Drugging Membrane Protein Interactions

Abstract

The majority of therapeutics target membrane proteins, accessible on the surface of cells, to alter cellular signaling. Cells use membrane proteins to transduce signals into cells, transport ions and molecules, bind cells to a surface or substrate, and catalyze reactions. Newly devised technologies allow us to drug conventionally "undruggable" regions of membrane proteins, enabling modulation of protein-protein, protein-lipid, and protein-nucleic acid interactions. In this review, we survey the state of the art of high-throughput screening and rational design in drug discovery, and we evaluate the advances in biological understanding and technological capacity that will drive pharmacotherapy forward against unorthodox membrane protein targets.

Keywords: curvature sensing; drug discovery; high-throughput screening; rational design; transmembrane domains.

Figure 1

Uses of exogenous chemical probes to investigate cell membranes and membrane proteins (MPs). (a) MP transmembrane domain (TMD) structure–function relationships can be investigated without crystallizing full-length MPs. (b) TMD structures also enable rational design of anti-TMD peptides and small molecules. (c) Curvature-sensing peptides and proteins can be used to sense curved membranes, such as those found on small, highly curved extracellular vesicles. (d) Modulating membrane protein–protein and protein–lipid interactions also offers an opportunity to understand the fine-tuning of the immune response in response to pattern recognition receptor activation, with applications in cancer immunotherapy. (e) Conjugating an environment-sensitive fluorophore to peptide probes provides a convenient readout for interaction with the membrane. (f) Computational advances have improved predictions of TMD–TMD interactions.

Figure 2

Strategies for lipid sensing and curvature targeting. Highly curved membranes contain lipid-packing defects, which are transient low-density regions resulting from a mismatch between individual lipid geometry and global membrane curvature. (a) In hydrophobic insertion, large hydrophobic residues (phenylalanine, leucine, tryptophan) can insert into transient lipid-packing defects in the membrane, stabilizing curvature. (b) In shape-based sensing, shape complementarity between a concave, cationic protein surface and a convex, anionic membrane stabilizes interactions such as the interaction of a Bin–Amphiphysin–Rvs (BAR) domain with a membrane. (c) Electrostatic insertions by metalloproteins use metal ions to coordinate with lipid head groups. In the case of the Ca²⁺-binding C2B domain of Syt-1 (Protein Data Bank code: 1UOW), Ca²⁺ ions form a complex between membrane-penetrating loops and anionic lipid head groups, allowing loops to insert ~2 nm into the membrane. (d) Multivalent clustering and oligomerization can also scaffold proteins around membrane curvature.

Figure 3

Selective small molecule and peptide immunomodulators of the Toll-like receptor (TLR) family. TLR agonists and antagonists provide the ability to activate or inhibit the immune response. Agonists are currently being investigated to strengthen the anticancer and antiviral immune response, but TLR antagonists have received the most attention for inflammatory and autoimmune diseases. However, other areas of therapeutic intervention using modulators of TLR signaling continue to be explored. Agonists and antagonists under investigation for targeting TLRs have been reviewed elsewhere (88, 89). This illustration is not meant to be exhaustive but rather to demonstrate the feasibility of using TLR family members as small-molecule drug targets.

Figure 4

Advances affecting the drug discovery work flow. High-throughput screening and rational design are two contrasting approaches to drug discovery. Improved membrane protein structural information (red), improved biological understanding of membranes (green), and new technologies (blue) affect different segments of the discovery pipeline. MD: molecular dynamics. SAR: structure-activity relationship.

Figure 5

Rational design of anti–transmembrane domain (TMD) peptides. (a) In the initial peptide design, a backbone geometry is first selected from existing structures that contain motifs found in the TMD target; amino acid residues from the target TMD are then added to the backbone (green); and finally a side chain–repacking algorithm is run on the computed helical antimembrane protein (CHAMP) peptide (pink). (b) Sequence motifs are illustrated on target integrin TMD idealized conformations, with common small sequences (red) and a common leucine (purple). (c) A tightly packing interface between the CHAMP peptide (green), the integrin TMD (red), and the hot spot (blue) is predicted. (d) Integrin activation by an anti-TMD peptide is explained by a model indicating the effect of the anti-TMD peptide in shifting the equilibrium of integrin subunits towards the active state. Modified from Reference .