Structural Dynamics Predominantly Determine the Adaptability of Proteins to Amino Acid Deletions.

The insertion or deletion (indel) of amino acids has a variety of effects on protein function, ranging from disease-forming changes to gaining new functions. Despite their importance, indels have not been systematically characterized towards protein engineering or modification goals. In the present work, we focus on deletions composed of multiple contiguous amino acids (mAA-dels) and their effects on the protein (mutant) folding ability. Our analysis reveals that the mutant retains the native fold when the mAA-del obeys well-defined structural dynamics properties: localization in intrinsically flexible regions, showing low resistance to mechanical stress, and separation from allosteric signaling paths. Motivated by the possibility of distinguishing the features that underlie the adaptability of proteins to mAA-dels, and by the rapid evaluation of these features using elastic network models, we developed a positive-unlabeled learning-based classifier that can be adopted for protein design purposes. Trained on a consolidated set of features, including those reflecting the intrinsic dynamics of the regions where the mAA-dels occur, the new classifier yields a high recall of 84.3% for identifying mAA-dels that are stably tolerated by the protein. The comparative examination of the relative contribution of different features to the prediction reveals the dominant role of structural dynamics in enabling the adaptation of the mutant to mAA-del without disrupting the native fold.

Immune escape facilitation by mutations of epitope residues in RdRp of SARS-CoV-2.

Mutations drive viral evolution and genome variability that causes viruses to escape host immunity and to develop drug resistance. SARS-CoV-2 has considerably higher mutation rate. SARS-CoV-2 possesses a RNA dependent RNA polymerase (RdRp) which helps to replicate its genome. The mutation P323L in RdRp is associated with the loss of a particular epitope (321-327) from this protein. We consider the effects of mutations in some of the epitope region including the naturally occurring mutation P323L on the structure of the epitope and their interface with paratope using all-atom molecular dynamics (MD) simulation studies. We observe that the mutations cause conformational changes in the epitope region by opening up the region associated with increase in the radius of gyration and intramolecular hydrogen bonds, making the region less accessible. Moreover, we study the conformational stability of the epitope region and epitope:paratope interface under the mutation from the fluctuations in the dihedral angles. We observe that the mutation renders the epitope and the epitope:paratope interface unstable compared to the corresponding wild type ones. Thus, the mutations may help in escaping antibody mediated immunity of the hostCommunicated by Ramaswamy H. Sarma.

High-Throughput Screening for the Potential Inhibitors of SARS-CoV-2 with Essential Dynamic Behavior.

Global health security has been challenged by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Due to the lengthy process of generating vaccinations, it is vital to reposition currently available drugs in order to relieve anti-epidemic tensions and accelerate the development of therapies for Coronavirus Disease 2019 (COVID-19), the public threat caused by SARS-CoV-2. High throughput screening techniques have established their roles in the evaluation of already available medications and the search for novel potential agents with desirable chemical space and more cost-effectiveness. Here, we present the architectural aspects of highthroughput screening for SARS-CoV-2 inhibitors, especially three generations of virtual screening methodologies with structural dynamics: ligand-based screening, receptor-based screening, and machine learning (ML)-based scoring functions (SFs). By outlining the benefits and drawbacks, we hope that researchers will be motivated to adopt these methods in the development of novel anti- SARS-CoV-2 agents.

Unveiling mutation effects on the structural dynamics of the main protease from SARS-CoV-2 with hybrid simulation methods.

The main protease of SARS-CoV-2 (called Mpro or 3CLpro) is essential for processing polyproteins encoded by viral RNA. Several Mpro mutations were found in SARS-CoV-2 variants, which are related to higher transmissibility, pathogenicity, and resistance to neutralization antibodies. Macromolecules adopt several favored conformations in solution depending on their structure and shape, determining their dynamics and function. In this study, we used a hybrid simulation method to generate intermediate structures along the six lowest frequency normal modes and sample the conformational space and characterize the structural dynamics and global motions of WT SARS-CoV-2 Mpro and 48 mutations, including mutations found in P.1, B.1.1.7, B.1.351, B.1.525 and B.1.429+B.1.427 variants. We tried to contribute to the elucidation of the effects of mutation in the structural dynamics of SARS-CoV-2 Mpro. A machine learning analysis was performed following the investigation regarding the influence of the K90R, P99L, P108S, and N151D mutations on the dimeric interface assembling of the SARS-CoV-2 Mpro. The parameters allowed the selection of potential structurally stable dimers, which demonstrated that some single surface aa substitutions not located at the dimeric interface (K90R, P99L, P108S, and N151D) are able to induce significant quaternary changes. Furthermore, our results demonstrated, by a Quantum Mechanics method, the influence of SARS-CoV-2 Mpro mutations on the catalytic mechanism, confirming that only one of the chains of the WT and mutant SARS-CoV-2 Mpros are prone to cleave substrates. Finally, it was also possible to identify the aa residue F140 as an important factor related to the increasing enzymatic reactivity of a significant number of SARS-CoV-2 Mpro conformations generated by the normal modes-based simulations.

Effect on the conformations of the spike protein of SARS-CoV-2 due to mutation.

The spike protein of SARS-CoV-2 mediates receptor binding and cell entry and is the key immunogenic target for virus neutralization and the present attention of many vaccine layouts. It exhibits significant conformational flexibility. We study the structural fluctuations of spike protein among the most common mutations that appeared in the variant of concerns (VOC). We report the thermodynamics of conformational changes in mutant spike protein with respect to the wild-type from the distributions of the dihedral angles obtained from the equilibrium configurations generated via all-atom molecular dynamics simulations. We find that the mutation causes the increase in distance between the N-terminal domain and receptor binding domain, leading to an obtuse angle cosine θ distribution in the trimeric structure in spike protein. Thus, an increase in open state is conferred to the more infectious variants of SARS-CoV-2. The thermodynamically destabilized and disordered residues of receptor binding motif among the mutant variants of spike protein are proposed to serve as better binding sites for the host factor. We identify a short stretch of region connecting the N-terminal domain and receptor binding domain forming a linker loop where many residues undergo stabilization in the open state compared to the closed one.

Design Suggestion of Epidemic Prevention System for Shared Car Based on Scenario and Data

Entering the post-epidemic era, the travel demand for shared cars is increasing day by day. In the normalized epidemic prevention and control, epidemic prevention in shared cars needs to be designed systematically. This paper analyzes the existing risk of COVID-19 propagation based on two perspectives: scenario and data, and discusses the existing means of protection. Then based on the existing measures, the design suggestions are given from two aspects: scenario-based and data-based. Based on the scenario, the layout design and disinfection is implemented in regard to various ways that COVID-19 is transmitted;based on data, travel data integration should be promoted to achieve macro-structural dynamic adjustment and integrated governance from the overall transportation system. In the context of the industries, the shared car industry should response to new trend immediately and implement innovative ideas to obtain a service that is better suited for individuals in the post-epidemic era. In the end, several major functions of design in terms of developing the urban transportation system are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Posttranslational modifications optimize the ability of SARS-CoV-2 spike for effective interaction with host cell receptors.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein is the prime target for vaccines, diagnostics, and therapeutic antibodies against the virus. While anchored in the viral envelope, for effective virulence, the spike needs to maintain structural flexibility to recognize the host cell surface receptors and bind to them, a property that can heavily depend upon the dynamics of the unresolved domains, most prominently the stalk. Construction of the complete, membrane-bound spike model and the description of its dynamics are critical steps in understanding the inner working of this key element of the viral infection by SARS-CoV-2. Combining homology modeling, protein-protein docking, and molecular dynamics (MD) simulations, we have developed a full spike structure in a native membrane. Multimicrosecond MD simulations of this model, the longest known single trajectory of the full spike, reveal conformational dynamics employed by the protein to explore the surface of the host cell. In agreement with cryogenic electron microscopy (cryo-EM), three flexible hinges in the stalk allow for global conformational heterogeneity of spike in the fully glycosylated system mediated by glycan-glycan and glycan-lipid interactions. The dynamical range of the spike is considerably reduced in its nonglycosylated form, confining the area explored by the spike on the host cell surface. Furthermore, palmitoylation of the membrane domain amplifies the local curvature that may prime the fusion. We show that the identified hinge regions are highly conserved in SARS coronaviruses, highlighting their functional importance in enhancing viral infection, and thereby, provide points for discovery of alternative therapeutics against the virus.

Dynamics of Interagency Networks under Stress in Public Health Emergencies: Evidence from China

Disasters are continuously evolving complex processes. Coupling with rapidly changing conditions, response networks must change to meet external needs and adapt to the environment. This study explores the dynamics between stress and structural and functional characteristics of response networks in the centralized political context. Semantic analysis of policy documents shows that unmet needs are an underlying driver of the formation and the dynamics of task-oriented interagency networks. Network analysis shows that the interagency network is a hybrid network that evolves from a decentralized to a centralized structure as stress decreases. Moreover, the leading organizations also shift, which confirms the coordination by feedback in emergency response. After discussing research findings, this study offers recommendations (a) to identify and empower brokers for better coordination and (b) to combine coordination by feedback and coordination by plan. © 2022 Taylor & Francis Group, LLC.

The implications of additive manufacturing technology adoption for supply chain resilience: A systematic search and review

As a disruptive digital technology, adopting additive manufacturing impacts the state and structural dynamics of supply chains, thus affecting their capability to be resilient. Supply chain resilience is essential for business continuity and dealing with unforeseen disruptions such as the COVID-19 pandemic. To date, no research has exclusively investigated the implications of adopting additive manufacturing technology for supply chain resilience, and this study aims to overcome this knowledge gap by using the existing literature and drawing on the dynamic capabilities view. Hence, a systematic search of the literature followed by a critical review of the gathered evidence from 87 peer-reviewed journal papers is performed, leading to the generation of propositions on how additive manufacturing adoption impacts the state of the supply chain, thus influencing certain supply chain capabilities and vulnerabilities that affect supply chain resilience. These propositions provide a research agenda to empirically examine how adopting different processes and applications of additive manufacturing technology can affect supply chain resilience in different industries. Additionally, this study puts forward a detailed framework that indicates how and to what extent adopting additive manufacturing can influence the supply chain capabilities and vulnerabilities that underlie supply chain resilience. While the results suggest that adopting additive manufacturing is expected to improve supply chain resilience by mainly enhancing the state of the supply chain and positively influencing certain supply chain capabilities, it can also cause certain supply chain vulnerabilities to arise, which seem to be interrelated with some of the present additive manufacturing adoption barriers. © 2021 Elsevier B.V.

OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications.

The COVID-19 pandemic unveils unforeseen and unprecedented fragilities in supply chains (SC). A primary stressor of SCs and their subsequent shocks derives from disruption propagation (i.e., the ripple effect) through related networks. In this paper, we conceptualize current state and future research directions on the ripple effect for pandemic context. We scrutinize the existing OR (Operational Research) studies published in international journals dealing with disruption propagation and structural dynamics in SCs. Our study pursues two major contributions in relation to two research questions. First, we collate state-of-the-art research on disruption propagation in SCs and identify a methodical taxonomy along with theories displaying their value and applications for coping with the impacts of pandemics on SCs. Second, we reveal and systemize managerial insights from theory used for operating (adapting) amid a pandemic and during times of recovery, along with becoming more resistant to future pandemics. Streamlining the literature allowed us to reveal several new research tensions and novel categorizations and classifications. The outcomes of our study show that methodical contributions and the resulting managerial insights can be categorized into three levels, i.e., network, process, and control. Our analysis reveals that adaptation capabilities play the most crucial role in managing the SCs under pandemic disruptions. Our findings depict how the existing OR methods can help coping with the ripple effect at five pandemic stages (i.e., Anticipation; Early Detection; Containment; Control and Mitigation; and Elimination) following the WHO classification. The outcomes and findings of our study can be used by industry and researchers alike to progress the decision-support systems guiding SCs amid the COVID-19 pandemic and toward recovery. Suggestions for future research directions are offered and discussed.