Prebiotic chemistry and origins of life research with atomistic computer simulations

On the role of α-alumina in the origin of life: Surface-driven assembly of amino acids

We investigate the hypothesis that mineral/water interfaces played a crucial catalytic role in peptide formation by promoting the self-assembly of amino acids. Using classical molecular dynamics simulations, we demonstrate that the α-alumina(0001) surface exhibits an affinity of 4 kBT for individual glycine or GG dipeptide molecules due to hydrogen bonds. In simulations with multiple glycine molecules, surface-bound glycine enhances further adsorption, leading to the formation of long chains connected by hydrogen bonds between the carboxyl and amine groups of glycine molecules. We find that the likelihood of observing chains longer than 10 glycine units increases by at least five orders of magnitude at the surface compared to the bulk. This surface-driven assembly is primarily due to local high density and alignment with the alumina surface pattern. Together, these results propose a model for how mineral surfaces can induce configuration-specific assembly of amino acids, thereby promoting condensation reactions.

Flipons and the origin of the genetic code

This paper is focused on the origins of the contemporary genetic code. A novel explanation is proposed for how the mapping of nucleotides in DNA to amino acids in proteins arose that derives from repeat nucleotide sequences able to form alternative nucleic acid structures (ANS), such as the unusual left-handed Z-DNA, triplex, G-quadruplex and I-motif conformations. The scheme identifies sequence-specific contacts that map ANS repeats to dipeptide polymers (DPS). The stereochemistry required naturally evolves into a non-overlapping, triplet code for mapping nucleotides to amino acids. The ANS/DPS complexes form a simple, genetically transmitted, self-templating, autonomously replicating collection of 'tinkers' for Nature to evolve. Tinkers have agency and promote their own synthesis by forming catalytic scaffolds with metals, further enhancing their capabilities. Initial support for the model is provided by computational models built with AlphaFold3. The predictions made are properly falsifiable with the currently available methodology.

Synthesis and Stability of Biomolecules in C-H-O-N Fluids under Earth's Upper Mantle Conditions

How life started on Earth is an unsolved mystery. There are various hypotheses for the location ranging from outer space to the seafloor, subseafloor, or potentially deeper. Here, we applied extensive ab initio molecular dynamics simulations to study chemical reactions between NH3, H2O, H2, and CO at pressures (P) and temperatures (T) approximating the conditions of Earth's upper mantle (i.e., 10-13 GPa, 1000-1400 K). Contrary to the previous assumptions that large organic molecules might readily disintegrate in aqueous solutions at extreme P-T conditions, we found that many organic compounds formed without any catalysts and persisted in C-H-O-N fluids under these extreme conditions, including glycine, ribose, urea, and uracil-like molecules. Particularly, our free-energy calculations showed that the C-N bond is thermodynamically stable at 10 GPa and 1400 K. Moreover, while the pyranose (six-membered ring) form of ribose is more stable than the furanose (five-membered ring) form at ambient conditions, we found that the formation of the five-membered-ring form of ribose is thermodynamically more favored at extreme conditions, which is consistent with the exclusive incorporation of β-d-ribofuranose in RNA. We have uncovered a previously unexplored pathway through which the crucial biomolecules could be abiotically synthesized from geofluids in the deep interior of Earth and other planets, and these formed biomolecules could potentially contribute to the early stage of the emergence of life.

How the addition of atomic hydrogen to a multiple bond can be catalyzed by water molecules

Observational data show complex organic molecules in the interstellar medium (ISM). Hydrogenation of small unsaturated carbon double bond could be one way for molecular complexification. It is important to understand how such reactivity occurs in the very cold and low-pressure ISM. Yet, there is water ice in the ISM, either as grain or as mantle around grains. Therefore, the addition of atomic hydrogen on double-bonded carbon in a series of seven molecules have been studied and it was found that water catalyzes this reaction. The origin of the catalysis is a weak charge transfer between the π MO of the unsaturated molecule and H atom, allowing a stabilizing interaction with H2O. This mechanism is rationalized using the non-covalent interaction and the quantum theory of atoms in molecules approaches.

Efficient machine learning approach for accurate free-energy profiles and kinetic rates

The computational exploration of reactive processes is challenging due to the requirement of thorough sampling across the free energy landscape using accurate ab initio methods. To address these constraints, machine learning potentials are employed, yet their training for this kind of problem is still a laborious and tedious task. In this study, we present an efficient approach to train these potentials by cleverly using a single batch of unbiased trajectories that avoid the pitfalls of trajectories artificially biased along a suboptimal collective variable. This strategy, when integrated with current enhanced sampling techniques, allows to obtain free energy profiles and kinetic rates of ab initio quality, yet dramatically reducing the computational cost.

A New Route to the Prebiotic Synthesis of Glycine via Ab Initio-Based Machine Learning Calculations

In this work, we study the synthesis of glycine, the simplest amino acid, using ab initio molecular dynamics and enhanced sampling techniques to explore and quantify novel potential pathways. Our protocol integrates state-of-the-art machine learning approaches, allowing us to sample relevant chemical spaces more efficiently. We discover a novel "oxyglycolate path", distinct from the "standard" Strecker mechanism, identify new intermediates, and provide a full thermodynamic characterization of all reaction steps. This alternative pathway aligns better with meteoritic and experimental observations, paving the way for further investigations. Integrating quantum accuracy and machine learning in prebiotic chemistry represents a methodological milestone advancing the exploration of life's prebiotic origins.

Uptake and reactivity of NO2 on the hydroxylated silica surface: A source of reactive oxygen species

We report state-of-the-art first-principles molecular dynamics results on the heterogeneous chemical uptake of NO2, a major anthropogenic pollutant, on the dry and wet hydroxylated surface of α-quartz, which is a significant component of silica-based catalysts and atmospheric dust aerosols. Our investigation spotlights an unexpected chemical pathway by which NO2 (i) can be adsorbed as HONO by deprotonation of interfacial silanols (i.e., -Si-OH group) on silica, (ii) can be barrierless converted to nitric acid, and (iii) can finally dissociated to surface bounded NO and hydroxyl gas phase radicals. This chemical pathway does not invoke any previously experimentally postulated NO2 dimerization, dimerization that is less likely to occur at low NO2 concentrations. Moreover, water significantly catalyzes the HONO formation and the dissociation of nitric acid into surface-bounded NO and OH radicals, while visible light adsorption can further promote these chemical transformations. This work highlights how water-restricted solvation regimes on common mineral substrates are likely to be a source of reactive oxygen species, and it offers a theoretical framework for further and desirable experimental efforts, aiming to better constrain trace gases/mineral interactions at different relative humidity conditions.

Impact of M Dwarfs Ultraviolet Radiation on Prebiotic Chemistry: The Case of Adenine

To date, several exoplanets have been found to orbit within the habitable zone of main sequence M stars (M dwarfs). These stars exhibit different levels of chromospheric activity that produces ultraviolet (UV) radiation. UV may be harmful to life, but it can also trigger reactions of prebiotic importance on the surface of a potentially habitable planet (PHP). We created a code to obtain the adenine yield for a known adenine synthesis route from diaminomaleonitrile (DAMN). We used computational methods to calculate the reaction coefficient rates (photolysis rate J and rate constant K) for the intermediate molecules DAMN, diaminofumaronitrile (DAFN), and 4-aminoimidazole-5-carbonitrile (AICN) of the adenine synthesis route. We used stellar UV sources and a mercury lamp to compare the theoretical results with experiments performed with lamps. The surface UV flux of planets in the habitable zone of two active M dwarfs (Proxima Centauri and AD Leonis) and the prebiotic Earth was calculated using the photochemical model ATMOS, considering a CO₂-N₂-H₂O atmosphere. We obtained UV absorption coefficients for DAMN and DAFN and thermodynamic parameters that are useful for prebiotic chemistry studies. According to our results, experiments using UV lamps may underestimate the photolysis production of molecules of prebiotic importance. Our results indicate that photolysis reactions are fast with a yield of 50% of AICN in 10 s for the young Sun and ∼1 h for Proxima Centauri b. Planets around active M dwarfs may provide the most favorable environment for UV-mediated production of compounds relevant to the origins of life. The kinetic reaction AICN + HCN  adenine is the bottleneck of the pathway with reaction rates <10^-22 L/(mol·s).

Formation and evolution of C-C, C-O, C[double bond, length as m-dash]O and C-N bonds in chemical reactions of prebiotic interest

A series of prebiotic chemical reactions yielding the precursor building blocks of amino acids, proteins and carbohydrates, starting solely from HCN and water is studied here. We closely follow the formation and evolution of the pivotal C-C, C-O, C[double bond, length as m-dash]O, and C-N bonds, which dictate the chemistry of the molecules of life. In many cases, formation of these bonds is set in motion by proton transfers in which individual water molecules act as catalysts so that water atoms end up in the products. Our results indicate that the prebiotic formation of carbon dioxide, formaldehyde, formic acid, formaldimine, glycolaldehyde, glycine, glycolonitrile, and oxazole derivatives, among others, are best described as highly nonsynchronous concerted single step processes. Nonetheless, for all reactions involving double proton transfer, the formation and breaking of O-H bonds around a particular O atom occur in a synchronous fashion, apparently independently from other primitive processes. For the most part, the first process to initiate seems to be the double proton transfer in the reactions where they are present, then bond breaking/formation around the reactive carbon in the carbonyl group and finally rupture of the C-N bonds in the appropriate cases, which are the most reluctant to break. Remarkably, within the limitations of our non-dynamical computational model, the wide ranges of temperature and pressure in which these reactions occur, downplay the problematic determination of the exact constraints on the early Earth.

Combining Machine Learning Approaches and Accurate Ab Initio Enhanced Sampling Methods for Prebiotic Chemical Reactions in Solution

The study of the thermodynamics, kinetics, and microscopic mechanisms of chemical reactions in solution requires the use of advanced free-energy methods for predictions to be quantitative. This task is however a formidable one for atomistic simulation methods, as the cost of quantum-based ab initio approaches, to obtain statistically meaningful samplings of the relevant chemical spaces and networks, becomes exceedingly heavy. In this work, we critically assess the optimal structure and minimal size of an ab initio training set able to lead to accurate free-energy profiles sampled with neural network potentials. The results allow one to propose an ab initio protocol where the ad hoc inclusion of a machine-learning (ML)-based task can significantly increase the computational efficiency, while keeping the ab initio accuracy and, at the same time, avoiding some of the notorious extrapolation risks in typical atomistic ML approaches. We focus on two representative, and computationally challenging, reaction steps of the classic Strecker-cyanohydrin mechanism for glycine synthesis in water solution, where the main precursors are formaldehyde and hydrogen cyanide. We demonstrate that indistinguishable ab initio quality results are obtained, thanks to the ML subprotocol, at about 1 order of magnitude less of computational load.

Protocells: Milestones and Recent Advances

The origin of life is still one of humankind's great mysteries. At the transition between nonliving and living matter, protocells, initially featureless aggregates of abiotic matter, gain the structure and functions necessary to fulfill the criteria of life. Research addressing protocells as a central element in this transition is diverse and increasingly interdisciplinary. The authors review current protocell concepts and research directions, address milestones, challenges and existing hypotheses in the context of conditions on the early Earth, and provide a concise overview of current protocell research methods.

Automated Exploration of Prebiotic Chemical Reaction Space: Progress and Perspectives

Prebiotic chemistry often involves the study of complex systems of chemical reactions that form large networks with a large number of diverse species. Such complex systems may have given rise to emergent phenomena that ultimately led to the origin of life on Earth. The environmental conditions and processes involved in this emergence may not be fully recapitulable, making it difficult for experimentalists to study prebiotic systems in laboratory simulations. Computational chemistry offers efficient ways to study such chemical systems and identify the ones most likely to display complex properties associated with life. Here, we review tools and techniques for modelling prebiotic chemical reaction networks and outline possible ways to identify self-replicating features that are central to many origin-of-life models.

Step by Step Strecker Amino Acid Synthesis from Ab Initio Prebiotic Chemistry

The amino acids synthesis from elementary precursors in abiotic conditions is traditionally described according to the Strecker reaction, thoroughly invoked to justify the observation of amino acids in extraterrestrial samples and their emergence in the primordial Earth. To this day, however, a quantitative microscopic description of the mechanism, thermodynamics, and kinetics of the multistep Strecker reaction is still lacking. In the present work we tackle this study by adopting a state-of-the-art ab initio computational approach, combining an efficient scheme of exploration of the relevant chemical networks with a rigorous determination of the underlying free energy and transition states. We determine the step-by-step chemical pathway from "Strecker precursors" to glycine in solution and calculate the corresponding full free energy landscape. Our results agree well with the scarce available experimental data and complete them, thus providing the first end-to-end study of this complex reaction, a crucial bottleneck for the emergence of life.

Prebiotic Peptide Bond Formation Through Amino Acid Phosphorylation. Insights from Quantum Chemical Simulations

Condensation reactions between biomolecular building blocks are the main synthetic channels to build biopolymers. However, under highly diluted prebiotic conditions, condensations are thermodynamically hampered since they release water. Moreover, these reactions are also kinetically hindered as, in the absence of any catalyst, they present high activation energies. In living organisms, in the formation of peptides by condensation of amino acids, this issue is overcome by the participation of adenosine triphosphate (ATP), in which, previous to the condensation, phosphorylation of one of the reactants is carried out to convert it as an activated intermediate. In this work, we present for the first time results based on density functional theory (DFT) calculations on the peptide bond formation between two glycine (Gly) molecules adopting this phosphorylation-based mechanism considering a prebiotic context. Here, ATP has been modeled by a triphosphate (TP) component, and different scenarios have been considered: (i) gas-phase conditions, (ii) in the presence of a Mg²⁺ ion available within the layer of clays, and (iii) in the presence of a Mg²⁺ ion in watery environments. For all of them, the free energy profiles have been fully characterized. Energetics derived from the quantum chemical calculations indicate that none of the processes seem to be feasible in the prebiotic context. In scenarios (i) and (ii), the reactions are inhibited due to unfavorable thermodynamics associated with the formation of high energy intermediates, while in scenario (iii), the reaction is inhibited due to the high free energy barrier associated with the condensation reactions. As a final consideration, the role of clays in this TP-mediated peptide bond formation route is advocated, since the interaction of the phosphorylated intermediate with the internal clay surfaces could well favor the reaction free energies.

Role of Mineral Surfaces in Prebiotic Chemical Evolution. In Silico Quantum Mechanical Studies

There is a consensus that the interaction of organic molecules with the surfaces of naturally-occurring minerals might have played a crucial role in chemical evolution and complexification in a prebiotic era. The hurdle of an overly diluted primordial soup occurring in the free ocean may have been overcome by the adsorption and concentration of relevant molecules on the surface of abundant minerals at the sea shore. Specific organic⁻mineral interactions could, at the same time, organize adsorbed molecules in well-defined orientations and activate them toward chemical reactions, bringing to an increase in chemical complexity. As experimental approaches cannot easily provide details at atomic resolution, the role of in silico computer simulations may fill that gap by providing structures and reactive energy profiles at the organic⁻mineral interface regions. Accordingly, numerous computational studies devoted to prebiotic chemical evolution induced by organic⁻mineral interactions have been proposed. The present article aims at reviewing recent in silico works, mainly focusing on prebiotic processes occurring on the mineral surfaces of clays, iron sulfides, titanium dioxide, and silica and silicates simulated through quantum mechanical methods based on the density functional theory (DFT). The DFT is the most accurate way in which chemists may address the behavior of the molecular world through large models mimicking chemical complexity. A perspective on possible future scenarios of research using in silico techniques is finally proposed.