Insights into the stereoselectivity of human SETD7 methyltransferase

Molecular Docking of Chiral Drug Enantiomers With Different Bioactivities

Chirality has an important role in the drug design because enantiomers may exhibit different bioactivity when interacting with macromolecules of a living organism. In our previous work, based on the analysis of a set of 100 chiral drugs, a relationship was established between the sign of chirality of enantiomers and their bioactivity. To understand the reasons for the observed patterns of chiral specificity of drug enantiomers, the interaction of 10 enantiomeric pairs of chiral drugs with the corresponding target proteins has been considered using molecular docking and further postprocessing by quantum chemistry methods. The data obtained confirm that the energetic aspect of the interaction between opposite enantiomers and target protein affects the enantiomer biological activity. In addition, the results show that molecular docking is able to distinguish between bioactive and inactive/less active enantiomers, although many docking programs are not accurate enough to distinguish a weak inhibitor from a strong one.

The binding mechanism of failed, in processing and succeed inhibitors target SARS-CoV-2 main protease

Since the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), several variants have caused a persistent pandemic. Consequently, it is crucial to develop new potential anti-SARS-CoV-2 drugs with specificity. To minimize potential failures and preserve valuable clinical resources for the development of other useful drugs, researchers must enhance their understanding of the interactions between drugs and SARS-CoV-2. While numerous crystal structures of the SARS-CoV-2 main protease (SCM) and its inhibitors have been reported, they provide only static snapshots and fail to capture the dynamic nature of SCM/inhibitor interactions. Herein, we conducted molecular dynamics simulations for five SCM complexes: ritonavir (SCM/RTV), lopinavir (SCM/LPV), the identified inhibitor N3 (SCM/N3), the approved inhibitor ensitrelvir (SCM/ESV), and the approved drug nirmatrelvir (SCM/NMV). Additionally, we explored the potential for covalent bond formation in the N3 and NMV inhibitors through QM/MM calculations using Umbrella sampling. The results show that the binding site is highly flexible to fit those five different inhibitors and each compound has its unique binding mode at the same binding site. Moreover, the binding affinities of positive and negative inhibitors to SCM exhibit significant differences. By gaining insights into the dynamics, we can potentially elucidate why lopinavir/ritonavir, initially considered promising, failed to effectively treat COVID-19. Furthermore, understanding the mechanistic aspects of N3 and NMV inhibition on SCM not only contributes to rational drug discovery against COVID-19 but also aids future studies on the catalytic mechanisms of main proteases in other novel coronaviruses.Communicated by Ramaswamy H. Sarma.

Identification of potential ATP-competitive cyclin-dependent kinase 1 inhibitors: De novo drug generation, molecular docking, and molecular dynamics simulation

Cyclin-dependent kinases 1 (CDK1) has been identified as a potential target for the search for new antitumor drugs. However, no clinically effective CDK1 inhibitors are now available for cancer treatment. Therefore, this study aimed to offer potential CDK1 inhibitors using de novo drug generation, molecular docking, and molecular dynamics (MD) simulation studies. We first utilized the BREED algorithm (a de novo drug generation approach) to produce a novel library of small molecules targeting CDK1. To initially obtain novel potential CDK1 inhibitors with favorable physicochemical properties and excellent druggability, we performed a virtual rule-based rational drug screening on our generated library and found ten initial hits. Then, the molecular interactions and dynamic stability of these ten initial hits and CDK1 complexes during their all-atom MD simulations (total 18 μs) and binding pose metadynamics simulations were investigated, resulting in five final hits. Furthermore, another MD simulation (total 2.1 μs) with different force fields demonstrated the binding ability of the five hits to CDK1. It was found that these five hits, CBMA001 (ΔG = -29.88 kcal/mol), CBMA002 (ΔG = -34.89 kcal/mol), CBMA004 (ΔG = -32.47 kcal/mol), CBMA007 (ΔG = -31.16 kcal/mol), and CBMA008 (ΔG = -34.78 kcal/mol) possessed much greater binding affinity to CDK1 than positive compound Flavopiridol (FLP, ΔG = -25.38 kcal/mol). Finally, CBMA002 and CBMA004 were identified as excellent selective CDK1 inhibitors in silico. Together, this study provides a workflow for rational drug design and two promising selective CDK1 inhibitors that deserve further investigation.

Lysine methyltransferase inhibitors: where we are now

Protein lysine methyltransferases constitute a large family of epigenetic writers that catalyse the transfer of a methyl group from the cofactor S-adenosyl-l-methionine to histone- and non-histone-specific substrates. Alterations in the expression and activity of these proteins have been linked to the genesis and progress of several diseases, including cancer, neurological disorders, and growing defects, hence they represent interesting targets for new therapeutic approaches. Over the past two decades, the identification of modulators of lysine methyltransferases has increased tremendously, clarifying the role of these proteins in different physio-pathological states. The aim of this review is to furnish an updated outlook about the protein lysine methyltransferases disclosed modulators, reporting their potency, their mechanism of action and their eventual use in clinical and preclinical studies.