In modern pharmacology, one of the most persistent and complex challenges lies in targeting protein classes that, until recently, were considered “undruggable” due to their structure, function, or subcellular localisation. Among these, the solute carrier (SLC) transporter family stands out – a vast superfamily of over 450 membrane proteins responsible for transporting metabolites, nutrients, ions, and drugs across cell membranes. These proteins are central to a wide range of physiological processes, and their dysfunction has been linked to numerous diseases, including cancer, metabolic disorders, neurological conditions, and rare diseases.
Despite their essential functions, SLC transporters remain largely overlooked in drug development: over 80% have no known chemical modulators capable of altering their activity. Several factors contribute to this neglect, including technical challenges in producing and structurally characterising membrane proteins, the lack of highly sensitive phenotypic assays, and functional redundancy within the SLC family. For years, these hurdles have discouraged the pharmaceutical industry from prioritising SLCs as therapeutic targets, effectively orphaning them in the drug discovery landscape.
However, recent breakthroughs in converging technologies – from quantitative proteomics and high-content microscopy to genetic engineering and artificial intelligence – are prompting a paradigm shift. A growing number of studies and international research consortia are now turning renewed attention to SLCs, marking a new phase in the therapeutic reintegration of this critical protein family.
Takeaways
The Great Promise of SLCs
SLC (solute carrier) transporters are integral membrane proteins responsible for moving substances across cellular membranes. Unlike ABC transporters, which rely on ATP to drive active transport, SLCs enable passive diffusion or co-transport with ions. These proteins are found in nearly all cell types and regulate the exchange of a wide range of molecules – including glucose, amino acids, fatty acids, vitamins, metal ions, neurotransmitters, and drugs.
Their pharmacological importance is twofold. First, SLCs directly influence drug absorption, distribution, metabolism, and excretion (ADME). Second, they represent promising therapeutic targets for various diseases. Functional genomics and phenotype-association studies have linked mutations in SLC genes to rare monogenic disorders as well as complex phenotypes in oncology, neurology, and immunology.
Yet, as César-Razquin et al. noted in Cell, “despite their number, ubiquity, and function, SLC transporters have been largely overlooked in systematic pharmacological research.” A comprehensive analysis of over 400 human SLCs found that more than 350 have no known ligands or active chemical modulators. Only a small subset of these transporters is included in high-throughput screening libraries.
In recent years, however, the scientific community has mounted coordinated efforts to close this gap. The European consortium RESOLUTE – funded by the European Commission and supported by major industry players like Bayer, Sanofi, Pfizer, and Novartis – has launched a systematic mapping of SLCs, covering expression profiles, functions, associated phenotypes, and predicted structures. Specialised journals have also begun spotlighting the “emerging druggability” of SLC transporters, with increasing focus on AI-driven rational design and computational chemistry.
A New Approach to Turning Overlooked Targets into Viable Drug Candidates
A tangible example of this new wave in drug discovery is Solgate, a biotech startup founded in Vienna in 2020 with a clear mission: to make SLC transporters druggable and bring novel drug candidates to the clinic.
“We founded Solgate based on a very specific scientific observation: the SLC family holds enormous pharmacological promise but remains technologically inaccessible without a multidisciplinary infrastructure,” explains Enrico Girardi, Solgate’s Chief Scientific Officer. “That’s why, during our first three years, we focused entirely on building a platform capable of tackling this challenge in a systematic way.”
Solgate’s platform integrates high-resolution proteomics, high-content microscopy, automated cellular assays, CRISPR-based gene editing, and machine learning. It prioritises transporters through computational analyses that cross-reference genetic data, patient-specific mutations, tissue-specific expression patterns, and phenotypic outcomes.
“One of the core elements is AI-assisted structural modelling,” Girardi adds. “In many cases, crystallographic structures are unavailable, so we use artificial intelligence to predict protein folding and simulate interactions with potential chemical modulators.”
Solgate has already secured partnerships with several pharmaceutical companies and launched a spin-off in collaboration with a U.S.-based fund to pursue targeted therapeutic programmes. Some in-house candidates are currently undergoing preclinical optimisation, with one compound . according to the current roadmap – expected to enter clinical trials by 2027.
The company now has around 15 employees representing ten nationalities and is expanding rapidly. Its new headquarters at the Vienna BioCenter, currently under construction, will accommodate up to 50 researchers.
“Our goal is to become the partner of choice for anyone looking to develop drugs targeting SLC transporters,” concludes Girardi. “We want to transform a technological barrier into a concrete therapeutic opportunity.”
Inside Solgate’s Platform for SLC Transporter Drug Discovery
Solgate has developed an integrated platform that combines cutting-edge molecular biology, genetic engineering, and artificial intelligence to identify and modulate SLC transporters. Its core components include:
- High-Content Screening (HCS)
This allows real-time monitoring of cellular effects resulting from transporter activation or inhibition, using multiparametric phenotypic readouts. - Quantitative Proteomics
Large-scale analysis of SLC expression and localisation, including how cells respond to external stimuli and test compounds. - CRISPR/Cas9 Genetic Models
Targeted editing of SLC genes to validate their function and create optimised cell models for screening. - AI and Computational Chemistry
Machine learning algorithms integrate genetic, structural, and chemical data to predict protein–ligand interactions — even in the absence of experimentally resolved structures. - Automated Screening
Robotic platforms carry out phenotypic and binding assays on small-molecule libraries specifically optimised for membrane transporters.
“We’ve built an infrastructure that allows us to move from gene target to active compound in a rational and scalable way,” says Girardi. “Our approach is designed to overcome the traditional limitations of drug discovery for membrane proteins.”
Glimpses of Futures
To anticipate the future of SLC transporter research, we can apply the STEPS framework, which analyses its potential impact across five key dimensions: Social, Technological, Economic, Political, and Sustainable.
S – SOCIAL
Targeting transporters involved in chronic conditions could greatly improve therapeutic efficacy while reducing side effects. Personalised treatments — tailored to individual genetic markers — require pharmacologically modifiable biological targets.
T – TECHNOLOGICAL
The convergence of computational chemistry, structural biology, and AI is reshaping what’s considered druggable. SLC transporters exemplify this shift: rational drug screening is now possible even without crystallographic data.
E – ECONOMIC
Unlocking the potential of an underexplored target class expands opportunities for novel drug pipelines. For biotech and pharma firms, focusing on SLCs offers a strategic edge in areas of unmet medical need where the market remains relatively open.
P – POLITICAL
Austria’s experience shows how targeted public policy — through initiatives led by AWS and FFG — can drive the growth of deep-tech enterprises in specialised fields. Supporting translational research is a key pillar of national industrial strategy.
S – SUSTAINABILITY
More selective therapies translate into more effective and sustainable treatments. Reducing the use of systemic drugs with low precision directly impacts public health, optimises resources, and promotes equitable access to care.
