Mutations in the Receptor Binding Domain of Severe Acute Respiratory Coronavirus-2 Omicron Variant Spike Protein Significantly Stabilizes Its Conformation.

The Omicron variant and its sub-lineages are the only current circulating SARS-CoV-2 viruses worldwide. In this study, the conformational stability of the isolated Receptor Binding Domain (RBD) of Omicron's spike protein is examined in detail. The parent Omicron lineage has over ten mutations in the ACE2 binding region of the RBD that are specifically associated with its ß hairpin loop domain. It is demonstrated through biophysical molecular computations that the mutations in the ß hairpin loop domain significantly increase the intra-protein interaction energies of intra-loop and loop-RBD interactions. The interaction energy increases include the formation of new hydrogen bonds in the ß hairpin loop domain that help stabilize this critical ACE2 binding region. Our results also agree with recent experiments on the stability of Omicron's core ß barrel domain, outside of its loop domain, and help demonstrate the overall conformational stability of the Omicron RBD. It is further shown here through dynamic simulations that the unbound state of the Omicron RBD remains closely aligned with the bound state configuration, which was not observed for the wild-type RBD. Overall, these studies demonstrate the significantly increased conformational stability of Omicron over its wild-type configuration and raise a number of questions on whether conformational stability could be a positive selection feature of SARS-CoV-2 viral mutational changes.

Flap structure within receptor binding domain of SARS-CoV-2 spike periodically obstructs hACE2 Binding subdomain bearing similarities to HIV-1 protease flap.

The SARS-CoV-2 prefusion spike protein is characterized by a high degree of flexibility and temporal transformations associated with its multifunctional behavior. In this study, we have examined the dynamics of the Receptor Binding Domain (RBD) of the SARS-CoV-2 spike protein in detail. Its primary, binding subdomain with human Angiotensin Covering Enzyme II includes a highly conspicuous flap or loop that is part of a beta hairpin loop structural motif. Dynamic details of the RBD obtained through RMSF and Order Parameter calculations are consistent with structural details including the stability of "glue" points or dominant interaction energy residues of the RBD in the Up and Down states with its neighboring N-terminal domain (NTD) protomer. The RBD flap in the Up state protomer periodically obstructs the binding site on an approximate 70 ns time interval and is reminiscent of an HIV-1 protease polypeptide flap that opens and closes to modulate that enzymes activity. No claim is made here regarding the possible modulating role of the flap; however, the flap may be a potential site for therapeutic targeting aimed at keeping it in the closed state, as previously demonstrated in the inhibition of the HIV-1 protease polypeptide. The RBD primary binding subdomain is further shown to have not only similar dynamics but, also, an approximate 30% sequence similarity to the HIV-1 protease polypeptide.

Transformations, Lineage Comparisons, and Analysis of Down-to-Up Protomer States of Variants of the SARS-CoV-2 Prefusion Spike Protein, Including the UK Variant B.1.1.7.

Monitoring and strategic response to variants in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represent a considerable challenge in the current pandemic and for future viral outbreaks. Mutations/deletions of the virion's prefusion Spike protein may have significant impact on vaccines and therapeutics that utilize this key structural protein in their mitigation strategies. In this study, we have demonstrated how dominant energetic landscape mappings ("glue points") based on ab inito all-atom force fields coupled with phylogenetic sequence alignment information can identify key residue mutations and deletions associated with variants. We also found several examples of excellent homology of stabilizing residue glue points across the lineages of betacoronavirus Spike proteins that we have called "sequence homologous glue points." SARS-CoV-2 demonstrates the least number of stabilizing glue points associated with interchain interactions among Down-state protomers across lineages. Additionally, we computationally studied variants among the trimeric Spike protein of SARS-CoV-2 using all-atom molecular dynamics to ascertain structural and energetic changes among variants. We examined both a theoretically based triple mutant and the UK or B.1.1.7 variant. For the theoretical triple mutant, we demonstrated through alanine substitutions that three key residues could cause the transition of Down-to-Up protomer states, where the transition is characterized by the "arm" length of the receptor-binding domain (RBD) rather than the hinge angle. For the B.1.1.7 variant, we demonstrated the critical importance of mutations D614G and N501Y on the structure and binding, respectively, of the Spike protein. We note that these same two key mutations are also found in the South African B.1.351 variant. IMPORTANCE Viral variants represent a major challenge to monitoring viral outbreaks and formulating strategic health care responses. Variants represent transmitting viruses that have specific mutations and deletions associated with their genome. In the case of SARS-CoV-2 and other related viruses (betacoronaviruses), many of these mutations and deletions are associated with the Spike protein that the virus uses to infect cells. Here, we have analyzed both SARS-CoV-2 variants and related viruses, such as Middle Eastern respiratory syndrome coronavirus (MERS-CoV), in order to understand not only differences, but also key similarities between them. Understanding similarities can be as important as differences in determining key functional features of a class of viruses, such as the betacoronaviruses. We have used both phylogenetic analysis, which traces genetic similarities and differences, along with independent biophysics analysis, which adds function or behavior, in order to determine possible functional differences and hence possible transmission and infection differences among variants and lineages.

Transformations, Lineage Comparisons, and Analysis of Down to Up Protomer States of Variants of the SARS-CoV-2 Prefusion Spike Protein Including the UK Variant B.1.1.7.

Monitoring and strategic response to variants in SARS-CoV-2 represents a considerable challenge in the current pandemic, as well as potentially future viral outbreaks of similar magnitude. In particular mutations and deletions involving the virion's prefusion Spike protein have significant potential impact on vaccines and therapeutics that utilize this key structural viral protein in their mitigation strategies. In this study, we have demonstrated how dominant energetic landscape mappings ("glue points") coupled with sequence alignment information can potentially identify or flag key residue mutations and deletions associated with variants. Surprisingly, we also found excellent homology of stabilizing residue glue points across the lineage of ß coronavirus Spike proteins, and we have termed this as "sequence homologous glue points". In general, these flagged residue mutations and/or deletions are then computationally studied in detail using all-atom biocomputational molecular dynamics over approximately one microsecond in order to ascertain structural and energetic changes in the Spike protein associated variants. Specifically, we examined both a theoretically-based triple mutant and the so-called UK or B.1.1.7 variant. For the theoretical triple mutant, we demonstrated through Alanine mutations, which help "unglue" key residue-residue interactions, that these three key stabilizing residues could cause the transition of Down to Up protomer states, where the Up protomer state allows binding of the prefusion Spike protein to hACE2 host cell receptors, whereas the Down state is believed inaccessible. Thus, we are able to demonstrate the importance of glue point residue identification in the overall stability of the prefusion Spike protein. For the B.1.1.7 variant, we demonstrated the critical importance of D614G and N5017 on the structure and binding, respectively, of the Spike protein. Notably, we had previously identified D614 as a key glue point in the inter-protomer stabilization of the Spike protein prior to the emergence of its mutation. The mutant D614G is a structure breaking Glycine mutation demonstrating a relatively more distal Down state RBD and a more stable conformation in general. In addition, we demonstrate that the mutation N501Y may significantly increase the Spike protein binding to hACE2 cell receptors through its interaction with Y41 of hACE2 forming a potentially strong hydrophobic residue binding pair. We note that these two key mutations, D614G and N501Y, are also found in the so-called South African (SA; B.1.351) variant of SARS-CoV-2. Future studies along these lines are, therefore, aimed at mapping glue points to residue mutations and deletions of associated prefusion Spike protein variants in order to help identify and analyze possible "variants of interest" and optimize efforts aimed at the mitigation of this current and future virions.

Static all-atom energetic mappings of the SARS-Cov-2 spike protein and dynamic stability analysis of "Up" versus "Down" protomer states.

The SARS-CoV-2 virion responsible for the current world-wide pandemic COVID-19 has a characteristic Spike protein (S) on its surface that embellishes both a prefusion state and fusion state. The prefusion Spike protein (S) is a large trimeric protein where each protomer may be in a so-called Up state or Down state, depending on the configuration of its receptor binding domain (RBD) within its distal, prefusion S1 domain. The Up state is believed to allow binding of the virion to ACE-2 receptors on human epithelial cells, whereas the Down state is believed to be relatively inactive or reduced in its binding behavior. We have performed detailed all-atom, dominant energy landscape mappings for noncovalent interactions (charge, partial charge, and van der Waals) of the SARS-CoV-2 Spike protein in its static prefusion state based on two recent and independent experimental structure publications. We included both interchain interactions and intrachain (domain) interactions in our mappings in order to determine any telling differences (different so-called "glue" points) between residues in the Up and Down state protomers. The S2 proximal, fusion domain demonstrated no appreciable energetic differences between Up and Down protomers, including interchain as well as each protomer's intrachain, S1-S2 interactions. However, the S1 domain interactions across neighboring protomers, which include the RBD-NTD cross chain interactions, showed significant energetic differences between Up-Down and Down-Down neighboring protomers. This included, for example, a key RBD residue ARG357 in the Up-Down interaction and a three residue sequence ALA520-PRO521-ALA522, associated with a turn structure in the RBD of the Up state protomer, acting as a stabilizing interaction with the NTD of its neighbor protomer. Additionally, our intra chain dominant energy mappings within each protomer, identified a significant "glue" point or possible "latch" for the Down state protomer between the S1 subdomain, SD1, and the RBD domain of the same protomer that was completely missing in the Up state protomer analysis. Ironically, this dominant energetic interaction in the Down state protomer involved the backbone atoms of the same three residue sequence ALA520-PRO521-ALA522 of the RBD with the amino acid R-group of GLN564 in the SD1 domain. Thus, this same three residue sequence acts as a stabilizer of the RBD in the Up conformation through its interactions with its neighboring NTD chain and a kind of latch in the Down state conformation through its interactions with its own SD1 domain. The dominant interaction energy residues identified here are also conserved across reported variations of SARS-CoV-2, as well as the closely related virions SARS-Cov and the bat corona virus RatG13. We conducted preliminary molecular dynamics simulations across 0.1 µ seconds to see if this latch provided structural stability and indeed found that a single point mutation (Q564G) resulted in the latch releasing transforming the protomer from the Down to the Up state conformation. Full trimeric Spike protein studies of the same mutation across all protomers, however, did not exhibit latch release demonstrating the critical importance of interchain interactions across the S1 domain, including RBD-NTD neighboring chain interactions. Therapies aimed at disrupting these noncovalent interactions could be a viable route for the physico-chemical mitigation of this deadly virion.

Static All-Atom Energetic Mappings of the SARS-Cov-2 Spike Protein with Potential Latch Identification of the Down State Protomer.

The SARS-Cov-2 virion responsible for the current world-wide pandemic Covid-19 has a characteristic Spike protein (S) on its surface that embellishes both a prefusion state and fusion state. The prefusion Spike protein (S) is a large trimeric protein where each protomer may be in a so-called Up state or Down state, depending on the configuration of its receptor binding domain (RBD). The Up state is believed to allow binding of the virion to ACE-2 receptors on human epithelial cells, whereas the Down state is believed to be relatively inactive or reduced in its binding behavior. We have performed detailed all-atom, dominant energy landscape mappings for noncovalent interactions (charge, partial charge, and van der Waals) of the SARS-Cov-2 Spike protein in its static prefusion state based on recent structural information. We included both interchain interactions and intrachain (domain) interactions in our mappings in order to determine any telling differences (different so-called "glue" points) between residues in the Up and Down state protomers. In general, the S2 or fusion machinery domain of S is relatively rigid with strong noncovalent interactions facilitated by helical secondary structures, whereas the S1 domain, which contains the RBD and N-terminal domain (NTD), is relatively more flexible and characterized by beta strand structural motifs. The S2 domain demonstrated no appreciable energetic differences between Up and Down protomers, including interchain as well as each protomer's intrachain, S1-S2 interactions. However, the S1 domain interactions across neighboring protomers, which include the RBD-NTD cross chain interactions, showed significant energetic differences between Up-Down and Down-Down neighboring protomers. Surprisingly, the Up-Down, RBD-NTD interactions were overall stronger and more numerous than the Down-Down cross chain interactions, including the appearance of the three residue sequence ALA520-PRO521-ALA522 associated with a turn structure in the RBD of the Up state protomer. Additionally, our intrachain dominant energy mappings within each protomer, identified a significant "glue" point or possible "latch" for the Down state protomer between the S1 subdomain, SD1, and the RBD domain of the same protomer that was completely missing in the Up state protomer analysis. Ironically, this dominant energetic interaction in the Down state protomer involved the backbone atoms of the same three residue sequence ALA520-PRO521-ALA522 of the RBD with the R-group of GLN564 in the SD1 domain. Thus, this same three residue sequence acts as a stabilizer of the RBD in the Up conformation through its interactions with its neighboring NTD chain and a kind of latch in the Down state conformation through its interactions with its own SD1 domain. The dominant interaction energy residues identified here are also conserved across reported variations of SARS-Cov-2, as well as the closely related virions SARS-Cov and the bat corona virus RatG13. To help verify the potential latch for the Down state protomer, we conducted some preliminary molecular dynamic simulations that effectively turn off this specific latch glue point via a single point mutation of GLN564. Interestingly, the single point mutation lead to the latch releasing in less than a few nanoseconds, but the latch remained fixed in the wild state protomer for up to 0.1 microseconds that were simulated. Many more detailed studies are needed to understand the dynamics of the Up and Down states of the Spike protein, including the stabilizing chain-chain interactions and the mechanisms of transition from Down to Up state protomers. Nonetheless, static dominant energy landscape mappings and preliminary molecular dynamic studies given here may represent a useful starting point for more detailed dynamic analyses and hopefully an improved understanding of the structure-function relationship of this highly complex protein associated with COVID-19.

Generalized Entropy Generation Expressions in Gases.

In this study, we generalize our previous methods for obtaining entropy generation in gases without the need to carry through a specific expansion method, such as the Chapman-Enskog method. The generalization, which is based on a scaling analysis, allows for the study of entropy generation in gases for any arbitrary state of the gas and consistently across the conservation equations of mass, momentum, energy, and entropy. Thus, it is shown that it is theoretically possible to alter specific expressions and associated physical outcomes for entropy generation by changing the operating process gas state to regions significantly different than the perturbed, local equilibrium or Chapman-Enskog type state. Such flows could include, for example, hypersonic flows or flows that may be generally called hyper-equilibrium state flows. Our formal scaling analysis also provides partial insight into the nature of entropy generation from an informatics perspective, where we specifically demonstrate the association of entropy generation in gases with uncertainty generated by the approximation error associated with density function expansions.

Targeting HIV-1 Envelope Proteins Using a Fragment Discovery All-Atom Computational Algorithm.

INTRODUCTION: HIV viral envelope proteins are targets for small inhibitor molecules aimed at disrupting the cellular entry process. Potential peptide-class inhibitor molecules (rDNA drugs) have been previously identified, with mixed results, through biomimicry and phage display experimental methods. Here we describe a new approach based on computational fragment discovery. The method has the potential to not only optimize peptide binding affinity but also to rapidly produce alternative inhibitors against mutated strains. METHODS: A comprehensive, all-atom implicit solvent method is used to bombard the C-heptad repeat unit of HIV-1 target envelope protein GP41 with single D-amino acid residues as they exist in their native state. A nascent peptide computational search process then identifies potential favorable sequences of attached ligands based on four peptide bond criteria. Finally, dynamic simulations of nascent peptides attached to host targets help refine potential peptide inhibitors for experimental HIV-1 challenge assays and testing. RESULTS AND DISCUSSION: Initial testing of the method was done using 64,000 total ligands of D-amino acid residues at a total computational time of 0.05 microseconds per ligand, which resulted in several thousand attached ligands. Peptide bond criteria search employing three of the four bond constraints with a tolerance of 20 percent, resulted in four potential peptide inhibitors of 5 to 6 residues in length. Only one of the four peptides demonstrated IC50 values and partial viral inhibition based on cell challenge assays using CEM-SS host cells. That peptide inhibitor also computationally demonstrated long-time attachment and stability to a helical groove in its C-heptad target. This initial testing of peptide fragment discovery against HIV-1 has helped us refine the protocols and identify key areas of improvement. CONCLUSION: Our methods demonstrate the potential to design efficient peptide inhibitors to viral target proteins based on an all-atom dynamic simulation and using a ligand library as fragments of potential nascent peptides. Our methods can be greatly improved through the use of higher numbers of ligands, increased time of bombardment, and tighter constraints on the peptide bond search step. Our method may be important in the need to rapidly respond to target mutations and to advance multiple targeting methods based multiple peptide inhibitors.

Few Ramachandran Angle Changes Provide Interaction Strength Increase in Aß42 versus Aß40 Amyloid Fibrils.

The pathology of Alzheimer's disease can ultimately be traced to the increased aggregation stability of Aß42 peptides which possess two extra residues (Ile 41 &Ala 42) that the non-pathological strain (Aß40) lacks. We have found Aß42 fibrils to exhibit stronger energies in inter-chain interactions and we have also identified the cause for this increase to be the result of different Ramachandran angle values in certain residues of the Aß42 strain compared to Aß40. These unique angle configurations result in the peptide planes in the fibril structures to be more vertical along the fibril axis for Aß42 which thus reduces the inter-atomic distance between interacting atoms on vicinal peptide chains thereby increasing the electrostatic interaction energies. We lastly postulate that these different Ramachandran angle values could possibly be traced to the unique conformational folding avenues sampled by the Aß42 peptide owing to the presence of its two extra residues.

A simple contact mapping algorithm for identifying potential peptide mimetics in protein-protein interaction partners.

A simple, static contact mapping algorithm has been developed as a first step at identifying potential peptide biomimetics from protein interaction partner structure files. This rapid and simple mapping algorithm, "OpenContact" provides screened or parsed protein interaction files based on specified criteria for interatomic separation distances and interatomic potential interactions. The algorithm, which uses all-atom Amber03 force field models, was blindly tested on several unrelated cases from the literature where potential peptide mimetics have been experimentally developed to varying degrees of success. In all cases, the screening algorithm efficiently predicted proposed or potential peptide biomimetics, or close variations thereof, and provided complete atom-atom interaction data necessary for further detailed analysis and drug development. In addition, we used the static parsing/mapping method to develop a peptide mimetic to the cancer protein target, epidermal growth factor receptor. In this case, secondary, loop structure for the peptide was indicated from the intra-protein mapping, and the peptide was subsequently synthesized and shown to exhibit successful binding to the target protein. The case studies, which all involved experimental peptide drug advancement, illustrate many of the challenges associated with the development of peptide biomimetics, in general.

Langevin dynamics for the transport of flexible biological macromolecules in confined geometries.

The transport of flexible biological macromolecules in confined geometries is found in a variety of important biophysical systems including biomolecular movements through pores in cell walls, vesicle walls, and synthetic nanopores for sequencing methods. In this study, we extend our previous analysis of the Fokker-Planck and Langevin dynamics for describing the coupled translational and rotational motions of single structured macromolecules near structured external surfaces or walls [M. H. Peters, J. Chem. Phys. 110, 528 (1999); 112, 5488 (2000)] to the problem of many interacting macromolecules in the presence of structured external surfaces representing the confining geometry. Overall macromolecular flexibility is modeled through specified interaction potentials between the structured Brownian subunits (B-particles), as already demonstrated for protein and DNA molecules briefly reviewed here. We derive the Fokker-Planck equation using a formal multiple time scale perturbation expansion of the Liouville equation for the entire system, i.e., solvent, macromolecules, and external surface. A configurational-orientational Langevin displacement equation is also obtained for use in Brownian dynamics applications. We demonstrate important effects of the external surface on implicit solvent forces through formal descriptions of the grand friction tensor and equilibrium average force of the solvent on the B-particles. The formal analysis provides both transparency of all terms of the Langevin displacement equation as well as a prescription for their determination. As an example, application of the methods developed, the real-time movement of an α-helix protein through a carbon nanotube is simulated.

Brownian diffusion and surface kinetics of liposome and viral particle uptake by human lung cancer cells in-vitro.

In this study, the simultaneous roles of transport, diffusion, and surface kinetic uptake of liposome (Lip-FD), adenoviral (AD-Cy2), and liposome-adenoviral complex (lip-FD-Ad) particles by a non-small cell human lung cancer (A549) were examined through a coupling of in vitro experimental and mathematical modeling techniques. Experimentally, quantitative fluorescence spectroscopy was used to monitor time dependent particle uptake rates including low temperature (5 degrees C) conditions where endocytosis could be inhibited. Mathematically, analytic solutions to the Brownian particle diffusion equation with Langmuir type boundary conditions for the adsoprtion, desorption, and endocytosis process, were obtained for both unsteady and steady-state (no endocytosis) conditions. By direct comparisons of experimental data to model solutions, the adsorption constants, desorption constants, and number of cell surface receptor sites were determined for all particle types considered. It was found that the particle adsorption and desorption constants were of the same order of magnitude compared to earlier studies (Singh, M., T. Ghose, G. Faulkner, and M. Mezei. Cancer Res. 49:3976-3984, 1990.) using different cell lines, particle types, and methodologies. Also in agreement with previous studies using differing cell lines and methodologies (Miller, C. R., B. Boundurant, S. D. McLeon, K. A. McGovern, and D. F. O'Brien. Biochemistry 37:12875-12883, 1998; Perry, D. G., and W. J. Martin II. J. Immunol. Methods 181:269-285, 1995; Muller, W. J., K. Zen, A. B. Fisher, and H. Shuman. Am. J. Physiol. L11-L19, 1995), the number of cell surface receptor sites was predicted to be several orders of magnitude higher for liposome and liposome-viral complex than for viral particles alone, suggesting a nonspecific or nonrestrictive binding pattern for liposomes and liposome complexes and a specific or restrictive binding pattern for viral particles. The surface kinetic constants obtained here for the A549 cells may be useful in physiological modeling or pharmacokinetic applications of chemical or genetic carrying particles in the treatment of lung cancer and other lung diseases. Furthermore, the methodologies given here are straightforward and can be applied to other particle-cell uptake systems.

Nonequilibrium, multiple-timescale simulations of ligand-receptor interactions in structured protein systems.

Predicting the long-time, nonequilibrium dynamics of receptor-ligand interactions for structured proteins in a host fluid is a formidable task, but of great importance to predicting and analyzing cell-signaling processes and small molecule drug efficacies. Such processes take place on timescales on the order of milliseconds to seconds, so "brute-force" real-time, molecular or atomic simulations to determine absolute ligand-binding rates to receptor targets and over a statistical ensemble of systems are not currently feasible. In the current study, we implement on real protein systems a previously developed 3-5 hybrid molecular dynamics/Brownian dynamics algorithm, which takes advantage of the underlying, disparate timescales involved and overcomes the limitations of brute-force approaches. The algorithm is based on a multiple timescale analysis of the total system Hamiltonian, including all atomic and molecular structure information for the system: water, ligand, and receptor. In general, the method can account for the complex hydrodynamic, translational-orientational diffusion aspects of ligand-docking dynamics as well as predict the actual or absolute rates of ligand binding. To test some of the underlying features of the method, simulations were conducted here for an artificially constructed spherical protein "made" from the real protein insulin. Excellent comparisons of simulation calculations of the so-called grand particle friction tensor to analytical values were obtained for this system when protein charge effects were neglected. When protein charges were included, we found anomalous results caused by the alteration of the spatial, microscopic structure of water proximal to the protein surface. Protein charge effects were found to be highly significant and consistent with the recent hypothesis of Hoppert and Mayer (Am Sci 1999;87:518-525) for charged macromolecules in water, which involves the formation of a "water dense region" proximal to the charged protein surface followed by a "dilute water region." We further studied the algorithm on a D-peptide/HIV capside protein system and demonstrated the algorithms utility to study the nonequilibrium docking dynamics in this contemporary problem. In general, protein charge effects, which alter water structural properties in an anomalous fashion proximal to the protein surface, were found to be much more important than the so-called hydrodynamic interaction effects between ligand and receptor. The diminished role of hydrodynamic interactions in protein systems allows for a much simpler overall dynamic algorithm for the nonequilibrium protein-docking process. Further studies are now underway to critically examine this simpler overall algorithm in analyzing the nonequilibrium protein-docking problem.