A coarse-grained model for synergistic action of multiple enzymes on cellulose

Background Degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, β-glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates. Results We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose. Conclusions Our coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis

HIV-1 and SARS-CoV-2: Patterns in the evolution of two pandemic pathogens

Humanity is currently facing the challenge of two devastating pandemics caused by two very different RNA viruses: HIV-1, which has been with us for decades, and SARS-CoV-2, which has swept the world in the course of a single year. The same evolutionary strategies that drive HIV-1 evolution are at play in SARS-CoV-2. Single nucleotide mutations, multi-base insertions and deletions, recombination, and variation in surface glycans all generate the variability that, guided by natural selection, enables both HIV-1’s extraordinary diversity and SARS-CoV-2’s slower pace of mutation accumulation. Even though SARS-CoV-2 diversity is more limited, recently emergent SARS-CoV-2 variants carry Spike mutations that have important phenotypic consequences in terms of both antibody resistance and enhanced infectivity. We review and compare how these mutational patterns manifest in these two distinct viruses to provide the variability that fuels their evolution by natural selection.Fil: Fischer, Will. Los Alamos National Laboratory; Estados Unidos. New Mexico Consortium; MéxicoFil: Giorgi, Elena E.. New Mexico Consortium; México. Los Alamos National Laboratory; Estados UnidosFil: Chakraborty, Srirupa. Center For Nonlinear Studies; Estados Unidos. Los Alamos National Laboratory; Estados UnidosFil: Nguyen, Kien. Los Alamos National Laboratory; Estados UnidosFil: Bhattacharya, Tanmoy. Los Alamos National Laboratory; Estados UnidosFil: Theiler, James. Los Alamos National Laboratory; Estados UnidosFil: Goloboff, Pablo Augusto. American Museum of Natural History; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico - Tucumán. Unidad Ejecutora Lillo; ArgentinaFil: Yoon, Hyejin. Los Alamos National Laboratory; Estados UnidosFil: Abfalterer, Werner. Los Alamos National Laboratory; Estados UnidosFil: Foley, Brian T.. Los Alamos National Laboratory; Estados UnidosFil: Tegally, Houriiyah. University Of Kwazulu-natal; SudáfricaFil: San, James Emmanuel. University Of Kwazulu-natal; SudáfricaFil: de Oliveira, Tulio. University of KwaZulu-Natal; SudáfricaFil: Gnanakaran, Sandrasegaram. Los Alamos National Laboratory; Estados UnidosFil: Korber, Bette. Los Alamos National Laboratory; Estados Unidos. New Mexico Consortium; Méxic

Role of solvent on chemical reaction dynamics of small molecules

For this thesis work, equilibrium (EMD) and non-equilibrium (NEMD) molecular dynamics simulations have been used to determine the underlying structural and dynamical processes in solution phase reactions involving diatomic solutes. This characterization is necessary to predict solvent effects on process involving larger molecules. The impulsive photodissociation of mercuric iodide in ethanol, HgI2 → HgI + I, produces highly vibrationally excited HgI with narrow bond length distributions. This has been used as a prototype to study wavepacket motion, vibrational relaxation and rotational dynamics. The vibrational energy decay rate of HgI obtained from the EMD simulations is in quantitative agreement with the experimentally determined value. Energy dissipation is mainly facilitated by the Lennard-Jones force fluctuations. The NEMD simulations support the experimental observation of the vibrational wavepacket motion on the rotational dynamics of the HgI which strongly depends on the variations in the partial charges of HgI with internuclear distance. Another system considered in this thesis work, the aqueous hypochlorite ion, undergoes light induced charge shifting from the negatively charged O atom (ClO−) to the Cl atom (OCl−). The charge shifting event, ClO− → OCl− , is used as a prototype to study solvation dynamics. The NEMD simulations predict that solvent response occurs on two timescales which are close to those measured by experiments on the same system. The rapid and slower time components have been associated with the destruction of solvent structure around the O atom and the creation of a new structure around the Cl atom, respectively. The applicability of linear response to this process is also examined with an eye toward possible future experiments. The curvatures of the harmonic free energy surfaces of ClO− and OCl − are not the same indicating that there is nonlinearity in the solvation dynamics caused by the asymmetry of the system: The average solvent structures around the two forms are not interchangeable. This study has shown the importance of incorporating the change in effective atomic radii during an electronic transition, if necessary with a corresponding modification of Lennard-Jones potential parameters

A coarse-grained model for synergistic action of multiple enzymes on cellulose

Abstract Background Degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, β-glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates. Results We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose. Conclusions Our coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.</p

Visualization of the HIV-1 Env glycan shield across scales

The dense array of N-linked glycans on the HIV-1 envelope glycoprotein (Env), known as the "glycan shield," is a key determinant of immunogenicity, yet intrinsic heterogeneity confounds typical structure-function analysis. Here, we present an integrated approach of single-particle electron cryomicroscopy (cryo-EM), computational modeling, and site-specific mass spectrometry (MS) to probe glycan shield structure and behavior at multiple levels. We found that dynamics lead to an extensive network of interglycan interactions that drive the formation of higher-order structure within the glycan shield. This structure defines diffuse boundaries between buried and exposed protein surface and creates a mapping of potentially immunogenic sites on Env. Analysis of Env expressed in different cell lines revealed how cryo-EM can detect subtle changes in glycan occupancy, composition, and dynamics that impact glycan shield structure and epitope accessibility. Importantly, this identified unforeseen changes in the glycan shield of Env obtained from expression in the same cell line used for vaccine production. Finally, by capturing the enzymatic deglycosylation of Env in a time-resolved manner, we found that highly connected glycan clusters are resistant to digestion and help stabilize the prefusion trimer, suggesting the glycan shield may function beyond immune evasion

High throughput analysis of B cell dynamics and neutralizing antibody development during immunization with a novel clade C HIV-1 envelope.

A protective HIV-1 vaccine has been hampered by a limited understanding of how B cells acquire neutralizing activity. Our previous vaccines expressing two different HIV-1 envelopes elicited robust antigen specific serum IgG titers in 20 rhesus macaques; yet serum from only two animals neutralized the autologous virus. Here, we used high throughput immunoglobulin receptor and single cell RNA sequencing to characterize the overall expansion, recall, and maturation of antigen specific B cells longitudinally over 90 weeks. Diversification and expansion of many B cell clonotypes occurred broadly in the absence of serum neutralization. However, in one animal that developed neutralization, two neutralizing B cell clonotypes arose from the same immunoglobulin germline and were tracked longitudinally. Early antibody variants with high identity to germline neutralized the autologous virus while later variants acquired somatic hypermutation and increased neutralization potency. The early engagement of precursors capable of neutralization with little to no SHM followed by prolonged affinity maturation allowed the two neutralizing lineages to successfully persist despite many other antigen specific B cells. The findings provide new insight into B cells responding to HIV-1 envelope during heterologous prime and boost immunization in rhesus macaques and the development of selected autologous neutralizing antibody lineages

HIV-1 and SARS-CoV-2: Patterns in the evolution of two pandemic pathogens.

Humanity is currently facing the challenge of two devastating pandemics caused by two very different RNA viruses: HIV-1, which has been with us for decades, and SARS-CoV-2, which has swept the world in the course of a single year. The same evolutionary strategies that drive HIV-1 evolution are at play in SARS-CoV-2. Single nucleotide mutations, multi-base insertions and deletions, recombination, and variation in surface glycans all generate the variability that, guided by natural selection, enables both HIV-1's extraordinary diversity and SARS-CoV-2's slower pace of mutation accumulation. Even though SARS-CoV-2 diversity is more limited, recently emergent SARS-CoV-2 variants carry Spike mutations that have important phenotypic consequences in terms of both antibody resistance and enhanced infectivity. We review and compare how these mutational patterns manifest in these two distinct viruses to provide the variability that fuels their evolution by natural selection