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Coronavirus SARS-CoV-2 infects host cells via binding to the cell receptor ACE2 with its spike proteins. Atomistic molecular dynamics simulations reveal that the receptor binding domain (RBD) of spike protein can tightly bind to both open and closed ACE2 receptors, mostly by specific interactions between RBD and ACE2 N-terminal helices. The water molecules residing at the RBD-ACE2 interface play critical roles in stabilizing the complex structure: on average about 15 water mo [Detail] ...
Download cover Download table of contentsIn May 1985 there was at University of California Santa Cruz an influential meeting that was the first serious discussion of sequencing the entire human genome. The author was one of the participants and described the meeting and related issues.
COVID-19 is now rapidly spreading worldwide. While the majority of COVID-19 patients show only mild or moderate symptoms, some could deteriorate quickly and may succumb to a sudden death. It is therefore important to identify who will be more likely to develop severe outcomes and be treated with particular or preventive care. Here in this literature survey, we collected epidemiologic and clinical data from 36 articles on 51,270 patients with different severity of COVID-19, aiming to characterize the population that are prone to severe condition and bad outcomes. These data reveal that old males and those with high BMI or underlying diseases, especially cardiovascular disease, hypertension and diabetes, are overrepresented among severe cases. High leukocyte and lymphopenia are common features in severe and critical patients. Upon deterioration of the disease, both CD4+ and CD8+ T cells are decreased, while almost all serum cytokines, especially pro-inflammatory cytokines, increased.
Background: Microfluidic systems have advantages such as a high throughput, small reaction volume, and precise control of the cellular position and environment. These advantages have allowed microfluidics to be widely used in several fields of synthetic biology in recent years.
Results: In this article, we reviewed the microfluidic-based methods for synthetic biology from two aspects: the construction of synthetic gene circuits and the analysis of synthetic gene systems. We used some examples to illuminate the progresses and challenges in the steps of synthetic gene circuits construction and approaches of gene expression analysis with microfluidic systems.
Conclusion: Comparing to traditional methods, microfluidic tools promise great advantages in the synthetic genetic circuit building and analysis process. Moreover, new microfluidic systems together with the mathematical modeling of synthetic circuits or consortiums are desirable to perform complex genetic circuit construction and understand the natural gene regulation in cells and population interactions better.
Background: A novel coronavirus (the SARS-CoV-2) has been identified in January 2020 as the causal pathogen for COVID-19 , a pandemic started near the end of 2019. The Angiotensin converting enzyme 2 protein (ACE2) utilized by the SARS-CoV as a receptor was found to facilitate the infection of SARS-CoV-2, initiated by the binding of the spike protein to human ACE2.
Methods: Using homology modeling and molecular dynamics (MD) simulation methods, we report here the detailed structure and dynamics of the ACE2 in complex with the receptor binding domain (RBD) of the SARS-CoV-2 spike protein.
Results: The predicted model is highly consistent with the experimentally determined structures, validating the homology modeling results. Besides the binding interface reported in the crystal structures, novel binding poses are revealed from all-atom MD simulations. The simulation data are used to identify critical residues at the complex interface and provide more details about the interactions between the SARS-CoV-2 RBD and human ACE2.
Conclusion: Simulations reveal that RBD binds to both open and closed state of ACE2. Two human ACE2 mutants and rat ACE2 are modeled to study the mutation effects on RBD binding to ACE2. The simulations show that the N-terminal helix and the K353 are very important for the tight binding of the complex, the mutants are found to alter the binding modes of the CoV2-RBD to ACE2.
Background: The lipostatic set-point theory, ascribing fat mass homeostasis to leptin mediated central feedback regulation targeting the body’s fat storage, has caused a variety of conundrums. We recently proposed a leanocentric locking-point theory and the corresponding mathematical model, which not only resolve these conundrums but also provide valuable insights into weight control and health assessment. This paper aims to further test the leanocentric theory.
Methods: Partial lipectomy is a touchstone to test both the leanocentric and lipostatic theories. Here we perform in silico lipectomy by using a mathematical model embodying the leanocentric theory to simulate the long-term body fat change after removing some fat cells in the body.
Results: The mathematical modeling uncovers a phenomenon called post-surgical fat loss, which was well-documented in real partial lipectomy surgeries; thus, the phenomenon can serve as an empirical support to the leanocentric theory. On the other hand, the leanocentric theory, but not the lipostatic theory, can well explain the post-surgical fat loss.
Conclusions: The leanocentric locking-point theory is a promising theory and deserves further testing. Partial lipectomy surgeries are beneficial to obese patients for quite a long period.
Background: The COVID-19 pandemic has become a formidable threat to global health and economy. The coronavirus SARS-CoV-2 that causes COVID-19 is known to spread by human-to-human transmission, and in about 40% cases, the exposed individuals are asymptomatic which makes it difficult to contain the virus.
Methods: This paper presents a modified SEIR epidemiological model and uses concepts of optimal control theory for analysis of the effects of intervention methods of the COVID19. Fundamentally the pandemic intervention problem can be viewed as a mathematical optimization problem as there are contradictory outcomes in terms of reduced infection and fatalities but with serious economic downturns.
Results: Concepts of optimal control theory have been used to determine the optimal control (intervention) levels of i) social contact mitigation and suppression, and ii) pharmaceutical intervention modalities, with minimum impacts on the economy. Numerical results show that with optimal intervention policies, there is a significant reduction in the number of infections and fatalities. The computed optimum intervention policy also provides a timeline of systematic enforcement and relaxation of stay-at-home regulations, and an estimate of the peak time and number of hospitalized critical care patients.
Conclusion: The proposed method could be used by local and state governments in planning effective strategies in combating the pandemic. The optimum intervention policy provides the necessary lead time to establish necessary field hospitals before getting overwhelmed by new patient arrivals. Our results also allow the local and state governments to relax social contact suppression guidelines in an orderly manner without triggering a second wave.
Background: Now the coronavirus disease 2019 (COVID-19) epidemic becomes a global phenomenon and its development concerns billions of peoples’ lives. The development of the COVID-19 epidemic in China could be used as a reference for the other countries’ control strategy.
Methods: We used a classical susceptible-infected-recovered (SIR) model to forecast the development of the COVID-19 epidemic in China by nowcasting. The linear regression analyses were employed to predict the COVID-19 epidemic’s inflexion point. Finally, we used a susceptible-exposed-infected-recovered (SEIR) model to simulate the development of the COVID-19 epidemic in China throughout 2020.
Results: Our nowcasts show that the COVID-19 transmission rate started to slow down on January 30. The linear regression analyses further show that the inflexion point of this epidemic would arrive between February 17 and 18. The final SEIR model simulation forecasted that the COVID-19 epidemic would probably infect about 82,000 people and last throughout 2020 in China. We also applied our method to USA’s and global COVID-19 data and the nowcasts show that the development of COVID-19 pandemic is not optimistic in the rest of 2020.
Conclusion: The COVID-19 epidemic’s scale in China is much smaller than the previous estimations. After implemented strict control and prevention measures, such as city lockdown, it took a week to slow down the COVID-19 transmission and about four weeks to really mitigate the COVID-19 prevalence in China.
