Sep 23, 2026 · 19 min · 8 segments
On this episode of EngBio Tech Dr Mahsa Baniasadi joins to explore her exciting project entitled ‘Harnessing AI-assisted synthetic Biology for enzyme engineering towards PFAS bioremediation’. Can AI…
Mahsa BaniasadiGuestSniffla HeavenHostSo what role then would molecular modelling and computational simulations play before you even step into the laboratory?
So when we do molecular modeling, we have a structure of the enzyme on the computer and also a structure of the PFAS.
We put them together and we will see where the PFAS will be located exactly inside the enzyme.
And by that, we will find the area and the region of the enzyme, which we call it hot spot.
And based on that, we will find which area in the enzyme we need to modify if we wanted to be more capable of degrading the enzyme.
And I guess that's the sort of thing that you'd have had to try and do before without AI assistance.
So we always find, particularly with environmental biotechnology, one of the biggest challenges can be scaling up.
What hurdles do you anticipate moving forward from the lab to full-scale treatment systems? What do you think the hurdles are going to be there?
Yeah, so apart from the common problems of a scale-up, when we work with the enzyme, one problem is the low stability and low activity of the enzyme.
Yeah, so in order to face that in our project, we have a work package, which is the immobilization of enzyme on a solid support.
And then use those supports in a packed bed by a reactor in a continuous mode.
And this way we will tackle the problem of instability and losing our enzymes.
So with this sort of thing, I know with PFAS a lot of the times, a lot of the treatments or the methods of removing them, kind of ends up breaking things down or putting them into other compounds.
And how do we know if the engineered enzymes are actually destroying PFAS rather than transforming it into potentially harmful compounds?
So what role then would molecular modelling and computational simulations play before you even step into the laboratory?
So when we do molecular modeling, we have a structure of the enzyme on the computer and also a structure of the PFAS.
We put them together and we will see where the PFAS will be located exactly inside the enzyme.
And by that, we will find the area and the region of the enzyme, which we call it hot spot.
And based on that, we will find which area in the enzyme we need to modify if we wanted to be more capable of degrading the enzyme.
And I guess that's the sort of thing that you'd have had to try and do before without AI assistance.
So we always find, particularly with environmental biotechnology, one of the biggest challenges can be scaling up.
What hurdles do you anticipate moving forward from the lab to full-scale treatment systems? What do you think the hurdles are going to be there?
Yeah, so apart from the common problems of a scale-up, when we work with the enzyme, one problem is the low stability and low activity of the enzyme.
Yeah, so in order to face that in our project, we have a work package, which is the immobilization of enzyme on a solid support.
And then use those supports in a packed bed by a reactor in a continuous mode.
And this way we will tackle the problem of instability and losing our enzymes.
So with this sort of thing, I know with PFAS a lot of the times, a lot of the treatments or the methods of removing them, kind of ends up breaking things down or putting them into other compounds.
And how do we know if the engineered enzymes are actually destroying PFAS rather than transforming it into potentially harmful compounds?
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