Precise knowledge of chemical composition and atomic structure of functional nanosized systems, such as metal clusters stabilized by an organic molecular layer, allows for detailed computational work to investigate structure-property relations. Here, we discuss selected recent examples of computational work that has advanced understanding of how these clusters work in catalysis, how they interact with biological systems, and how they can make self-assembled, macroscopic materials. A growing challenge is to develop effective new simulation methods that take into account the cluster-environment interactions. These new hybrid methods are likely to contain components from electronic structure theory combined with machine learning algorithms for accelerated evaluations of atom-atom interactions.Monolayer-protected metal clusters (MPCs) are hybrid metal nanoparticles consisting of a metal core and a protecting layer of organic ligand molecules. They have a precise mass and chemical composition, and in many cases their structure is known to atomic precision 1 . During the last decade, experimental and computational investigations of MPCs have burgeoned, yielding ample novel information about physical, chemical, catalytic, optical, biological and medical properties of these atomically defined nanomaterials 1 . The often precise knowledge of the MPCs' atomic structure creates an excellent starting point to use various atomistic simulation tools to understand their structure-property relations. However, MPCs can have complex interactions with their environments, which creates challenges to simulations due to needed length scales, time scales or the need to describe the complex chemical interactions properly on an equal footing.As Fig. 1 illustrates, there are currently several methods that can be used for computational investigations of MPCs' physical and chemical properties. Quantum-chemical (QC) methods are based on optimizing the total many-body wave function of the quantum system (a function of 3N components for N atoms). They can conveniently deal with small molecules with great chemical accuracy and have traditionally provided benchmark results for strengths of various chemical bonds. However, their application area is still limited to small systems on the order of 10 metal atoms. Density functional theory (DFT) is a major workhorse dealing with MPCs' electronic structure, optical properties and reactions. DFT uses the total electron density of the system (a function of 3 components) as the basic physical variable, reducing the complexity of the ground-state problem immensely as compared to QC methods. With modern massively