Extent and nature of contacts between protein molecules in crystal lattices and between subunits of protein oligomers

Dasgupta, Swagata; Iyer, Ganesh H.; Bryant, Stephen H.; Lawrence, Charles E.; Bell, Jeffrey A.

doi:10.1002/(sici)1097-0134(199708)28:4<494::aid-prot4>3.0.co;2-a

Cited by 166 publications

(167 citation statements)

References 54 publications

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“…P6-b, P6-c, and P6-e do not have this motif. Glycine and small amino acids have been suggested to promote crystallization through the reduction of surface entropy (8,14,(52)(53)(54), and the presence of GX 3 G motifs at each protein-protein interface is consistent with a tightly packed crystal. Furthermore the volume per molecular weight (Matthew's coefficient) (55 (21).…”

Section: Resultsmentioning

confidence: 99%

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Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

163

165

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Protein crystals have catalytic and materials applications and are central to efforts in structural biology and therapeutic development. Designing predetermined crystal structures can be subtle given the complexity of proteins and the noncovalent interactions that govern crystallization. De novo protein design provides an approach to engineer highly complex nanoscale molecular structures, and often the positions of atoms can be programmed with sub-Å precision. Herein, a computational approach is presented for the design of proteins that self-assemble in three dimensions to yield macroscopic crystals. A three-helix coiled-coil protein is designed de novo to form a polar, layered, three-dimensional crystal having the P6 space group, which has a "honeycomb-like" structure and hexameric channels that span the crystal. The approach involves: (i) creating an ensemble of crystalline structures consistent with the targeted symmetry; (ii) characterizing this ensemble to identify "designable" structures from minima in the sequencestructure energy landscape and designing sequences for these structures; (iii) experimentally characterizing candidate proteins. A 2.1 Å resolution X-ray crystal structure of one such designed protein exhibits sub-Å agreement [backbone root mean square deviation (rmsd)] with the computational model of the crystal. This approach to crystal design has potential applications to the de novo design of nanostructured materials and to the modification of natural proteins to facilitate X-ray crystallographic analysis.M olecular design provides powerful tools for exploring how molecular properties dictate macroscopic structure and function. One of the most precise forms of self-organization, crystallization achieves orientation and symmetry across many length scales and can be leveraged to engineer materials with well-defined molecular order (1). In addition to their central role in structure determination, molecular crystals have many applications, including nanoparticle templating (2, 3), nonlinear optical devices (4), molecular scaffolding (5), and porous frameworks (6). A predictive understanding of how to achieve self-assembled macroscale structure and desired properties remains challenging, however, particularly when large, conformationally flexible molecules are employed.Small synthetic molecules have been designed that display complementary functional groups in a manner consistent with a chosen crystal structure. Intermolecular contacts are often patterned using strong, directional interactions (e.g., hydrogen bonding, metalcoordination, and electrostatic interactions) (7). The constituent molecules, however, are typically small and synthetic, thus limiting size, shape, and functionality. Hence, simultaneously achieving functional properties and the presentation of complementary intermolecular interactions that confer a targeted crystal structure can be difficult. Commonly, weak intermolecular forces stabilize crystalline ordering, and as a result, quantitative, predictive approaches to crystal de...

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Section: Resultsmentioning

confidence: 99%

“…The large residue (Tyr1) at the N terminus of P6-a may also contribute to destabilization of the parallel configuration. Charged side-chains often have high conformational entropy, and they are believed to disrupt crystal-packing interfaces (8,52,53,57,58). These residues are frequently mutated to induce crystallographic order (54,59).…”

Section: Resultsmentioning

confidence: 99%

Computational design of a protein crystal

Lanci

MacDermaid

Kang

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

163

165

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“…The pairwise contacts in a protein crystal are much less extensive than in homodimers or complexes (Janin & Rodier, 1995;Dasgupta et al, 1997;Janin, 1997;Carugo & Argos, 1997). The average area of crystal-packing interfaces is only 570 Å 2 per interface (Fig.…”

Section: Crystal Packing Creates Small Interfaces With Little Conformmentioning

confidence: 99%

Macromolecular recognition in the Protein Data Bank

Janin

Rodier

Chakrabarti

et al. 2006

Acta Crystallogr D Biol Cryst

101

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Crystal structures deposited in the Protein Data Bank illustrate the diversity of biological macromolecular recognition: transient interactions in protein-protein and protein-DNA complexes and permanent assemblies in homodimeric proteins. The geometric and physical chemical properties of the macromolecular interfaces that may govern the stability and specificity of recognition are explored in complexes and homodimers compared with crystal-packing interactions. It is found that crystal-packing interfaces are usually much smaller; they bury fewer atoms and are less tightly packed than in specific assemblies. Standard-size interfaces burying 1200-2000 Å 2 of protein surface occur in protease-inhibitor and antigen-antibody complexes that assemble with little or no conformation changes. Short-lived electron-transfer complexes have small interfaces; the larger size of the interfaces observed in complexes involved in signal transduction and homodimers correlates with the presence of conformation changes, often implicated in biological function. Results of the CAPRI (critical assessment of predicted interactions) blind prediction experiment show that docking algorithms efficiently and accurately predict the mode of assembly of proteins that do not change conformation when they associate. They perform less well in the presence of large conformation changes and the experiment stimulates the development of novel procedures that can handle such changes.

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“…At least three types of contacts can be identified from the protein structures deposited in the Protein Data Bank (PDB) (26): (i) contacts between components of protein-protein complexes (24, 27); (ii) contacts between the subunits of homodimeric (and higher oligomeric) proteins (25,28); and (iii) contacts between monomeric protein molecules in their crystal lattice (29,30). Specific, biologically relevant interactions occur between the interfaces of the first two types, whereas those resulting from molecular packing in protein crystals are nonspecific.…”

mentioning

confidence: 99%

Conservation and relative importance of residues across protein-protein interfaces

Guharoy

Chakrabarti

2005

Proc. Natl. Acad. Sci. U.S.A.

245

205

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A core region surrounded by a rim characterizes biological interfaces. We ascertain the importance of the core by showing the sequence entropies of the residues comprising the core to be smaller than those in the rim. Such a distinction is not seen in the 2-fold-related, nonphysiological interfaces formed in crystal lattices of monomeric proteins, thereby providing a procedure for characterizing the oligomeric state from crystal structures of protein molecules. This method is better than those that rely on the comparison of the sequence entropies in the interface and the rest of the protein surface, especially in cases where the surface harbors additional binding sites. To a good approximation there is a correlation between the accessible surface area lost because of complexation and ⌬⌬G values obtained through alanine-scanning mutagenesis (26 -38 cal per Å 2 of the surface buried) for residues located in the core, a relationship that is not discernable for rim residues. If, however, a residue participates in hydrogen bonding across the interface, the extent of stabilization is 52 cal͞mol per 1 Å 2 of the nonpolar surface area buried by the residue. As opposed to an amino acid classification used earlier, an environment-based grouping of residues yields a better discrimination in the sequence entropy between the core and the rim.protein-protein interaction ͉ hot spots in the interface ͉ residue conservation ͉ crystal packing ͉ quaternary structure prediction

show abstract

Extent and nature of contacts between protein molecules in crystal lattices and between subunits of protein oligomers

Cited by 166 publications

References 54 publications

Computational design of a protein crystal

Computational design of a protein crystal

Macromolecular recognition in the Protein Data Bank

Conservation and relative importance of residues across protein-protein interfaces

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