Unlocking the Potential of Quantum Computing Part II – Advancements, Challenges, and Growing Industry Adoption

Quantum computing is gaining recognition for its potential to reshape drug discovery and biotechnology. As advancements in quantum algorithms and hardware continue, this technology is providing new insights into complex biological systems, offering the possibility of faster and more accurate drug development processes. Researchers are now focusing on how quantum computing can enhance areas such as protein dynamics, molecular design, and disease modeling. In this second part of our series, we explore how quantum computing transforms these specific areas, how technology firms and pharmaceutical companies are forming partnerships, and how researchers are overcoming computational challenges that previously limited its widespread use.

ProteinQure Combining Reinforcement Learning and Atomistic Simulations for Protein-Based Therapeutics

ProteinQure, a Toronto-based startup founded in 2017, combines reinforcement learning and atomistic simulations to design novel protein drugs. The company uses reinforcement learning to optimize protein therapeutic designs, with models that improve their predictions of protein behavior through continuous learning and adjustments. Researchers apply atomistic simulations to model interactions between atoms within proteins and other biomolecules, providing detailed insights into their structural and dynamic properties, which are crucial for understanding drug efficacy. Using these advanced technologies alongside proprietary algorithms and external supercomputing resources, ProteinQure can design small peptide-based therapeutics, including cyclic peptides, and explore protein structures that lack known crystal structures.

PharmaCADD Using Pharmulator to Rapidly Reconstruct 3D Protein Structures 

PharmaCADD, a South Korea-based startup founded in 2019, uses its main technology platform, Pharmulator, which incorporates deep neural network algorithms, molecular dynamic simulations, and quantum mechanics computation. Pharmulator can reconstruct a 3D protein structure from an amino acid sequence in just a few seconds.The platform uses deep neural networks to predict the spatial arrangement of atoms within a protein, while molecular dynamics simulations model protein behavior in various environments.

Riverlane Using Advanced Algorithms to Simulate Molecular Interactions

Riverlane develops software that uses advanced algorithms to simulate complex molecular interactions with high accuracy and efficiency. The technology integrates classical and machine learning methods to model protein folding, molecular dynamics, and the interactions between small molecules and proteins. This approach enables the simulation of intricate biological processes, providing insights into biomolecular behavior. Riverlane’s software is designed to handle large-scale molecular data, allowing for the exploration of drug candidates and optimization of therapeutic molecule designs.

Roivant Acquiring Silicon Therapeutics and Its Advanced Physics-Based Simulation Technology 

Roivant, the scientific subsidiary of Roivant Sciences, was established through the acquisition of the computational drug discovery company, Silicon Therapeutics. Silicon Therapeutics developed a research platform that combines physics-based molecular simulations, quantum physics, statistical thermodynamics, and molecular dynamics to enhance conventional drug discovery processes. The company focused on innate immunity in cancer and inflammation and had developed its own pipeline of early small molecule drug candidates, with four in the discovery phase and two in the preclinical phase as of June 2019. Silicon Therapeutics was also active in the field of conformational genetics, linking genetic mutations to biological functions, to further inform therapeutic development.

XtalPi’s AI-Powered ID4 Platform and Quantum Physics Used for Precise Drug Property and Crystal Structure Prediction  

Founded in 2014 by a group of quantum physicists at MIT, XtalPi is a quantum physics-based, AI-powered drug R&D company. XtalPi’s Intelligent Digital Drug Discovery and Development (ID4) platform combines quantum mechanics, artificial intelligence, and high-performance cloud computing algorithms to predict the physiochemical and pharmaceutical properties of small-molecule drug candidates with high precision. It also predicts their crystal structures, a crucial factor in successful drug development. As of now, XtalPi has raised $786.4 million from investors, including Sequoia China, Tencent, and Google, making it one of the most well-funded computational drug discovery startups. The company also has multiple research collaborations with pharmaceutical companies, including Pfizer.

Related posts:

Quantum Biology: A Look at Current Applications and Developments Unlocking the Potential of Quantum Computing Part I – Advancements, Challenges, and Growing Industry Adoption International Green Party Showcases AI Solutions for a Healthy and Sustainable Future Big Tech Gets Their Qubits in Line: Quantum Computing Adding Another Dimension to Pharma Innovation

Author

Denisse Sandoval