Phase Space Invaders (ψ)

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In episode 24, Katarzyna talks about the everyday concerns and common threads of an editor's job, from continuously learning about the rapid developments in the field to navigating the review process. She shares some inside stories about the experimental features that journals tinker with these days, and it's good to know that many interesting ideas are being tested out there in the wild. We then discuss a bit about the evolution of the publishing process, including its perception among us research scientists. We largely leave the questions of profits and finance out of the conversation, so this is purely a conversation between two science aficionados who care deeply about the scientific enterprise being transparent, just, open to novelty and focused on quality evidence.

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In episode 23, Zoe and me discuss the current status and promises of drug design, a field where many things seem trivial but nothing is really simple. Zoe talks about the challenges that precision medicine is facing, and how it fits into the grand landscape of future therapies. We go through some success stories, and I ask Zoe how the recent additions to drug design workflows help them in everyday scientific practice, both in terms of physics-based and data-driven models. We then spend a moment talking about the opportunities and responsibilities of a journal editor, and what are the lessons Zoe learned from creating her startup.

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In episode 22, we start by talking about the 2022 review of enhanced sampling methods that Lucie co-authored, one that provides long-needed organizing principles and unifying vocabulary for applications in this field. We also outline some challenges and community needs still waiting for the bold souls out there looking for ambitious projects. Lucie then moves on to share her experience with alternative publishing models, both as a member of Biophysics Colab and a former editor of eLife, and we dwell a bit on the challenges and possible solutions to what some would call a crisis in publishing, where evaluation metrics and publishing companies created unsustainable or even counterproductive incentive structures in sharing scientific results. We end on personal notes: already last year when I was visiting her lab in Stockholm, Lucie agreed to be on the very first list of interviewees, but it took me so long to figure it out that eventually Lucie gave birth to her twins and went on a maternal leave, so now that she's back more than a year later, I also asked her to share a few reflections on becoming a parent in academia.

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In episode 21, Tamar first explains how her unique background impacted the way she approached and conceptualized problems in biology, and how her research projects were born in the first place. We talk about the more recent research coming from Tamar's group on frameshifting, a fascinating process by which the readout of the genetic code can be offset by one or two letters to produce multiple proteins from a single viral gene. We then move on to discuss whether it's algorithms or compute that have contributed more to the growth of computational biophysics. Tamar's textbook and the multiple perspective articles she's written over the years serve us to dwell on the importance of writing for clarity and interdisciplinary collaboration. We end on a people-centric note, talking about the social bonds involved in both running and experimental collaborations.

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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.