Phenotypic comparisons of consensus variants versus laboratory resurrections of Precambrian proteins
Consensus-sequence engineering has generated protein variants with enhanced stability, and sometimes, with modulated biological function. Consensus mutations are often interpreted as the introduction of ancestral amino acid residues. However, the precise relationship between consensus engineering and ancestral protein resurrection is not fully understood. Here, we report the properties of proteins encoded by consensus sequences derived from a multiple sequence alignment of extant, class A β-lactamases, as compared with the properties of ancient Precambrian β-lactamases resurrected in the laboratory. These comparisons considered primary sequence, secondary, and tertiary structure, as well as stability and catalysis against different antibiotics. Out of the three consensus variants generated, one could not be expressed and purified (likely due to misfolding and/or low stability) and only one displayed substantial stability having substrate promiscuity, although to a lower extent than ancient β-lactamases. These results: (i) highlight the phenotypic differences between consensus variants and laboratory resurrections of ancestral proteins; (ii) question interpretations of consensus proteins as phenotypic proxies of ancestral proteins; and (iii) support the notion that ancient proteins provide a robust approach toward the preparation of protein variants having large numbers of mutational changes while possessing unique biomolecular properties. Proteins 2014. © 2014 Wiley Periodicals, Inc.
Essential function of the N-termini tails of the proteasome for the gating mechanism revealed by molecular dynamics simulations
Proteasome is involved in the degradation of proteins. Proteasome activators bind to the proteasome core particle (CP) and facilitate opening a gate of the CP, where Tyr8 and Asp9 in the N-termini tails of the CP form the ordered open gate. In a double mutant (Tyr8Gly/Asp9Gly), the N-termini tails are disordered and the stabilized open-gate conformation cannot be formed. To understand the gating mechanism of the CP for the translocation of the substrate, four different molecular dynamics simulations were carried out: ordered- and Tyr8Gly/Asp9Gly disordered-gate models of the CP complexed with an ATP-independent PA26 and ordered- and disordered-gate models of the CP complexed with an ATP-dependent PAN-like activator. The free-energies of the translocation of a polypeptide substrate moving through the gate were estimated. In the ordered-gate models, the substrate in the activator was more stable than that in the CP. The conformational entropy of the N-termini tails of the CP was larger when the substrate was in the activator than in the CP. In the disordered-gate models, the substrate in the activator was more destabilized than in the ordered-gate models. The mutated N-termini tails became randomized and their increased conformational entropy could no longer increase further even when the substrate was in the activator, meaning the randomized N-termini tails had lost the ability to stabilize the substrate in the activator. Thus, it was concluded that the dynamics of the N-termini tails entropically play a key role in the translocation of the substrate. Proteins 2014. © 2014 Wiley Periodicals, Inc.
Our understanding of protein folding, stability, and function has begun to more explicitly incorporate dynamical aspects. Nuclear magnetic resonance has emerged as a powerful experimental method for obtaining comprehensive site-resolved insight into protein motion. It has been observed that methyl-group motion tends to cluster into three “classes” when expressed in terms of the popular Lipari-Szabo model-free squared generalized order parameter. Here the origins of the three classes or bands in the distribution of order parameters are examined. As a first step, a Bayesian based approach, which makes no a priori assumption about the existence or number of bands, is developed to detect the banding of values derived either from NMR experiments or molecular dynamics simulations. The analysis is applied to seven proteins with extensive molecular dynamics simulations of these proteins in explicit water to examine the relationship between O2 and fine details of the motion of methyl bearing side chains. All of the proteins studied display banding, with some subtle differences. We propose a very simple yet plausible physical mechanism for banding. Finally, our Bayesian method is used to analyze the measured distributions of methyl group motions in the catabolite activating protein and several of its mutants in various liganded states and discuss the functional implications of the observed banding to protein dynamics and function. Proteins 2014. © 2014 Wiley Periodicals, Inc.