## 1 Introduction  
Mosquito-transmitted diseases are the main sources of human illness and death in numerous countries worldwide. Malaria is the most devastating mosquito-borne disease. It is caused by _Plasmodium_ protozoan parasites following the infective bites of females of the _Anopheles_ mosquito [1]. In 2021, there were an estimated 247 million malaria cases in 84 endemic countries and 619,000 malaria deaths [2]. Dengue is a viral infection transmitted to humans through the bite of infected _Aedes_ mosquitoes. It is the most important and fastest-spreading mosquito-borne viral disease worldwide. Roughly half of the world's population currently lives in areas that are environmentally suitable for dengue transmission [3, 4]. Other viral diseases transmitted by mosquitoes include chikungunya, Zika, yellow fever, West Nile fever, Japanese encephalitis, and Rift Valley fever [5]. Different vector control methods are used to stop the transmission of mosquito-borne diseases and to limit the nuisance caused by these dipterans. These methods are based on two main complementary strategies. The first one consists of a reduction in mosquito populations in the environment by using physical, mechanical, biological, genetic, and/or biocidal methods [6, 7]. The second strategy relies on the use of personal protections via different devices, among which the repellents occupy a key place because they provide immediate, localized, and personal protection against host-seeking mosquitoes [8]. DEET (\(N\),\(N\)-diethyl-\(m\)-tolumamide) is the most widely used repellent worldwide despite some drawbacks [8; 9]. Faced with the limited number of other skin-applied repellents approved by regulatory authorities which are commercially available (e.g., IR3535, picardin), there is a need to identify original structures with new mechanisms of action. Indeed, the more mosquito repellents available, the more we limit the emergence of resistance phenomena. The reduced effectiveness of DEET against _Aedes_ and _Anopheles_ mosquitoes has already been demonstrated in various situations [10; 11; 12]. In silico approaches allow us to speed up the discovery process of new mosquito repellents through the use of two main paradigms. The first one relies on the use of odorant-binding proteins (OBPs) that play a key role in mosquito olfaction. Among the OBPs, the crystal structures of OBP1 have been used in docking analysis for the structure-based discovery of new molecules with a potential repellent activity against _Aedes_ or _Anopheles_ mosquitoes [13; 14; 15; 16]. The second one consists in the computation of (Quantitative) Structure-Activity Relationship ((Q)SAR) models [17]. Molecules with their experimental repellent activity are encoded by molecular descriptors and then a linear or nonlinear statistical method [18] is used for establishing formal relationships between the structure of the molecules and their repellent activity. The choice of the statistical approach mainly depends on the complexity of the problem at hand. Structural features (SFs), topological indices (TIs) and/or physicochemical properties are used for describing the molecules and feature selection methods allow the selection of the most information-rich set of descriptors and guarantee their optimal number to address overfitting problems. While the programs for calculating the SFs and TIs do not give different results if the native algorithms are used, the same is not true for the programs aiming at calculating the physicochemical properties of molecules that are QSPR (Quantitative Structure-Property Relationship) models. It is well-known that two different QSPR models built for the same physicochemical property can lead to significantly different prediction results for the same molecule.