severe respiratory diseases, pneumonia, and systemic inflammatory response syndrome, leading to a worldwide sustained pandemic. Both SARS-CoV-2 and the original severe acute respiratory syndrome coronavirus (SARS-CoV) enter human cells by protein-protein docking to human angiotensin-converting enzyme 2 (ACE2) on the host cell membrane via CoV spike (S) glycoproteins. A recent experimental study found that the binding affinity between ACE2 and the receptorbinding domain (RBD) of the S protein of SARS-CoV-2 is more than tenfold higher than that of SARS-CoV, which may contribute to the higher infectivity and transmissibility of SARS-CoV-2 compared to SARS-CoV. [1-3] Molecular structures of the S protein of SARS-CoV-2 have been observed at high resolution by using cryo-electron microscopy (cryo-EM). [1,4,5] The complex structures of ACE2 bound to the SARS-CoV-2 S have also been experimentally determined. [6-9] Surprisingly, all these experiments showed that the backbone structures of the RBD of SARS-CoV-2 S are almost same as that of SARS-CoV S (see Figure 1a). [6,10] A molecular dynamic (MD) study has shown that the binding energy of SARS-CoV-2 S to ACE2 is almost same as that of A recent experimental study found that the binding affinity between the cellular receptor human angiotensin-converting enzyme 2 (ACE2) and receptor-binding domain (RBD) in the spike (S) protein of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is more than tenfold higher than that of the original severe acute respiratory syndrome coronavirus (SARS-CoV). However, main chain structures of the SARS-CoV-2 RBD are almost the same with that of the SARS-CoV RBD. Understanding the physical mechanism responsible for the outstanding affinity between the SARS-CoV-2 S and ACE2 is an "urgent challenge" for developing blockers, vaccines, and therapeutic antibodies against the coronavirus disease 2019 (COVID-19) pandemic. Taking into account the mechanisms of hydrophobic interaction, hydration shell, surface tension, and the shielding effect of water molecules, this study reveals a hydrophobic-interaction-based mechanism by means of which SARS-CoV-2 S and ACE2 bind together in an aqueous environment. The hydrophobic interaction between the SARS-CoV-2 S and ACE2 protein is found to be significantly greater than that between SARS-CoV S and ACE2. At the docking site, the hydrophobic portions of the hydrophilic side chains of SARS-CoV-2 S are found to be involved in the hydrophobic interaction between SARS-CoV-2 S and ACE2.

Since 2020, the receptor-binding domain (RBD) of the spike protein of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been constantly mutating, producing most of the notable missense mutations in the context of “variants of concern”, probably in response to the vaccine-driven alteration of immune profiles of the human population. The Delta variant, in particular, has become the most prevalent variant of the epidemic, and it is spreading in countries with the highest vaccination rates, causing the world to face the risk of a new wave of the contagion. Understanding the physical mechanism responsible for the mutation-induced changes in the RBD’s binding affinity, its transmissibility, and its capacity to escape vaccine-induced immunity is the “urgent challenge” in the development of preventive measures, vaccines, and therapeutic antibodies against the coronavirus disease 2019 (COVID-19) pandemic. In this study, entropy–enthalpy compensation and the Gibbs free energy change were used to analyze the impact of the RBD mutations on the binding affinity of SARS-CoV-2 variants with the receptor angiotensin converting enzyme 2 (ACE2) and existing antibodies. Through the analysis, we found that the existing mutations have already covered almost all possible detrimental mutations that could result in an increase of transmissibility, and that a possible mutation in amino-acid position 498 of the RBD can potentially enhance its binding affinity. A new calculation method for the binding energies of protein–protein complexes is proposed based on the entropy–enthalpy compensation rule. All known structures of RBD–antibody complexes and the RBD–ACE2 complex comply with the entropy–enthalpy compensation rule in providing the driving force behind the spontaneous protein–protein docking. The variant-induced risk of breakthrough infections in vaccinated people is attributed to the L452R mutation’s reduction of the binding affinity of many antibodies. Mutations reversing the hydrophobic or hydrophilic performance of residues in the spike RBD potentially cause breakthrough infections of coronaviruses due to the changes in geometric complementarity in the entropy–enthalpy compensations between antibodies and the virus at the binding sites.

The thermal conductivity of monolayer graphene nanoribbons (GNRs) with different tensile strain is investigated by using a nonequilibrium molecular dynamics method. Significant increasing amplitude of the molecular thermal vibration, molecular potential energy vibration and thermal conductivity vibration of stretching GNRs were detected. Some 20%∼30% thermal conductivity decay is found in 9%∼15% tensile strain of GNR cases. It is explained by the fact that GNR structural ridges scatter some low-frequency phonons which pass in the direction perpendicular to the direction of GNR stretching which was indicated by a phonon density of state investigation.

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Molecular dynamics (MD) is appearing in increasing applications in materials science, nanotechnologies, condensed matter physics, computational physics, biochemistry, and biophysics. Finding mechanically static equilibrium configurations of molecular systems is one of the most practical tasks in MD. Most existing potential energy optimization algorithms do not permit searching equilibrium configurations through longer MD trajectories. We introduce a simple method of utilizing a microcanonical (NVE) ensemble to obtain static equilibriums of molecular systems, that is significantly faster than the standard implementations of quick-min (QM) and fast inertial relaxation engine (FIRE) optimization algorithms. The new method is based on the capability of NVE to convert potential energy to kinetic energy. The surprising efficiency of the method is illustrated using an indentation test on monolayer graphene and, in particular, the versatility of the method is illustrated using relaxation of a polystyrene chain through longer MD trajectories and large deformation. The capability of the new method in finding more stable equilibrium configurations than common optimization algorithms is demonstrated in relaxation of a pressured lubricating oil layer and a warped monolayer graphene cantilever.