𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 𝐦𝐞𝐝𝐢𝐜𝐢𝐧𝐞

QT4HC Summary for Algoritmiq research offering: 𝐐𝐮𝐚𝐧𝐭𝐮𝐦 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 𝐦𝐞𝐝𝐢𝐜𝐢𝐧𝐞: 𝐫𝐞𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠 𝐦𝐞𝐝𝐢𝐜𝐢𝐧𝐞 𝐰𝐢𝐭𝐡 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 𝐬𝐜𝐢𝐞𝐧𝐜𝐞 𝐚𝐧𝐝 𝐪𝐮𝐚𝐧𝐭𝐮𝐦 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬, summarised by Plamen Dobrev
(originally published on LinkedIn):

Advances in science in the latest decades have been made greatly by combining knowledge and expertise from different research fields. In most recent times, experts coming from quantum science and technology, network science, chemistry and life sciences are working to tackle some of the greatest challenges in medicine and biology. Since the start of the -omics era, the development of genomics, proteomics, transcriptomics etc., it has become clear that the simplification of biological systems in order to be studied easier is incapable of representing their biological function in context of their network interactions with all other partners in a living biological organism. As a more holistic approach, the interactome of all genes, proteins and biochemistry pathways has been investigated to build a network which takes into account all known interactions.

Network Topology of the interactome

Based on network topology it has become clear that affecting a single protein (or in general node in the network) will not have the desired effect on the entire functionality of interactome, as has been shown in many experimental studies where a knock out of a single gene often doesn’t have any phenotype. Similarly, the disease networks, inferred from the interactome, suggest that diseases are not isolated and multiple conditions may have the same root. Despite some success in network medicine, the latter is still limited by computational power needed to investigate the complex topology of the interactome and the incompletenesses of data for many medical conditions. Quantum chemistry can have a big impact on both, identifying network pathways and developing new compounds which can affect them in order to be used as effective medications. Nowadays quantum computers suffer from two main problems: high noise and impossibility for precise read-out of the results from the computation.

Interactome (definition): In molecular biology, an interactome is the whole set of molecular interactions in a particular cell. The term specifically refers to physical interactions among molecules (such as those among proteins, also known as protein–protein interactions, PPIs; or between small molecules and proteins[1]) but can also describe sets of indirect interactions among genes (genetic interactions).

The Quantum advantage

These challenges are far from being solved, therefore today’s quantum computers are useful only for academic purposes solving specific scientific problems. However, quantum inspired algorithms for classical computers have already been shown to improve computational efficiency in random walk network analysis, crucial for interactome studies. Further, due to the same physics principles used for the calculations carried out in quantum computer and those governing quantum systems, like molecules, quantum computers are extremely suitable for simulating compounds and their subatomic structure. The latter being essential for simulating a drug candidates and their binding to potential protein targets.

Quantum Network Medicine Manifesto

For such an approach, only certain parts of the calculations need to be carried out on a quantum computer while all the others can be carried out on a classical machines, which makes the usage of quantum computing foreseeable in a near future. Moreover, the fast calculation of compound quantum properties will allow search of the overwhelmingly big compound space in search of potential drug targets. As a conclusion, quantum computing applied for both, compound design and molecular docking as well as interactome network analysis is something which we can expect to see in the near future.

Credit to All figures: Algoritmiq, as originally published in their article: https://arxiv.org/abs/2206.12405