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...

From exponentially large numbers of possible sequences, protein design seeks to identify the properties of those that fold to predetermined structures and have targeted structural and functional properties. The interactions that confer structure and function involve intermolecular forces and large numbers of interacting amino acids. As a result, the identification of sequences can be subtle and complex. Sophisticated methods for characterizing sequences consistent with a particular structure have been developed, assisting the design of novel proteins. Developments in such computational protein design are discussed, along with recent accomplishments, ranging from the redesign of existing proteins to the design of new functionalities and nonbiological applications.

We have computed pKa shifts for carboxylic residues of the serine protease inhibitor turkey ovomucoid third domain (residues Asp7, Glu10, Glu19, Asp27, and Glu43). Both polarizable and nonpolarizable empirical force fields were employed. Hydration was represented by the surface generalized Born and Poisson-Boltzmann continuum model. The calculations were carried out in the most physically straightforward fashion, by directly comparing energies of the protonated and deprotonated protein forms, without any additional parameter fitting or adjustment. Our studies have demonstrated that (i) the Poisson-Boltzmann solvation model is more than adequate in reproducing pKa shifts, most likely due to its intrinsically many-body formalism; (ii) explicit treatment of electrostatic polarization included in our polarizable force field (PFF) calculations appears to be crucial in reproducing the acidity constant shifts. The average error of the PFF results was found to be as low as 0.58 pKa units, with the best fixed-charges average deviation being 3.28 units. Therefore, the pKa shifts phenomena and the governing electrostatics are clearly many-body controlled in their intrinsic nature; (iii) our results confirm previously reported conclusions that pKa shifts for protein residues are controlled by the immediate environment of the residues in question, as opposed to long-range interactions in proteins. We are confident that our confirmation of the importance of explicit inclusion of polarization in empirical force fields for protein studies will be useful far beyond the immediate goal of accurate calculation of acidity constants.

The architecture of a biological membrane hinges upon the fundamental fact that its properties are determined by more than the sum of its individual components. Studies on model membranes have shown the need to characterize in molecular detail how properties such as thickness, fluidity, and macroscopic bending rigidity are regulated by the interactions between individual molecules in a non-trivial fashion. Simulation-based approaches are invaluable to this purpose but are typically limited to short sampling times and model systems that are often smaller than the required properties. To alleviate both limitations, the use of coarse-grained (CG) models is nowadays an established computational strategy. We here present a new CG force field for cholesterol, which was developed by using measured properties of small molecules, and can be used in combination with our previously developed force field for phospholipids. The new model performs with precision comparable to atomistic force fields in predicting the properties of cholesterol-rich phospholipid bilayers, including area per lipid, bilayer thickness, tail order parameter, increase in bending rigidity, and propensity to form liquid-ordered domains in ternary mixtures. We suggest the use of this model to quantify the impact of cholesterol on macroscopic properties and on microscopic phenomena involving localization and trafficking of lipids and proteins on cellular membranes.

A coarse-grained (CG) model for peptides and proteins was developed as an extension of the Surface Property fItting Coarse grAined (SPICA) force field (FF). The model was designed to examine membrane proteins that are fully compatible with the lipid membranes of the SPICA FF. A preliminary version of this protein model was created using thermodynamic properties, including the surface tension and density in the SPICA (formerly called SDK) FF. In this study, we improved the CG protein model to facilitate molecular dynamics (MD) simulations with a reproduction of multiple properties from both experiments and all-atom (AA) simulations. An elastic network model was adopted to maintain the secondary structure within a single chain. The side-chain analogues reproduced the transfer free energy profiles across the lipid membrane and demonstrated reasonable association free energy (potential of mean force) in water compared to those from AA MD. A series of peptides/proteins adsorbed onto or penetrated into the membrane simulated by the CG MD correctly predicted the penetration depths and tilt angles of peripheral and transmembrane peptides/proteins as comparable to those in the orientations of proteins in membranes (OPM) database. In addition, the dimerization free energies of several transmembrane helices within a lipid bilayer were comparable to those from experimental estimation. Application studies on a series of membrane protein assemblies, scramblases, and poliovirus capsids demonstrated the good performance of the SPICA FF.