Podcast Summary
Understanding Viruses: Intelligence in Simplicity: Professor Dmitri Korkin views viruses as simple, necessary organisms with the ability to modify themselves and function as intelligent machines. Evolution and computational methods help us understand and combat them, while their swarm-like behavior and potential for engineered pandemics pose concerns.
Viruses, though often seen as terrifying, are also fascinating due to their unique ability to function as intelligent machines with incredible simplicity and efficiency. Dmitri Korkin, a bioinformatics professor, views viruses as limited organisms with necessary functions and the ability to modify themselves. He sees their intelligence as lying in their simplicity and their swarm-like behavior. The evolutionary process has played a significant role in their development. While natural pandemics pose a threat, the potential for engineered pandemics is also a concern. Computational methods, such as those used by Korkin's group to map the coronavirus's structure, can help us understand viruses better and develop antiviral drugs and vaccines. Additionally, the history of money, including the emergence of cryptocurrency like Bitcoin, was touched upon as a fascinating parallel to the development of viruses.
Historically dangerous viruses like smallpox are more contagious than current viruses: Smallpox, a historically dangerous virus, is more contagious than current viruses with an R0 value of 5-7 compared to 1.5-3 for coronavirus, and understanding factors like contagion rate, incubation period, and percentage of symptomatic population can help us prepare for and mitigate future outbreaks.
While the possibility of engineering a more dangerous virus is a valid concern, the focus should be on naturally occurring viruses due to their historical prevalence and impact. Smallpox, for instance, was once considered one of the most dangerous viruses with a high contagion rate and long incubation period. Smallpox is a double-stranded DNA virus that is much more contagious than influenza or coronaviruses, with an R0 value of 5-7 compared to 1.5-3 for the current coronavirus. The contagion level of a virus depends on several factors, including its ability to spread through the air, replicate quickly, and survive on surfaces. Additionally, the percentage of the symptomatic population is crucial, as asymptomatic individuals can still spread the virus. The swine flu, for example, infected billions of people with a relatively low fatality rate, highlighting the potential for a virus to rapidly spread through a population. Understanding these factors can help us prepare for and mitigate the impact of future viral outbreaks.
Understanding the origins of COVID-19 through virus mutations: Scientists study mutations in viruses to understand their origins, prevent future pandemics, and potentially create universal vaccines. Ethical considerations surround virus engineering.
The COVID-19 pandemic is a result of a mutation in a coronavirus that allowed it to jump from animals to humans. Scientists are still working to understand the exact mutations that made this possible and how it happened. This research is important for preventing future pandemics and potentially designing universal vaccines. However, there are ethical considerations surrounding the engineering of viruses, as they can't be controlled once released. The dream is to create a universal vaccine that would protect against all strains of a virus, regardless of where it originated. Currently, scientists are keeping an eye on influenza and other emerging viruses as potential threats. The more pathogenic a virus is, the less contagious it tends to be, and vice versa. Understanding these mechanisms can lead to better vaccines and potentially prevent future pandemics.
Viral proteins enable attachment to human cells: Viruses attach to human cells using specific proteins, then hijack ribosomes to produce necessary viral components, replicating within the cell.
Viruses, such as coronavirus, have specific proteins, like the spike protein, which enable them to attach to human cells and infect the body. This attachment process involves the viral particle interacting with human receptors, such as AC2. Once attached, the virus fuses its membrane with the host cell membrane, releasing its RNA and hijacking the host ribosomes to produce necessary viral proteins. The coronavirus particle also has a membrane protein that forms the envelope and helps maintain its shape. While research is ongoing about the function of other proteins, such as the envelope protein, it's clear that viruses rely on these interactions to infect and replicate within human cells. The discovery of vaccines and advancements in our understanding of viral biology have given us powerful tools to combat and even eradicate certain viruses, like smallpox.
Exploring the Proteins of Coronaviruses: Coronaviruses have numerous proteins due to their long RNA strands. Bioinformatics aids in understanding their functions, while collaborations between scientists streamline the discovery process.
The coronavirus, like other viruses, has various proteins that play crucial roles in its structure and function. Three major surface proteins form the viral envelope, while the nucleoprotein protects the viral RNA and creates a capsid. Coronaviruses have significantly more proteins than influenza viruses, with at least 29, due to the longer length of their RNA strands. Researchers use computational methods to infer the functions of these proteins by comparing them to known proteins. However, identifying the functions of truly novel proteins is a more challenging task. Bioinformatics provides data-grounded predictions that help experimental scientists streamline the discovery process. Collaborations between virologists, biochemists, pharmaceutical scientists, and computational scientists are essential for understanding and combating viruses. Despite the complexity of biology, it's surprising yet amazing that we've made significant strides in understanding RNA, DNA, and proteins, including the vast number of proteins in coronaviruses. Computational science's evolution made it inevitable that we would apply it to biology.
Computational Role in Biology: Understanding Proteins and Viruses: Computational science and mathematics play a crucial role in biology, especially in protein folding and virus research. Despite data abundance, extracting key knowledge remains a challenge. Projects like Folding@home show the potential of computational power to advance understanding.
Computer science and mathematics are playing increasingly important roles in the complex field of biology, particularly in understanding the functions of viruses and cells. Biology has made significant strides in recent years with the generation of vast amounts of information about the cell, but there is still a long way to go in processing and extracting key knowledge from this data. Protein folding, a crucial aspect of understanding protein function, remains a major challenge from the computational side. Despite the complexity and intricacy of protein structures, efforts like the Folding@home project demonstrate the potential of harnessing computational power to make progress in this area. Ultimately, the collaboration between computational scientists, data scientists, and biologists will be essential in advancing our understanding of the biological world.
Using machine learning to understand protein folding: Machine learning approaches, such as Folding@home and AlphaFold, are making progress towards understanding and solving protein folding, using vast amounts of structural data to inform their algorithms.
While protein folding is a complex and computationally expensive process, there is hope that machine learning approaches can make significant strides in solving this problem. Proteins typically fold into a canonical form, but they can also adopt different conformations, especially when they consist of multiple structural units called domains. These domains have distinct functions and folds. Protein folding involves the folding of subunits into their respective domains, and then the folding of these domains into the larger 3D structure. Although there is some understanding of the basic mechanisms, we are still struggling to put it all together to fold larger proteins. Machine learning approaches, such as Folding@home, have emerged as promising solutions. While Folding@home was originally designed as a game, it has shown that humans can solve these complex problems. DeepMind's AlphaFold is a learning approach that has shown promising results in recent competitions, indicating that we are making progress towards understanding and solving protein folding. However, we are not yet at the level of AlphaGo or Deep Blue in terms of mastering this problem, but we are getting closer. The vast amount of structural data generated in the past several decades can be summarized, generalized, and used to inform these machine learning approaches.
The power of open data sharing in scientific research: The COVID-19 pandemic highlights the importance of open data sharing and collaboration in scientific research, with the prevalence of preprints and accelerated review cycles reflecting a shift towards prioritizing knowledge over traditional journal publications.
The scientific community's open culture and collaboration have been crucial in the fight against the COVID-19 pandemic. The availability of open protein data sets, such as the Protein Data Bank, has enabled scientists to share and build upon each other's research, leading to rapid advancements in understanding the novel coronavirus's structure and function. This open culture is reflected in the increasing prevalence of preprints and accelerated review cycles, prioritizing the dissemination of knowledge over traditional journal publications. The future of knowledge sharing in science is likely to continue prioritizing transparency and collaboration, allowing for faster and more efficient scientific progress. The discussion touched upon the history of the Protein Data Bank and the importance of open data sharing in scientific research. The COVID-19 pandemic has demonstrated the power of this collaborative approach, with scientists rapidly sharing information and discoveries to better understand and combat the virus. The increasing prevalence of preprints and accelerated review cycles reflects a shift towards prioritizing knowledge over traditional journal publications. The Structural Genomics of SARS-CoV-2 paper discussed in the conversation is an example of this open and collaborative approach, with the researchers sharing their findings as a preprint to make their discoveries available to the scientific community as quickly as possible.
Applying Bioinformatics to Rapidly Understand New Viruses: Bioinformatics plays a crucial role in understanding new viruses by analyzing their genome sequences, identifying potential genes, and defining protein structures. This rapid response can help bridge the gap in resources and accelerate the development of antivirals and vaccines for neglected diseases.
The discovery and study of a new virus, such as the one that caused the outbreak in Wuhan, China in late 2019, can be facilitated through the use of bioinformatics. This was demonstrated when a group of undergraduate students at Worcester Polytechnic Institute conducted a study on a previously discovered coronavirus in the fall of 2019. They were able to understand the structures of the proteins and how they interacted with host proteins, as well as the evolution of the virus. However, they finished their projects just before the news of the new virus emerged. The students then applied their knowledge to the new virus once the genome sequence was released. The genome sequence is the critical first step in understanding a virus, as it contains all the information needed to print the proteins. By comparing the new virus to existing coronaviruses, they were able to identify potential genes and define the boundaries of the genes to identify the proteins and their structures. This demonstrates the power of bioinformatics in the rapid response to new viral outbreaks. Despite the significance of the discovery, the virus in question is considered a neglected disease due to its relatively small impact and lack of resources dedicated to developing new antivirals or vaccines. However, the use of bioinformatics can help bridge this gap and accelerate the understanding and response to new viruses.
Predicting SARS-CoV-2 protein structures using homology modeling and studying protein complexes: Researchers predict SARS-CoV-2 protein structures using similar sequences and study their interactions to understand functions. High accuracy but incomplete coverage.
Researchers use a combination of bioinformatics tools and existing knowledge about similar proteins to predict the 3D structures of SARS-CoV-2 proteins. This process, called homology or template-based modeling, relies on the idea that similar sequences have similar structures. Once the structures are determined, researchers look for protein complexes to understand how proteins interact and perform their functions. These interactions are both structural and functional, meaning they form the protein's structure while also carrying out specific functions. The advantage of using previously solved complexes is the high accuracy of modeling, but the disadvantage is incomplete coverage of all 29 SARS-CoV-2 proteins. The differences between the virus and its closest relatives, SARS and other coronaviruses, are often clustered together in the 3D structure, revealing new insights into the novel coronavirus.
Understanding the new coronavirus through structural analysis: Researchers are studying the new coronavirus's structure to identify potential drug targets and predict interactions using tools like the interactometer. Existing drugs may be effective due to unchanged binding sites, but all predictions need validation through experiments.
The new coronavirus, compared to SARS, shows distinct structural and functional differences. Some proteins are intact, while others are heavily mutated. The binding sites on the viral surface that interact with known small molecules remain unchanged, suggesting that existing drugs may be effective against the new coronavirus. Researchers are currently trying to understand the overall structural characteristics of the virus and predict potential interactions between its proteins using tools like the interactometer. The success of these studies would provide valuable insights into the regions of the virus that could be promising targets for new drugs. The virus is roughly the same size as SARS and MHV, with an average particle size of around 18 nanometers and 50 to 100 spike proteins. These findings are based on both structural knowledge and existing interactions deciphered from related viruses. Overall, this research provides a foundation for understanding the new coronavirus and developing effective treatments. However, all predictions need to be validated through experiments.
Understanding the Complex Structure of a Virus: Recent research challenges the traditional model of a virus as a sphere with spikes, suggesting a more complex structure with implications for designing nanoparticles and vaccines.
Researchers are working to understand the structure of a specific virus by examining its spiky exterior and the elongated, ellipsoid-like particles that make it up. These particles, which are not perfectly symmetric due to imaging limitations and material treatment, have been traditionally modeled as spheres with spikes. However, recent evidence suggests they may be more complex, leading to efforts to create a more accurate model. This research could have implications for designing nanoparticles that mimic the virus and potentially reduce its impact. Viruses are often referred to as particles, and in this context, the term "virion" is used to describe a single virus particle. The virion of the virus under discussion has approximately 5200 spikes and 200 to 400 membrane protein dimers arranged in a lattice on its surface. Occasionally, an envelope protein, which forms a pentameric ring, is also observed. Understanding the structure of the virus is crucial for designing vaccines, which work by training the immune system to recognize and fight the virus. Vaccines can be designed using various methods, including introducing non-functional parts of the virus or creating a virus with no genetic material. The biggest hurdle in vaccine development is ensuring the vaccine is effective and safe.
Understanding Molecular Mechanisms for Vaccines and Antiviral Drugs: Collaborative efforts of scientific community are crucial to combat COVID-19 through both vaccine development and antiviral drugs. Remdesivir is the most promising antiviral drug, but ongoing research is necessary due to uncertainty against new strains.
The current global response to the COVID-19 pandemic involves both the development of vaccines and antiviral drugs. The understanding of the molecular mechanisms of the virus is crucial for designing vaccines and antiviral drugs. Although the accelerated timeline for vaccine development is historically unprecedented, it is essential, especially for the coronavirus crisis. Antiviral drugs, on the other hand, are designed to stop the virus from functioning once an infection occurs. Remdesivir is currently the most promising antiviral drug against SARS-CoV-2, as it blocks a critical function of the virus. However, the efficacy of antiviral drugs against new strains of the virus is uncertain, making ongoing research crucial. In the short term, social distancing measures and wearing masks are the primary methods to fight the pandemic. However, antiviral drugs are seen as a promising short-term solution, especially since they have already been administered in hospitals. The collaborative efforts of the scientific community are crucial in this fight, with ongoing research focusing on understanding the virus's functional and structural aspects to provide potential drug candidates. Ultimately, both vaccines and antiviral drugs are necessary to effectively combat the COVID-19 pandemic.
Understanding the Evolution of Viruses Amidst Uncertainties: The ongoing pandemic highlights the importance of studying viruses' evolution and adapting to new mutations, while following public health guidelines remains crucial.
The ongoing pandemic poses uncertainties for the economy due to the possibility of second waves and potential mutations of the virus. The evolutionary mechanisms of the virus, which allow it to adapt and respond to new antivirals, add to this uncertainty. Viruses, though not living organisms, are remarkable examples of evolution at work, as they hijack the necessary functions from their host cells to survive. The recent discovery of large viruses has led scientists to reconsider the origins and evolution mechanisms of viruses. In the context of the pandemic, aging-based simulations help model the spread of viruses between individuals, providing valuable insights for public health interventions. Despite the complexities of the virus and its evolution, it's essential to follow doctors' advice and precautions to mitigate the risks.
Modeling infectious diseases in confined environments using agent-based simulations: Agent-based simulations allow researchers to model the spread of infectious diseases in confined environments, integrating key parameters and providing real-time insights into the evolution and interaction between the infected and the pathogen.
Researchers have developed an agent-based model to study the spread of infectious diseases, such as Norwalk virus or even fictional viruses like the one from the Contagion movie, in confined environments like cruise ships. By introducing a pathogen agent, they can model the behavior of the virus as well as the hosts, allowing for the integration of key parameters like transmission methods, survival time on surfaces, and viral particle shedding. This approach provides real-time insights into the evolution and interaction between the infected and the pathogen, making it a valuable tool for studying infectious outbreaks in various settings. Agent-based simulations offer a flexible and efficient way to model complex systems, allowing researchers to investigate a wide range of viruses and outbreak scenarios. The addition of a pathogen agent also opens up new possibilities for studying the behavior of the virus itself, providing valuable insights that may not be possible through traditional epidemiological studies.
Understanding the Unique Characteristics of the Virus: Simulations help inform policy decisions, people are most contagious during the first week, masks protect others more than wearers.
The current pandemic has highlighted the importance of understanding the unique characteristics of the virus, particularly its long symptomatic period and potential for asymptomatic transmission. Scientists are using various tools, including agent-based simulations, to gain insights into the dynamics of the infection and inform policy decisions. While these simulations can help compare different intervention methods, they may also offer some predictive capabilities. For instance, recent studies suggest that people are most contagious during the first week of infection, whether symptomatic or asymptomatic. The role of masks in mitigating the spread of the virus is also a topic of ongoing debate, with evidence suggesting that they are more effective at protecting others than the wearer. Overall, the pandemic underscores the need for continued scientific research to better understand the virus and develop effective strategies for containment and prevention.
Masks during pandemics: Balancing distancing and emotional connection: Masks during pandemics help prevent virus spread but can create emotional distance. Historically used during illness outbreaks, they're part of pandemic coping. Personal experiences shared, highlighting complexities of global health crises.
The use of masks during times of high infection rates, like the current COVID-19 pandemic, is a complex issue with both distancing and emotional implications. While masks can help prevent the spread of viruses, they can also create a sense of distance and remove emotional expressions. However, they can also signal care and concern for others' well-being. Historically, during times of widespread illness like the Spanish flu, masks were commonly used. From a psychological perspective, masks can be part of the larger experiment of dealing with the pandemic. The speaker, who was born in Russia, shared their personal experiences of growing up during the Soviet Union's collapse and their passion for science, particularly mathematics. They also noted that while there are strong researchers in their field in Russia, they have not experienced significant difficulties in collaborating with them. Overall, the discussion highlighted the complexities of dealing with a global health crisis and the role of masks in balancing distancing and emotional connection.
A Russian Scientist's Struggles and Inspiration in the Field of AI: A Russian scientist shares their challenges in the AI community, including lack of support and difficulties traveling, but remains inspired by Russian scientific legends and dedicated to their research, inspiring future generations.
The speaker, a scientist, has had a challenging experience with the scientific community in Russia, particularly in the field of artificial intelligence. They feel a lack of support and opportunities for collaboration, leading to difficulties in traveling and maintaining citizenship. However, despite these challenges, the speaker continues to be inspired by Russian scientific greats like Kolmogorov and is optimistic about remote collaborations. The speaker's work in bioinformatics and computer science has given them a new appreciation for the fragility and complexity of human life. Despite the difficulties, they remain dedicated to their research and to inspiring the next generation of scientists. The speaker's collection of science bobbleheads, including those of Watson and Crick, Rosalind Franklin, and Kolmogorov, reflects their fascination with scientific discoveries and the people behind them.
The value of collaboration, resilience, and scientific exploration: Recognizing vulnerability, bonding as a society, and the pursuit of knowledge through scientific research are essential for progress and resilience.
Korkin emphasized the significance of recognizing our vulnerability and the importance of bonding as a society. Furthermore, he expressed hope that scientific research, such as his own, can make a meaningful difference. Wilson's words on the vastness of genetic diversity on Earth further highlight the importance of scientific exploration and discovery. In essence, this conversation underscores the value of collaboration, resilience, and the pursuit of knowledge. If you enjoyed this episode, consider supporting the podcast by downloading Cash App and using the code LexPodcast. Don't forget to subscribe, leave a review, and connect with me on Twitter at Lex Friedman. Thank you for listening, and we'll see you next time.
