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- SARS-CoV-2 spike protein (3)
- ACE2 host receptor (2)
- Binding energetics (2)
- Molecular dynamics (2)
- Signal transmission (2)
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- ACE2 (1)
- Alanine scanning (1)
- Allosteric communications (1)
- Allosteric drugs (1)
- Allosteric inhibitors (1)
- Allosteric interactions (1)
- Allosteric regulation (1)
- Betweenness centrality (1)
- Binding free energy (1)
- Biometrics (1)
- Coevolution (1)
- Computational modeling (1)
- Conformational landscapes (1)
- Convolutional neural networks (CNN) (1)
- Deep learning (1)
- Drug design (1)
- Dynamic network analysis (1)
- Dynamic residue networks (1)
- ECG identification (1)
- Electrocardiogram (ECG) (1)
- Heat shock proteins (1)
- Molecular simulations (1)
- Mutational scanning (1)
- Network analysis (1)
- Privacy (1)
Articles 1 - 10 of 10
Full-Text Articles in Other Computer Sciences
Exploring Binding Pockets In The Conformational States Of The Sars-Cov-2 Spike Trimers For The Screening Of Allosteric Inhibitors Using Molecular Simulations And Ensemble-Based Ligand Docking, Grace Gupta, Gennady M. Verkhivker
Exploring Binding Pockets In The Conformational States Of The Sars-Cov-2 Spike Trimers For The Screening Of Allosteric Inhibitors Using Molecular Simulations And Ensemble-Based Ligand Docking, Grace Gupta, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and …
Assessing The Reidentification Risks Posed By Deep Learning Algorithms Applied To Ecg Data, Arin Ghazarian, Jianwei Zheng, Daniele Struppa, Cyril Rakovski
Assessing The Reidentification Risks Posed By Deep Learning Algorithms Applied To Ecg Data, Arin Ghazarian, Jianwei Zheng, Daniele Struppa, Cyril Rakovski
Mathematics, Physics, and Computer Science Faculty Articles and Research
ECG (Electrocardiogram) data analysis is one of the most widely used and important tools in cardiology diagnostics. In recent years the development of advanced deep learning techniques and GPU hardware have made it possible to train neural network models that attain exceptionally high levels of accuracy in complex tasks such as heart disease diagnoses and treatments. We investigate the use of ECGs as biometrics in human identification systems by implementing state-of-the-art deep learning models. We train convolutional neural network models on approximately 81k patients from the US, Germany and China. Currently, this is the largest research project on ECG identification. …
Computer Simulations And Network-Based Profiling Of Binding And Allosteric Interactions Of Sars-Cov-2 Spike Variant Complexes And The Host Receptor: Dissecting The Mechanistic Effects Of The Delta And Omicron Mutations, Gennady M. Verkhivker, Steve Agajanian, Ryan Kassab, Keerthi Krishnan
Computer Simulations And Network-Based Profiling Of Binding And Allosteric Interactions Of Sars-Cov-2 Spike Variant Complexes And The Host Receptor: Dissecting The Mechanistic Effects Of The Delta And Omicron Mutations, Gennady M. Verkhivker, Steve Agajanian, Ryan Kassab, Keerthi Krishnan
Mathematics, Physics, and Computer Science Faculty Articles and Research
In this study, we combine all-atom MD simulations and comprehensive mutational scanning of S-RBD complexes with the angiotensin-converting enzyme 2 (ACE2) host receptor in the native form as well as the S-RBD Delta and Omicron variants to (a) examine the differences in the dynamic signatures of the S-RBD complexes and (b) identify the critical binding hotspots and sensitivity of the mutational positions. We also examined the differences in allosteric interactions and communications in the S-RBD complexes for the Delta and Omicron variants. Through the perturbation-based scanning of the allosteric propensities of the SARS-CoV-2 S-RBD residues and dynamics-based network centrality and …
Dissecting Mutational Allosteric Effects In Alkaline Phosphatases Associated With Different Hypophosphatasia Phenotypes: An Integrative Computational Investigation, Fei Xiao, Ziyun Zhou, Xingyu Song, Mi Gan, Jie Long, Gennady M. Verkhivker, Guang Hu
Dissecting Mutational Allosteric Effects In Alkaline Phosphatases Associated With Different Hypophosphatasia Phenotypes: An Integrative Computational Investigation, Fei Xiao, Ziyun Zhou, Xingyu Song, Mi Gan, Jie Long, Gennady M. Verkhivker, Guang Hu
Mathematics, Physics, and Computer Science Faculty Articles and Research
Hypophosphatasia (HPP) is a rare inherited disorder characterized by defective bone mineralization and is highly variable in its clinical phenotype. The disease occurs due to various loss-of-function mutations in ALPL, the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). In this work, a data-driven and biophysics-based approach is proposed for the large-scale analysis of ALPL mutations-from nonpathogenic to severe HPPs. By using a pipeline of synergistic approaches including sequence-structure analysis, network modeling, elastic network models and atomistic simulations, we characterized allosteric signatures and effects of the ALPL mutations on protein dynamics and function. Statistical analysis of molecular features computed for the …
Landscape-Based Mutational Sensitivity Cartography And Network Community Analysis Of The Sars-Cov-2 Spike Protein Structures: Quantifying Functional Effects Of The Circulating D614g Variant, Gennady M. Verkhivker, Steve Agajanian, Deniz Yasar Oztas, Grace Gupta
Landscape-Based Mutational Sensitivity Cartography And Network Community Analysis Of The Sars-Cov-2 Spike Protein Structures: Quantifying Functional Effects Of The Circulating D614g Variant, Gennady M. Verkhivker, Steve Agajanian, Deniz Yasar Oztas, Grace Gupta
Mathematics, Physics, and Computer Science Faculty Articles and Research
We developed and applied a computational approach to simulate functional effects of the global circulating mutation D614G of the SARS-CoV-2 spike protein. All-atom molecular dynamics simulations are combined with deep mutational scanning and analysis of the residue interaction networks to investigate conformational landscapes and energetics of the SARS-CoV-2 spike proteins in different functional states of the D614G mutant. The results of conformational dynamics and analysis of collective motions demonstrated that the D614 site plays a key regulatory role in governing functional transitions between open and closed states. Using mutational scanning and sensitivity analysis of protein residues, we identified the stability …
Computational Analysis Of Protein Stability And Allosteric Interaction Networks In Distinct Conformational Forms Of The Sars Cov 2 Spike D614g Mutant: Reconciling Functional Mechanisms Through Allosteric Model Of Spike Regulation, Gennady M. Verkhivker, Steve Agajanian, Deniz Oztas, Grace Gupta
Computational Analysis Of Protein Stability And Allosteric Interaction Networks In Distinct Conformational Forms Of The Sars Cov 2 Spike D614g Mutant: Reconciling Functional Mechanisms Through Allosteric Model Of Spike Regulation, Gennady M. Verkhivker, Steve Agajanian, Deniz Oztas, Grace Gupta
Mathematics, Physics, and Computer Science Faculty Articles and Research
In this study, we used an integrative computational approach to examine molecular mechanisms underlying functional effects of the D614G mutation by exploring atomistic modeling of the SARS-CoV-2 spike proteins as allosteric regulatory machines. We combined coarse-grained simulations, protein stability and dynamic fluctuation communication analysis with network-based community analysis to examine structures of the native and mutant SARS-CoV-2 spike proteins in different functional states. Through distance fluctuations communication analysis, we probed stability and allosteric communication propensities of protein residues in the native and mutant SARS-CoV-2 spike proteins, providing evidence that the D614G mutation can enhance long-range signaling of the allosteric spike …
Coevolution, Dynamics And Allostery Conspire In Shaping Cooperative Binding And Signal Transmission Of The Sars-Cov-2 Spike Protein With Human Angiotensin-Converting Enzyme 2, Gennady M. Verkhivker
Coevolution, Dynamics And Allostery Conspire In Shaping Cooperative Binding And Signal Transmission Of The Sars-Cov-2 Spike Protein With Human Angiotensin-Converting Enzyme 2, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
Binding to the host receptor is a critical initial step for the coronavirus SARS-CoV-2 spike protein to enter into target cells and trigger virus transmission. A detailed dynamic and energetic view of the binding mechanisms underlying virus entry is not fully understood and the consensus around the molecular origins behind binding preferences of SARS-CoV-2 for binding with the angiotensin-converting enzyme 2 (ACE2) host receptor is yet to be established. In this work, we performed a comprehensive computational investigation in which sequence analysis and modeling of coevolutionary networks are combined with atomistic molecular simulations and comparative binding free energy analysis of …
Optimal Multi-Stage Arrhythmia Classification Approach, Jianwei Zhang, Huimin Chu, Daniele Struppa, Jianming Zhang, Sir Magdi Yacoub, Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, Guohua Fu, Hai Yao, Dongbo Li, Hangyuan Guo, Cyril Rakovski
Optimal Multi-Stage Arrhythmia Classification Approach, Jianwei Zhang, Huimin Chu, Daniele Struppa, Jianming Zhang, Sir Magdi Yacoub, Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, Guohua Fu, Hai Yao, Dongbo Li, Hangyuan Guo, Cyril Rakovski
Mathematics, Physics, and Computer Science Faculty Articles and Research
Arrhythmia constitutes a problem with the rate or rhythm of the heartbeat, and an early diagnosis is essential for the timely inception of successful treatment. We have jointly optimized the entire multi-stage arrhythmia classification scheme based on 12-lead surface ECGs that attains the accuracy performance level of professional cardiologists. The new approach is comprised of a three-step noise reduction stage, a novel feature extraction method and an optimal classification model with finely tuned hyperparameters. We carried out an exhaustive study comparing thousands of competing classification algorithms that were trained on our proprietary, large and expertly labeled dataset consisting of 12-lead …
Establishing Computational Approaches Towards Identifying Malarial Allosteric Modulators: A Case Study Of Plasmodium Falciparum Hsp70s, Arnold Amusengeri, Lindy Astl, Kevin Lobb, Gennady M. Verkhivker, Özlem Tastan Bishop
Establishing Computational Approaches Towards Identifying Malarial Allosteric Modulators: A Case Study Of Plasmodium Falciparum Hsp70s, Arnold Amusengeri, Lindy Astl, Kevin Lobb, Gennady M. Verkhivker, Özlem Tastan Bishop
Mathematics, Physics, and Computer Science Faculty Articles and Research
Combating malaria is almost a never-ending battle, as Plasmodium parasites develop resistance to the drugs used against them, as observed recently in artemisinin-based combination therapies. The main concern now is if the resistant parasite strains spread from Southeast Asia to Africa, the continent hosting most malaria cases. To prevent catastrophic results, we need to find non-conventional approaches. Allosteric drug targeting sites and modulators might be a new hope for malarial treatments. Heat shock proteins (HSPs) are potential malarial drug targets and have complex allosteric control mechanisms. Yet, studies on designing allosteric modulators against them are limited. Here, we identified allosteric …
The Chapman Bone Algorithm: A Diagnostic Alternative For The Evaluation Of Osteoporosis, Elise Levesque, Anton Ketterer, Wajiha Memon, Cameron James, Noah Barrett, Cyril Rakovski, Frank Frisch
The Chapman Bone Algorithm: A Diagnostic Alternative For The Evaluation Of Osteoporosis, Elise Levesque, Anton Ketterer, Wajiha Memon, Cameron James, Noah Barrett, Cyril Rakovski, Frank Frisch
Mathematics, Physics, and Computer Science Faculty Articles and Research
Osteoporosis is the most common metabolic bone disease and goes largely undiagnosed throughout the world, due to the inaccessibility of DXA machines. Multivariate analyses of serum bone turnover markers were evaluated in 226 Orange County, California, residents with the intent to determine if serum osteocalcin and serum pyridinoline cross-links could be used to detect the onset of osteoporosis as effectively as a DXA scan. Descriptive analyses of the demographic and lab characteristics of the participants were performed through frequency, means and standard deviation estimations. We implemented logistic regression modeling to find the best classification algorithm for osteoporosis. All calculations and …