# Artificial Photosynthesis: Is Computation Ready for the Challenge Ahead?
## 1 Introduction
As a result of the sequence of reactions that take place within the photosynthetic process, the plant or alga converts solar energy into chemical energy. The key to success relies on: (1) Physical separation of the light collection (protein antenna) and the catalytic center; (2) absorption of two photons for generation of sufficient potential for water oxidation; (3) spatial separation of oxidative and reductive chemistry and relevant products; (4) multielectron character of water oxidation and proton/CO\({}_{2}\) reduction; (5) efficient management of proton-coupled electron transfer for both catalytic reactions, and last but not least (6), use of self-assembled and self-renewable molecular catalysts embedded in responsive matrix [13]. Natural photosystems operate as nearly perfect photoelectrical/photovoltaic molecular nanomachines, exhibiting internal quantum efficiency close to 100% [12]. When trying to replicate this complex process in a man-made environment, where the only components are solar light, a photocatalyst, CO\({}_{2}\) and water as reducing agent, the process is named artificial photosynthesis. In this way, mimicking the natural process, the light-driven conversion of water and CO\({}_{2}\) leads to the formation of chemical fuels. The fabrication of such a full bioelectrode has been reported very recently [8]. It consists of highly-oriented PSI on a single layer graphene electrode involving a \"sandwich\" stacking structure with different biological and organic molecular linkers. To assure a high orientation of the PSI, the protein was wired to the functionalized graphene surface and genetically engineered to incorporate affinity tags (or metal-binding peptides) into their structure. Another strategy is to create intermolecular interaction between the light harvesting protein (LHP) and natural electron donors, such as cytochrome \(c\)553, which promotes the electron transfer to the electrode and can be used as the biological conductive interface between graphene and LHP. Yet, with this strategy an additional degree of complexity is added, since a specific orientations of the cytochrome over the electrode needs to be additionally provided. Despite the great experimental effort in building such complex devices, many questions are still unanswered. In particular, (i) how to effectively harvest light with small harvesting proteins and transfer the formed electrons to the redox center; (ii) how to maximize the direct electron transfer (DET) from the protein to the metal electrode, and consequently (iii) suppress charge recombination; and (iv) how to direct the charge flow to the selected targets (from material to protein or vice versa) to maximize the efficiency of the whole device. As the process of building the full system is lengthy due to the presence of different building blocks and the interfacing between protein and materials is not a trivial task, computation can indeed make a change in the approach for the rational design of such devices. Moreover, the availability of highly resolved structures from the field of structural biology, from X-ray crystallography, and more recently from cryo-electron microscopy (cryo-EM) allowed computation to firmly step into this field of research. As a consequence, using different computational methods in a multiscale fashion, it might be possible to reveal the mechanisms underneath these pressing questions and to predict the DET mechanism. This mission is extremely challenging, not only due to the presence of the biological light harvesting protein, but also due to the questions which the creation of such interfaces bring. In particular, three key aspects and questions can be defined: (i) How to properly describe the light harvesting process; (ii) how to maximize the charge separation at the interface, and (iii) how these separated charges can be collected at the reactive center to perform the redox reaction for the formation of solar fuels.