The fields of Computational Biochemistry and Theoretical Chemistry are at the heart of your scientific work. How did your path lead to this intersection of disciplines? Was there a decisive moment or inspiring figure(s) that influenced this choice?
My path at the intersection of Computational Biochemistry and Theoretical Chemistry was shaped both by a curiosity to explore how chemical reactions occur at the atomic level and by decisive moments throughout my academic journey. During my undergraduate and doctoral studies, I had the opportunity to engage with topics related to atomic and molecular structure and later, during a postdoctoral position, with molecular modelling and computational simulation. This opened up a whole new world of possibilities to study biomolecular systems in detail. A decisive moment was my first experience with quantum chemistry methods applied to enzymes, during my postdoctoral work in Oxford, where I realised the impact these tools could have on understanding enzymatic catalysis and the molecular functioning of proteins. It was also at the University of Oxford that I was offered the role of Associate Director of the Computational Centre for Drug Discovery at Oxford, a position I held for around fifteen years. This played a crucial role in shaping my scientific career and funding my research. I only stepped down from the role when I became Vice-Rector for Research at U.Porto, as it was not feasible to carry out both responsibilities adequately. Moreover, several family members, colleagues and friends played a fundamental role in my scientific journey. The way they approached problems, particularly scientific ones, motivated me to deepen my knowledge and pursue a path that integrates theoretical chemistry and biochemistry. Today, I see that intersection as essential for addressing complex scientific challenges, from the design of new drugs to understanding the mechanisms behind plastic biodegradation.

In today’s context, particularly the growing integration of artificial intelligence and the use of big data across various fields of knowledge, do you believe we are living in a unique period for uncovering new possibilities and unexplored avenues? What disruptive potential do you see in these tools for scientific research in your area of expertise?
We are indeed living in a unique and extremely promising time for scientific research, driven by the integration of artificial intelligence (AI) and the use of big data. The ability to process vast volumes of data and identify complex patterns is transforming the way we tackle scientific problems, including those in Computational Biochemistry and Theoretical Chemistry. In my area of research, I see tremendous potential in these tools. AI has significantly accelerated the discovery and optimisation of molecules with biomedical and industrial applications. For example, machine learning models can generate structural models of proteins, as demonstrated by the impact of AlphaFold2, or suggest new candidate enzyme inhibitors. Furthermore, integrating big data with advanced computational methods is allowing the development of hybrid approaches that combine simulation, analysis of large datasets and predictive modelling, leading to faster and sometimes more robust insights. This is precisely what our research group has recently begun to explore, particularly in predicting the catalytic mechanism of the α-amylase enzyme. I believe this digital revolution is not only expanding the frontiers of knowledge but also democratising access to science, as more accessible tools enable a greater number of researchers to contribute to innovative discoveries. This, in turn, accelerates the pace of research and opens the door to solving an increasing number of scientific challenges.

Among your many scientific contributions, several have had significant implications in fields such as biomedicine and drug development. Could you highlight a particularly noteworthy discovery? We would also love to hear what lines of research currently spark your greatest interest?
One of the most exciting contributions in my scientific career was the use of distributed computing in drug design. Initiated in 2000, our Screensaver Lifesaver project harnessed the idle time of over 3.5 million personal computers in more than 200 countries, with their owners agreeing to participate by downloading the project's screensaver. By using the idle processing power of these computers, the project software created a virtual supercomputer that analysed billions of compounds against protein targets, in the search for treatments for cancer, anthrax and smallpox. The project was a collaboration between Intel, United Devices and the Centre for Computational Drug Discovery at the University of Oxford, led by Prof. Graham Richards and funded by the National Foundation for Cancer Research, in which I was Associate Director at the time. The project was awarded the Italgas Prize for Research and Technological Innovation in 2001. Currently, my research interests lie in computational enzymology, aiming to understand and optimise biomolecules with applications not only in medicine but also in biocatalysis. One particularly fascinating area we are beginning to explore involves using AI to accelerate the discovery of enzyme inhibitors, which are essential in the development of new drugs. Another area that greatly interests me is the modelling of transition states in complex enzymatic reactions. Many essential biochemical reactions remain incompletely understood at the atomic level, and advances in computational enzymology are enabling us to map these reactions with unprecedented precision. This can directly impact the design of biomimetic catalysts and the engineering of enzymes for pharmaceutical and industrial applications. Overall, what excites me most is the opportunity to explore new approaches to solving bio/chemical problems that, until recently, were considered out of reach.

Your scientific journey bridges fundamental and applied science. What is your perspective on the future of Computational Biochemistry in developing solutions to major global challenges, such as sustainability or climate change?
I believe we are only beginning to tap into the true potential of Computational Biochemistry, and that, together with advances in computing technologies and AI, we will be able to tackle these global challenges in an increasingly efficient and sustainable way. The ability to model and predict biochemical processes with high precision allows for the accelerated discovery of new enzymes and biomolecules that can be applied directly in pollutant biodegradation, carbon capture and the development of more efficient biofuels. In terms of sustainability, one of the most promising developments is the use of computational simulations to study enzymes that degrade plastics more effectively. Mechanistic understanding of these enzyme-catalysed reactions, achieved through quantum and classical methods, can be decisive in the bioengineering of more active and robust enzyme variants, making biochemical recycling a viable alternative to plastic waste accumulation. Another impactful area is bioenergy. Optimising enzymes involved in biomass degradation can increase the efficiency of biofuel production, reducing dependence on fossil fuels. Additionally, computational studies of natural and synthetic enzymatic systems for CO₂ fixation hold potential for contributing to climate change mitigation strategies, facilitating the conversion of atmospheric carbon dioxide into compounds useful for industry.

Your scientific career has also been marked by international experiences. With the growing importance of cross-border collaboration in scientific research, what are, in your opinion, the main challenges and opportunities these partnerships offer (such as bridges between academia and industry) in advancing science?
International collaboration provides opportunities to work with multidisciplinary teams, encourages the sharing of resources and access to cutting-edge technological infrastructures and has thus been a key driver in advancing science. In most scientific fields, international partnerships are essential to address complex challenges in an interdisciplinary and integrated manner. Moreover, international collaborations often provide access to competitive funding and large collaborative projects, such as European consortia and global initiatives. In the context of Computational Biochemistry, these collaborations also enable experimental validation of computational models, making predictions more robust and applicable. For example, our research group currently focuses on two major scientific interests: plastic biodegradation and the development of antidotes and drugs derived from snake venom. In both cases, scientific collaboration is absolutely essential. For plastic biodegradation, we are part of the EnZync consortium, involving several experimental researchers and funded with six million euros by the Danish Novo Nordisk Foundation. In the case of antidote and drug development from snake venom, we collaborate with various international institutions, including experimental groups from the University of Liverpool in the UK, IAAST in India, the National University in Singapore and the University of Costa Rica, among others. An interesting, and at the same time unfortunate, reality is that it is relatively easy to find funding for global and first-world problems, such as plastic biodegradation, but extremely difficult for issues typically associated with the developing world, like developing antidotes for snakebites. Nonetheless, scientific collaborations also come with significant challenges, such as adapting to different scientific and administrative cultures, particularly the latter. Unfortunately, these administrative issues took up a great deal of my time while I was Vice-Rector for Research at U.Porto. Industry involvement is very important to help put certain scientific discoveries into practice. However, differences in intellectual property regulations and data-sharing policies can also pose barriers to collaboration. Furthermore, engaging with industry requires balancing academic goals with the needs of the private sector, which are not always easily aligned. Still, the advancement of strategic areas like drug discovery, sustainable biotechnology and bioenergy increasingly relies on global collaborative networks. I believe the future of scientific research will undoubtedly involve even greater integration between academia and industry, driving innovative solutions to current and future global challenges.

Interdisciplinary collaboration is also key to solving complex scientific problems. What approaches do you consider most effective for creating synergies between different fields of knowledge?
Interdisciplinary collaboration is essential for tackling complex scientific problems, as it allows for the integration of different perspectives, methodologies and tools. To make such collaboration as effective as possible, it is vital to implement certain measures that help overcome pressing issues, such as the need for a multidisciplinary team with a shared language, both literary and scientific. Projects with clear and well-defined objectives support the training of future researchers across different scientific fields, and promoting cross-disciplinary events such as conferences and workshops is an effective way of encouraging interdisciplinarity. Ideally, there should be institutional support and well-targeted funding... unfortunately, this is not always the case. I believe the future of science increasingly depends on interdisciplinary collaborations. In Computational Biochemistry, for example, integrating areas such as Quantum Physics, Experimental Biology and, more recently, Artificial Intelligence has led to significant advances in understanding complex biological systems and developing new drugs.

You hold an Honorary Doctorate from Stockholm University and were awarded the Madinaveitia-Lourenço Prize by the Royal Spanish Society of Chemistry in 2019 – among other international honours. In your view, what role do global scientific networks play in accelerating innovation and sharing knowledge?
I have been very fortunate to receive both national and international recognition throughout my scientific career. Recently, in 2024, I was appointed a member of the Lisbon Academy of Sciences and simultaneously named a Chemistry Europe Fellow by Chemistry Europe. The previous year, I was awarded the U.Porto Scientific Research Excellence Award and, in 2019, received both the Madinaveitia-Lourenço Prize from the Royal Spanish Society of Chemistry and the FCUP Centenary Prize. The Honorary Doctorate from Stockholm University was especially meaningful as it is the only award that university bestows aside from the Nobel Prizes. Science is, in general, a collective endeavour, and global scientific networks play a fundamental role in accelerating innovation and sharing knowledge by enabling collaboration among researchers from different countries and disciplines. These networks facilitate the exchange of ideas, methodologies and technologies, making research more efficient and impactful. Some of their main benefits include access to knowledge and resources, facilitating the resolution of global challenges (such as the recent pandemic), fostering interdisciplinarity and accelerating technological development. All of this also helps train new researchers and may even influence the creation of new disciplines. In the context of Computational Biochemistry and Theoretical Chemistry, for example, international collaboration has been key to progress in areas such as modelling complex biological systems and computational enzymology.

Among the many roles you play – scientist, lecturer, consultant and even administrator – how do you find balance between the intensity of academic and scientific work and your personal life? Is there a philosophy or particular habit you consider essential to maintaining motivation and wellbeing?
Finding balance between the intensity of academic and scientific work and personal life has always been a constant challenge but, for me, an essential one to maintain motivation and wellbeing. My family, including my two daughters, never complained about my incredibly busy life. In fact, they are now very successful young professionals themselves. Science is a highly demanding field, with tight deadlines, constant peer review and the need for continuous innovation. However, over time, I developed strategies and habits that helped me manage these responsibilities more sustainably. I do not think there is a single formula for balancing all responsibilities, but developing healthy habits and respecting one’s limits are essential elements for ensuring a sustainable and fulfilling scientific career. For this, it is crucial to not only have enthusiasm for research but also an excellent team, effective time management, clear priorities, task delegation, time reserved for activities outside of science, and a strong support network both inside and outside academia. But most importantly, to maintain balance and motivation throughout a career, it is essential to have family and friends who offer different perspectives and emotional support, and colleagues with whom it is possible to discuss professional challenges. Everyone around me contributed decisively to my career and the scientific recognition I received along the way. To them – family and friends on a personal level, and colleagues on a professional and scientific level – I owe what I have achieved, and to all of them I extend my heartfelt 'thank you'.

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