Pub Date : 2023-08-10DOI: 10.1142/s2737416523500485
Yasmin Rahmati, Khosrow Khalifeh, Emran Heshmati
{"title":"Dynamic behavior and ligand binding properties of the wild type Deoxycytidine kinase and its characterized gemcitabine-resistant variant: A bioinformatics and computational study","authors":"Yasmin Rahmati, Khosrow Khalifeh, Emran Heshmati","doi":"10.1142/s2737416523500485","DOIUrl":"https://doi.org/10.1142/s2737416523500485","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46989722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-04DOI: 10.1142/s2737416523420061
Vipin Kumar, Prabhakar Chetti
{"title":"Effect of π-bridge in D–π–A architecture and Adsorption of Phenothiazine Dyes on TiO2 Nanocrystalline for Dye-Sensitized Solar Cells: A DFT Approach","authors":"Vipin Kumar, Prabhakar Chetti","doi":"10.1142/s2737416523420061","DOIUrl":"https://doi.org/10.1142/s2737416523420061","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43017183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01Epub Date: 2023-06-08DOI: 10.1142/s2737416523500278
Xiaoqi Wei, Jiahui Chen, Guo-Wei Wei
Topological data analysis (TDA) is an emerging field in mathematics and data science. Its central technique, persistent homology, has had tremendous success in many science and engineering disciplines. However, persistent homology has limitations, including its inability to handle heterogeneous information, such as multiple types of geometric objects; being qualitative rather than quantitative, e.g., counting a 5-member ring the same as a 6-member ring, and a failure to describe non-topological changes, such as homotopic changes in protein-protein binding. Persistent topological Laplacians (PTLs), such as persistent Laplacian and persistent sheaf Laplacian, were proposed to overcome the limitations of persistent homology. In this work, we examine the modeling and analysis power of PTLs in the study of the protein structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike receptor binding domain (RBD). First, we employ PTLs to study how the RBD mutation-induced structural changes of RBD-angiotensin-converting enzyme 2 (ACE2) binding complexes are captured in the changes of spectra of the PTLs among SARS-CoV-2 variants. Additionally, we use PTLs to analyze the binding of RBD and ACE2-induced structural changes of various SARS-CoV-2 variants. Finally, we explore the impacts of computationally generated RBD structures on a topological deep learning paradigm and predictions of deep mutational scanning datasets for the SARS-CoV-2 Omicron BA.2 variant. Our results indicate that PTLs have advantages over persistent homology in analyzing protein structural changes and provide a powerful new TDA tool for data science.
{"title":"Persistent topological Laplacian analysis of SARS-CoV-2 variants.","authors":"Xiaoqi Wei, Jiahui Chen, Guo-Wei Wei","doi":"10.1142/s2737416523500278","DOIUrl":"10.1142/s2737416523500278","url":null,"abstract":"<p><p>Topological data analysis (TDA) is an emerging field in mathematics and data science. Its central technique, persistent homology, has had tremendous success in many science and engineering disciplines. However, persistent homology has limitations, including its inability to handle heterogeneous information, such as multiple types of geometric objects; being qualitative rather than quantitative, e.g., counting a 5-member ring the same as a 6-member ring, and a failure to describe non-topological changes, such as homotopic changes in protein-protein binding. Persistent topological Laplacians (PTLs), such as persistent Laplacian and persistent sheaf Laplacian, were proposed to overcome the limitations of persistent homology. In this work, we examine the modeling and analysis power of PTLs in the study of the protein structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike receptor binding domain (RBD). First, we employ PTLs to study how the RBD mutation-induced structural changes of RBD-angiotensin-converting enzyme 2 (ACE2) binding complexes are captured in the changes of spectra of the PTLs among SARS-CoV-2 variants. Additionally, we use PTLs to analyze the binding of RBD and ACE2-induced structural changes of various SARS-CoV-2 variants. Finally, we explore the impacts of computationally generated RBD structures on a topological deep learning paradigm and predictions of deep mutational scanning datasets for the SARS-CoV-2 Omicron BA.2 variant. Our results indicate that PTLs have advantages over persistent homology in analyzing protein structural changes and provide a powerful new TDA tool for data science.</p>","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":"22 5","pages":"569-587"},"PeriodicalIF":2.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569362/pdf/nihms-1888545.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41202808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01Epub Date: 2023-04-25DOI: 10.1142/s2737416523500230
Nicolas Ancona, Ananta Bastola, Emil Alexov
Almost all biological reactions are pH dependent and understanding the origin of pH dependence requires knowledge of the pKa's of ionizable groups. Here we report a new edition of PKAD, the PKAD-2, which is a database of experimentally measured pKa's of proteins, both wild type and mutant proteins. The new additions include 117 wild type and 54 mutant pKa values, resulting in total 1742 experimentally measured pKa's. The new edition of PKAD-2 includes 8 new wild type and 12 new mutant proteins, resulting in total of 220 proteins. This new edition incorporates a visual 3D image of the highlighted residue of interest within the corresponding protein or protein complex. Hydrogen bonds were identified, counted, and implemented as a search feature. Other new search features include the number of neighboring residues <4A from the heaviest atom of the side chain of a given amino acid. Here, we present PKAD-2 with the intention to continuously incorporate novel features and current data with the goal to be used as benchmark for computational methods.
{"title":"PKAD-2: New entries and expansion of functionalities of the database of experimentally measured pKa's of proteins.","authors":"Nicolas Ancona, Ananta Bastola, Emil Alexov","doi":"10.1142/s2737416523500230","DOIUrl":"10.1142/s2737416523500230","url":null,"abstract":"<p><p>Almost all biological reactions are pH dependent and understanding the origin of pH dependence requires knowledge of the pKa's of ionizable groups. Here we report a new edition of PKAD, the PKAD-2, which is a database of experimentally measured pKa's of proteins, both wild type and mutant proteins. The new additions include 117 wild type and 54 mutant pKa values, resulting in total 1742 experimentally measured pKa's. The new edition of PKAD-2 includes 8 new wild type and 12 new mutant proteins, resulting in total of 220 proteins. This new edition incorporates a visual 3D image of the highlighted residue of interest within the corresponding protein or protein complex. Hydrogen bonds were identified, counted, and implemented as a search feature. Other new search features include the number of neighboring residues <4A from the heaviest atom of the side chain of a given amino acid. Here, we present PKAD-2 with the intention to continuously incorporate novel features and current data with the goal to be used as benchmark for computational methods.</p>","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":"22 5","pages":"515-524"},"PeriodicalIF":4.6,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373500/pdf/nihms-1915764.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10354730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-28DOI: 10.1142/s2737416523500448
M. D. Olawale, E. Akintemi, N. Ojo, A. Isaac, H. Su, J. Obaleye
{"title":"Synthesis, Characterization, Density Functional Theory, Monte Carlo, and Molecular Dynamics Simulations of [NI(II)(TPY)2] Metal Organic Framework and Congo Red Dye Application","authors":"M. D. Olawale, E. Akintemi, N. Ojo, A. Isaac, H. Su, J. Obaleye","doi":"10.1142/s2737416523500448","DOIUrl":"https://doi.org/10.1142/s2737416523500448","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48736938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-28DOI: 10.1142/s273741652342005x
S. Sarfaraz, Ahmed Lakhani, Riaz Hussain, K. Ayub
{"title":"Fine-Tuning of the Electronic and Optical Properties of Dodecabenzocoronene through Boron and Nitrogen Doping: A DFT Insight","authors":"S. Sarfaraz, Ahmed Lakhani, Riaz Hussain, K. Ayub","doi":"10.1142/s273741652342005x","DOIUrl":"https://doi.org/10.1142/s273741652342005x","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47754378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-25DOI: 10.1142/s2737416523920023
N. M. Tam, L. Tran, Q. Vo, Minh Quan Pham, H. Phung
{"title":"Erratum: Designing Potential Inhibitors of SARS-CoV-2 Mpro Using Deep Learning and Steered Molecular Dynamic Simulations","authors":"N. M. Tam, L. Tran, Q. Vo, Minh Quan Pham, H. Phung","doi":"10.1142/s2737416523920023","DOIUrl":"https://doi.org/10.1142/s2737416523920023","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44424341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-21DOI: 10.1142/s2737416523500436
Yuri Alves de Oliveira Só, MonicaA. Silva, A. S. Kiametis, C. Sette, M. L. Pereira Júnior, L. A. R. Júnior, R. Gargano
{"title":"A Multi-target Study of Natural Compounds in Preventing Neurodegenerative Disease Progression: A Computational Modeling Study","authors":"Yuri Alves de Oliveira Só, MonicaA. Silva, A. S. Kiametis, C. Sette, M. L. Pereira Júnior, L. A. R. Júnior, R. Gargano","doi":"10.1142/s2737416523500436","DOIUrl":"https://doi.org/10.1142/s2737416523500436","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45909266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-21DOI: 10.1142/s2737416523500424
Y. Dharmendar Reddy, I. Mangamma
{"title":"Influence of velocity slip and viscous dissipation on MHD heat transfer Fe3O4 - Ethylene Glycol Nanofluid flow over a shrinking sheet with thermal radiation","authors":"Y. Dharmendar Reddy, I. Mangamma","doi":"10.1142/s2737416523500424","DOIUrl":"https://doi.org/10.1142/s2737416523500424","url":null,"abstract":"","PeriodicalId":15603,"journal":{"name":"Journal of Computational Biophysics and Chemistry","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48329201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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