Targeting SLC transporters: small molecules as modulators and therapeutic opportunities

Solute carrier (SLCs) transporters mediate the transport of a broad range of solutes across biological membranes. Dysregulation of SLCs has been associated with various pathologies, including metabolic and neurological disorders, as well as cancer and rare diseases. SLCs are therefore emerging as key targets for therapeutic intervention with several recently approved drugs targeting these proteins. Unlocking this large and complex group of proteins is essential to identifying unknown SLC targets and developing next-generation SLC therapeutics. Recent progress in experimental and computational techniques has significantly advanced SLC research, including drug discovery. Here, we review emerging topics in therapeutic discovery of SLCs, focusing on state-of-the-art approaches in structural, chemical, and computational biology, and discuss current challenges in transporter drug discovery.

Structural Analysis of Genomic and Proteomic Signatures Reveal Dynamic Expression of Intrinsically Disordered Regions in Breast Cancer and Tissue

Structural features of proteins capture underlying information about protein evolution and function, which enhances the analysis of proteomic and transcriptomic data. Here we develop Structural Analysis of Gene and protein Expression Signatures (SAGES), a method that describes expression data using features calculated from sequence-based prediction methods and 3D structural models. We used SAGES, along with machine learning, to characterize tissues from healthy individuals and those with breast cancer. We analyzed gene expression data from 23 breast cancer patients and genetic mutation data from the COSMIC database as well as 17 breast tumor protein expression profiles. We identified prominent expression of intrinsically disordered regions in breast cancer proteins as well as relationships between drug perturbation signatures and breast cancer disease signatures. Our results suggest that SAGES is generally applicable to describe diverse biological phenomena including disease states and drug effects.

Structural signatures: a web server for exploring a database of and generating protein structural features from human cell lines and tissues

Structural features of proteins provide powerful insights into biological function and similarity. Specifically, previous work has demonstrated that structural features of tissue and drug-treated cell line samples can be used to predict tissue type and characterize drug relationships, respectively. We have developed structural signatures, a web server for annotating and analyzing protein features from gene sets that are often found in transcriptomic and proteomic data. This platform provides access to a structural feature database derived from normal and disease human tissue samples. We show how analysis using this database can shed light on the relationship between states of single-cell RNA-sequencing lung cancer samples. These various structural feature signatures can be visualized on the server itself or downloaded for additional analysis. The structural signatures server tool is freely available at https://structural-server.kinametrix.com/.