Constructing a folding model for protein S6 guided by native fluctuations deduced from NMR structures

Topological Twists in Nature

The first entangled protein was observed about 30 years ago, resulting in an increased interest for uncovering the biological functions and biophysical properties of these complex topologies. Recently, the Pierced Lasso Topology (PLT) was discovered in which a covalent bond forms an intramolecular loop, leaving one or both termini free to pierce the loop. This topology is related to knots and other entanglements. PLTs exist in many well-researched systems where the PLTs have previously been unnoticed. PLTs represents 18% of all disulfide containing proteins across all kingdoms of life. In this review, we investigate the biological implications of this specific topology in which the PLT-forming disulfide may act as a molecular switch for protein function and consequently human health.

Design of a structure-based model for protein folding from flexible conformations

We introduce a coarse-grained, structure-based model for protein folding that considers the flexibility of the native state in the definition of the model interactions.

Structure of the human monomeric NEET protein MiNT and its role in regulating iron and reactive oxygen species in cancer cells

The NEET family is a relatively new class of three related [2Fe-2S] proteins (CISD1-3), important in human health and disease. While there has been growing interest in the homodimeric gene products of CISD1 (mitoNEET) and CISD2 (NAF-1), the importance of the inner mitochondrial CISD3 protein has only recently been recognized in cancer. The CISD3 gene encodes for a monomeric protein that contains two [2Fe-2S] CDGSH motifs, which we term mitochondrial inner NEET protein (MiNT). It folds with a pseudosymmetrical fold that provides a hydrophobic motif on one side and a relatively hydrophilic surface on the diametrically opposed surface. Interestingly, as shown by molecular dynamics simulation, the protein displays distinct asymmetrical backbone motions, unlike its homodimeric counterparts that face the cytosolic side of the outer mitochondrial membrane/endoplasmic reticulum (ER). However, like its counterparts, our biological studies indicate that knockdown of MiNT leads to increased accumulation of mitochondrial labile iron, as well as increased mitochondrial reactive oxygen production. Taken together, our study suggests that the MiNT protein functions in the same pathway as its homodimeric counterparts (mitoNEET and NAF-1), and could be a key player in this pathway within the mitochondria. As such, it represents a target for anticancer or antidiabetic drug development.

Critical Fluctuations in the Native State of Proteins

Based on protein structural ensembles determined by nuclear magnetic resonance, we study the position fluctuations of residues by calculating distance-dependent correlations and conducting finite-size scaling analysis. The fluctuations exhibit high susceptibility and long-range correlations up to the protein sizes. The scaling relations between the correlations or susceptibility and protein sizes resemble those in other physical and biological systems near their critical points. These results indicate that, at the native states, motions of each residue are felt by every other one in the protein. We also find that proteins with larger susceptibility are more frequently observed in nature. Overall, our results suggest that the protein's native state is critical.

Constructing sequence-dependent protein models using coevolutionary information

Recent developments in global statistical methodologies have advanced the analysis of large collections of protein sequences for coevolutionary information. Coevolution between amino acids in a protein arises from compensatory mutations that are needed to maintain the stability or function of a protein over the course of evolution. This gives rise to quantifiable correlations between amino acid sites within the multiple sequence alignment of a protein family. Here, we use the maximum entropy-based approach called mean field Direct Coupling Analysis (mfDCA) to infer a Potts model Hamiltonian governing the correlated mutations in a protein family. We use the inferred pairwise statistical couplings to generate the sequence-dependent heterogeneous interaction energies of a structure-based model (SBM) where only native contacts are considered. Considering the ribosomal S6 protein and its circular permutants as well as the SH3 protein, we demonstrate that these models quantitatively agree with experimental data on folding mechanisms. This work serves as a new framework for generating coevolutionary data-enriched models that can potentially be used to engineer key functional motions and novel interactions in protein systems.