Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network
Heme proteins serve diverse and pivotal biological functions. Therefore, clarifying the mechanisms of these diverse functions of heme is a crucial scientific topic. Distortion of heme porphyrin is one of the key factors regulating the chemical properties of heme. Here, we constructed convolutional n...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-08-01
|
| Series: | Biomolecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2218-273X/12/9/1172 |
| _version_ | 1797490726875955200 |
|---|---|
| author | Hiroko X. Kondo Hiroyuki Iizuka Gen Masumoto Yuichi Kabaya Yusuke Kanematsu Yu Takano |
| author_facet | Hiroko X. Kondo Hiroyuki Iizuka Gen Masumoto Yuichi Kabaya Yusuke Kanematsu Yu Takano |
| author_sort | Hiroko X. Kondo |
| collection | DOAJ |
| description | Heme proteins serve diverse and pivotal biological functions. Therefore, clarifying the mechanisms of these diverse functions of heme is a crucial scientific topic. Distortion of heme porphyrin is one of the key factors regulating the chemical properties of heme. Here, we constructed convolutional neural network models for predicting heme distortion from the tertiary structure of the heme-binding pocket to examine their correlation. For saddling, ruffling, doming, and waving distortions, the experimental structure and predicted values were closely correlated. Furthermore, we assessed the correlation between the cavity shape and molecular structure of heme and demonstrated that hemes in protein pockets with similar structures exhibit near-identical structures, indicating the regulation of heme distortion through the protein environment. These findings indicate that the tertiary structure of the heme-binding pocket is one of the factors regulating the distortion of heme porphyrin, thereby controlling the chemical properties of heme relevant to the protein function; this implies a structure–function correlation in heme proteins. |
| first_indexed | 2024-03-10T00:37:09Z |
| format | Article |
| id | doaj.art-380a0de9ffe946d6b0109245c434ab44 |
| institution | Directory Open Access Journal |
| issn | 2218-273X |
| language | English |
| last_indexed | 2024-03-10T00:37:09Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomolecules |
| spelling | doaj.art-380a0de9ffe946d6b0109245c434ab442023-11-23T15:14:06ZengMDPI AGBiomolecules2218-273X2022-08-01129117210.3390/biom12091172Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural NetworkHiroko X. Kondo0Hiroyuki Iizuka1Gen Masumoto2Yuichi Kabaya3Yusuke Kanematsu4Yu Takano5Faculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, JapanGraduate School of Information Science and Technology, Hokkaido University, Kita 14, Nishi 9, Kitaku, Sapporo 060-0814, JapanInformation Systems Division, RIKEN Information R&D and Strategy Headquarters, 2-1 Hirosawa, Wako 351-0198, JapanFaculty of Engineering, Kitami Institute of Technology, 165 Koen-cho, Kitami 090-8507, JapanGraduate School of Information Sciences, Hiroshima City University, 3-4-1 Ozukahigashi Asaminamiku, Hiroshima 731-3194, JapanGraduate School of Information Sciences, Hiroshima City University, 3-4-1 Ozukahigashi Asaminamiku, Hiroshima 731-3194, JapanHeme proteins serve diverse and pivotal biological functions. Therefore, clarifying the mechanisms of these diverse functions of heme is a crucial scientific topic. Distortion of heme porphyrin is one of the key factors regulating the chemical properties of heme. Here, we constructed convolutional neural network models for predicting heme distortion from the tertiary structure of the heme-binding pocket to examine their correlation. For saddling, ruffling, doming, and waving distortions, the experimental structure and predicted values were closely correlated. Furthermore, we assessed the correlation between the cavity shape and molecular structure of heme and demonstrated that hemes in protein pockets with similar structures exhibit near-identical structures, indicating the regulation of heme distortion through the protein environment. These findings indicate that the tertiary structure of the heme-binding pocket is one of the factors regulating the distortion of heme porphyrin, thereby controlling the chemical properties of heme relevant to the protein function; this implies a structure–function correlation in heme proteins.https://www.mdpi.com/2218-273X/12/9/1172heme distortionpocket conformationconvolutional neural networkmachine learning |
| spellingShingle | Hiroko X. Kondo Hiroyuki Iizuka Gen Masumoto Yuichi Kabaya Yusuke Kanematsu Yu Takano Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network Biomolecules heme distortion pocket conformation convolutional neural network machine learning |
| title | Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network |
| title_full | Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network |
| title_fullStr | Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network |
| title_full_unstemmed | Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network |
| title_short | Elucidation of the Correlation between Heme Distortion and Tertiary Structure of the Heme-Binding Pocket Using a Convolutional Neural Network |
| title_sort | elucidation of the correlation between heme distortion and tertiary structure of the heme binding pocket using a convolutional neural network |
| topic | heme distortion pocket conformation convolutional neural network machine learning |
| url | https://www.mdpi.com/2218-273X/12/9/1172 |
| work_keys_str_mv | AT hirokoxkondo elucidationofthecorrelationbetweenhemedistortionandtertiarystructureofthehemebindingpocketusingaconvolutionalneuralnetwork AT hiroyukiiizuka elucidationofthecorrelationbetweenhemedistortionandtertiarystructureofthehemebindingpocketusingaconvolutionalneuralnetwork AT genmasumoto elucidationofthecorrelationbetweenhemedistortionandtertiarystructureofthehemebindingpocketusingaconvolutionalneuralnetwork AT yuichikabaya elucidationofthecorrelationbetweenhemedistortionandtertiarystructureofthehemebindingpocketusingaconvolutionalneuralnetwork AT yusukekanematsu elucidationofthecorrelationbetweenhemedistortionandtertiarystructureofthehemebindingpocketusingaconvolutionalneuralnetwork AT yutakano elucidationofthecorrelationbetweenhemedistortionandtertiarystructureofthehemebindingpocketusingaconvolutionalneuralnetwork |