Computational Design of a Protein Crystal

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 sequence-structure 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

Probabilistic computational protein design: Advances in methodology and the incorporation of non-biological molecular components

Computational protein design method has been developed to understand the underling physicochemical principles that determine the uniqueness of protein conformation often endowing biological function. Many designed sequences have been successful in revealing the energetic ingredients that govern the global and local details of folding; such successes are due in part to the advances in searching methods and scoring functions. Given the intrinsic complexity of proteins, myriads of subtle interactions govern the folding and approximations must be used for efficient computation. Sensitivity to the scoring energy function remains to be examined for discrimination of native-like ensembles of proteins. In this thesis, an entropy-based protein design strategy providing deterministic site-specific amino acid probabilities has been explored upon the variation of molecular mechanical potential energy functions. Secondly, the flexibility and extensibility of the method have been demonstrated in engineering de novo function in the human H-ferritin for noble metal cluster growth. The method has been used to de novo design of a tetra-α-helical bundle for anesthetic halothane binding, where the calculation is expedited by a symmetry approximation and expanded to accommodate non-natural amino acids and/or guest-molecules, thereby simultaneously determining the amino acid sequences and the bound ligand conformations. Finally, the probabilistic strategy has been applied to understand physicochemical properties in natural systems and to facilitate experimental studies. The folding of a Zn-binding domain has been explored by computationally designed substitution with the natural fluorescent probe Trp mutation. The probability profiles in the allosteric enzyme Adelnylate kinase has been used to design sequences that may have preferential stabilities for the open and the closed conformations of the enzyme in an attempt to understand the role of allostery in enzyme catalysis. As the last example, methods for designing sequences with targeted pI values have been introduced and applied to the partial redesign of cytochrome P450 2C9

Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices

Abstract Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10−72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10−4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10−5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids