Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry

While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.Chemistry and Chemical BiologyPhysic

Protein folding and the robustness of cells

The intricate intracellular infrastructure of all known life forms is based on proteins. The folded shape of a protein determines both the protein’s function and the set of molecules it will bind to. This tight coupling between a protein’s function and its interconnections in the molecular interaction network has consequences for the molecular course of evolution. It is also counter to human engineering approaches. Here we report on a simulation study investigating the impact of random errors in an abstract metabolic network of 500 enzymes. Tight coupling between function and interconnectivity of nodes is compared to the case where these two properties are independent. Our results show that the model system under consideration is more robust if function and interconnection are intertwined. These findings are discussed in the context of nanosystems engineering

Simple one pot preparation of chemical hydrogels from cellulose dissolved in cold LiOH/urea

In this work, non-derivatized cellulose pulp was dissolved in a cold alkali solution (LiOH/urea) and chemically cross-linked with methylenebisacrylamide (MBA) to form a robust hydrogel with superior water absorption properties. Different cellulose concentrations (i.e., 2, 3 and 4 wt%) and MBA/glucose molar ratios (i.e., 0.26, 0.53 and 1.05) were tested. The cellulose hydrogel cured at 60 °C for 30 min, with a MBA/glucose molar ratio of 1.05, exhibited the highest water swelling capacity absorbing ca. 220 g H2O/g dry hydrogel. Moreover, the data suggest that the cross-linking occurs via a basic Michael addition mechanism. This innovative procedure based on the direct dissolution of unmodified cellulose in LiOH/urea followed by MBA cross-linking provides a simple and fast approach to prepare chemically cross-linked non-derivatized high-molecular-weight cellulose hydrogels with superior water uptake capacity.Portuguese Foundation for Science and Technology, FCT, via the projects PTDC/AGR-TEC/4814/2014, PTDC/ASP-SIL/30619/2017 and UIDB/05183/2020, and the research grant IF/01005/2014.info:eu-repo/semantics/publishedVersio

Environmental boundary conditions for the origin of life converge to an organo-sulfur metabolism

Published in final edited form as: Nat Ecol Evol. 2019 December ; 3(12): 1715–1724. doi:10.1038/s41559-019-1018-8.It has been suggested that a deep memory of early life is hidden in the architecture of metabolic networks, whose reactions could have been catalyzed by small molecules or minerals before genetically encoded enzymes. A major challenge in unravelling these early steps is assessing the plausibility of a connected, thermodynamically consistent proto-metabolism under different geochemical conditions, which are still surrounded by high uncertainty. Here we combine network-based algorithms with physico-chemical constraints on chemical reaction networks to systematically show how different combinations of parameters (temperature, pH, redox potential and availability of molecular precursors) could have affected the evolution of a proto-metabolism. Our analysis of possible trajectories indicates that a subset of boundary conditions converges to an organo-sulfur-based proto-metabolic network fuelled by a thioester- and redox-driven variant of the reductive tricarboxylic acid cycle that is capable of producing lipids and keto acids. Surprisingly, environmental sources of fixed nitrogen and low-potential electron donors are not necessary for the earliest phases of biochemical evolution. We use one of these networks to build a steady-state dynamical metabolic model of a protocell, and find that different combinations of carbon sources and electron donors can support the continuous production of a minimal ancient 'biomass' composed of putative early biopolymers and fatty acids.80NSSC17K0295 - Intramural NASA; 80NSSC17K0296 - Intramural NASA; T32 GM100842 - NIGMS NIH HHSAccepted manuscrip

Casting Polymer Nets to Optimize Noisy Molecular Codes

Life relies on the efficient performance of molecular codes, which relate symbols and meanings via error-prone molecular recognition. We describe how optimizing a code to withstand the impact of molecular recognition noise may be approximated by the statistics of a two-dimensional network made of polymers. The noisy code is defined by partitioning the space of symbols into regions according to their meanings. The "polymers" are the boundaries between these regions and their statistics defines the cost and the quality of the noisy code. When the parameters that control the cost-quality balance are varied, the polymer network undergoes a first-order transition, where the number of encoded meanings rises discontinuously. Effects of population dynamics on the evolution of molecular codes are discussed.Comment: PNAS 200

Modelling and simulation framework for reactive transport of organic contaminants in bed-sediments using a pure java object - oriented paradigm

Numerical modelling and simulation of organic contaminant reactive transport in the environment is being increasingly relied upon for a wide range of tasks associated with risk-based decision-making, such as prediction of contaminant profiles, optimisation of remediation methods, and monitoring of changes resulting from an implemented remediation scheme. The lack of integration of multiple mechanistic models to a single modelling framework, however, has prevented the field of reactive transport modelling in bed-sediments from developing a cohesive understanding of contaminant fate and behaviour in the aquatic sediment environment. This paper will investigate the problems involved in the model integration process, discuss modelling and software development approaches, and present preliminary results from use of CORETRANS, a predictive modelling framework that simulates 1-dimensional organic contaminant reaction and transport in bed-sediments

Structural characterization of the D290V mutation site in hnRNPA2 low-complexity-domain polymers.

Human genetic studies have given evidence of familial, disease-causing mutations in the analogous amino acid residue shared by three related RNA binding proteins causative of three neurological diseases. Alteration of aspartic acid residue 290 of hnRNPA2 to valine is believed to predispose patients to multisystem proteinopathy. Mutation of aspartic acid 262 of hnRNPA1 to either valine or asparagine has been linked to either amyotrophic lateral sclerosis or multisystem proteinopathy. Mutation of aspartic acid 378 of hnRNPDL to either asparagine or histidine has been associated with limb girdle muscular dystrophy. All three of these aspartic acid residues map to evolutionarily conserved regions of low-complexity (LC) sequence that may function in states of either intrinsic disorder or labile self-association. Here, we present a combination of solid-state NMR spectroscopy with segmental isotope labeling and electron microscopy on the LC domain of the hnRNPA2 protein. We show that, for both the wild-type protein and the aspartic acid 290-to-valine mutant, labile polymers are formed in which the LC domain associates into an in-register cross-β conformation. Aspartic acid 290 is shown to be charged at physiological pH and immobilized within the polymer core. Polymers of the aspartic acid 290-to-valine mutant are thermodynamically more stable than wild-type polymers. These observations give evidence that removal of destabilizing electrostatic interactions may be responsible for the increased propensity of the mutated LC domains to self-associate in disease-causing conformations