A general model of multivalent binding with ligands of heterotypic subunits and multiple surface receptors

Multivalent cell surface receptor binding is a ubiquitous biological phenomenon with functional and therapeutic significance. Predicting the amount of ligand binding for a cell remains an important question in computational biology as it can provide great insight into cell-to-cell communication and rational drug design toward specific targets. In this study, we extend a mechanistic, two-step multivalent binding model to account for multiple ligands and receptors, optionally allowing heterogeneous complexes. We derive the macroscopic pre-dictions for both specifically arranged and randomly assorted complexes, and demonstrate how this model enables large-scale predictions on mixture binding and the binding space of a ligand. This model provides an elegant and computationally efficient framework for analyzing multivalent binding.

Thermodynamic modeling reveals widespread multivalent binding by RNA-binding proteins

MotivationUnderstanding how proteins recognize their RNA targets is essential to elucidate regulatory processes in the cell. Many RNA-binding proteins (RBPs) form complexes or have multiple domains that allow them to bind to RNA in a multivalent, cooperative manner. They can thereby achieve higher specificity and affinity than proteins with a single RNA-binding domain. However, current approaches to de-novo discovery of RNA binding motifs do not take multivalent binding into account.ResultsWe present Bipartite Motif Finder (BMF), which is based on a thermodynamic model of RBPs with two cooperatively binding RNA-binding domains. We show that bivalent binding is a common strategy among RBPs, yielding higher affinity and sequence specificity. We furthermore illustrate that the spatial geometry between the binding sites can be learned from bound RNA sequences. These discovered bipartite motifs are consistent with previously known motifs and binding behaviors. Our results demonstrate the importance of multivalent binding for RNA-binding proteins and highlight the value of bipartite motif models in representing the multivalency of protein-RNA interactions.AvailabilityBMF source code is available at https://github.com/soedinglab/bipartite_motif_finder under a GPL license. The BMF web server is accessible at https://bmf.soedinglab.org.

Structural insights into the multivalent binding of the Arabidopsis FLOWERING LOCUS T promoter by the CO-NF-Y master transcription factor complex

Flowering plants sense various environmental and endogenous signals to trigger the floral transition and start the reproductive growth cycle. CONSTANS (CO) is a master transcription factor in the photoperiod floral pathway that integrates upstream signals and activates the florigen gene FLOWERING LOCUS T (FT). Here, we performed comprehensive structural and biochemical analyses to study the molecular mechanism underlying the regulation of FT by CO in Arabidopsis thaliana. We show that the four previously characterized cis-elements in the FT promoter proximal region, CORE1, CORE2, P1 and P2, are all direct CO binding sites. Structural analysis of CO in complex with NUCLEAR FACTOR-YB/YC (NF-YB/YC) and the CORE2 or CORE1 elements revealed the molecular basis for the specific recognition of the shared TGTG motifs. Biochemical analysis suggested that CO might form a homomultimeric assembly via its N-terminal B-Box domain and simultaneously occupy multiple cis-elements within the FT promoter. We suggest that this multivalent binding gives the CO-NF-Y complex high affinity and specificity for FT promoter binding. Overall, our data provide a detailed molecular model for the regulation of FT by the master transcription factor complex CO-NF-Y during the floral transition.