Mark B. Swindells

We describe a graphical system for automatically generating multiple 2D diagrams of ligand-protein interactions from 3D coordinates. The diagrams portray the hydrogen-bond interaction patterns and hydrophobic contacts between the ligand(s) and the main-chain or side-chain elements of the protein. The system is able to plot, in the same orientation, related sets of ligand-protein interactions. This facilitates popular research tasks, such as analyzing a series of small molecules binding to the same protein target, a single ligand binding to homologous proteins, or the completely general case where both protein and ligand change.

One of the primary factors determining how proteins interact with other molecules is the size of clefts in the protein's surface. In enzymes, for example, the active site is often characterized by a particularly large and deep cleft, while interactions between the molecules of a protein dimer tend to involve approximately planar surfaces. Here we present an analysis of how cleft volumes in proteins relate to their molecular interactions and functions. Three separate datasets are used, representing enzyme-ligand binding, protein-protein dimerization and antibody-antigen complexes. We find that, in single-chain enzymes, the ligand is bound in the largest cleft in over 83% of the proteins. Usually the largest cleft is considerably larger than the others, suggesting that size is a functional requirement. Thus, in many cases, the likely active sites of an enzyme can be identified using purely geometrical criteria alone. In other cases, where there is no predominantly large cleft, chemical interactions are required for pinpointing the correct location. In antibody-antigen interactions the antibody usually presents a large cleft for antigen binding. In contrast, protein-protein interactions in homodimers are characterized by approximately planar interfaces with several clefts involved. However, the largest cleft in each subunit still tends to be involved.

The EF-hand motif, which assumes a helix-loop-helix structure normally responsible for Ca2+ binding, is found in a large number of functionally diverse Ca2+ binding proteins collectively known as the EF-hand protein superfamily. In many superfamily members, Ca2+ binding induces a conformational change in the EF-hand motif, leading to the activation or inactivation of target proteins. In calmodulin and troponin C, this is described as a change from the closed conformational state in the absence of Ca2+ to the open conformational state in its presence. It is now clear from structures of other EF-hand proteins that this "closed-to-open" conformational transition is not the sole model for EF-hand protein structural response to Ca2+. More complex modes of conformational change are observed in EF-hand proteins that interact with a covalently attached acyl group (e.g., recoverin) and in those that dimerize (e.g., S100B, calpain). In fact, EF-hand proteins display a multitude of unique conformational states, together constituting a conformational continuum. Using a quantitative 3D approach termed vector geometry mapping (VGM), we discuss this tertiary structural diversity of EF-hand proteins and its correlation with target recognition.