# Artificial Photosynthesis: Is Computation Ready for the Challenge Ahead?
## 4 Protein/Surface Interactions  
The realization of artificial photosynthesis devices often takes place in an all-solid state device in which the protein is directly or indirectly interacting with a metal surface, to control the ET flow [5; 8; 9]. In addition, often the LHC is interacting with another small protein which act as shuttle of electrons (such as cytochrome), facilitating the ET process. Thus, protein adsorption on a surface is an interesting challenge for computation, as many different interactions are present, such as hydration, conformational changes and orientation of the protein to enhance the ET to/from the surface. These aspects become important when the design of novel bio-compatible applications is considered, like for biosensors [161], drug delivery systems [162] and bio-hybrid materials [163]. Experimental observations of protein absorption on a substrate have focused mainly on morphology [164], structural deformation of the protein upon adsorption [165], the effect of the surface chemistry [166] as well as kinetic of ET [167]. Yet, it is still difficult to assess the single-protein microscopic details from experimental observation, as they mainly consider thin layers or aggregate states. Computation plays once more an important role, considering MD simulations, capable to provide not only atomistic details on the adsorbed configurations, but also the time evolution of few hundreds of nanoseconds, even up to microseconds for small proteins [168]. The adsorption process commonly involves the presence of a solvent (normally water) and the vast amount of molecules makes systematic studies still challenging. A common approach [169] consists of considering first an implicit solvent to determine the most energetically favorable protein orientations on the surface, followed by relaxation of the whole system including the explicit solvent molecules. Despite the reliability of this approach, it is still difficult to describe the whole absorption process from computation [170] and often this first step is skipped, with more focus oriented toward the description of the properties of the already formed protein-substrate interface, such as the intensity and direction of ET. When immobilized on a surface, the ET occurs between the surface and redox center of the protein, giving rise to a transition from electronic to ionic charge transfer, as the electrons have to leave/enter the protein, causing the oxidation/reduction of the redox center, which is commonly observed by cyclic voltammetry measurements. This change in ionization of the protein is accompanied by changes in the environments (as it can be also charged, due to the ET process) and reduces the electrostatic barrier for subsequent steps by electrical screening [171]. If this process take places in a system in which the electrolyte is absent, or is not directly involved in the ET process, it is often termed as electron transport, and is generally considered in a solid state configuration [172]. As in this last process ions from the electrolyte are not present, charge balance is not possible and the whole process requires the electronic conduction across the whole protein to reach the electrode (or vice versa) which is defined as the electron flow through/across the protein which is in contact with the surface [173]. Computational approach to biomolecules adsorbed on surfaces can be strongly beneficial to experimentalists not only to unravel the ET mechanisms, but also to predict the behavior of biological systems with details that are not yet accessible by experimental techniques. To assess these processes at the interfaces, as for processes described in previous sections, a variety of computational methods and approaches can be considered, ranging from MD to sample the conformations of the protein adsorbed on the surface, to QM, QM/MM and ab-initio molecular dynamic (AIMD) to assess the ET and transport in both ground and excited states. For a comprehensive review on the strength and kind of different applicable methods, we refer to [174; 122].