Computational approaches for modelling multidrug efflux pumps of the resistance nodulation-cell division superfamily

Multidrug efflux pumps of the Resistance Nodulation-cell Division (RND) superfamily are integral membrane transporters that play a central role in intrinsic and acquired antibiotic resistance in Gram-negative bacteria. Computational approaches have proven invaluable in complementing experimental studies by providing atomistic insight into substrate recognition, transport mechanisms, and inhibitor binding. In this chapter, we provide detailed protocols and tools for most common computational methods applied to RND efflux systems, including homology modelling, molecular docking, all-atom molecular dynamics simulations, and estimation of binding free energy. Each method is presented with practical details on software, input preparation and analysis strategies. Guidelines are included for avoiding common pitfalls and for ensuring reproducibility across computational platforms. Comparisons of the strengths and limitations of these approaches are provided, together with a word of caution on overclaiming results from in silico models without experimental validation. Finally, we discuss the current landscape of computational applications in efflux research illustrating both the opportunities and caveats of these approaches. Together, these methods enable systematic investigation of transporter dynamics, substrate polyspecificity, and inhibition strategies, and can be adapted to other membrane transporters of clinical relevance.