Arif Pramudwiatmoko, G. Gutmann, Y. Ueno, A. Kakugo, M. Yamamura, A. Konagaya
There are limitations in interactions with molecular objects in laboratory experiments due to the very small size of the objects. Common media to show the experimental results of molecular objects is still lack of observer interaction to understand it intuitively. In order to overcome this lack of interaction, this research takes tensegrity representation of molecular objects reproducing experimental results and creates interactive 3D objects to be presented in a virtual reality (VR) environment. The tensegrity representation enables us to enhance the interaction experience with the natural user interface with haptic technology and hand tracking controller. A particle simulation system that utilizes multiple GPUs resources is used to fulfill haptic VR requirements. We developed a unified particle object model using springs and particles which we call anchors which act as tensegrity structure of the object to support conformation of filament-type objects such as microtubules. Some object parameters can be set to match the flexural rigidity of the object with some experimental results. The bending shape of the object is evaluated using the classic bending equation and the results show high compatibility. Viscoelastic behavior also shows similarities with the viscosity reported in other studies. The object's flexural rigidity can be adjusted to match the target value with the direction of the prediction equation. The object model provides a better insight about molecular objects with natural and real-time interactions to provide a more intuitive understanding with the molecular objects presented. The results show that this model can also be applied to any filament-type or rod-like molecular object. Chem-Bio Informatics Journal, Vol.20, pp.19–43 (2020) 20
{"title":"Tensegrity representation of microtubule objects using unified particle objects and springs","authors":"Arif Pramudwiatmoko, G. Gutmann, Y. Ueno, A. Kakugo, M. Yamamura, A. Konagaya","doi":"10.1273/cbij.20.19","DOIUrl":"https://doi.org/10.1273/cbij.20.19","url":null,"abstract":"There are limitations in interactions with molecular objects in laboratory experiments due to the very small size of the objects. Common media to show the experimental results of molecular objects is still lack of observer interaction to understand it intuitively. In order to overcome this lack of interaction, this research takes tensegrity representation of molecular objects reproducing experimental results and creates interactive 3D objects to be presented in a virtual reality (VR) environment. The tensegrity representation enables us to enhance the interaction experience with the natural user interface with haptic technology and hand tracking controller. A particle simulation system that utilizes multiple GPUs resources is used to fulfill haptic VR requirements. We developed a unified particle object model using springs and particles which we call anchors which act as tensegrity structure of the object to support conformation of filament-type objects such as microtubules. Some object parameters can be set to match the flexural rigidity of the object with some experimental results. The bending shape of the object is evaluated using the classic bending equation and the results show high compatibility. Viscoelastic behavior also shows similarities with the viscosity reported in other studies. The object's flexural rigidity can be adjusted to match the target value with the direction of the prediction equation. The object model provides a better insight about molecular objects with natural and real-time interactions to provide a more intuitive understanding with the molecular objects presented. The results show that this model can also be applied to any filament-type or rod-like molecular object. Chem-Bio Informatics Journal, Vol.20, pp.19–43 (2020) 20","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"4 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79988129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, with the emergence of new technologies employing information science, open innovation and collaborative drug discovery research, utilizing biological and chemical experimental data, have been actively conducted. The Young Researcher Association of Chem-Bio Informatics Society (“CBI Wakate”) has constructed an online discussion space using Slack and provided a cloud-based collaborative platform in which researchers have freely discussed specific issues and aimed at raising the level of cross-sectoral communication regarding technology and knowledge. On this platform, we created three channels—dataset, model evaluation and scripts—where participants with different backgrounds co-developed a solution for solubility prediction. In the dataset channel, we exchanged our knowledge and Chem-Bio Informatics Journal, Vol.20, pp.5–18 (2020) 6 methodology for calculations using the chemical descriptors for the original dataset and also discussed methods to improve the dataset for pharmaceutical purposes. We have also developed a protocol for evaluating the applicability of solubility prediction models for drug discovery by using the ChEMBL database and for sharing the dataset among users on the cloud. In the model evaluation channel, we discussed the necessary conditions for the prediction model to be used in daily drug discovery research. We examined the effect of these discussions on script development and suggested future improvements. This study provides an example of a new cloud-based open collaboration that can be useful for various projects in the early stage of drug discovery.
{"title":"Open Innovation Platform using Cloud-based Applications and Collaborative Space: A Case Study of Solubility Prediction Model Development","authors":"Tsuyoshi Esaki, Keiko Kumazawa, Kazutoshi Takahashi, Reiko Watanabe, Tomohide Masuda, Hirofumi Watanabe, Yugo Shimizu, A. Okada, Seisuke Takimoto, Tomohiro Shimada, Kazuyoshi Ikeda","doi":"10.1273/cbij.20.5","DOIUrl":"https://doi.org/10.1273/cbij.20.5","url":null,"abstract":"In recent years, with the emergence of new technologies employing information science, open innovation and collaborative drug discovery research, utilizing biological and chemical experimental data, have been actively conducted. The Young Researcher Association of Chem-Bio Informatics Society (“CBI Wakate”) has constructed an online discussion space using Slack and provided a cloud-based collaborative platform in which researchers have freely discussed specific issues and aimed at raising the level of cross-sectoral communication regarding technology and knowledge. On this platform, we created three channels—dataset, model evaluation and scripts—where participants with different backgrounds co-developed a solution for solubility prediction. In the dataset channel, we exchanged our knowledge and Chem-Bio Informatics Journal, Vol.20, pp.5–18 (2020) 6 methodology for calculations using the chemical descriptors for the original dataset and also discussed methods to improve the dataset for pharmaceutical purposes. We have also developed a protocol for evaluating the applicability of solubility prediction models for drug discovery by using the ChEMBL database and for sharing the dataset among users on the cloud. In the model evaluation channel, we discussed the necessary conditions for the prediction model to be used in daily drug discovery research. We examined the effect of these discussions on script development and suggested future improvements. This study provides an example of a new cloud-based open collaboration that can be useful for various projects in the early stage of drug discovery.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"12 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79954088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HLA (Human Leucocyte Antigen) class I molecules present a variable but limited repertoire of antigenic peptides for T-cell recognition. Identification of specific antigenic peptides is essential for the development of immunotherapy. High polymorphism of HLA genes and a large number of possible peptides to be evaluated, however, have made the identification by experiments costly and time-consuming. Computational methods have been proposed to address this problem. In cases where plenty number of binding affinity data of peptides are available, various QSAR and machine learning approaches efficiently evaluate the affinity of test peptides, while in the cases where just a little data are available, structure-based approaches like elaborate docking have been proposed. We have developed a software named HLABAP that is designed to predict the binding affinities for a set of peptides against a particular HLA class I allele. By the combination of homology modeling for posing instead of docking and geometry optimization of the complex structures between the HLA molecule and peptides, HLABAP well predicts the binding affinities for the peptides. The results have shown that HLABAP should be applicable to identify possible antigenic peptides against a particular allele of HLA class I prior to the experiments far efficiently than the ordinary docking methods.
{"title":"HLABAP: HLA Class I-Binding Antigenic Peptide Predictor","authors":"R. Kataoka, Shinji Amari, T. Ikegami, N. Hirayama","doi":"10.1273/cbij.20.1","DOIUrl":"https://doi.org/10.1273/cbij.20.1","url":null,"abstract":"HLA (Human Leucocyte Antigen) class I molecules present a variable but limited repertoire of antigenic peptides for T-cell recognition. Identification of specific antigenic peptides is essential for the development of immunotherapy. High polymorphism of HLA genes and a large number of possible peptides to be evaluated, however, have made the identification by experiments costly and time-consuming. Computational methods have been proposed to address this problem. In cases where plenty number of binding affinity data of peptides are available, various QSAR and machine learning approaches efficiently evaluate the affinity of test peptides, while in the cases where just a little data are available, structure-based approaches like elaborate docking have been proposed. We have developed a software named HLABAP that is designed to predict the binding affinities for a set of peptides against a particular HLA class I allele. By the combination of homology modeling for posing instead of docking and geometry optimization of the complex structures between the HLA molecule and peptides, HLABAP well predicts the binding affinities for the peptides. The results have shown that HLABAP should be applicable to identify possible antigenic peptides against a particular allele of HLA class I prior to the experiments far efficiently than the ordinary docking methods.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"56 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2020-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75799601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gene expression analysis for understanding cancer cell development is a basic, but an important step, to further our knowledge in cancer research. We may also be interested in understanding gene interactions that may lead to cancer development. One of the most important interactions is a regulatory interaction that involves transcription factor genes. In this research, we are attempting to construct a new regulatory network that imitates the transcription and translation processes of mRNA. We construct this network from four different cancer types: bile-duct cancer (BDC), lung adenocarcinoma (LUAD), colorectal cancer (CRC), and hepatocyte carcinoma (HCC). We also integrate differential expression data to obtain the interactions among differentially expressed genes. We then try to find intersecting sub-networks that exist across all cancer types. We believe that the transcription factor genes found in intersection sub-networks may reveal an important mechanism that affects cancer cell growth. In this research, we found that genes, such as those in the TEAD4, IRX5, HMGA1, and E2F gene family and the SOX gene family, are found in the enrichment analysis of the intersection sub-network obtained from multiple cancer data-sets. These genes point us toward dysregulation of the cell cycle, cell division, and cell proliferation mechanisms in cancer cells. These genes may become new cancer drug targets for cancer treatment.
{"title":"Discovery of a Robust Gene Regulatory Network with a Complex Transcription Factor Network on Organ Cancer Cell-line RNA Sequence Data","authors":"Bharata Kalbuaji, Y-h. Taguchi, A. Konagaya","doi":"10.1273/cbij.19.32","DOIUrl":"https://doi.org/10.1273/cbij.19.32","url":null,"abstract":"Gene expression analysis for understanding cancer cell development is a basic, but an important step, to further our knowledge in cancer research. We may also be interested in understanding gene interactions that may lead to cancer development. One of the most important interactions is a regulatory interaction that involves transcription factor genes. In this research, we are attempting to construct a new regulatory network that imitates the transcription and translation processes of mRNA. We construct this network from four different cancer types: bile-duct cancer (BDC), lung adenocarcinoma (LUAD), colorectal cancer (CRC), and hepatocyte carcinoma (HCC). We also integrate differential expression data to obtain the interactions among differentially expressed genes. We then try to find intersecting sub-networks that exist across all cancer types. We believe that the transcription factor genes found in intersection sub-networks may reveal an important mechanism that affects cancer cell growth. In this research, we found that genes, such as those in the TEAD4, IRX5, HMGA1, and E2F gene family and the SOX gene family, are found in the enrichment analysis of the intersection sub-network obtained from multiple cancer data-sets. These genes point us toward dysregulation of the cell cycle, cell division, and cell proliferation mechanisms in cancer cells. These genes may become new cancer drug targets for cancer treatment.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"23 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79274581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
High-throughput screening (HTS) is a common practice in drug discovery. Although the chemoinformatics community has proposed various approaches for HTS data analysis, medicinal chemists continue to long for intuitive tools for the structure-activity relationship (SAR) analysis of HTS hits. Here, the author propose SAR analysis tools that were designed to help medicinal chemists grasp the chemical space of interest with conventional SAR tables. These tools comprise an on-the-fly analysis environment and a series of computational protocols for data processing prior to the interactive analysis. The protocols are designed for the following processes: i) structural classification based on simple rules to mimic visual inspection by medicinal chemists; ii) exhaustive generation of promising SAR tables using Pharmacofragment (PHF), a novel substructure concept; and iii) comprehensive analogue search to identify compounds that correspond to blank cells in SAR tables from compounds at hand. A case study using data from a screen for ribosomal protein S6 phosphorylation inhibitors (PubChem AID:493208) suggests that these tools are useful for generating conventional SAR tables for practical application to large-scale data such as HTS.
{"title":"Exhaustive SAR analysis tools for HTS hits based on intuition of medicinal chemists","authors":"H. Koga","doi":"10.1273/CBIJ.19.19","DOIUrl":"https://doi.org/10.1273/CBIJ.19.19","url":null,"abstract":"High-throughput screening (HTS) is a common practice in drug discovery. Although the chemoinformatics community has proposed various approaches for HTS data analysis, medicinal chemists continue to long for intuitive tools for the structure-activity relationship (SAR) analysis of HTS hits. Here, the author propose SAR analysis tools that were designed to help medicinal chemists grasp the chemical space of interest with conventional SAR tables. These tools comprise an on-the-fly analysis environment and a series of computational protocols for data processing prior to the interactive analysis. The protocols are designed for the following processes: i) structural classification based on simple rules to mimic visual inspection by medicinal chemists; ii) exhaustive generation of promising SAR tables using Pharmacofragment (PHF), a novel substructure concept; and iii) comprehensive analogue search to identify compounds that correspond to blank cells in SAR tables from compounds at hand. A case study using data from a screen for ribosomal protein S6 phosphorylation inhibitors (PubChem AID:493208) suggests that these tools are useful for generating conventional SAR tables for practical application to large-scale data such as HTS.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"199 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77718286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An antibiotic flucloxacillin (FX) which is widely used for the treatment of staphylococcal infection, is known to cause liver injury. A genome-wide association study has shown that FX induced idiosyncratic drug toxicity (IDT) is associated with HLA-B*57:01 . FX is processed in the human body to produce several metabolites. Molecular interactions of FX or its metabolites with HLA-B*57:01 should play a crucial role in the occurrence of the adverse drug reaction. In this study, we have undertaken docking simulations of interactions of FX and its metabolites with HLA-B*57:01 to understand molecular mechanisms leading to the onset of IDT.
{"title":"In silico analysis of interactions of flucloxacillin and its metabolites with HLA-B*57:01","authors":"Hideto Isogai, N. Hirayama","doi":"10.1273/CBIJ.19.1","DOIUrl":"https://doi.org/10.1273/CBIJ.19.1","url":null,"abstract":"An antibiotic flucloxacillin (FX) which is widely used for the treatment of staphylococcal infection, is known to cause liver injury. A genome-wide association study has shown that FX induced idiosyncratic drug toxicity (IDT) is associated with HLA-B*57:01 . FX is processed in the human body to produce several metabolites. Molecular interactions of FX or its metabolites with HLA-B*57:01 should play a crucial role in the occurrence of the adverse drug reaction. In this study, we have undertaken docking simulations of interactions of FX and its metabolites with HLA-B*57:01 to understand molecular mechanisms leading to the onset of IDT.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"24 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2019-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83464842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Yoshizawa, R. Est, Daisuke Yoshinaga, Mikihito Tanaka, Ryuma Shineha, A. Konagaya
Over the last decade Japanese researchers have taken the lead in the emerging discipline of molecular robotics. This new technology aims to produce artificial molecular systems that can adapt to changes in the environment, self-organize and evolve. This paper explores the question of how to stimulate responsible research and innovation in the field of molecular robotics technologies. For this, we first draw lessons from earlier societal responses in Japan to emerging technologies, such as genetic engineering, nanotechnology, synthetic biology and genomic research. Next we describe various real-time technology assessment (TA) activities on molecular robotics in Japan to depict the state-of-the-art of the academic and public debate on the social aspects of molecular robotics. Lessons from earlier societal responses to emerging technologies demonstrated three potential challenges: finding and involving the ‘right’ experts and stakeholders, keeping regulations up to date, and getting scientists and citizens involved in science communication. A literature review, ‘future workshop’ and scenario workshop raised a number of ethical, social, political and cultural issues, and addressed desirable and undesirable scenarios for the next few decades. Twitter text mining analysis indicates that the level of attention, knowledge and awareness about molecular robots among a broader audience is still very limited. In conclusion, we identify four activities crucial to enable responsible innovation in molecular robotics—getting to grips with the speed of the development of molecular robotics, monitoring related technical trends, the establishment of a more stable TA knowledge base, and a sustained interaction between molecular roboticists and social scientists.
{"title":"Responsible innovation in molecular robotics in Japan","authors":"G. Yoshizawa, R. Est, Daisuke Yoshinaga, Mikihito Tanaka, Ryuma Shineha, A. Konagaya","doi":"10.1273/CBIJ.18.164","DOIUrl":"https://doi.org/10.1273/CBIJ.18.164","url":null,"abstract":"Over the last decade Japanese researchers have taken the lead in the emerging discipline of molecular robotics. This new technology aims to produce artificial molecular systems that can adapt to changes in the environment, self-organize and evolve. This paper explores the question of how to stimulate responsible research and innovation in the field of molecular robotics technologies. For this, we first draw lessons from earlier societal responses in Japan to emerging technologies, such as genetic engineering, nanotechnology, synthetic biology and genomic research. Next we describe various real-time technology assessment (TA) activities on molecular robotics in Japan to depict the state-of-the-art of the academic and public debate on the social aspects of molecular robotics. Lessons from earlier societal responses to emerging technologies demonstrated three potential challenges: finding and involving the ‘right’ experts and stakeholders, keeping regulations up to date, and getting scientists and citizens involved in science communication. A literature review, ‘future workshop’ and scenario workshop raised a number of ethical, social, political and cultural issues, and addressed desirable and undesirable scenarios for the next few decades. Twitter text mining analysis indicates that the level of attention, knowledge and awareness about molecular robots among a broader audience is still very limited. In conclusion, we identify four activities crucial to enable responsible innovation in molecular robotics—getting to grips with the speed of the development of molecular robotics, monitoring related technical trends, the establishment of a more stable TA knowledge base, and a sustained interaction between molecular roboticists and social scientists.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"47 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78415590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intravenous anesthetic barbitals act on the GABAA receptor, and this receptor is the principal molecular target of loss of consciousness. Their action and side effects differ according to the enantiomer. Elucidation of their enantiomeric action is essential for a safe anesthetic agent. This study investigates molecular mechanisms of discrimination of enantiomeric barbital in the binding site of the GABAA receptor. Amobarbital, (R)-, (S)-pentobarbital, and (R)-, (S)-isobarbital bonded to the TM2-TM2’ transmembrane domain (TMD), i.e., the propofol binding site. There was a 2.9 kcal moldifference in enantiomeric pentobarbital bindings. Pentobarbital discrimination in the TM2-TM2’ TMD site was caused not only by the barbital ring’s hydrogen-bond, but also by steric fittings of the methyl-group adjacent to the chiral carbon atom.
{"title":"Molecular Discrimination of Barbital Enantiomer at the Propofol Binding Site of the Human β3 Homomeric GABAA Receptor","authors":"T. Seto, Minoru Katō, Kennichi Koyano","doi":"10.1273/CBIJ.18.154","DOIUrl":"https://doi.org/10.1273/CBIJ.18.154","url":null,"abstract":"Intravenous anesthetic barbitals act on the GABAA receptor, and this receptor is the principal molecular target of loss of consciousness. Their action and side effects differ according to the enantiomer. Elucidation of their enantiomeric action is essential for a safe anesthetic agent. This study investigates molecular mechanisms of discrimination of enantiomeric barbital in the binding site of the GABAA receptor. Amobarbital, (R)-, (S)-pentobarbital, and (R)-, (S)-isobarbital bonded to the TM2-TM2’ transmembrane domain (TMD), i.e., the propofol binding site. There was a 2.9 kcal moldifference in enantiomeric pentobarbital bindings. Pentobarbital discrimination in the TM2-TM2’ TMD site was caused not only by the barbital ring’s hydrogen-bond, but also by steric fittings of the methyl-group adjacent to the chiral carbon atom.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"44 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2018-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83945693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The statistical properties of the inter-fragment interaction energy matrix of the fragment molecular orbital method are analyzed using the random matrix theory. The eigenvalue and eigenvector distributions, the inverse participation ratio, and the unfolded eigenvalue statistics are compared with the corresponding random matrix ensemble. Cluster analysis of the fragments with strong correlations is presented using the inverse participation ratio of the random matrix theory.
{"title":"Random matrix theory for an inter-fragment interaction energy matrix in fragment molecular orbital method","authors":"M. Yamanaka","doi":"10.1273/CBIJ.18.123","DOIUrl":"https://doi.org/10.1273/CBIJ.18.123","url":null,"abstract":"The statistical properties of the inter-fragment interaction energy matrix of the fragment molecular orbital method are analyzed using the random matrix theory. The eigenvalue and eigenvector distributions, the inverse participation ratio, and the unfolded eigenvalue statistics are compared with the corresponding random matrix ensemble. Cluster analysis of the fragments with strong correlations is presented using the inverse participation ratio of the random matrix theory.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"35 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2018-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85270101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Nakano, Kaori Fukuzawa, Yoshio Okiyama, C. Watanabe, Y. Komeiji, Y. Mochizuki
The fragment molecular orbital (FMO) method is recently attracting attention as a method of calculating the electronic state of macromolecular systems. To enhance the speed of the FMO method, it is necessary to apply an approximation in which SCF calculations are neglected for distant fragment (monomer) pairs (dimers) and instead the electrostatic interactions between the two monomers are calculated. This approximation is called the dimer-es approximation. The accuracy and speed brought by the dimer-es approximation depend on the minimum threshold distance between two atoms to apply the approximation. This threshold distance given in unit of van der Waals radii is named “Ldimer-es”. In this communication, we examined dependence of HF and MP2 electron correlation energy errors on “Ldimer-es”, and it is preferable to calculate FMO4-HF and FMO4-MP2 for calculation of FMO-HF and FMO-MP2 of side chain-split peptides with Ldimer-es=2.0.
{"title":"Accuracy of Dimer-ES Approximation on Fragment Molecular Orbital (FMO) Method","authors":"T. Nakano, Kaori Fukuzawa, Yoshio Okiyama, C. Watanabe, Y. Komeiji, Y. Mochizuki","doi":"10.1273/CBIJ.18.119","DOIUrl":"https://doi.org/10.1273/CBIJ.18.119","url":null,"abstract":"The fragment molecular orbital (FMO) method is recently attracting attention as a method of calculating the electronic state of macromolecular systems. To enhance the speed of the FMO method, it is necessary to apply an approximation in which SCF calculations are neglected for distant fragment (monomer) pairs (dimers) and instead the electrostatic interactions between the two monomers are calculated. This approximation is called the dimer-es approximation. The accuracy and speed brought by the dimer-es approximation depend on the minimum threshold distance between two atoms to apply the approximation. This threshold distance given in unit of van der Waals radii is named “Ldimer-es”. In this communication, we examined dependence of HF and MP2 electron correlation energy errors on “Ldimer-es”, and it is preferable to calculate FMO4-HF and FMO4-MP2 for calculation of FMO-HF and FMO-MP2 of side chain-split peptides with Ldimer-es=2.0.","PeriodicalId":40659,"journal":{"name":"Chem-Bio Informatics Journal","volume":"38 1","pages":""},"PeriodicalIF":0.3,"publicationDate":"2018-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79176877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：