Conserved Sites and Recognition Mechanisms of T1R1 and T2R14 Receptors Revealed by Ensemble Docking and Molecular Descriptors and Fingerprints Combined with Machine Learning

Article Agriculture, Multidisciplinary

Rapid screening based on machine learning and molecular docking of umami peptides from porcine bone

Qing Liu et al.

Summary: This study presents a rapid screening method for umami peptides and identifies nine umami peptides from porcine bone using composite machine learning and molecular docking.

JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE (2023)

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Article Chemistry, Applied

Identification and virtual screening of novel umami peptides from chicken soup by molecular docking

Jingcheng Zhang et al.

Summary: By combining python script invocation and molecular docking, 20 potential umami peptides were successfully screened out from chicken soup. Sensory analysis showed that nine peptides had dominant umami taste, with PPQEAAQF having the highest umami intensity. Molecular docking revealed critical residues of taste receptors that play important roles in binding with umami peptides.

FOOD CHEMISTRY (2023)

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Article Chemistry, Applied

A TastePeptides-Meta system including an umami/bitter classification model Umami_YYDS, a TastePeptidesDB database and an open-source package Auto_Taste_ML

Zhiyong Cui et al.

Summary: This study established a taste peptide database and a prediction model to provide a convenient method for rapid screening of umami peptides, which was validated by sensory experiments.

FOOD CHEMISTRY (2023)

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Article Engineering, Biomedical

In-silico investigation of umami peptides with receptor T1R1/T1R3 for the discovering potential targets: A combined modeling approach

Wenli Wang et al.

Summary: This study analyzed the sequence and properties of umami peptides, and investigated their active sites and binding residues with the receptor T1R1/T1R3. The results identified the key active sites as well as the crucial residues in the receptor that bind umami peptides. A decision rule was proposed to predict potential umami peptides, providing convenience and efficiency.

BIOMATERIALS (2022)

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Article Biophysics

Study on the distribution of umami receptors on the tongue and its signal coding logic based on taste bud biosensor

Yuxia Fan et al.

Summary: This study investigated the distribution and signal coding logic of umami receptors on the tongue using taste bud biosensors. The results showed different response currents of taste bud biosensors to MSG and IMP, with T1R1 receptor being more expressed in the rostral tongue cells with higher sensitivity to MSG. This method has the potential to explain the interaction mechanism of umami substances with their receptors more accurately and develop artificial intelligent taste sensory.

BIOSENSORS & BIOELECTRONICS (2022)

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Article Chemistry, Applied

Identification of Oncorhynchus mykiss nebulin-derived peptides as bitter taste receptor TAS2R14 blockers by in silico screening and molecular docking

Zhipeng Yu et al.

Summary: Peptides ADM and ADW from Oncorhynchus mykiss nebulin hydrolysates were found to block the binding of bitter substances into the bitter taste receptor TAS2R14, reducing bitterness intensity. Hydrogen bond interaction and hydrophobic interaction played important roles in the high affinities of these peptides for the receptor.

FOOD CHEMISTRY (2022)

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Article Chemistry, Medicinal

iANP-EC: Identifying Anticancer Natural Products Using Ensemble Learning Incorporated with Evolutionary Computation

Loc Nguyen et al.

Summary: Cancer is a deadly disease, and finding better and more adaptive anticancer drugs has always been a focus of research. In addition to chemically synthetic compounds, natural products have been proved to be a highly potential source for anticancer drug discovery. This study constructs a stable, robust, and effective computational framework, using machine learning approaches and evolutionary computation, to identify key substructures that drive anticancer activities.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022)

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Article Biochemical Research Methods

Improving protein-ligand docking and screening accuracies by incorporating a scoring function correction term

Liangzhen Zheng et al.

Summary: This article presents a novel strategy to develop a reliable protein-ligand scoring function by augmenting the traditional scoring function Vina score using a correction term. The experimental results on various benchmarks show that this strategy enhances the prediction abilities for docking and screening tasks, and can be combined with multiple docking applications.

BRIEFINGS IN BIOINFORMATICS (2022)

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Review Food Science & Technology

A survey on computational taste predictors

Marta Malavolta et al.

Summary: This review summarizes the latest advances in taste prediction and analyzes the available food-related databases and taste prediction tools developed in recent years.

EUROPEAN FOOD RESEARCH AND TECHNOLOGY (2022)

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Article Chemistry, Applied

Identification and comparison of umami-peptides in commercially available dry-cured Spanish mackerels (Scomberomorus niphonius)

Wei Wang et al.

Summary: This study identified and compared umami peptides from eight commercial dry-cured Spanish mackerels via molecular simulation. The results showed that the sequence of peptides varied in different samples, with only ten sequences being repeated across multiple samples. Four peptides were found to exhibit umami taste and umami-enhancing effects, forming hydrogen bonds and hydrophobic bonds in ligand-receptor interactions.

FOOD CHEMISTRY (2022)

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Article Chemistry, Applied

A rational tool for the umami evaluation of peptides based on multi-techniques

Wenli Wang et al.

Summary: Umami peptides have become a key interest in flavoring agent development, with five novel peptides discovered in pufferfish in this study. Among these peptides, DF9 and AK11 showed the highest umami intensity and lower Ka values, in agreement with sensory evaluation, revealing the umami mechanism of peptides.

FOOD CHEMISTRY (2022)

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Article Chemistry, Applied

Taste and stability characteristics of two key umami peptides from pufferfish (Takifugu obscurus)

Ninglong Zhang et al.

Summary: The umami taste of Takifugu obscurus comes from two peptides, PR-7 and YV-8, which exhibit umami taste and enhancing effects at near neutral pH values. PR-7 also shows significant kokumi activity. Both peptides demonstrate remarkable stability at different pH levels, especially YV-8, which may be attributed to its stable structural property. These peptides have the potential to be used in complex foods as a desirable alternative to monosodium L-glutamate.

FOOD CHEMISTRY (2022)

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Article Food Science & Technology

Prediction of bitterant and sweetener using structure-taste relationship models based on an artificial neural network

Weichen Bo et al.

Summary: This study used computational methods to predict the taste characteristics of molecules. The results showed that different structure-taste relationship models have unique characteristics and achieved accurate predictions in various taste categories. The MLP-Fingerprint model exhibited a higher predictive AUC value compared to the MLP-Descriptor model and the CNN model.

FOOD RESEARCH INTERNATIONAL (2022)

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Article Agriculture, Multidisciplinary

Activation Spectra of Human Bitter Taste Receptors Stimulated with Cyclolinopeptides Corresponding to Fresh and Aged Linseed Oil

Tatjana Lang et al.

Summary: Cyclolinopeptides in linseed oil are responsible for its bitterness, and a specific compound called methionine sulfoxide-containing cyclolinopeptide-4 is the main determinant of this bitterness.

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY (2022)

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Article Chemistry, Medicinal

Delta Machine Learning to Improve Scoring-Ranking-Screening Performances of Protein-Ligand Scoring Functions

Chao Yang et al.

Summary: In this study, the robustness and applicability of machine-learning scoring functions were further improved by expanding the training set, developing meaningful features, using a linear empirical scoring function as the baseline, and applying extreme gradient boosting (XGBoost) with Delta-machine learning. The new scoring function demonstrated superior performance in scoring and ranking in various structure types and showed reliability and robustness in virtual screening applications.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022)

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Article Chemistry, Medicinal

AA-Score: a New Scoring Function Based on Amino Acid-Specific Interaction for Molecular Docking

Xiaolin Pan et al.

Summary: This study presents a new protein-ligand scoring function called AA-Score, which shows improved performance in scoring, docking, and ranking compared to traditional scoring functions. The function utilizes amino acid-specific interaction components and includes various types of interactions. An easy-to-use tool for analyzing protein-ligand interactions and predicting binding affinity using AA-Score is also developed. The source code and examples can be found at https://github.com/xundrug/AA-Score-Tool.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022)

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Review Chemistry, Multidisciplinary

Featurization strategies for protein-ligand interactions and their applications in scoring function development

Guoli Xiong et al.

Summary: Classical scoring functions have reached a plateau in predictive performance, while machine learning scoring functions relying on sophisticated techniques show great potential in binding affinity prediction. Automated-extraction features are emerging as a new trend in featurization for protein-ligand interactions, helping capture important physical processes.

WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE (2022)

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Article Chemistry, Applied

Characterization and molecular docking study of taste peptides from chicken soup by sensory analysis combined with nano-LC-Q-TOF-MS/MS

Li Liang et al.

Summary: Dynamic quantitative descriptive analysis and temporal dominance of sensations were used to analyze the taste profiles of chicken soup. Nine taste peptides were identified and evaluated, with umami and saltiness being the dominant tastes. Molecular docking results indicated the key binding sites for taste receptors and their correlation with umami intensity.

FOOD CHEMISTRY (2022)

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Article Food Science & Technology

IUP-BERT: Identification of Umami Peptides Based on BERT Features

Liangzhen Jiang et al.

Summary: This study developed a peptide sequence-based umami peptide predictor, iUP-BERT, using a deep learning pretrained neural network feature extraction method. After optimization, the model showed improved performance compared to existing methods. The built iUP-BERT web server can aid in improving the palatability of dietary supplements.

FOODS (2022)

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Article Chemistry, Applied

Taste mechanism of umami peptides from Chinese traditional fermented fish (Chouguiyu) based on molecular docking using umami receptor T1R1/ T1R3

Daqiao Yang et al.

Summary: Umami peptides formed during fermentation enhance the unique taste of Chouguiyu. After identifying 400 umami peptides using peptidomics, it was found that most of them were significantly enhanced after fermentation. Molecular docking analysis revealed that these umami peptides interacted with specific amino acid residues in T1R3.

FOOD CHEMISTRY (2022)

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Article Chemistry, Applied

Characteristics of umami peptides identified from porcine bone soup and molecular docking to the taste receptor T1R1/T1R3

Li Liang et al.

Summary: Four potential umami peptides were identified from porcine bone soup, and three of them were proven to have dominant umami taste. The key binding sites of taste receptors and the role of electrostatic interaction and hydrogen bond in umami taste were revealed.

FOOD CHEMISTRY (2022)

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Article Agriculture, Multidisciplinary

Reaction Mixtures Rich in [γ-Glu](n≥1)-Arg Derived from Enzymatic Synthesis as Potential Salt and Umami Enhancers

Jing Wu et al.

Summary: Some arginyl dipeptides and gamma-glutamyl peptides have been identified as salt and umami enhancers. In this study, a series of gamma-glutamyl peptides containing Arg were synthesized and evaluated for their taste-enhancing effects. The results showed that certain peptides had significant effects in increasing both saltiness and umaminess, especially at a high solid concentration of 30%.

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY (2022)

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Article Agriculture, Multidisciplinary

Decoding of the Saltiness Enhancement Taste Peptides from the Yeast Extract and Molecular Docking to the Taste Receptor T1R1/ T1R3

Yimeng Shan et al.

Summary: This study identified taste peptides in yeast extract and found some taste peptides that enhance saltiness, confirming the enhancing effects of sourness and umami on saltiness perception.

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY (2022)

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Article Agriculture, Multidisciplinary

Typical Umami Ligand-Induced Binding Interaction and Conformational Change of T1R1-VFT

Ninglong Zhang et al.

Summary: In this study, the binding characteristics between T1R1-VFT and umami molecules were explored through experiments and simulations. The results showed that the binding process is driven by hydrogen bond, van der Waals forces, and electrostatic interactions, and induces conformational changes of T1R1-VFT. These findings improve our understanding of how the umami receptor recognizes specific ligand molecules.

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY (2022)

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Article Agriculture, Multidisciplinary

Bitter Peptides YFYPEL, VAPFPEVF, and YQEPVLGPVRGPFPIIV, Released during Gastric Digestion of Casein, Stimulate Mechanisms of Gastric Acid Secretion via Bitter Taste Receptors TAS2R16 and TAS2R38

Phil Richter et al.

Summary: This study aimed to investigate whether non-bitter casein is degraded into bitter peptides that stimulate gastric acid secretion. An in vitro model of gastric digestion and casein-fed pig experiments confirmed this process, while sensory analyses and in vitro screening validated the bitterness of the peptides. Functional involvement of TAS2R16 and TAS2R38 gene expression with the peptides was confirmed in HGT-1 cells. These findings are important for understanding protein digestion and its application in dietary context.

JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY (2022)

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Letter Chemistry, Medicinal

On the Choice of Active Site Sequences for Kinase-Ligand Affinity Prediction

Jannis Born et al.

Summary: Recent work suggests that using active site information instead of full protein sequence improves the accuracy of predicting kinase-ligand binding affinity. In this study, we propose and compare multiple definitions of the active site, and find that our novel definition outperforms previous definitions and better models ATP noncompetitive inhibitors. Additionally, by leveraging the discontiguity of the active site sequence, we develop novel protein-sequence augmentation strategies that further enhance performance.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022)

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Review Physics, Multidisciplinary

Explainable AI: A Review of Machine Learning Interpretability Methods

Pantelis Linardatos et al.

Summary: Recent advances in artificial intelligence have led to widespread industrial adoption, with machine learning systems demonstrating superhuman performance. However, the complexity of these systems has made them difficult to explain, hindering their application in sensitive domains. Therefore, there is a renewed interest in the field of explainable artificial intelligence.

ENTROPY (2021)

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Article Biochemistry & Molecular Biology

UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning

Phasit Charoenkwan et al.

Summary: A novel machine-learning meta-predictor UMPred-FRL was developed for improved umami peptide identification, combining six machine learning algorithms and seven feature encodings to achieve more accurate performance compared to baseline models.

INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2021)

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Article Biochemistry & Molecular Biology

Using diverse potentials and scoring functions for the development of improved machine-learned models for protein-ligand affinity and docking pose prediction

Omar N. A. Demerdash

Summary: The emergence of computational drug discovery promises to reduce the workload and costs for experimentalists, but predicting the binding structure and affinity of protein-ligand complexes remains challenging. Research shows that synergy among different features can improve model accuracy, and assessing the importance of physical terms can provide insights into the relevant physics and guide future investigations.

JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2021)

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Article Multidisciplinary Sciences

Structures of the σ2, receptor enable docking for bioactive ligand discovery

Assaf Alon et al.

Summary: The study determined the crystal structure of sigma(2) receptor with roluperidone and PB28, identified new chemical compounds with higher affinities, and confirmed the role of sigma(2) receptor in pain perception, highlighting the potential for developing new pain treatments.

NATURE (2021)

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Article Chemistry, Multidisciplinary

The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction

Chao Shen et al.

Summary: Structure-based drug design relies on detailed knowledge of protein-ligand binding complexes, but accurate prediction of ligand-binding poses remains challenging. This study developed XGBoost-trained classifiers using a cross-docking dataset from the PDBbind database to discriminate binding poses, showing that specific features such as ECIF and Vina energy terms significantly impact performance, and inclusion of Vina energy terms in training can enhance model generalization.

JOURNAL OF CHEMINFORMATICS (2021)

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Article Chemistry, Applied

Identification of novel umami peptides from myosin via homology modeling and molecular docking

Zhipeng Yu et al.

Summary: This study used homology modeling and molecular docking to investigate the interactions between peptides and the umami receptor, revealing critical amino acid residues involved. Five novel peptides were synthesized with umami intensity stronger than monosodium glutamate, suggesting their potential in enhancing food flavor.

FOOD CHEMISTRY (2021)

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Article Chemistry, Applied

Isolation, characterization and molecular docking of novel umami and umami-enhancing peptides from Ruditapes philippinarum

Yue Zhang et al.

Summary: Fourteen novel umami peptides were isolated and identified from Ruditapes philippinarum, with KSAEN and QIEELEGK having higher sensory evaluations, and PAATIPE and HNESQN showing the best umami-enhancing taste in a 0.35% MSG solution. Molecular docking showed that certain amino acids may play important roles in the interaction of peptides with taste receptors, contributing to the umami taste of the shellfish.

FOOD CHEMISTRY (2021)

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Article Multidisciplinary Sciences

Highly accurate protein structure prediction with AlphaFold

John Jumper et al.

Summary: Proteins are essential for life, and accurate prediction of their structures is a crucial research problem. Current experimental methods are time-consuming, highlighting the need for accurate computational approaches to address the gap in structural coverage. Despite recent progress, existing methods fall short of atomic accuracy in protein structure prediction.

NATURE (2021)

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Article Biochemistry & Molecular Biology

PLIP 2021: expanding the scope of the protein-ligand interaction profiler to DNA and RNA

Melissa F. Adasme et al.

Summary: With the growth of protein structure data, the analysis of molecular interactions between ligands and their target molecules becomes increasingly important. PLIP, a tool for protein-ligand interaction profiling, has been successful in detecting and visualizing these interactions, with applications ranging from characterizing docking experiments to evaluating novel ligand-protein complexes. Additionally, PLIP has been extended to encompass interactions with DNA and RNA, demonstrating its utility in scenarios such as cancer drug targeting DNA and RNA-protein complexes associated with neurological diseases.

NUCLEIC ACIDS RESEARCH (2021)

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Review Chemistry, Multidisciplinary