for the prediction of peptide bitter taste. The best-developed model, BitterPep-GCN, learns the embedding of amino acids in the bitter peptide sequences and uses mixed pooling for bitter classification. The embeddings were used to analyze the sequence motifs responsible for the bitter taste.

The dark sides of the GPCR tree - research progress on understudied GPCRs.

A large portion of the human GPCRome is still in the dark and understudied, consisting even of entire subfamilies of GPCRs such as odorant receptors, class A and C orphans, adhesion GPCRs, Frizzleds and taste receptors. However, it is undeniable that these GPCRs bring an untapped therapeutic potential that should be explored further. Open questions on these GPCRs span diverse topics such as deorphanisation, the development of tool compounds and tools for studying these GPCRs, as well as understanding basic signalling mechanisms. This review gives an overview of the current state of knowledge for each of the diverse subfamilies of understudied receptors regarding their physiological relevance, molecular mechanisms, endogenous ligands and pharmacological tools. Furthermore, it identifies some of the largest knowledge gaps that should be addressed in the foreseeable future and lists some general strategies that might be helpful in this process.

The path to the G protein-coupled receptor structural landscape: Major milestones and future directions.

G protein-coupled receptors (GPCRs) play a crucial role in cell function by transducing signals from the extracellular environment to the inside of the cell. They mediate the effects of various stimuli, including hormones, neurotransmitters, ions, photons, food tastants and odorants, and are renowned drug targets. Advancements in structural biology techniques, including X-ray crystallography and cryo-electron microscopy (cryo-EM), have driven the elucidation of an increasing number of GPCR structures. These structures reveal novel features that shed light on receptor activation, dimerization and oligomerization, dichotomy between orthosteric and allosteric modulation, and the intricate interactions underlying signal transduction, providing insights into diverse ligand-binding modes and signalling pathways. However, a substantial portion of the GPCR repertoire and their activation states remain structurally unexplored. Future efforts should prioritize capturing the full structural diversity of GPCRs across multiple dimensions. To do so, the integration of structural biology with biophysical and computational techniques will be essential. We describe in this review the progress of nuclear magnetic resonance (NMR) to examine GPCR plasticity and conformational dynamics, of atomic force microscopy (AFM) to explore the spatial-temporal dynamics and kinetic aspects of GPCRs, and the recent breakthroughs in artificial intelligence for protein structure prediction to characterize the structures of the entire GPCRome. In summary, the journey through GPCR structural biology provided in this review illustrates how far we have come in decoding these essential proteins architecture and function. Looking ahead, integrating cutting-edge biophysics and computational tools offers a path to navigating the GPCR structural landscape, ultimately advancing GPCR-based applications.

Viral capsid structural assembly governs the reovirus binding interface to NgR1.

Understanding the mechanisms underlying viral entry is crucial for controlling viral diseases. In this study, we investigated the interactions between reovirus and Nogo-receptor 1 (NgR1), a key mediator of reovirus entry into the host central nervous system. NgR1 exhibits a unique bivalent interaction with the reovirus capsid, specifically binding at the interface between adjacent heterohexamers arranged in a precise structural pattern on the curved virus surface. Using single-molecule techniques, we explored for the first time how the capsid molecular architecture and receptor polymorphism influence virus binding. We compared the binding affinities of human and mouse NgR1 to reovirus µ1/σ3 proteins in their isolated form, self-assembled in 2D capsid patches, and within the native 3D viral topology. Our results underscore the essential role of the concave side of NgR1 and emphasize that the spatial organization and curvature of the virus are critical determinants of the stability of the reovirus-NgR1 complex. This study highlights the importance of characterizing interactions in physiologically relevant spatial configurations, providing precise insights into virus-host interactions and opening new avenues for therapeutic interventions against viral infections.

Phylogenetic placement of the genus Anhellia and the description of A. nectandrae sp. nov.

The phylogenetic position of a new species of Anhellia (Myriangiales) was investigated by analysis of nucleotide sequences of ribosomal large subunit (LSU) and ITS regions. The new sequence was aligned with 28 sequences obtained from GenBank, including four species of Davidiellaceae (Capnodiales) used as outgroup. This study is the first attempt to resolve the placement of the genus Anhellia within Myriangiales. The genus Anhellia was strongly supported in Myriangiaceae by phylogenetic analyses. In addition, A. nectandrae sp. nov., collected on Nectandra rigida from a fragment of Atlantic forest in Brazil, is described, illustrated and a table with morphological features to all known Anhellia species is provided.

Phylogenetic and Mutation Analysis of the Venezuelan Equine Encephalitis Virus Sequence Isolated in Costa Rica from a Mare with Encephalitis.

Venezuelan Equine Encephalitis virus (VEEV) is an arboviral pathogen in tropical America that causes lethal encephalitis in horses and humans. VEEV is classified into six subtypes (I to VI). Subtype I viruses are divided into epizootic (IAB and IC) and endemic strains (ID and IE) that can produce outbreaks or sporadic diseases, respectively. The objective of this study was to reconstruct the phylogeny and the molecular clock of sequences of VEEV subtype I complex and identify mutations within sequences belonging to epizootic or enzootic subtypes focusing on a sequence isolated from a mare in Costa Rica. Bayesian phylogeny of the VEEV subtype I complex tree with 110 VEEV complete genomes was analyzed. Evidence of positive selection was evaluated with Datamonkey server algorithms. The putative effects of mutations on the 3D protein structure in the Costa Rica sequence were evaluated. The phylogenetic analysis showed that Subtype IE-VEEV diverged earlier than other subtypes, Costa Rican VEEV-IE ancestors came from Nicaragua in 1963 and Guatemala in 1907. Among the observed non-synonymous mutations, only 17 amino acids changed lateral chain groups. Fourteen mutations located in the NSP3, E1, and E2 genes are unique in this sequence, highlighting the importance of E1-E2 genes in VEEV evolution.

Protein-protein interactions at a glance: Protocols for the visualization of biomolecular interactions.

Protein-protein interactions (PPIs) play a key role in many biological processes and are intriguing targets for drug discovery campaigns. Advancements in experimental and computational techniques are leading to a growth of data accessibility, and, with it, an increased need for the analysis of PPIs. In this respect, visualization tools are essential instruments to represent and analyze biomolecular interactions. In this chapter, we reviewed some of the available tools, highlighting their features, and describing their functions with practical information on their usage.

Identification of sources of resistance to anthracnose stalk rot in maize / Identificação de fontes de resistência à antracnose do colmo do milho

ABSTRACT: Adoption of resistant cultivars is the primary measure used to control anthracnose stalk rot. The goal of this study was to identify maize-resistant genotypes to anthracnose stalk rot, which are similar to the hybrid 2B710. Experiments were performed at Embrapa Maize and Sorghum experimental fields in Brazil. The first experimental trial evaluated 234 maize lines as well as two commercials hybrids, BRS1010 (susceptible) and 2B710 (resistant). Artificial inoculations were performed with a strain at the blister (R2) phase, and evaluation of disease severity was performed after 30 days. The second experimental trial evaluated 48 maize lines and hybrids, inoculated with two Colletotrichum graminicola strains. In the first trial, eight resistance groups were formed, and the last lines were more resistant, as was the hybrid 2B710, with values between 11.50% and 23.0% of severity. In the second trial, there was an interaction between the two factors, lines and isolates, and the lines often showed the same reaction features as those obtained in the first trial. However, the disease severity was higher for most lines, even when using other isolates. These lines with effective levels of resistance could be used in future studies of inheritance, in programs to develop hybrids, and to identify molecular markers associated with resistance to anthracnose stalk rot in maize.

RESUMO: O uso de cultivares resistentes é a principal medida para o manejo da antracnose do colmo em milho. Neste trabalho, objetivou-se identificar linhagens com níveis de resistência à antracnose do colmo, similar ao híbrido 2B710, considerado resistente. Dois experimentos foram conduzidos na Embrapa Milho e Sorgo. No primeiro experimento, foram avaliados 234 linhagens e os híbridos BRS1010 (suscetível) e 2B710 (resistente). Foi realizada inoculação artificial com um isolado de C. graminicola , na fase de pré-pendoamento e, após 30 dias, foi realizada a avaliação da severidade da antracnose no colmo. O segundo experimento foi conduzido com 48 linhagens e os híbridos inoculados com dois isolados de C. graminicola . No primeiro experimento, os genótipos formaram oito grupos com base na severidade da doença e as linhagens do último grupo foram consideradas as mais resistentes, incluindo o híbrido 2B710, em que os genótipos apresentaram valores de severidade entre 11,50 a 23%. No segundo experimento, houve interação entre os fatores linhagens e isolados e, de modo geral, as linhagens apresentaram a mesma tendência de reação obtida no primeiro experimento, no entanto, a severidade da doença foi maior para a maioria das linhagens, mesmo quando utilizado o outro isolado. Com isso, foi possível realizar a seleção de linhagens com bons níveis de resistência, as quais podem ser utilizadas em programas de melhoramento, em estudos de herança, desenvolvimento de híbridos e identificação de marcadores moleculares, associados com resistência à antracnose do colmo.