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Forecasting Protein Aggregation with an Improved Algorithm
A new, improved algorithm for studying protein aggregation could help biologics manufacturers design better-performing products with less experimental effort. The software, developed by scientists based in Barcelona, offers the ability to analyze the aggregation of proteins drawn from the AlphaFold protein structure database, as well as helping companies identify more soluble alternatives.
“Protein aggregation is a bottleneck in the production and manufacturing of biologics,” explains Salvador Ventura, PhD, a professor in the department of biochemistry and molecular biology at the Autonomous University of Barcelona (UAB).
The problem, he explains, is that many proteins used as therapies evolved to be soluble at the concentrations found in the human body. But therapeutics, such as antibodies, are produced in as high a concentration as possible.
“We want the product to deliver the maximum dose with the minimum amount of injection,” he says. “But proteins aren’t designed to be soluble at these concentrations, and their aggregation causes different effects.”
These can include the patient’s immune system reacting negatively or the aggregated product ceasing to work.
To overcome this problem, Ventura says, companies and labs try to forecast protein aggregation, usually experimentally with high-throughput combinational assays. But these approaches are not convenient for startups or small spinoff companies.
A computational approach, such as his algorithm, now in its fourth generation, can help these companies predict and design around protein aggregation.
It offers the ability to draw protein structures from AlphaFold to analyze likely protein aggregation using simulations of molecular dynamics. Users, he says, can also choose to mutate selected parts of the protein, identify other proteins in the same family, and even look at the possible impact of pH on solubility.
“Our lab is both computational and experimental, so most of the designs we’ve made, we’ve already proved by experiment,” Ventura says.
Limitations include the scarcity of high-quality experimental data available to train the algorithm, he explains.
Going forward, the team intends to model which solution and formulation conditions best maintain the stability of therapeutic proteins in manufacturing and clinical settings. “We’re working on these next steps already,” he says. “Although, as yet, we don’t have an algorithm for this.”
Ventura spoke about the latest version of his algorithm at the Bioprocessing Summit Europe in March.
The post Forecasting Protein Aggregation with an Improved Algorithm appeared first on GEN – Genetic Engineering and Biotechnology News.
Hosted by Drug Discovery World and supported by Sartorius and BioIVT, this webinar will explore the opportunities and challenges that exist within cancer research drug discovery and development.
You will hear from Dr Sudha Rao, Chief Scientific Officer of Kazia Therapeutics, Karol Budzik, PhD, Business Development Associate at Vyriad Therapeutics and Lars van der Veen, Chief Scientific Officer at iOnctura.
Presentations will cover how cancer treatments have shifted towards reprogramming the biology driving tumour growth, immune escape and treatment resistance, the trajectory that in vivo CAR-T treatments are taking, and how challenging tumours burdened by stroma and immune-mediated resistance can be tackled.
Q&A with the speakers follows the presentations.
The post New webinar: Tackling drug discovery challenges in cancer research appeared first on Drug Discovery World (DDW).
Amid the rise of psychedelics in the mental health space, researchers have begun to explore psilocybin as a treatment for chemotherapy-induced peripheral neuropathy.
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New Spectrometry Technique Could Aid Formulation Development
New Spectrometry Technique Could Aid Formulation Development
A new technique combining two forms of spectrometry could help biopharmaceutical companies improve their choice of formulation buffer for antibody manufacturing by revealing how molecular forms and three-dimensional shapes of complex biologics respond to their environment. That’s the view of Christian Bleiholder, PhD, a professor at Florida State University who helped develop the technique.
According to Bleiholder, what happens structurally when a complex biological molecule, such as an antibody or viral spike protein, binds to its target is currently poorly understood.
“This is where [this approach] can help with the bioprocessing and formulation,” he says, as structural changes “can affect the lifespan [of the product] and lead to issues, such as aggregation.”
Because antibodies are complex, existing techniques tend to be powerful at different levels of complexity, he explains. Mass spectrometry is particularly powerful for distinguishing molecular composition, while structural approaches such as X-ray crystallography and cryo-electron microscopy can provide high-resolution structural information.
The challenge is understanding the link between these things within a heterogeneous sample, he says.
To overcome this, Bleiholder and his team worked with Bruker Daltonics to develop Tandem-Trapped Ion Mobility Spectrometry (Tandem-TIMS). This combines tandem ion mobility spectrometry with tandem mass spectrometry to disentangle three overlapping layers of molecular complexity: molecular form, three-dimensional shape, and binding or assembly state, he says.
He explains that, if the proteins have different structures, they can be characterized with tandem ion mobility spectrometry, and then mass spectrometry can be used to look at their molecular forms and binding states.
Going forward, Bleiholder hopes the technique can be used for formulation development but also earlier, during drug discovery of new products, such as multi-specific antibodies, to determine which molecular states are important and how those change when a biologic engages its target. He also plans to look at automating the technique.
Bleiholder spoke about using Tandem-TIMS at the Bioprocessing Summit in Boston earlier this year.
The post New Spectrometry Technique Could Aid Formulation Development appeared first on GEN – Genetic Engineering and Biotechnology News.
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