The paper investigates relationships between chemical structure, surface active properties and antibacterial activity of 70 bis-quaternary ammonium chlorides. Chemical structure and properties of ammonium chlorides were described by 7 condition attributes and antimicrobial properties were mapped by a decision attribute. Dominance-based Rough Set Approach (DRSA) was applied to discover rules exhibiting monotonicity relationships in the data, which are unknown a priori and hold in some parts of the evaluation space. Strong decision rules discovered in this way may enable creating prognostic models of new compounds with the best antimicrobial properties. Moreover, the estimated relevance of the attributes that form the discovered rules allow to distinguish which of the structure and surface active properties describe compounds that have the best and the worst antimicrobial properties.