One of the critical aspects when developing transferable parameters is conformational sampling. One approach is to sample structures from classical molecular dynamics (MD) trajectories. Obtaining a sufficient sampling of the conformations of all the standard amino acids through MD simulations is non-trivial. Moreover, the choice of force field and simulation conditions may introduce some unwanted bias into the parameters. Instead, we use an alternative approach based on conformations sampled from a rotamer library. Several rotamer libraries have been developed, including backbone-dependent ones, facilitated by the abundance of high-quality protein crystal structures. These effectively report the most commonly occurring conformations of amino acids in typical protein environments and thus represent a very focused and efficient way of selecting structures to include in the fitting procedure. Similar approaches of sampling across a set of conformers have been applied in other studies. The main difference being that we here use a comparatively large set of conformations sampled from the smoothed backbone-dependent rotamer library by Shapovalov and Dunbrack. After having selected the set of structures to be used in the parameter derivation, there is still the matter of selecting the method with which to derive the parameters. Numerous approaches have been reported in the literature (see e.g. Ref. 22 for an overview). Our aim is to be able to reproduce the electric potential (EP) as accurately as possible using only atom-centered point charges and isotropic polarizabilities. Based on preliminary testing, we found that EP fitting gave the best performance, and, since it is also rather flexible, it is relatively easy to introduce constraints, e.g. to ensure integer charge within groups of atoms and to equalize parameters on chemically equivalent atoms. Such constraints are useful in the parameterization of amino-acid residues, which are part of a larger protein structure, and thus require capping groups (typically acetyl and N-methyl groups). Moreover, we can fit simultaneously to the EP across all conformers, as has been explored previously. The reason for doing this is two-fold. First, we expect an improved transferability of the parameters by including a large set of structures that contains conformations representative of those commonly occurring in native proteins. Second, we seek to combat the well-known problem of redundancy in EP fitting. Addressing the latter point by including a large number of structures is most likely not sufficient to resolve the problem of ill-conditioned EP fits, so we also reduce the number of free parameters by employing non-redundant fitting and by imposing additional constraints on the parameters.