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Physical Sciences and Mathematics
Mathematics, Physics, and Computer Science Faculty Articles and Research
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- Molecular dynamics (3)
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Articles 1 - 6 of 6
Full-Text Articles in Biochemistry, Biophysics, and Structural Biology
From Deep Mutational Mapping Of Allosteric Protein Landscapes To Deep Learning Of Allostery And Hidden Allosteric Sites: Zooming In On “Allosteric Intersection” Of Biochemical And Big Data Approaches, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta, Sian Xiao, Peng Tao
From Deep Mutational Mapping Of Allosteric Protein Landscapes To Deep Learning Of Allostery And Hidden Allosteric Sites: Zooming In On “Allosteric Intersection” Of Biochemical And Big Data Approaches, Gennady M. Verkhivker, Mohammed Alshahrani, Grace Gupta, Sian Xiao, Peng Tao
Mathematics, Physics, and Computer Science Faculty Articles and Research
The recent advances in artificial intelligence (AI) and machine learning have driven the design of new expert systems and automated workflows that are able to model complex chemical and biological phenomena. In recent years, machine learning approaches have been developed and actively deployed to facilitate computational and experimental studies of protein dynamics and allosteric mechanisms. In this review, we discuss in detail new developments along two major directions of allosteric research through the lens of data-intensive biochemical approaches and AI-based computational methods. Despite considerable progress in applications of AI methods for protein structure and dynamics studies, the intersection between allosteric …
Machine Learning And Protein Allostery, Sian Xiao, Gennady M. Verkhivker, Peng Tao
Machine Learning And Protein Allostery, Sian Xiao, Gennady M. Verkhivker, Peng Tao
Mathematics, Physics, and Computer Science Faculty Articles and Research
The fundamental biological importance and complexity of allosterically regulated proteins stem from their central role in signal transduction and cellular processes. Recently, machine-learning approaches have been developed and actively deployed to facilitate theoretical and experimental studies of protein dynamics and allosteric mechanisms. In this review, we survey recent developments in applications of machine-learning methods for studies of allosteric mechanisms, prediction of allosteric effects and allostery-related physicochemical properties, and allosteric protein engineering. We also review the applications of machine-learning strategies for characterization of allosteric mechanisms and drug design targeting SARS-CoV-2. Continuous development and task-specific adaptation of machine-learning methods for protein allosteric …
Structural And Computational Studies Of The Sars-Cov-2 Spike Protein Binding Mechanisms With Nanobodies: From Structure And Dynamics To Avidity-Driven Nanobody Engineering, Gennady M. Verkhivker
Structural And Computational Studies Of The Sars-Cov-2 Spike Protein Binding Mechanisms With Nanobodies: From Structure And Dynamics To Avidity-Driven Nanobody Engineering, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
Nanobodies provide important advantages over traditional antibodies, including their smaller size and robust biochemical properties such as high thermal stability, high solubility, and the ability to be bioengineered into novel multivalent, multi-specific, and high-affinity molecules, making them a class of emerging powerful therapies against SARS-CoV-2. Recent research efforts on the design, protein engineering, and structure-functional characterization of nanobodies and their binding with SARS-CoV-2 S proteins reflected a growing realization that nanobody combinations can exploit distinct binding epitopes and leverage the intrinsic plasticity of the conformational landscape for the SARS-CoV-2 S protein to produce efficient neutralizing and mutation resistant characteristics. Structural …
Allosteric Determinants Of The Sars-Cov-2 Spike Protein Binding With Nanobodies: Examining Mechanisms Of Mutational Escape And Sensitivity Of The Omicron Variant, Gennady M. Verkhivker
Allosteric Determinants Of The Sars-Cov-2 Spike Protein Binding With Nanobodies: Examining Mechanisms Of Mutational Escape And Sensitivity Of The Omicron Variant, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against the SARS-CoV-2 virus and resilience against mutational escape. In this study, we performed a comprehensive computational analysis of the SARS-CoV-2 spike trimer complexes with single nanobodies Nb6, VHH E, and complex with VHH E/VHH V nanobody combination. We combined coarse-grained and all-atom molecular simulations and collective dynamics analysis with binding free energy scanning, perturbation-response scanning, and network centrality analysis to examine mechanisms of nanobody-induced allosteric modulation and cooperativity in the SARS-CoV-2 spike trimer complexes with these nanobodies. By quantifying energetic and allosteric …
Allosteric Mechanism Of The Circadian Protein Vivid Resolved Through Markov State Model And Machine Learning Analysis, Hongyu Zhou, Zheng Dong, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao
Allosteric Mechanism Of The Circadian Protein Vivid Resolved Through Markov State Model And Machine Learning Analysis, Hongyu Zhou, Zheng Dong, Gennady M. Verkhivker, Brian D. Zoltowski, Peng Tao
Mathematics, Physics, and Computer Science Faculty Articles and Research
The fungal circadian clock photoreceptor Vivid (VVD) contains a photosensitive allosteric light, oxygen, voltage (LOV) domain that undergoes a large N-terminal conformational change. The mechanism by which a blue-light driven covalent bond formation leads to a global conformational change remains unclear, which hinders the further development of VVD as an optogenetic tool. We answered this question through a novel computational platform integrating Markov state models, machine learning methods, and newly developed community analysis algorithms. Applying this new integrative approach, we provided a quantitative evaluation of the contribution from the covalent bond to the protein global conformational change, and proposed an …
Cellular And Molecular Targets Of Menthol Actions, Murat Oz, Eslam El Nebrisi, Keun-Hang Susan Yang, Frank Christopher Howarth, Lina T. Al Kury
Cellular And Molecular Targets Of Menthol Actions, Murat Oz, Eslam El Nebrisi, Keun-Hang Susan Yang, Frank Christopher Howarth, Lina T. Al Kury
Mathematics, Physics, and Computer Science Faculty Articles and Research
Menthol belongs to monoterpene class of a structurally diverse group of phytochemicals found in plant-derived essential oils. Menthol is widely used in pharmaceuticals, confectionary, oral hygiene products, pesticides, cosmetics, and as a flavoring agent. In addition, menthol is known to have antioxidant, anti-inflammatory, and analgesic effects. Recently, there has been renewed awareness in comprehending the biological and pharmacological effects of menthol. TRP channels have been demonstrated to mediate the cooling actions ofmenthol. There has been new evidence demonstrating thatmenthol can significantly influence the functional characteristics of a number of different kinds of ligand and voltage-gated ion channels, indicating that at …