The architecture of the protein domain universe

Understanding the design of the universe of protein structures may provide insights into protein evolution. We study the architecture of the protein domain universe, which has been found to poses peculiar scale-free properties (Dokholyan et al., Proc. Natl. Acad. Sci. USA 99: 14132-14136 (2002)). We examine the origin of these scale-free properties of the graph of protein domain structures (PDUG) and determine that that the PDUG is not modular, i.e. it does not consist of modules with uniform properties. Instead, we find the PDUG to be self-similar at all scales. We further characterize the PDUG architecture by studying the properties of the hub nodes that are responsible for the scale-free connectivity of the PDUG. We introduce a measure of the betweenness centrality of protein domains in the PDUG and find a power-law distribution of the betweenness centrality values. The scale-free distribution of hubs in the protein universe suggests that a set of specific statistical mechanics models, such as the self-organized criticality model, can potentially identify the principal driving forces of molecular evolution. We also find a gatekeeper protein domain, removal of which partitions the largest cluster into two large sub-clusters. We suggest that the loss of such gatekeeper protein domains in the course of evolution is responsible for the creation of new fold families.Comment: 14 pages, 3 figure

mRNA vaccines for cancer immunotherapy

Immunotherapy has emerged as a breakthrough strategy in cancer treatment. mRNA vaccines are an attractive and powerful immunotherapeutic platform against cancer because of their high potency, specificity, versatility, rapid and large-scale development capability, low-cost manufacturing potential, and safety. Recent technological advances in mRNA vaccine design and delivery have accelerated mRNA cancer vaccines’ development and clinical application. In this review, we present various cancer vaccine platforms with a focus on nucleic acid vaccines. We discuss rational design and optimization strategies for mRNA cancer vaccine development. We highlight the platforms available for delivery of the mRNA vaccines with a focus on lipid nanoparticles (LNPs) based delivery systems. Finally, we discuss the limitations of mRNA cancer vaccines and future challenges

Folding of Cu, Zn superoxide dismutase and Familial Amyotrophic Lateral Sclerosis

Cu,Zn superoxide dismutase (SOD1) has been implicated in the familial form of the neurodegenerative disease Amyotrophic Lateral Sclerosis (ALS). It has been suggested that mutant mediated SOD1 misfolding/aggregation is an integral part of the pathology of ALS. We study the folding thermodynamics and kinetics of SOD1 using a hybrid molecular dynamics approach. We reproduce the experimentally observed SOD1 folding thermodynamics and find that the residues which contribute the most to SOD1 thermal stability are also crucial for apparent two-state folding kinetics. Surprisingly, we find that these residues are located on the surface of the protein and not in the hydrophobic core. Mutations in some of the identified residues are found in patients with the disease. We argue that the identified residues may play an important role in aggregation. To further characterize the folding of SOD1, we study the role of cysteine residues in folding and find that non-native disulfide bond formation may significantly alter SOD1 folding dynamics and aggregation propensity.Comment: 16 pages, 5 figure

Physical Microscopic Model of Proteins Under Force

Nature has evolved proteins to counter-act forces applied on living cells, and designed proteins that can sense forces. One can appreciate Nature’s ingenuity in evolving these proteins to be highly sensitive to force and to have a high dynamic force range at which they operate. To achieve this level of sensitivity, many of these proteins are comprised of multiple domains and linking peptides connecting these domain, each of them have their own force response regimes. Here, using a simple model of a protein, we address the question of how each individual domain responds to force. We also ask how multi-domain proteins respond to forces. We find that the end-to-end distance of individual domains under force scales linearly with force. In multi-domain proteins, we find that the force response has a rich range: at low force, extension is predominantly governed by “weaker” linking peptides or domain intermediates, while at higher force, the extension is governed by unfolding of individual domains. Overall, the force extension curve comprises multiple sigmoidal transition governed by unfolding of linking peptides and domains. Our study provides a basic framework for the understanding of protein response to force, and allows for interpretation experiments in which force is used to study the mechanical properties of multi-domain proteins

Applications of Discrete Molecular Dynamics in biology and medicine

Discrete Molecular Dynamics (DMD) is a physics-based simulation method using discrete energetic potentials rather than traditional continuous potentials, allowing microsecond time scale simulations of biomolecular systems to be performed on personal computers rather than supercomputers or specialized hardware. With the ongoing explosion in processing power even in personal computers, applications of DMD have similarly multiplied. In the past two years, researchers have used DMD to model structures of disease-implicated protein folding intermediates, study assembly of protein complexes, predict protein-protein binding conformations, engineer rescue mutations in disease-causative protein mutants, design a protein conformational switch to control cell signaling, and describe the behavior of polymeric dispersants for environmental cleanup of oil spills, among other innovative applications

Identifying the protein folding nucleus using molecular dynamics

Molecular dynamics simulations of folding in an off-lattice protein model reveal a nucleation scenario, in which a few well-defined contacts are formed with high probability in the transition state ensemble of conformations. Their appearance determines folding cooperativity and drives the model protein into its folded conformation. Amino acid residues participating in those contacts may serve as “accelerator pedals” used by molecular evolution to control protein folding rate.R01-52126 - PHS HHS; GM20251-01 - NIGMS NIH HHS; GM08291-09 - NIGMS NIH HHSAccepted manuscrip

Discrete molecular dynamics studies of the folding of a protein-like model

Background: Many attempts have been made to resolve in time the folding of model proteins in computer simulations. Different computational approaches have emerged. Some of these approaches suffer from the insensitivity to the geometrical properties of the proteins (lattice models), while others are computationally heavy (traditional MD). Results: We use a recently-proposed approach of Zhou and Karplus to study the folding of the protein model based on the discrete time molecular dynamics algorithm. We show that this algorithm resolves with respect to time the folding --- unfolding transition. In addition, we demonstrate the ability to study the coreof the model protein. Conclusion: The algorithm along with the model of inter-residue interactions can serve as a tool to study the thermodynamics and kinetics of protein models.Comment: 15 pages including 20 figures (Folding & Design in press