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In episode 20, I start by asking Rommie how their research on the SARS-CoV-2 virus first unfolded during the early days of the pandemic, and from this story, we move on to discuss her original motivation to study large complex systems. We touch upon the exciting experimental developments that enable the realistic modeling of systems as big as entire viruses, and highlight some unexpected findings that came out of the large-scale simulations. Rommie also shares her reflections about the collaboration-driven nature of her lab and the complexities involved in interdisciplinary communication, and we wrap up with a few thoughts about the AI-driven brain drain from academia to industry.
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In episode 19, Alex and I discuss the history and future of developments in the CHARMM family of force fields, and whether Alex believes there is more physics that we need to include in our classical energy functions to work around our current challenges in biomolecular modeling. Throughout the conversation, he's advocated for a pragmatic, down-to-earth approach, with the idea of "big molecules, small physics". Alex also highlights the need to augment AI tools with HI, or human intelligence, arguing that so far most attempts at automating model development too much end up with parameters that are unphysical and non-transferable. Yet another interesting point is our often surprising reliance on truly ancient experimental data, and we try to make a point that these very non-sexy physical chemistry measurements straight from the 60s and 70s could truly advance the field if anyone was willing to fund them and actually get them done.
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In Episode 18, Erik Lindahl reminds us that despite our dependence on computational power and advanced technology, real breakthroughs are often waiting for those who have the patience to think carefully, come up with eye-opening ideas, and follow their sense of purpose. We discuss the different ways to be smart in science, highlighting the paradoxical need for both complexity and simplicity in thinking, and talk about what kind of questions in biology will keep us all busy for decades to come. Finally, Erik shares the story behind his series of lectures on concepts in molecular biophysics, a great component of the curriculum of every scientist in the field.
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In episode seventeen, Caroline Lynn Kamerlin talks about the art of asking bold and impactful scientific questions, as well as how to engage in truly interdisciplinary research, something she sees as a consequence of her formal background in natural philosophy. We talk about the emerging concepts around enzyme promiscuity, how this view has steadily become accepted in the field, and how it affects not only research but also human lives. That leads us to consider the ever-emerging problem of bacterial resistance and public health, and since public health is just two steps away from science education, we do venture there too.
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In the sixteenth episode, Janusz Bujnicki tells me about his early switch to bioinformatics, a stroke of serendipity that defined his future career, and how he later managed to reincorporate both biophysics and experimental biology into his research agenda. We talk about the current state of the field of RNA structural prediction, and how we need to bring together physics and data to tackle the ever more complex biological questions that show up on the horizon. Then, we switch gears to discuss the fascinating world of science advisors for policy-making, or to what extent our scientific knowledge can be employed to shape long-term policies, including the blurry borders between science, philosophy and politics. I think it's a laudable aspiration for many of us to understand how we can have a tangible impact on the real world while keeping our humility in check.
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In the fifteenth episode, Paulo Souza and I discuss the challenges inherent in managing a project of such a scope, and the philosophy behind the systematic way in which Martini is continuously improved and reparameterized. Paulo describes how a user-centric approach helps refine and troubleshoot the model through its widescale adoption, and how different inherent limitations of coarse-grained modeling can be addressed to progressively make the force field more predictive and less reliant on user-defined biases. Then, we talk about the interplay between force field development and modern trends in biology, biomedicine and computational sciences - from small molecules to lipid nanoparticles, huge systems such as organelles or viruses, and molecular complexity, understood as going beyond simplified model systems and approaching biologically relevant mixtures and compositions.
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In the fourteenth episode, Syma Khalid and I talk about the challenges we're faced with when trying to understand the environment of the bacterial cell envelope, and the outer membrane in particular. We discuss how the lessons taken from the computational study of these structures can inform the design of future antibacterial agents. Then, we move on to consider strategies for making the scientific environment of one's research group a place to thrive, develop, and live a happy and fulfilling life.
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In the thirteenth episode, Daniel Zuckerman and I talk about textbooks on statistical biophysics and a physics-based vision of biology, a few of which he himself authored. Daniel reveals that his passion for clarity in writing comes from his early humanities background, and makes a case for how well-thought and physically motivated narratives can unlock profound insights into the inner workings of biology. Then, we move on to discuss the physical theory behind trajectory ensembles, Daniel's preferred lens through which to view statistical mechanics. We dissect the strengths and limitations of this approach, and let ourselves speculate about its future evolution.
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In the twelfth episode, Vlad Cojocaru and I discuss how the simulation field can integrate further layers of complexity in modeling transcription control and genome organization in humans. Vlad shares his insights on the computational biology of transcription factors, including DNA-mediated allostery and pioneer transcription factors, which are crucial for cellular reprogramming. Our discussion then shifts to the underexplored topic of researchers' returning to our home countries as group leaders. We examine the hopes, fears, and conditions for success in making this transition, aiming to rewrite common narratives from our unique perspectives.
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In the eleventh episode, Justin Lemkul and I talk about the motivations and challenges behind providing technical help on online forums and mailing lists. Justin shares his story of becoming a prolific technical advisor for the Gromacs community, which evolves into a discussion about automatability, the role of expertise in running and documenting simulation-based projects, and the incentives for people who contribute their time to helping the community. We then move on to discuss polarizable force fields for nucleic acids, including the problems they might help solve and the practical ways in which we might arrive at these solutions. We conclude by pointing out the need for more nuanced undergraduate curricula that reflect the current open questions in nucleic acids research to attract students who will make the future discoveries.
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In the tenth episode, Ariane Nunes-Alves and I talk about a kinetics-centric view of drug design, making the case that modeling kinetics in atomistic simulation is an important frontier that, despite clear biomedical relevance, is rarely explicitly addressed either in model parameterization or with the latest AI methods. We discuss the need to turn to a more explicit image of the drug's pathway towards its target, including not only affinities and residence times, but also the cellular environment. Then, we switch to the social sphere to discuss how much of a PI's professional time circles around interpersonal interactions, and where can we computational scientists go to find our community in the era of fragmentation and specialization of social media.
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In the ninth episode, Michele Vendruscolo and I discuss the current state of research on misfolding diseases, typically associated with excessive protein aggregation and formation of insoluble amyloids. Michele presents an optimistic perspective in which the convergence of recent clinical and software developments opens up new avenues for efficient treatment of such debilitating conditions as Alzheimer's and Parkinson's disease. This interconnection between the everyday work of scientists and the experience and outlook of affected individuals inspires us to reflect on the societal responsibilities of a scientist, from disseminating our results to inspiring newcomers to engage with urgent global crises to mentoring the next generation of problem-solvers and revolutionary thinkers.
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In this episode, I'm attempting to string together the most common threads brought up by my guests in the first eight interviews on the podcast. Reflecting on these conversations, I'm suggesting some grand challenges for the field in the years to come.
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In the eight episode, Rossen Apostolov and I depart from the standard format to talk about the core concepts behind BioExcel, the European Center of Excellence for computational biology. We discuss their main objectives and challenges, from working with code to organizing schools and webinars, talk about the challenges of sustaining funding through maintaining excellence in research, and review ways to share the gained experience with the broader computational world to inspire similar ventures elsewhere. It is a partial attempt to answer questions raised in previous conversations by pointing to existing models for international collaboration across many subfields.
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In the seventh episode, Aleksei Aksimentiev and I delve into the intersection of physics, biology, and nanotechnology, exploring the innovative world of nanopores and biomolecular sequencing. Aleksei shares his journey from particle physics in Ukraine to leading-edge research in the US, and underscores how on the unpredictable path of scientific discovery, openness to new ideas can lead to groundbreaking advancements. Alongside, we discuss the pivotal role of mentorship in fostering scientific curiosity and the pursuit of ambitious goals, illustrating how a supportive mentor can be the key to unlocking potential and driving forward the frontier of biophysics.
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In the sixth episode, Giulia Palermo and I discuss the challenges of studying truly multiscale biomolecular systems, such as the CRISPR/Cas9 complex she famously got involved with. While such problems can take us way out of our comfort zones, they also provide us with clear pathways to innovative and transformative science, something very much needed in the new revolutionary era of RNA biology. In this vein, Giulia also reflects on the nature of scientific creativity, the component that goes beyond our formal training but that can eventually spell the difference between a groundbreaking discovery and run-of-the-mill research.
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In the fifth episode, Paul Robustelli and I discuss how the once very sharp boundary between academia and industry has been becoming increasingly porous, and what implications it will have for future careers in science. Paul shares his experiences and observations about the competing models of funding scientific research, and makes a point that they can eventually synergize rather than compete. We also talk about the often neglected creative or artistic nature of scientists, and how we can use it to better connect with other scientists in a more genuine way.
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In the fourth episode, Modesto Orozco and I talk about the rough path to the predictive power modern computational science has achieved in biology, and the immense possibilities it opens to today's computational biologists working across the scales of space and time. Modesto also reflects on why sharing simulation data is crucial to make sure that our results are trustworthy, and how access to other people's simulations can become a gold mine in the data-driven era of computer modeling.
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In the third episode, Wojtek Kopeć and I discuss the overlooked yet exciting social aspect of scientific collaboration, and what the world of academia could learn from the industry and statisticians to avoid falling behind. Wojtek also shares his personal experience of starting a lab as a new PI, and we reflect on the role of honesty on social media in addressing the hardships of being a scientist.
- Visa fler
