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1. Theoretical Investigations of the Role of Mutations in Dynamics of Kinesin Motor Proteins

   https://doi.org/DOI: 10.1021/acs.jpcb.8b00830  

   Mikita Misiura, Qian Wang (April 2018, Journal of physical chemistry)

   Motor proteins are active enzymatic molecules that are critically important for a variety of biological phenomena. It is known that some neurodegenerative diseases are caused by specific mutations in motor proteins that lead to their malfunctioning. Hereditary spastic paraplegia is one of such diseases, and it is associated with the mutations in the neuronal conventional kinesin gene, producing the decreased speed and processivity of this motor protein. Despite the importance of this problem, there is no clear understanding on the role of mutations in modifying dynamic properties of motor proteins. In this work, we investigate theoretically the molecular basis for negative effects of two specific mutations, N256S and R280S, on the dynamics of kinesin motor proteins. We hypothesize that these mutations might accelerate the adenosine triphosphate (ATP) release by increasing the probability of open conformations for the ATP-binding pocket. Our approach is based on the use of coarse-grained structure-based molecular dynamics simulations to analyze the conformational changes and chemical transitions in the kinesin molecule, which is also supplemented by investigation of a mesoscopic discrete-state stochastic model. Computer simulations suggest that mutations N256S and R280S can decrease the free energy difference between open and closed biochemical states, making the open conformation more stable and the ATP release faster, which is in agreement with our hypothesis. Furthermore, we show that in the case of N256S mutation, this effect is caused by disruption of interactions between α helix and switch I and loop L11 structural elements. Our computational results are qualitatively supported by the explicit analysis of the discrete-state stochastic model. 

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2. Mechanisms of Protein Search for Targets on DNA: Theoretical Insights

   https://doi.org/doi:10.3390/molecules23092106  

   Shvets, Alexey A; Kochugaeva, Maria P.; Kolomeisky, Anatoly B. (August 2018, Molecules)

   Protein-DNA interactions are critical for the successful functioning of all natural systems. The key role in these interactions is played by processes of protein search for specific sites on DNA. Although it has been studied for many years, only recently microscopic aspects of these processes became more clear. In this work, we present a review on current theoretical understanding of the molecular mechanisms of the protein target search. A comprehensive discrete-state stochastic method to explain the dynamics of the protein search phenomena is introduced and explained. Our theoretical approach utilizes a first-passage analysis and it takes into account the most relevant physical-chemical processes. It is able to describe many fascinating features of the protein search, including unusually high effective association rates, high selectivity and specificity, and the robustness in the presence of crowders and sequence heterogeneity. 

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3. How dynamic surface restructuring impacts intra-particle catalytic cooperativity

   https://doi.org/10.1063/5.0239455  

   Punia, Bhawakshi; Chaudhury, Srabanti; Kolomeisky, Anatoly (November 2024, The Journal of Chemical Physics)

   Recent experiments indicated that nanoparticles (NPs) might efficiently catalyze multiple chemical reactions, frequently exhibiting new phenomena. One of those surprising observations is intra-particle catalytic cooperativity, when the reactions at one active site can stimulate the reactions at spatially distant sites. Theoretical explanations of these phenomena have been presented, pointing out the important role of charged hole dynamics. However, the crucial feature of nanoparticles that can undergo dynamic structural surface rearrangements, potentially affecting the catalytic properties, has not yet been accounted for. We present a theoretical study of the effect of dynamic restructuring in NPs on intra-particle catalytic cooperativity. It is done by extending the original static discrete-state stochastic framework that quantitatively evaluates the catalytic communications. The dynamic restructuring is modeled as stochastic transitions between states with different dynamic properties of charged holes. Our analysis reveals that the communication times always decrease with increasing rates of dynamic restructuring, while the communication lengths exhibit a dynamic behavior that depends on how dynamic fluctuations affect migration and death rates of charged holes. Computer simulations fully support theoretical predictions. These findings provide important insights into the microscopic mechanisms of catalysis on single NPs, suggesting specific routes to rationally design more efficient catalytic systems. 

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4. Dynamics of chemical reactions on single nanocatalysts with heterogeneous active sites

   https://doi.org/10.1063/5.0137751  

   Chaudhury, Srabanti; Jangid, Pankaj; Kolomeisky, Anatoly B. (February 2023, The Journal of Chemical Physics)

   Modern chemical science and industries critically depend on the application of various catalytic methods. However, the underlying molecular mechanisms of these processes still remain not fully understood. Recent experimental advances that produced highly-efficient nanoparticle catalysts allowed researchers to obtain more quantitative descriptions, opening the way to clarify the microscopic picture of catalysis. Stimulated by these developments, we present a minimal theoretical model that investigates the effect of heterogeneity in catalytic processes at the single-particle level. Using a discrete-state stochastic framework that accounts for the most relevant chemical transitions, we explicitly evaluated the dynamics of chemical reactions on single heterogeneous nanocatalysts with different types of active sites. It is found that the degree of stochastic noise in nanoparticle catalytic systems depends on several factors that include the heterogeneity of catalytic efficiencies of active sites and distinctions between chemical mechanisms on different active sites. The proposed theoretical approach provides a single-molecule view of heterogeneous catalysis and also suggests possible quantitative routes to clarify some important molecular details of nanocatalysts. 

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5. Classical and nonclassical effects in surface hopping methodology for simulating coupled electronic-nuclear dynamics

   https://doi.org/10.1039/C9FD00042A  

   Martens, Craig C. (January 2019, Faraday Discussions)

   In this paper, we analyze the detailed quantum-classical behavior of two alternative approaches to simulating molecular dynamics with electronic transitions: the popular fewest switches surface hopping (FSSH) method, introduced by Tully in 1990 [Tully, \textit{J.~Chem.~Phys.}, 1990, \textbf{93}, 1061] and our recently developed quantum trajectory surface hopping (QTSH) method [Martens, \textit{J.~Phys.~Chem.~A}, 2019 \textbf{123}, 1110]. Both approaches employ an independent ensemble of trajectories that undergo stochastic transitions between electronic surfaces. The methods differ in their treatment of energy conservation, with FSSH imposing conservation of the classical kinetic plus potential energy by rescaling of the classical momenta when a surface hop occurs, while QTSH incorporates quantum forces throughout the dynamics which lead naturally to the conservation of the full quantum-classical energy. We investigate the population transfer and energy budget of the surface hopping methods for several simple model systems and compare with exact quantum result. In addition, the detailed dynamics of the trajectory ensembles in phase space are compared with the quantum evolution in the Wigner representation. Conclusions are drawn. 

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