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In Silico


11 Startups Using Quantum Theory To Accelerate Drug Discovery

   by Andrii Buvailo    2271
11 Startups Using Quantum Theory To Accelerate Drug Discovery

Molecular mechanics (MM) is a traditional computational approach when it comes to modeling in synthetic organic chemistry, medicinal chemistry and versatile aspects of drug design. However, MM methods have significant limitations, for example, when used to study electron-based properties within the drug-receptor microenvironment. Quantum mechanical (QM) methods allow to substantially increase the accuracy of predictions and provide much more relevant models of chemical and biological objects and their interactions, but QM methods are extremely (often prohibitively) computationally costly.

However, a series of advancements over recent years allowed to expand horizons in this direction, for example, the emergence of density functional theory (DFT), the overall increase in the computation power and the emergence of distributed cloud-based computational infrastructures.

[Interview] The Rise of Quantum Physics in Drug Discovery

   by Andrii Buvailo    802
[Interview] The Rise of Quantum Physics in Drug Discovery

Computer-aided drug design (CADD) is a central part of so-called “rational drug design”, pioneered in the last century by companies like Vertex. Over the last decades, CADD had great influence on the way new therapeutics are discovered, however, it also showed limitations due to modest accuracy of computational tools.  

The majority of software tools used for computational chemistry and biology rely on molecular mechanics -- a simplified representation of molecules, essentially reducing them down to “balls and sticks”: atoms and bonds between them. In this way it is easier to compute, but accuracy suffers greatly.

In order to gain adequate accuracy, one has to account for the electronic behavior of atoms and molecules, i.e. consider subatomic particles -- electrons and protons. This is what quantum mechanical (QM) methods are all about -- and the theory is not new, dating back to the early decades of the 20th century.  

"Hot" Research Areas in Drug Discovery - 2019

   by Andrii Buvailo    1841
"Hot" Research Areas in Drug Discovery - 2019

Things like gene editing, stem cells, immunotherapies and new types of biologics are now mega-trends in the pharmaceutical industry, widely covered in media, and I guess there is little doubt that biology is the next big thing in medicine. However, in this post I would like to outline several hot areas in small molecule drug discovery, suggesting a lot of untapped potential and investment prospects in this more “traditional” pharmaceutical research space.

Confluence of Technologies Can Bring “Virtual Pharmacology” to the Next Level

   by Andrii Buvailo    1697
Confluence of Technologies Can Bring “Virtual Pharmacology” to the Next Level

In 1970-80s, the idea of virtual screening was regarded as a conceptual way to substitute costly and time-consuming experimental “screen-everything-you-have” approaches with a much faster and cheaper predictive modelling to cherry-pick only the best molecules for subsequent synthesis and validation in a lab. A great number of computational tools and approaches emerged, aiming at “pre-screening” new promising molecules, so called “hits”, or augmenting experimental screening programs to optimize efforts.

Presenting a New Paradigm for Drug Discovery: Combining Computational Biophysics and AI through MatchMaker

   by Naheed Kurji    1214
Presenting a New Paradigm for Drug Discovery: Combining Computational Biophysics and AI through MatchMaker

In this Special Perspective, our fourth in an ongoing series, we will be presenting MatchMaker™, a novel deep proteome screening technology that we have developed and validated over the past 2 years to identify DTIs. MatchMaker builds on Cyclica’s passions of combining protein, chemistry, and genomic data, and augmenting it with high performance computing and algorithm development supported on the cloud.