SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study.

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Synonymous Mutations Can Alter Protein Dimerization Through Localized Interface Misfolding Involving Self-entanglements.

Synonymous mutations in messenger RNAs (mRNAs) can reduce protein-protein binding substantially without changing the protein's amino acid sequence. Here, we use coarse-grain simulations of protein synthesis, post-translational dynamics, and dimerization to understand how synonymous mutations can influence the dimerization of two E. coli homodimers, oligoribonuclease and ribonuclease T. We synthesize each protein from its wildtype, fastest- and slowest-translating synonymous mRNAs in silico and calculate the ensemble-averaged interaction energy between the resulting dimers. We find synonymous mutations alter oligoribonuclease's dimer properties. Relative to wildtype, the dimer interaction energy becomes 4% and 10% stronger, respectively, when translated from its fastest- and slowest-translating mRNAs. Ribonuclease T dimerization, however, is insensitive to synonymous mutations. The structural and kinetic origin of these changes are misfolded states containing non-covalent lasso-entanglements, many of which structurally perturb the dimer interface, and whose probability of occurrence depends on translation speed. These entangled states are kinetic traps that persist for long time scales. Entanglements cause altered dimerization energies for oligoribonuclease, as there is a large association (odds ratio: 52) between the co-occurrence of non-native self-entanglements and weak-binding dimer conformations. Simulated at all-atom resolution, these entangled structures persist for long timescales, indicating the conclusions are independent of model resolution. Finally, we show that regions of the protein we predict to have changes in entanglement are also structurally perturbed during refolding, as detected by limited-proteolysis mass spectrometry. Thus, non-native changes in entanglement at dimer interfaces is a mechanism through which oligomer structure and stability can be altered.

Deciphering the free energy landscapes of SARS-CoV-2 wild type and Omicron variant interacting with human ACE2.

The binding of the receptor binding domain (RBD) of the SARS-CoV-2 spike protein to the host cell receptor angiotensin-converting enzyme 2 (ACE2) is the first step in human viral infection. Therefore, understanding the mechanism of interaction between RBD and ACE2 at the molecular level is critical for the prevention of COVID-19, as more variants of concern, such as Omicron, appear. Recently, atomic force microscopy has been applied to characterize the free energy landscape of the RBD-ACE2 complex, including estimation of the distance between the transition state and the bound state, xu. Here, using a coarse-grained model and replica-exchange umbrella sampling, we studied the free energy landscape of both the wild type and Omicron subvariants BA.1 and XBB.1.5 interacting with ACE2. In agreement with experiment, we find that the wild type and Omicron subvariants have similar xu values, but Omicron binds ACE2 more strongly than the wild type, having a lower dissociation constant KD.

Identification of potential anti-hyperglycemic compounds in Cordyceps militaris ethyl acetate extract: in vitro and in silico studies.

Cordyceps militaris has been long known for valuable health benefits by folk experience and was recently reported with diabetes-tackling evidences, thus deserving extending efforts on screening for component-activity relationship. In this study, experiments were carried out to find the evidence, justification, and input for computations on the potential against diabetes-related protein structures: PDB-4W93, PDB-3W37, and PDB-4A3A. Liquid chromatography identified 14 bioactive compounds in the ethyl acetate extract (1-14) and quantified the contents of cordycepin (0.11%) and adenosine (0.01%). Bioassays revealed the overall potential of the extract against α-amylase (IC50 = 6.443 ± 0.364 mg.mL-1) and α-glucosidase (IC50 = 2.580 ± 0.194 mg.mL-1). A combination of different computational platforms was used to select the most promising candidates for applications as anti-diabetic bio-inhibitors, i.e. 1 (ground state: -888.49715 a.u.; dipole moment 3.779 Debye; DS¯ -12.3 kcal.mol-1; polarizability 34.7 Å3; logP - 1.30), 10 (ground state: -688.52406 a.u.; dipole moment 5.487 Debye; DS¯ -12.6 kcal.mol-1; polarizability 24.9 Å3; logP - 3.39), and 12 (ground state: -1460.07276 a.u.; dipole moment 3.976 Debye; DS¯ -12.5 kcal.mol-1; polarizability 52.4 Å3; logP - 4.39). The results encourage further experimental tests on cordycepin (1), mannitol (10), and adenosylribose (12) to validate their in-practice diabetes-related activities, thus conducive to hypoglycemic applications.Communicated by Ramaswamy H. Sarma.

Amyloid-ß Tetramers and Divalent Cations at the Membrane/Water Interface: Simple Models Support a Functional Role.

Charge polarization at the membrane interface is a fundamental process in biology. Despite the lower concentration compared to the abundant monovalent ions, the relative abundance of divalent cations (Ca2+, Mg2+, Zn2+, Fe2+, Cu2+) in particular spaces, such as the neuron synapse, raised many questions on the possible effects of free multivalent ions and of the required protection of membranes by the eventual defects caused by the free forms of the cations. In this work, we first applied a recent realistic model of divalent cations to a well-investigated model of a polar lipid bilayer, di-myristoyl phosphatidyl choline (DMPC). The full atomistic model allows a fairly good description of changes in the hydration of charged and polar groups upon the association of cations to lipid atoms. The lipid-bound configurations were analyzed in detail. In parallel, amyloid-ß 1-42 (Aß42) peptides assembled into tetramers were modeled at the surface of the same bilayer. Two of the protein tetramers' models were loaded with four Cu2+ ions, the latter bound as in DMPC-free Aß42 oligomers. The two Cu-bound models differ in the binding topology: one with each Cu ion binding each of the monomers in the tetramer; one with pairs of Cu ions linking two monomers into dimers, forming tetramers as dimers of dimers. The models here described provide hints on the possible role of Cu ions in synaptic plasticity and of Aß42 oligomers in storing the same ions away from lipids. The release of structurally disordered peptides in the synapse can be a mechanism to recover ion homeostasis and lipid membranes from changes in the divalent cation concentration.

Interaction of SARS-CoV-2 with host cells and antibodies: experiment and simulation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the devastating global COVID-19 pandemic announced by WHO in March 2020. Through unprecedented scientific effort, several vaccines, drugs and antibodies have been developed, saving millions of lives, but the fight against COVID-19 continues as immune escape variants of concern such as Delta and Omicron emerge. To develop more effective treatments and to elucidate the side effects caused by vaccines and therapeutic agents, a deeper understanding of the molecular interactions of SARS-CoV-2 with them and human cells is required. With special interest in computational approaches, we will focus on the structure of SARS-CoV-2 and the interaction of its spike protein with human angiotensin-converting enzyme-2 (ACE2) as a prime entry point of the virus into host cells. In addition, other possible viral receptors will be considered. The fusion of viral and human membranes and the interaction of the spike protein with antibodies and nanobodies will be discussed, as well as the effect of SARS-CoV-2 on protein synthesis in host cells.

How soluble misfolded proteins bypass chaperones at the molecular level.

Subpopulations of soluble, misfolded proteins can bypass chaperones within cells. The extent of this phenomenon and how it happens at the molecular level are unknown. Through a meta-analysis of the experimental literature we find that in all quantitative protein refolding studies there is always a subpopulation of soluble but misfolded protein that does not fold in the presence of one or more chaperones, and can take days or longer to do so. Thus, some misfolded subpopulations commonly bypass chaperones. Using multi-scale simulation models we observe that the misfolded structures that bypass various chaperones can do so because their structures are highly native like, leading to a situation where chaperones do not distinguish between the folded and near-native-misfolded states. More broadly, these results provide a mechanism by which long-time scale changes in protein structure and function can persist in cells because some misfolded states can bypass components of the proteostasis machinery.

Is Posttranslational Folding More Efficient Than Refolding from a Denatured State: A Computational Study.

The folding of proteins into their native conformation is a complex process that has been extensively studied over the past half-century. The ribosome, the molecular machine responsible for protein synthesis, is known to interact with nascent proteins, adding further complexity to the protein folding landscape. Consequently, it is unclear whether the folding pathways of proteins are conserved on and off the ribosome. The main question remains: to what extent does the ribosome help proteins fold? To address this question, we used coarse-grained molecular dynamics simulations to compare the mechanisms by which the proteins dihydrofolate reductase, type III chloramphenicol acetyltransferase, and d-alanine-d-alanine ligase B fold during and after vectorial synthesis on the ribosome to folding from the full-length unfolded state in bulk solution. Our results reveal that the influence of the ribosome on protein folding mechanisms varies depending on the size and complexity of the protein. Specifically, for a small protein with a simple fold, the ribosome facilitates efficient folding by helping the nascent protein avoid misfolded conformations. However, for larger and more complex proteins, the ribosome does not promote folding and may contribute to the formation of intermediate misfolded states cotranslationally. These misfolded states persist posttranslationally and do not convert to the native state during the 6 µs runtime of our coarse-grain simulations. Overall, our study highlights the complex interplay between the ribosome and protein folding and provides insight into the mechanisms of protein folding on and off the ribosome.

Unusual Robustness of Neurotransmitter Vesicle Membranes against Serotonin-Induced Perturbations.

Nature confines hundreds of millimolar of amphiphilic neurotransmitters, such as serotonin, in synaptic vesicles. This appears to be a puzzle, as the mechanical properties of lipid bilayer membranes of individual major polar lipid constituents of synaptic vesicles [phosphatidylcholine (PC), phosphatidylethanolamine (PE), and phosphatidylserine (PS)] are significantly affected by serotonin, sometimes even at few millimolar concentrations. These properties are measured by atomic force microscopy, and their results are corroborated by molecular dynamics simulations. Complementary 2H solid-state NMR measurements also show that the lipid acyl chain order parameters are strongly affected by serotonin. The resolution of the puzzle lies in the remarkably different properties displayed by the mixture of these lipids, at molar ratios mimicking those of natural vesicles (PC:PE:PS:Cholesterol = 3:5:2:5). Bilayers constituting of these lipids are minimally perturbed by serotonin, and show only a graded response at physiological concentrations (>100 mM). Significantly, the cholesterol (up to 33% molar ratio) plays only a minor role in dictating these mechanical perturbations, with PC:PE:PS:Cholesterol = 3:5:2:5 and 3:5:2:0 showing similar perturbations. We infer that nature uses an emergent mechanical property of a specific mixture of lipids, all individually vulnerable to serotonin, to appropriately respond to physiological serotonin levels.

Identifying inhibitors of NSP16-NSP10 of SARS-CoV-2 from large databases.

The COVID-19 pandemic, which has already claimed millions of lives, continues to pose a serious threat to human health, requiring the development of new effective drugs. Non-structural proteins of SARS-CoV-2 play an important role in viral replication and infection. Among them, NSP16 (non-structured protein 16) and its cofactor NSP10 (non-structured protein 10) perform C2'-O methylation at the 5' end of the viral RNA, which promotes efficient virus replication. Therefore, the NSP16-NSP10 complex becomes an attractive target for drug development. Using a multi-step virtual screening protocol which includes Lipinski's rule, docking, steered molecular dynamics and umbrella sampling, we searched for potential inhibitors from the PubChem and anti-HIV databases. It has been shown that CID 135566620 compound from PubChem is the best candidate with an inhibition constant in the sub-µM range. The Van der Waals interaction was found to be more important than the electrostatic interaction in the binding affinity of this compound to NSP16-NSP10. Further in vitro and in vivo studies are needed to test the activity of the identified compound against COVID-19.Communicated by Ramaswamy H. Sarma.

Molecular dynamics simulation of cancer cell membrane perforated by shockwave induced bubble collapse.

It has been widely accepted that cancer cells are softer than their normal counterparts. This motivates us to propose, as a proof-of-concept, a method for the efficient delivery of therapeutic agents into cancer cells, while normal cells are less affected. The basic idea of this method is to use a water jet generated by the collapse of the bubble under shockwaves to perforate pores in the cell membrane. Given a combination of shockwave and bubble parameters, the cancer membrane is more susceptible to bending, stretching, and perforating than the normal membrane because the bending modulus of the cancer cell membrane is smaller than that of the normal cell membrane. Therefore, the therapeutic agent delivery into cancer cells is easier than in normal cells. Adopting two well-studied models of the normal and cancer membranes, we perform shockwave induced bubble collapse molecular dynamics simulations to investigate the difference in the response of two membranes over a range of shockwave impulse 15-30 mPa s and bubble diameter 4-10 nm. The simulation shows that the presence of bubbles is essential for generating a water jet, which is required for perforation; otherwise, pores are not formed. Given a set of shockwave impulse and bubble parameters, the pore area in the cancer membrane is always larger than that in the normal membrane. However, a too strong shockwave and/or too large bubble results in too fast disruption of membranes, and pore areas are similar between two membrane types. The pore closure time in the cancer membrane is slower than that in the normal membrane. The implications of our results for applications in real cells are discussed in some details. Our simulation may be useful for encouraging future experimental work on novel approaches for cancer treatment.

Protein aggregation rate depends on mechanical stability of fibrillar structure.

The formation of the fibrillar structure of amyloid proteins/peptides is believed to be associated with neurodegenerative diseases, such as Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. Since the rate of aggregation can influence neurotoxicity, finding the key factors that control this rate is of paramount importance. It was recently found that the rate of protein aggregation is related to the mechanical stability of the fibrillar structure such that the higher the mechanical stability, the faster the fibril is formed. However, this conclusion was supported by a limited dataset. In this work, we expand the previous study to a larger dataset, including the wild type of Aß42 peptide and its 20 mutants, the aggregation rate of which was measured experimentally. By using all-atom steered molecular dynamics (SMD) simulations, we can assess the mechanical stability of the fibril structure, which is characterized by the rupture force, pulling work, and unbinding free energy barrier. Our result confirms that mechanical stability is indeed related to the aggregation rate. Since the estimation of the aggregation rate using all-atom simulations is almost forbidden by the current computational capabilities, our result is useful for predicting it based on information obtained from fast SMD simulations for fibrils.

Antibody-nanobody combination increases their neutralizing activity against SARS-CoV-2 and nanobody H11-H4 is effective against Alpha, Kappa and Delta variants.

The global spread of COVID-19 is devastating health systems and economies worldwide. While the use of vaccines has yielded encouraging results, the emergence of new variants of SARS-CoV-2 shows that combating COVID-19 remains a big challenge. One of the most promising treatments is the use of not only antibodies, but also nanobodies. Recent experimental studies revealed that the combination of antibody and nanobody can significantly improve their neutralizing ability through binding to the SARS-CoV-2 spike protein, but the molecular mechanisms underlying this observation remain largely unknown. In this work, we investigated the binding affinity of the CR3022 antibody and H11-H4 nanobody to the SARS-CoV-2 receptor binding domain (RBD) using molecular modeling. Both all-atom steered molecular dynamics simulations and coarse-grained umbrella sampling showed that, consistent with the experiment, CR3022 associates with RBD more strongly than H11-H4. We predict that the combination of CR3022 and H11-H4 considerably increases their binding affinity to the spike protein. The electrostatic interaction was found to control the association strength of CR3022, but the van der Waals interaction dominates in the case of H11-H4. However, our study for a larger set of nanobodies and antibodies showed that the relative role of these interactions depends on the specific complex. Importantly, we showed Beta, Gamma, Lambda, and Mu variants reduce the H11-H4 activity while Alpha, Kappa and Delta variants increase its neutralizing ability, which is in line with experiment reporting that the nanobody elicited from the llama is very promising for fighting against the Delta variant.

SARS-CoV-2 Omicron Variant Binds to Human Cells More Strongly than the Wild Type: Evidence from Molecular Dynamics Simulation.

The emergence of the variant of concern Omicron (B.1.1.529) of the severe acute respiratory syndrome coronavirus 2 has aggravated the Covid-19 pandemic due to its very contagious ability. The high infection rate may be due to the high binding affinity of Omicron to human cells, but both experimental and computational studies have yielded conflicting results on this issue. Some studies have shown that the Omicron variant binds to human angiotensin-converting enzyme 2 (hACE2) more strongly than the wild type (WT), but other studies have reported comparable binding affinities. To shed light on this open problem, in this work, we calculated the binding free energy of the receptor binding domain (RBD) of the WT and Omicron spike protein to hACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. We showed that Omicron binds to human cells more strongly than the WT due to increased RBD charge, which enhances electrostatic interaction with negatively charged hACE2. N440K, T478K, E484A, Q493R, and Q498R mutations in the RBD have been found to play a critical role in the stability of the RBD-hACE2 complex. The effect of homogeneous and heterogeneous models of glycans coating the viral RBD and the peptidyl domain of hACE2 was examined. Although the total binding free energy is not sensitive to the glycan model, the distribution of per-residue interaction energies depends on it. In addition, glycans have a little effect on the binding affinity of the WT RBD to hACE2.

Determination of Multidirectional Pathways for Ligand Release from the Receptor: A New Approach Based on Differential Evolution.

Steered molecular dynamics (SMD) simulation is a powerful method in computer-aided drug design as it can be used to access the relative binding affinity with high precision but with low computational cost. The success of SMD depends on the choice of the direction along which the ligand is pulled from the receptor-binding site. In most simulations, the unidirectional pathway was used, but in some cases, this choice resulted in the ligand colliding with the complex surface of the exit tunnel. To overcome this difficulty, several variants of SMD with multidirectional pulling have been proposed, but they are not completely devoid of disadvantages. Here, we have proposed to determine the direction of pulling with a simple scoring function that minimizes the receptor-ligand interaction, and an optimization algorithm called differential evolution is used for energy minimization. The effectiveness of our protocol was demonstrated by finding expulsion pathways of Huperzine A and camphor from the binding site of Torpedo California acetylcholinesterase and P450cam proteins, respectively, and comparing them with the previous results obtained using memetic sampling and random acceleration molecular dynamics. In addition, by applying this protocol to a set of ligands bound with LSD1 (lysine specific demethylase 1), we obtained a much higher correlation between the work of pulling force and experimental data on the inhibition constant IC50 compared to that obtained using the unidirectional approach based on minimal steric hindrance.

Amyloid ß Dodecamer Disrupts the Neuronal Membrane More Strongly than the Mature Fibril: Understanding the Role of Oligomers in Neurotoxicity.

The amyloid cascade hypothesis states that senile plaques, composed of amyloid ß (Aß) fibrils, play a key role in Alzheimer's disease (AD). However, recent experiments have shown that Aß oligomers are more toxic to neurons than highly ordered fibrils. The molecular mechanism underlying this observation remains largely unknown. One of the possible scenarios for neurotoxicity is that Aß peptides create pores in the lipid membrane that allow Ca2+ ions to enter cells, resulting in a signal of cell apoptosis. Hence, one might think that oligomers are more toxic due to their higher ability to create ion channels than fibrils. In this work, we study the effect of Aß42 dodecamer and fibrils on a neuronal membrane, which is similar to that observed in AD patients, using all-atom molecular dynamics simulations. Due to short simulation times, we cannot observe the formation of pores, but useful insight on the early events of this process has been obtained. Namely, we showed that dodecamer distorts the lipid membrane to a greater extent than fibrils, which may indicate that ion channels can be more easily formed in the presence of oligomers. Based on this result, we anticipate that oligomers are more toxic than mature fibrils, as observed experimentally. Moreover, the Aß-membrane interaction was found to be governed by the repulsive electrostatic interaction between Aß and the ganglioside GM1 lipid. We calculated the bending and compressibility modulus of the membrane in the absence of Aß and obtained good agreement with the experiment. We predict that the dodecamer will increase the compressibility modulus but has little effect on the bending modulus. Due to the weak interaction with the membrane, fibrils insignificantly change the membrane elastic properties.

Cocktail of REGN Antibodies Binds More Strongly to SARS-CoV-2 Than Its Components, but the Omicron Variant Reduces Its Neutralizing Ability.

A promising approach to combat Covid-19 infections is the development of effective antiviral antibodies that target the SARS-CoV-2 spike protein. Understanding the structures and molecular mechanisms underlying the binding of antibodies to SARS-CoV-2 can contribute to quickly achieving this goal. Recently, a cocktail of REGN10987 and REGN10933 antibodies was shown to be an excellent candidate for the treatment of Covid-19. Here, using all-atom steered molecular dynamics and coarse-grained umbrella sampling, we examine the interactions of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with REGN10987 and REGN10933 separately as well as together. Both computational methods show that REGN10933 binds to RBD more strongly than REGN10987. Importantly, the cocktail binds to RBD (simultaneous binding) more strongly than its components. The dissociation constants of REGN10987-RBD and REGN10933-RBD complexes calculated from the coarse-grained simulations are in good agreement with the experimental data. Thus, REGN10933 is probably a better candidate for treating Covid-19 than REGN10987, although the cocktail appears to neutralize the virus more efficiently than REGN10933 or REGN10987 alone. The association of REGN10987 with RBD is driven by van der Waals interactions, while electrostatic interactions dominate in the case of REGN10933 and the cocktail. We also studied the effectiveness of these antibodies on the two most dangerous variants Delta and Omicron. Consistent with recent experimental reports, our results confirmed that the Omicron variant reduces the neutralizing activity of REGN10933, REGN10987, and REGN10933+REGN10987 with the K417N, N440K, L484A, and Q498R mutations playing a decisive role, while the Delta variant slightly changes their activity.

Elastic moduli of normal and cancer cell membranes revealed by molecular dynamics simulations.

Recent studies indicate that there are mechanical differences between normal cells and cancer cells. Because the cell membrane takes part in a variety of vital processes, we test the hypothesis of whether or not two fundamental alterations in the cell membrane, i.e., the overexpression of phosphatidylserine lipids in the outer leaflet and a reduction in cholesterol concentration, could cause the softening in cancer cells. Adopting ten models of normal and cancer cell membranes, we carry out 1 µs all-atom molecular dynamics simulations to compare the structural properties and elasticity properties of two membrane types. We find that the overexpression of the phosphatidylserine lipids in the outer leaflet does not significantly alter the area per lipid, the membrane thickness, the lipid order parameters and the elasticity moduli of the cancer membranes. However, a reduction in the cholesterol concentration leads to clear changes in those quantities, especially decreases in the bending, tilt and twist moduli. This implies that the reduction of cholesterol concentration in the cancer membranes could contribute to the softening of cancer cells.

Computational Models for the Study of Protein Aggregation.

Protein aggregation has been studied by many groups around the world for many years because it can be the cause of a number of neurodegenerative diseases that have no effective treatment. Obtaining the structure of related fibrils and toxic oligomers, as well as describing the pathways and main factors that govern the self-organization process, is of paramount importance, but it is also very difficult. To solve this problem, experimental and computational methods are often combined to get the most out of each method. The effectiveness of the computational approach largely depends on the construction of a reasonable molecular model. Here we discussed different versions of the four most popular all-atom force fields AMBER, CHARMM, GROMOS, and OPLS, which have been developed for folded and intrinsically disordered proteins, or both. Continuous and discrete coarse-grained models, which were mainly used to study the kinetics of aggregation, are also summarized.

Final Remarks.

Aggregation of biomolecules is responsible for a number of neurodegenerative diseases, but it is also behind the formation of membraneless organelles that are vital to life. There are many novel experimental tools to investigate the phenomenon. There is also a rapid progress in its computational studies, as evidenced by the chapters in this volume.