The featureless interface formed by protein–protein interactions (PPIs) is notorious for being considered a difficult and poorly druggable target. However, recent advances have shown PPIs to be druggable, with the discovery of potent inhibitors and stabilizers, some of which are currently being clinically tested and approved for medical use. In this study, we assess the druggability of 12 commonly targeted PPIs using the computational tool, SiteMap. After evaluating 320 crystal structures, we find that the PPI binding sites have a wide range of druggability scores. This can be attributed to the unique structural and physiochemical features that influence their ligand binding and concomitantly, their druggability predictions. We then use these features to propose a specific classification system suitable for assessing PPI targets based on their druggability scores and measured binding-affinity. Interestingly, this system was able to distinguish between different PPIs and correctly categorize them into four classes (i.e. very druggable, druggable, moderately druggable, and difficult). We also studied the effects of protein flexibility on the computed druggability scores and found that protein conformational changes accompanying ligand binding in ligand-bound structures result in higher protein druggability scores due to more favorable structural features. Finally, the drug-likeness of many published PPI inhibitors was studied where it was found that the vast majority of the 221 ligands considered here, including orally tested/marketed drugs, violate the currently acceptable limits of compound size and hydrophobicity parameters. This outcome, combined with the lack of correlation observed between druggability and drug-likeness, reinforces the need to redefine drug-likeness for PPI drugs. This work proposes a PPI-specific classification scheme that will assist researchers in assessing the druggability and identifying inhibitors of the PPI interface.

The current pandemic caused by the COVID-19 disease has reached everywhere in the world and has affected every aspect of our lives. As of the current data, the World Health Organization (WHO) has reported more than 300 million confirmed COVID-19 cases worldwide and more than 5 million deaths. M^pro is an enzyme that plays a key role in the life cycle of the SARS-CoV-2 virus, and it is vital for the disease progression. The M^pro enzyme seems to have several allosteric sites that can hinder the enzyme catalytic activity. Furthermore, some of these allosteric sites are located at or nearby the dimerization interface which is essential for the overall M^pro activity. In this review paper, we investigate the potential of the M^pro allosteric site to act as a drug target, especially since they interestingly appear to be resistant to mutation. The work is illustrated through three subsequent sections: First, the two main categories of M^pro allosteric sites have been explained and discussed. Second, a total of six pockets have been studied and evaluated for their druggability and cavity characteristics. Third, the experimental and computational attempts for the discovery of new allosteric inhibitors have been illustrated and discussed. To sum up, this review paper gives a detailed insight into the feasibility of developing new M^pro inhibitors to act as a potential treatment for the COVID-19 disease. Graphical Abstract:

Protein tyrosine phosphatases (PTP) play important roles in the pathogenesis of many diseases. The fact that no PTP inhibitors have reached the market so far has raised many questions about their druggability. In this study, the active sites of 17 PTPs were characterized and assessed for its ability to bind drug-like molecules. Consequently, PTPs were classified according to their druggability scores into four main categories. Only four members showed intermediate to very druggable pocket; interestingly, the rest of them exhibited poor druggability. Particularly focusing on PTP1B, we also demonstrated the influence of several factors on the druggability of PTP active site. For instance, the open conformation showed better druggability than the closed conformation, while the tight-bound water molecules appeared to have minimal effect on the PTP1B druggability. Finally, the allosteric site of PTP1B was found to exhibit superior druggability compared to the catalytic pocket. This analysis can prove useful in the discovery of new PTP inhibitors by assisting researchers in predicting hit rates from high throughput or virtual screening and saving unnecessary cost, time, and efforts via prioritizing PTP targets according to their predicted druggability.

Butyrylcholinesterase (BChE) plays an important role in the progression of the Alzheimer’s disease. In this study, we used a structure-based virtual screening (VS) approach to discover new BChE inhibitors. A ligand database was filtered and docked to the BChE protein using Glide program. The outcome from VS was filtered and the top ranked hits were thoroughly examined for their fitting into the protein active site. Consequently, the best 38 hits were selected for in vitro testing using Ellman’s method, and six of which showed inhibition activity for BChE. Interestingly, the most potent hit (Compound 4) exhibited inhibitory activity against the BChE enzyme in the low micromolar level with an IC50 value of 8.3 µM. Hits obtained from this work can act as a starting point for future SAR studies to discover new BChE inhibitors as anti-Alzheimer agents.