Supercomputing Frontiers and Innovations最新文献_第4页

Computational Characterization of N-acetylaspartylglutamate Synthetase: From the Protein Primary Sequence to Plausible Catalytic Mechanism n -乙酰天冬氨酸谷氨酸合成酶的计算表征:从蛋白质一级序列到合理的催化机制

Supercomputing Frontiers and Innovations Pub Date : 2022-06-01 DOI: 10.14529/jsfi220201

Kniga A.E, Polyakov I.V, Nemukhin A.V

引用次数: 0

Predicting Binding Free Energies for DPS Protein-DNA Complexes and Crystals Using Molecular Dynamics 用分子动力学预测DPS蛋白- dna复合物和晶体的结合自由能

Supercomputing Frontiers and Innovations Pub Date : 2022-06-01 DOI: 10.14529/jsfi220203

引用次数: 2

Predicting the Activity of Boronate Inhibitors Against Metallo-beta-lactamase Enzymes 预测硼酸盐抑制剂对金属-内酰胺酶的活性

Supercomputing Frontiers and Innovations Pub Date : 2022-06-01 DOI: 10.14529/jsfi220202

引用次数: 1

Analysis of Ion Atmosphere Around Nucleosomes Using Supercomputer MD Simulations 核小体周围离子气氛的超级计算机MD模拟分析

Supercomputing Frontiers and Innovations Pub Date : 2022-06-01 DOI: 10.14529/jsfi220205

引用次数: 1

Computational Modeling of the Interaction of Molecular Oxygen with the Flavin-dependent Enzyme RutA 分子氧与黄素依赖酶RutA相互作用的计算模型

Supercomputing Frontiers and Innovations Pub Date : 2022-06-01 DOI: 10.14529/jsfi220204

引用次数: 2

Supercomputing Frontiers: 7th Asian Conference, SCFA 2022, Singapore, March 1–3, 2022, Proceedings 超级计算前沿:第七届亚洲会议，SCFA 2022，新加坡，2022年3月1日至3日，会议录

Supercomputing Frontiers and Innovations Pub Date : 2022-01-01 DOI: 10.1007/978-3-031-10419-0

引用次数: 0

Accounting of Receptor Flexibility in Ultra-Large Virtual Screens with VirtualFlow Using a Grey Wolf Optimization Method. 基于灰狼优化方法的VirtualFlow对超大虚拟屏幕中受体灵活性的计算。

Supercomputing Frontiers and Innovations Pub Date : 2020-11-07 DOI: 10.14529/jsfi200301

Christoph Gorgulla, Konstantin Fackeldey, Gerhard Wagner, Haribabu Arthanari

{"title":"Accounting of Receptor Flexibility in Ultra-Large Virtual Screens with VirtualFlow Using a Grey Wolf Optimization Method.","authors":"Christoph Gorgulla, Konstantin Fackeldey, Gerhard Wagner, Haribabu Arthanari","doi":"10.14529/jsfi200301","DOIUrl":"https://doi.org/10.14529/jsfi200301","url":null,"abstract":"Structure-based virtual screening approaches have the ability to dramatically reduce the time and costs associated to the discovery of new drug candidates. Studies have shown that the true hit rate of virtual screenings improves with the scale of the screened ligand libraries. Therefore, we have recently developed an open source drug discovery platform (VirtualFlow), which is able to routinely carry out ultra-large virtual screenings. One of the primary challenges of molecular docking is the circumstance when the protein is highly dynamic or when the structure of the protein cannot be captured by a static pose. To accommodate protein dynamics, we report the extension of VirtualFlow to allow the docking of ligands using a grey wolf optimization algorithm using the docking program GWOVina, which substantially improves the quality and efficiency of flexible receptor docking compared to AutoDock Vina. We demonstrate the linear scaling behavior of VirtualFlow utilizing GWOVina up to 128 000 CPUs. The newly supported docking method will be valuable for drug discovery projects in which protein dynamics and flexibility play a significant role.","PeriodicalId":52144,"journal":{"name":"Supercomputing Frontiers and Innovations","volume":"7 3","pages":"4-12"},"PeriodicalIF":0.0,"publicationDate":"2020-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/71/cf/nihms-1745091.PMC8530406.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10095076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Supercomputing Frontiers: 6th Asian Conference, SCFA 2020, Singapore, February 24–27, 2020, Proceedings 超级计算前沿:第六届亚洲会议，SCFA 2020，新加坡，2020年2月24日至27日，会议录

Supercomputing Frontiers and Innovations Pub Date : 2020-01-01 DOI: 10.1007/978-3-030-48842-0

D. Panda

引用次数: 0

Three-dimensional Inversion of Electromagnetic Geophysical Data with Parallel Computational Code on Supercomputer Complex “Lomonosov” 基于“罗蒙诺索夫”超级计算机并行计算代码的电磁地球物理数据三维反演

Supercomputing Frontiers and Innovations Pub Date : 2018-09-01 DOI: 10.14529/jsfi180302

引用次数: 0

In Situ Visualization for 3D Agent-Based Vocal Fold Inflammation and Repair Simulation. 基于agent的三维声带炎症和修复模拟的原位可视化。

Supercomputing Frontiers and Innovations Pub Date : 2017-07-01 DOI: 10.14529/jsfi170304

Nuttiiya Seekhao, Joseph JaJa, Luc Mongeau, Nicole Y K Li-Jessen

{"title":"In Situ Visualization for 3D Agent-Based Vocal Fold Inflammation and Repair Simulation.","authors":"Nuttiiya Seekhao, Joseph JaJa, Luc Mongeau, Nicole Y K Li-Jessen","doi":"10.14529/jsfi170304","DOIUrl":"https://doi.org/10.14529/jsfi170304","url":null,"abstract":"A fast and insightful visualization is essential in modeling biological system behaviors and understanding underlying inter-cellular mechanisms. High fidelity models produce billions of data points per time step, making in situ visualization techniques extremely desirable as they mitigate I/O bottlenecks and provide computational steering capability. In this work, we present a novel high-performance scheme to couple in situ visualization with the simulation of the vocal fold inflammation and repair using little to no extra cost in execution time or computing resources. The visualization component is first optimized with an adaptive sampling scheme to accelerate the rendering process while maintaining the precision of the displayed visual results. Our software employs VirtualGL to perform visualization in situ. The scheme overlaps visualization and simulation, resulting in the optimal utilization of computing resources. This results in an in situ system biology simulation suite capable of remote simulation of 17 million biological cells and 1.2 billion chemical data points, remote visualization of the results, and delivery of visualized frames with aggregated statistics to remote clients in real-time.","PeriodicalId":52144,"journal":{"name":"Supercomputing Frontiers and Innovations","volume":"4 3","pages":"68-79"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5701753/pdf/nihms920499.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35287055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6