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Solute carriers (SLCs) have often been overshadowed by more prominent protein families in drug discovery, such as kinases and G protein-coupled receptors. However, SLC proteins hold significant therapeutic potential due to their role in various diseases. Among them, the high-affinity norepinephrine transporter (NET/SLC6A2) has received considerable attention, but the limited chemical diversity of known ligands presents a challenge for identifying novel compounds. The new article published in Journal of Chemical Information and Modeling explores a computational screening pipeline developed to discover new NET inhibitors, utilizing a data-driven approach to expand known chemical space and optimize target selection.

The interest of pharmaceutical companies in DNA-encoded chemical libraries (DEL) technology has been growing over the years, with numerous organizations now having their own screening programs using DELs, or outsourcing capabilities from specialized DEL providers.

Image credit:Dilok Klaisataporn, iStock.

Proteins are essential components of living matter – they function as building blocks for cells and tissues, as well as participate in signaling and practically all biochemical activities. However, each protein operates correctly only for a limited amount of time and is eliminated by molecular machinery after it has reached its “functional shelflife”. To maintain a healthy and functional proteome, cells tightly control protein turnover processes, ensuring that misfolded, damaged, and old proteins exit the game in a timely manner. This sophisticated mechanism of degradation was recently hijacked by the drug discovery industry to develop new small molecule therapies — protein degraders.

Image credit: Orhan Turan, iStock by Getti Images.

Drug discovery is a long and challenging process, which may take up to fifteen years of experimentation and clinical trials, and several billion dollars in various expenses to bring a successful drug to patients. The process can be roughly divided into three stages: 1) biology research and early drug discovery; 2) preclinical drug development; and 3) clinical trials.

In order to start a drug discovery program, at the first stage, scientists study biological processes to come up with proper understanding of the underlying causes of a particular disease. Once drivers of the disease are known, scientists can select specific biological targets -- typically proteins involved in a disease-causing biological process.

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 promising areas in small molecule drug discovery, suggesting a lot of untapped potential and investment prospects in this more “traditional” pharmaceutical research space.

The majority of existing marketed drugs out there are designed to somehow modulate proteins in the body, thereby disrupting a disease progression. However, going one step back and trying to disrupt a pathological process earlier -- right before a protein is actually made in the body -- seems a powerful concept. This can be achieved by influencing ribonucleic acid (RNA), a central actor molecule in the process of gene expression -- the one leading to the formation of proteins as instructed by the human genome.

Enamine has the world’s largest catalog of building blocks which is monthly enriched with ca. 2,000 newly designed and synthesized compounds. Most of these compounds have been previously unknown and may already provide elegant solutions to your today’s challenges.

Being the global leader in supplying state-of-the-art chemical products for drug discovery (building blocks and screening compounds), Enamine also created a sophisticated ecommerce integration layer, allowing for a seamless eProcurment process to be enabled between buyers and vendors.

Patient diversity and developing drug resistance can undermine the efficiency of existing therapies in a long-term pharmacological treatment of diseases, such as cancer and infections.

(This post originally appeared on Forbes)

Pioneered by expensive and cumbersome legacy electronic data interchange (EDI) systems, the B2B e-commerce market has been evolving, showing a staggering growth rate with a projected volume of $1.1 trillion in the U.S. alone and $6.7 trillion globally by 2020.

(This post originally appeared on LinkedIn)

Notoriously toxic, covalent inhibitors have been nearly excluded from major drug discovery programs in the not so distant past. Ironically, a great amount of the important drugs exploit covalent inhibition as their mechanism of action (MOA). The view on covalent inhibitors is shifting towards a wider consideration, however, inspired by recent successes with EGFR inhibitors for treating cancer and many other promising examples. A recent publication in Nature provides a chemical proteomic platform for the global and quantitative analysis of lysine residues in native biological systems, offering further insights and ideas in this area.

(This article originally appeared at Forbes.com)

Artificial intelligence (AI) has become a hot topic in the area of life sciences lately. With a growing number of groundbreaking AI use cases in other hi-tech industries -- ranging from self-driving cars to speech and image recognition tools to personal assistants (you know Siri, don’t you?) -- players in the biopharmaceutical industry are looking toward AI to speed up drug discovery, cut R&D costs, decrease failure rates in drug trials and eventually create better medicines.

Scientists estimated that the human genome encodes above 20,000 different proteins in our body. However, available public databases contain records of known ligands for only about 10% of all proteins. The rest of proteins remains either not yet properly explored, or is labelled “undruggable”.