From systems to structure: bridging networks and mechanism

Abstract

There is a wide gap between the generation of large-scale biological data sets and more-detailed, structural and mechanistic studies. However, recent studies that explicitly combine data from systems and structural biological approaches are having a profound effect on our ability to predict how mutations and small molecules affect atomic-level mechanisms, disrupt systems-level networks, and ultimately lead to changes in organismal fitness. In fact, we argue that a shared framework for analysis of nonadditive genetic and thermodynamic responses to perturbations will accelerate the integration of reductionist and global approaches. A stronger bridge between these two areas will allow for a deeper and more-complete understanding of complex biological phenomenon and ultimately provide needed breakthroughs in biomedical research.

Figure 1. Interpretation of physical networks

A) A generic physical interaction network that could be derived from various systematic protein-protein interaction platforms. B) The interaction map in A) could represent a set mutually exclusive protein-protein interactions involving one common target (e.g. Ras complexes: Ras:GEF (1BKD), Ras:GAP (1WQ1), Ras:Raf (3KUD)) or a simultaneous assembly of proteins into a complex (e.g. SCF complex (1LDK)).

Figure 2. Evolutionarily analysis of interfaces involved in mediating protein-protein interactions

A) Regions of host proteins that are directly hijacked by viral factors are less conserved than interfaces that mediate interactions between host proteins. B) The human kinase PKR interacts with eIF2α and the viral protein K3L via a common surface. Residues coloured in blue line the interface region and display evidence for positive selection (elevated rates of amino acid substitutions). K3L (1LUZ) was docked to PKR based on a superposition of the PKR: eIF2α co crystal structure (2A1A).

Figure 3. Using unbiased systems approaches to solve, important biochemically intractable problems

A) Use of a targeted two-hybrid approach for BRCA2 identified DSS1, which allowed for the structural elucidation (1MJE) of this important factor involved in breast cancer progression. B) An unbiased affinity tag-purification mass spectrometry approach on all HIV proteins revealed a connection between the accessory protein Vif and the human transcription factor CBF-β. This host protein, which is required for efficient HIV infection, allowed for the reconstitution and structural characterization of an active Vif-Cul-5 ubiquitination complex, which is required for the degradation of the host restriction factor APOBEC3G. The unbiased systems approach allowed for the discovery that by hijacking CBF-β, Vif is manipulating the ubquitination machinery and adversely effecting host transcriptional regulation.

Figure 4. A common framework for understanding genetic and thermodynamic perturbations

Non-additive effects are analyzed by similar methods and have similar distributions in a genetic (left) or biophysical context (right). For non-neutral genetic interactions and biophysical couplings, the effects of perturbations are context dependent. Quantitative genetic analysis distinguishes between negative ((a Δ b Δ) < (a Δ)(b Δ)), positive ((a Δ b Δ) > (a Δ)(b Δ)), and neutral ((a Δ b Δ) = (a Δ)(b Δ )) interactions based on the fitness of the organism, represented here by colony size. Biophysical studies measure the free energy of a process, for example protein folding, across different variants to distinguish between negative (Δ G₃> Δ G₄; Δ G₁> Δ G₂), positive (Δ G₃< Δ G₄; Δ G₁< Δ G₂), or the absence (Δ G₃= Δ G₄; Δ G₁= Δ G₂) of thermodynamic coupling (Δ Δ G).