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Article ; Online: A Benchmark Dataset for Evaluating Practical Performance of Model Quality Assessment of Homology Models

Yuma Takei / Takashi Ishida

Bioengineering, Vol 9, Iss 118, p

2022 Volume 118

Abstract: Protein structure prediction is an important issue in structural bioinformatics. In this process, model quality assessment (MQA), which estimates the accuracy of the predicted structure, is also practically important. Currently, the most commonly used ... ...

Abstract	Protein structure prediction is an important issue in structural bioinformatics. In this process, model quality assessment (MQA), which estimates the accuracy of the predicted structure, is also practically important. Currently, the most commonly used dataset to evaluate the performance of MQA is the critical assessment of the protein structure prediction (CASP) dataset. However, the CASP dataset does not contain enough targets with high-quality models, and thus cannot sufficiently evaluate the MQA performance in practical use. Additionally, most application studies employ homology modeling because of its reliability. However, the CASP dataset includes models generated by de novo methods, which may lead to the mis-estimation of MQA performance. In this study, we created new benchmark datasets, named a homology models dataset for model quality assessment (HMDM), that contain targets with high-quality models derived using homology modeling. We then benchmarked the performance of the MQA methods using the new datasets and compared their performance to that of the classical selection based on the sequence identity of the template proteins. The results showed that model selection by the latest MQA methods using deep learning is better than selection by template sequence identity and classical statistical potentials. Using HMDM, it is possible to verify the MQA performance for high-accuracy homology models.
Keywords	model quality assessment ; evaluation of model accuracy ; protein structure prediction ; machine learning ; deep learning ; MQA ; Technology ; T ; Biology (General) ; QH301-705.5
Subject code	006
Language	English
Publishing date	2022-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: P3CMQA

Yuma Takei / Takashi Ishida

Bioengineering, Vol 8, Iss 40, p

Single-Model Quality Assessment Using 3DCNN with Profile-Based Features

2021 Volume 40

Abstract: Model quality assessment (MQA), which selects near-native structures from structure models, is an important process in protein tertiary structure prediction. The three-dimensional convolution neural network (3DCNN) was applied to the task, but the ... ...

Abstract	Model quality assessment (MQA), which selects near-native structures from structure models, is an important process in protein tertiary structure prediction. The three-dimensional convolution neural network (3DCNN) was applied to the task, but the performance was comparable to existing methods because it used only atom-type features as the input. Thus, we added sequence profile-based features, which are also used in other methods, to improve the performance. We developed a single-model MQA method for protein structures based on 3DCNN using sequence profile-based features, namely, P3CMQA. Performance evaluation using a CASP13 dataset showed that profile-based features improved the assessment performance, and the proposed method was better than currently available single-model MQA methods, including the previous 3DCNN-based method. We also implemented a web-interface of the method to make it more user-friendly.
Keywords	model quality assessment (MQA) ; estimation of model accuracy (EMA) ; protein structure prediction ; machine learning ; deep learning ; 3DCNN ; Technology ; T ; Biology (General) ; QH301-705.5
Subject code	612
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: End-to-end learning for compound activity prediction based on binding pocket information

Toshitaka Tanebe / Takashi Ishida

BMC Bioinformatics, Vol 22, Iss S3, Pp 1-

2021 Volume 11

Abstract: Abstract Background Recently, machine learning-based ligand activity prediction methods have been greatly improved. However, if known active compounds of a target protein are unavailable, the machine learning-based method cannot be applied. In such cases, ...

Abstract	Abstract Background Recently, machine learning-based ligand activity prediction methods have been greatly improved. However, if known active compounds of a target protein are unavailable, the machine learning-based method cannot be applied. In such cases, docking simulation is generally applied because it only requires a tertiary structure of the target protein. However, the conformation search and the evaluation of binding energy of docking simulation are computationally heavy and thus docking simulation needs huge computational resources. Thus, if we can apply a machine learning-based activity prediction method for a novel target protein, such methods would be highly useful. Recently, Tsubaki et al. proposed an end-to-end learning method to predict the activity of compounds for novel target proteins. However, the prediction accuracy of the method was still insufficient because it only used amino acid sequence information of a protein as the input. Results In this research, we proposed an end-to-end learning-based compound activity prediction using structure information of a binding pocket of a target protein. The proposed method learns the important features by end-to-end learning using a graph neural network both for a compound structure and a protein binding pocket structure. As a result of the evaluation experiments, the proposed method has shown higher accuracy than an existing method using amino acid sequence information. Conclusions The proposed method achieved equivalent accuracy to docking simulation using AutoDock Vina with much shorter computing time. This indicated that a machine learning-based approach would be promising even for novel target proteins in activity prediction.
Keywords	Drug discovery ; Virtual screening ; Docking simulation ; Graph convolution ; Deep neural network ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Biology (General) ; QH301-705.5
Subject code	006
Language	English
Publishing date	2021-10-01T00:00:00Z
Publisher	BMC
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Protein model accuracy estimation based on local structure quality assessment using 3D convolutional neural network.

Rin Sato / Takashi Ishida

PLoS ONE, Vol 14, Iss 9, p e

2019 Volume 0221347

Abstract: In protein tertiary structure prediction, model quality assessment programs (MQAPs) are often used to select the final structural models from a pool of candidate models generated by multiple templates and prediction methods. The 3-dimensional ... ...

Abstract	In protein tertiary structure prediction, model quality assessment programs (MQAPs) are often used to select the final structural models from a pool of candidate models generated by multiple templates and prediction methods. The 3-dimensional convolutional neural network (3DCNN) is an expansion of the 2DCNN and has been applied in several fields, including object recognition. The 3DCNN is also used for MQA tasks, but the performance is low due to several technical limitations related to protein tertiary structures, such as orientation alignment. We proposed a novel single-model MQA method based on local structure quality evaluation using a deep neural network containing 3DCNN layers. The proposed method first assesses the quality of local structures for each residue and then evaluates the quality of whole structures by integrating estimated local qualities. We analyzed the model using the CASP11, CASP12, and 3D-Robot datasets and compared the performance of the model with that of the previous 3DCNN method based on whole protein structures. The proposed method showed a significant improvement compared to the previous 3DCNN method for multiple evaluation measures. We also compared the proposed method to other state-of-the-art methods. Our method showed better performance than the previous 3DCNN-based method and comparable accuracy as the current best single-model methods; particularly, in CASP11 stage2, our method showed a Pearson coefficient of 0.486, which was better than those of the best single-model methods (0.366-0.405). A standalone version of the proposed method and data files are available at https://github.com/ishidalab-titech/3DCNN_MQA.
Keywords	Medicine ; R ; Science ; Q
Subject code	310 ; 006
Language	English
Publishing date	2019-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Location, Location, Location

Adam M. Heck / Takashi Ishida / Brandon Hadland

Frontiers in Cell and Developmental Biology, Vol

How Vascular Specialization Influences Hematopoietic Fates During Development

2020 Volume 8

Abstract: During embryonic development, sequential waves of hematopoiesis give rise to blood-forming cells with diverse lineage potentials and self-renewal properties. This process must accomplish two important yet divergent goals: the rapid generation of ... ...

Abstract	During embryonic development, sequential waves of hematopoiesis give rise to blood-forming cells with diverse lineage potentials and self-renewal properties. This process must accomplish two important yet divergent goals: the rapid generation of differentiated blood cells to meet the needs of the developing embryo and the production of a reservoir of hematopoietic stem cells to provide for life-long hematopoiesis in the adult. Vascular beds in distinct anatomical sites of extraembryonic tissues and the embryo proper provide the necessary conditions to support these divergent objectives, suggesting a critical role for specialized vascular niche cells in regulating disparate blood cell fates during development. In this review, we will examine the current understanding of how organ- and stage-specific vascular niche specialization contributes to the development of the hematopoietic system.
Keywords	developmental hematopoiesis ; hematopoietic stem cell ; hemogenic endothelium ; endothelial cell ; vascular niches ; aorta gonad mesonephros region ; Biology (General) ; QH301-705.5
Language	English
Publishing date	2020-11-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Subfascial infiltration of 0.5% ropivacaine, but not 0.25% ropivacaine, exacerbates damage and inflammation in surgically incised abdominal muscles of rats

Dandan Shen / Yuki Sugiyama / Kumiko Ishida / Satoshi Fuseya / Takashi Ishida / Mikito Kawamata / Satoshi Tanaka

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 13

Abstract: Abstract Ropivacaine-induced myotoxicity in surgically incised muscles has not been fully investigated. We evaluated the effects of infiltration anesthesia with ropivacaine on damage, inflammation and regeneration in the incised muscles of rats ... ...

Abstract	Abstract Ropivacaine-induced myotoxicity in surgically incised muscles has not been fully investigated. We evaluated the effects of infiltration anesthesia with ropivacaine on damage, inflammation and regeneration in the incised muscles of rats undergoing laparotomy. Ropivacaine or saline was infiltrated below the muscle fascia over the incised muscles. Pain-related behaviors and histological muscle damage were assessed. Macrophage infiltration at days 2 and 5 and proliferation of satellite cells at day 5 were detected by CD68 and MyoD immunostaining, respectively. Pain-related behaviors were inhibited by 0.25% and 0.5% of ropivacaine for 2 h after surgery. Single infiltration of 0.5% ropivacaine did not induce injury in intact muscles without incision, but single and repeated infiltration of 0.5% ropivacaine significantly augmented laparotomy-induced muscle injury and increased the numbers of CD68-positve macrophages and MyoD-positive cells compared to those in rats with infiltration of saline or 0.25% ropivacaine. In contrast, there were no significant differences in them between rats with saline infusion and rats with 0.25% ropivacaine infiltration. In conclusion, single or repeated subfascial infiltration of 0.25% ropivacaine can be used without exacerbating the damage and inflammation in surgically incised muscles, but the use of 0.5% ropivacaine may be a concern because of potentially increased muscle damage.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: MYB3R-SCL28-SMR module with a role in cell size control negatively regulates G2 progression in Arabidopsis

Hirotomo Takatsuka / Yuji Nomoto / Kesuke Yamada / Keito Mineta / Christian Breuer / Takashi Ishida / Ayumi Yamagami / Keiko Sugimoto / Takeshi Nakano / Masaki Ito

Plant Signaling & Behavior, Vol 18, Iss

2023 Volume 1

Abstract: Cell size control is one of the prerequisites for plant growth and development. Recently, a GRAS family transcription factor, SCARECROW-LIKE28 (SCL28), was identified as a critical regulator for both mitotic and postmitotic cell-size control. Here, we ... ...

Abstract	Cell size control is one of the prerequisites for plant growth and development. Recently, a GRAS family transcription factor, SCARECROW-LIKE28 (SCL28), was identified as a critical regulator for both mitotic and postmitotic cell-size control. Here, we show that SCL28 is specifically expressed in proliferating cells and exerts its function to delay G2 progression during mitotic cell cycle in Arabidopsis thaliana. Overexpression of SCL28 provokes a significant enlargement of cells in various organs and tissues, such as leaves, flowers and seeds, to different extents depending on the type of cells. The increased cell size is most likely due to a delayed G2 progression and accelerated onset of endoreplication, an atypical cell cycle repeating DNA replication without cytokinesis or mitosis. Unlike DWARF AND LOW-TILLERING, a rice ortholog of SCL28, SCL28 may not have a role in brassinosteroid (BR) signaling because sensitivity against brassinazole, a BR biosynthesis inhibitor, was not dramatically altered in scl28 mutant and SCL28-overexpressing plants. Collectively, our findings strengthen a recently proposed model of cell size control by SCL28 and suggest the presence of diversified evolutionary mechanisms for the regulation and action of SCL28.
Keywords	cell cycle ; g2 phase ; cell size ; transcription factor ; gras family ; myb3rs ; Plant ecology ; QK900-989 ; Biology (General) ; QH301-705.5
Subject code	580
Language	English
Publishing date	2023-12-01T00:00:00Z
Publisher	Taylor & Francis Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The atypical E2F transcription factor DEL1 modulates growth–defense tradeoffs of host plants during root-knot nematode infection

Satoru Nakagami / Kentaro Saeki / Kei Toda / Takashi Ishida / Shinichiro Sawa

Scientific Reports, Vol 10, Iss 1, Pp 1-

2020 Volume 8

Abstract: Abstract In plants, growth–defense tradeoffs are essential for optimizing plant performance and adaptation under stress conditions, such as pathogen attack. Root-knot nematodes (RKNs) cause severe economic losses in many crops worldwide, although little ... ...

Abstract	Abstract In plants, growth–defense tradeoffs are essential for optimizing plant performance and adaptation under stress conditions, such as pathogen attack. Root-knot nematodes (RKNs) cause severe economic losses in many crops worldwide, although little is known about the mechanisms that control plant growth and defense responses during nematode attack. Upon investigation of Arabidopsis thaliana infected with RKN (Meloidogyne incognita), we observed that the atypical transcription factor DP-E2F-like 1 (DEL1) repressed salicylic acid (SA) accumulation in RKN-induced galls. The DEL1-deficient Arabidopsis mutant (del1-1) exhibited excessive SA accumulation in galls and is more resistant to RKN infection. In addition, excessive lignification was observed in galls of del1-1. On the other hand, the root growth of del1-1 is reduced after RKN infection. Taken together, these findings suggest that DEL1 plays an important role in the balance between plant growth and defense responses to RKN infection by controlling SA accumulation and lignification.
Keywords	Medicine ; R ; Science ; Q
Subject code	580
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Targeting General Transcriptional Machinery as a Therapeutic Strategy for Adult T-Cell Leukemia

Regina Wan Ju Wong / Takashi Ishida / Takaomi Sanda

Molecules, Vol 23, Iss 5, p

2018 Volume 1057

Abstract: Cancer cells are highly reliant on certain molecular pathways, which support their survival and proliferation. The fundamental concept of molecularly targeted therapy is to target a protein that is specifically deregulated or overexpressed in cancer ... ...

Abstract	Cancer cells are highly reliant on certain molecular pathways, which support their survival and proliferation. The fundamental concept of molecularly targeted therapy is to target a protein that is specifically deregulated or overexpressed in cancer cells. However, drug resistance and tumor heterogeneity are major obstacles in the development of specific inhibitors. Additionally, many driver oncogenes exert their oncogenic property via abnormal expression without having genetic mutations. Interestingly, recent accumulating evidence has demonstrated that many critical cancer genes are driven by a unique class of enhancers termed super-enhancers. Genes associated with super-enhancers are relatively more susceptible to the inhibition of general transcriptional machinery compared with genes that are regulated by typical enhancers. Cancer cells are more sensitive to treatment with small-molecule inhibitors of CDK7 or BRD4 than non-transformed cells. These findings proposed a novel strategy to identify functionally important genes as well as novel therapeutic modalities in cancer. This approach would be particularly useful for genetically complicated cancers, such as adult T-cell leukemia (ATL), whereby a large mutational burden is present, but the functional consequences of each mutation have not been well-studied. In this review, we discuss recent findings on super-enhancers, underlying mechanisms, and the efficacy of small-molecule transcriptional inhibitors in ATL.
Keywords	super-enhancer ; transcription factor ; CDK7 ; CDK9 ; BRD4 ; adult T-cell leukemia ; Organic chemistry ; QD241-441
Subject code	570
Language	English
Publishing date	2018-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Taxonomic and Gene Category Analyses of Subgingival Plaques from a Group of Japanese Individuals with and without Periodontitis

Kazuki Izawa / Kazuko Okamoto-Shibayama / Daichi Kita / Sachiyo Tomita / Atsushi Saito / Takashi Ishida / Masahito Ohue / Yutaka Akiyama / Kazuyuki Ishihara

International Journal of Molecular Sciences, Vol 22, Iss 5298, p

2021 Volume 5298

Abstract: Periodontitis is an inflammation of tooth-supporting tissues, which is caused by bacteria in the subgingival plaque (biofilm) and the host immune response. Traditionally, subgingival pathogens have been investigated using methods such as culturing, DNA ... ...

Abstract	Periodontitis is an inflammation of tooth-supporting tissues, which is caused by bacteria in the subgingival plaque (biofilm) and the host immune response. Traditionally, subgingival pathogens have been investigated using methods such as culturing, DNA probes, or PCR. The development of next-generation sequencing made it possible to investigate the whole microbiome in the subgingival plaque. Previous studies have implicated dysbiosis of the subgingival microbiome in the etiology of periodontitis. However, details are still lacking. In this study, we conducted a metagenomic analysis of subgingival plaque samples from a group of Japanese individuals with and without periodontitis. In the taxonomic composition analysis, genus Bacteroides and Mycobacterium demonstrated significantly different compositions between healthy sites and sites with periodontal pockets. The results from the relative abundance of functional gene categories, carbohydrate metabolism, glycan biosynthesis and metabolism, amino acid metabolism, replication and repair showed significant differences between healthy sites and sites with periodontal pockets. These results provide important insights into the shift in the taxonomic and functional gene category abundance caused by dysbiosis, which occurs during the progression of periodontal disease.
Keywords	periodontal disease ; periodontitis ; subgingival plaque biofilm ; periodontal pathogens ; metagenomics ; human oral microbiome ; Biology (General) ; QH301-705.5 ; Chemistry ; QD1-999
Subject code	570
Language	English
Publishing date	2021-05-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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