Coarse-grained (CG) modelling with the Martini force field has come of age. By combining a variety of bead types and sizes with a new mapping approach, the newest version of the model is able to accurately simulate large biomolecular complexes at millisecond timescales. In this perspective, we discuss possible applications of the Martini 3 model in drug discovery and development pipelines and highlight areas for future development. Owing to its high simulation efficiency and extended chemical space, Martini 3 has great potential in the area of drug design and delivery. However, several aspects of the model should be improved before Martini 3 CG simulations can be routinely employed in academic and industrial settings. These include the development of automatic parameterisation protocols for a variety of molecule types, the improvement of backmapping procedures, the description of protein flexibility and the development of methodologies enabling efficient sampling. We illustrate our view with examples on key areas where Martini could give important contributions such as drugs targeting membrane proteins, cryptic pockets and protein–protein interactions and the development of soft drug delivery systems.

Aceruloplasminemia is a rare autosomal recessive genetic disease characterized by mild microcytic anemia, diabetes, retinopathy, liver disease, and progressive neurological symptoms due to iron accumulation in pancreas, retina, liver, and brain. The disease is caused by mutations in the Ceruloplasmin (CP) gene that produce a strong reduction or absence of ceruloplasmin ferroxidase activity, leading to an impairment of iron metabolism. Most patients described so far are from Japan. Prompt diagnosis and therapy are crucial to prevent neurological complications since, once established, they are usually irreversible. Here, we describe the largest series of non-Japanese patients with aceruloplasminemia published so far, including 13 individuals from 11 families carrying 13 mutations in the CP gene (7 missense, 3 frameshifts, and 3 splicing mutations), 10 of which are novel. All missense mutations were studied by computational modeling. Clinical manifestations were heterogeneous, but anemia, often but not necessarily microcytic, was frequently the earliest one. This study confirms the clinical and genetic heterogeneity of aceruloplasminemia, a disease expected to be increasingly diagnosed in the Next-Generation Sequencing (NGS) era. Unexplained anemia with low transferrin saturation and high ferritin levels without inflammation should prompt the suspicion of aceruloplasminemia, which can be easily confirmed by low serum ceruloplasmin levels. Collaborative joint efforts are needed to better understand the pathophysiology of this potentially disabling disease.

Advances in coarse-grained molecular dynamics (CGMD) simulations have extended the use of computational studies on biological macromolecules and their complexes, as well as the interactions of membrane protein and lipid complexes at a reduced level of representation, allowing longer and larger molecular dynamics simulations. Here, we present a computational platform dedicated to the preparation, running, and analysis of CGMD simulations. The platform is built on a completely revisited version of our Martini coarsE gRained MembrAne proteIn Dynamics (MERMAID) web server, and it integrates this with other three dedicated services. In its current version, the platform expands the existing implementation of the Martini force field for membrane proteins to also allow the simulation of soluble proteins using the Martini and the SIRAH force fields. Moreover, it offers an automated protocol for carrying out the backmapping of the coarse-grained description of the system into an atomistic one.

Atomistic molecular dynamics simulations of membrane proteins have been shown to be extremely useful for characterizing the molecular features underlying their function, but require high computational power, limiting the understanding of complex events in membrane proteins, e.g. ion channels gating, GPCRs activation. To overcome this issue, it has been shown that coarse-grained approaches, although requiring less computational power, are still capable of correctly describing molecular events underlying big conformational changes in biological systems. Here, we present the Martini coarse-grained membrane protein dynamics (MERMAID), a publicly available web interface that allows the user to prepare and run coarse-grained molecular dynamics (CGMD) simulations and to analyse the trajectories.

With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here we report two additional agonists and functional data of the most potent compound on two mutants, L104 ^3.32 and L255 ^6.51 . Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models, and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.