Binding Efficiency of Protein–Protein Complexes

Abstract

We examine the relationship between binding affinity and interface size for reversible protein-protein interactions (PPI), using cytokines from the tumor necrosis factor (TNF) superfamily and their receptors as a test case. Using surface plasmon resonance, we measured single-site binding affinities for the large receptor TNFR1 binding to its ligands TNFα (KD = 1.4 ± 0.4 nM) and lymphotoxin-α (KD = 50 ± 10 nM), and also for the small receptor Fn14 binding to TWEAK (KD = 70 ± 10 nM). We additionally assembled data for all other TNF/TNFR family complexes for which reliable single site binding affinities have been reported. We used these values to calculate the binding efficiency – defined as binding energy per Å2 of surface area buried at the contact interface – for the nine of these complexes for which co-crystal structures are available, and compared the results to those for a set of 144 protein-protein complexes with published affinity values. The results show that the most efficient PPI complexes generate ~20 cal.mol−1/Å2 of binding energy. A minimum contact area of ~500 Å2 is required for a stable complex, required to generate sufficient interaction energy to pay the entropic cost of co-localizing two proteins from 1 M solution. The most compact and efficient TNF/TNFR complex was BAFF/BR3, which achieved ~80% of the maximum achievable binding efficiency. Other small receptors also gave high binding efficiencies, while the larger receptors generated only 44-49% of this limit despite interacting primarily through just a single small domain. The results provide new insight into how much binding energy can be generated by a PPI interface of a given size, and establish a quantitative method to predict how large a natural or engineered contact interface must be to achieve a given level of binding affinity.

The Interface between Hepatitis B Virus Capsid Proteins Affects Self-Assembly, Pregenomic RNA Packaging, and Reverse Transcription

“…The extrapolated value for Cp149-V124A fell very close to this line. Excluding Cp149-V124A, the observed slope was Ϫ14.6 cal/mol/Å 2 , which is in excellent agreement with estimates of hydrophobic interactions at protein-protein interfaces in the literature (52,53). We note that the fraction of Tϭ4 and Tϭ3 capsids affects the calculated value of ⌬G contact by no more than 0.01 kcal/mol, which was below our ability to differentiate.…”

“…The observed Ϫ14.6 cal/mol of contact energy per square angstrom is surprisingly strong, given the poor complementarity at the interdimer interface, which has numerous gaps, including the hydrophobic pocket for CpAM binding. Our observed free energy is only slightly lower than the typical 20 cal/mol/Å 2 of contact energy for protein-protein interactions between highly complementary surfaces, such as receptor-ligand interactions (53). The sensitivity of Cp149-V124X to HAP12 correlates well with the size of the hydrophobic substitution, confirming that the V124X residues fill the pocket to different extents.…”

Feature selection and classification of protein-protein complexes based on their binding affinities using machine learning approaches

“…Apart from the test set of 30 complexes, we have examined the prediction power of our model on an additional blind set of seven complexes, which belongs to a common group called “Tumor necrosis factor (TNF) superfamily.” Among the seven complexes, three of them have high affinity and four have low affinity. Our method correctly classified all the three high affinity complexes, and three out of the four low affinity complexes, which showed an accuracy of 85.7%.…”

Receptor–Ligand Interactions: Binding Affinities Studied by Single‐Molecule and Super‐Resolution Microscopy on Intact Cells

“…Notably, literature reports a vast range of binding affinities for TNF-R1/TNFa in different cell lines, ranging from 3 to 920 pm using radioligand binding assays [42][43][44] to 0.59 to 290 nm using SPR. [45][46][47] We again point out that these large variations may in part be explained by the different techniques. It is known that TNF-R1 undergoes reorganization upon TNFa binding which may affect further ligand-receptor interactions; a receptor pre- Figure 2.…”