Discovery of a nanomolar glyoxalase-I inhibitor using integrated ligand-based pharmacophore modeling and molecular docking

The design of TOPK inhibitors using structure-based pharmacophore modeling and molecular docking based on an MD-refined homology model

The TOPK enzyme (also known as PBK) is a serine-threonine protein kinase that is rarely detected in normal tissues yet is found to be overexpressed and activated in a variety of cancers such as lung, colorectal, breast, and esophageal cancer. Its prevalence in cancerous cells is associated with their poor prognosis and responsiveness to treatment. This enzyme plays a vital role in cell division, specifically in regulating cytokinesis. Unlike drugs targeting early phases in mitosis, inhibition of cytokinesis by targeting biomolecules that are unique to multiplying cells poses no threat to the normal function of non-multiplying cells. Studies have shown that inhibition of cytokinesis is promising in suppressing the growth of proliferating cancerous cells as exemplified by the complete tumor regression seen with the suppression of TOPK. Herein, we report the identification of potent TOPK inhibitors with anticancer potential using a structure-based drug design approach. The only available crystal structure of TOPK corresponds to a double mutant (T9E and T198E) dimer with a distorted N-lobe conformation, thus 3D homology modeling was implemented to rebuild the enzyme's native conformation. The resulting refined model was used to generate 3D pharmacophore models for the virtual screening of small molecules databases. Retrieved hits were filtered, docked into the ATP binding site of the enzyme, rescored, and the binding free energies for the top consensually scoring hits were calculated. Consequently, 45 compounds were selected and their in vitro inhibitory activity against TOPK was tested revealing four potential hits with the most active compound having an IC₅₀ of 3.85 µM. This compound will be chosen as a lead compound to synthesize analogs aiming to enhance potency and drug-like properties and to enrich the SAR data.

Identification of the first "two digit nano-molar" inhibitors of the human glyoxalase-I enzyme as potential anticancer agents

BACKGROUND

Glyoxalase-I (Glo-I) enzyme is recognized as an indispensable druggable target in cancer treatment. Its inhibition will lead to the accumulation of toxic aldehyde metabolites and cell death. Paramount efforts were spent to discover potential competitive inhibitors to eradicate cancer.

OBJECTIVE

Based on our previously work on this target for discovering potent inhibitors of this enzyme, herein, we address the discovery of the most potent Glo-I inhibitors reported in literature with two digits nano-molar activity.

METHODS

Molecular docking and in vitro assay were performed to discover these inhibitors and explore the active site's binding pattern. A detailed SAR scheme was generated, which identifies the significant functionalities responsible for the observed activity.

RESULTS

Compound 1 with an IC50 of 16.5 nM exhibited the highest activity, catechol moiety as an essential zinc chelating functionality. It has been shown by using molecular modeling techniques that the catechol moiety is responsible for the chelation zinc atom at the active site, an essential feature for enzyme inhibition.

CONCLUSION

Catechol derivatives are successful zinc chelators in the Glo-I enzyme while showing exceptional activity against the enzyme to the nanomolar level.

Screening of natural compounds from Cyperus rotundus Linn against SARS-CoV-2 main protease (Mpro): An integrated computational approach

Coronavirus disease 2019 (COVID-19) is a viral respiratory disease that has been spreading across the globe. The World Health Organization (WHO) declared it as a public health emergency. The treatment of COVID-19 has been hampered due to the lack of effective therapeutic efforts. Main Protease (M^pro) is a key enzyme in the viral replication cycle and its non-specificity to human protease makes it a potential drug target. Cyperus rotundus Linn, which belongs to the Cyperaceae family, is a traditional herbal medicine that has been widely studied for its antiviral properties. In this study, a computational approach was used to screen natural compounds from C. rotundus Linn using BIOVIA Discovery Suite and novel potential molecules against M^pro of SARS-CoV-2 were predicted. Molecular docking was performed using LibDock protocol and selected ligands were further subjected to docking analysis by CDOCKER. The docking scores of the selected ligands were compared with standard antiretroviral drugs such as lopinavir and ritonavir to assess their binding potentials. Interaction pharmacophore analysis was then performed for the compounds exhibiting good binding scores to evaluate their protein–ligand interactions. The selected protein–ligand complexes were subjected to molecular dynamics simulation for 50 ns. Results of binding free energy analysis revealed that two compounds—β-amyrin and stigmasta-5,22-dien-3-ol—exhibited the best binding interactions and stability. Finally, absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were performed to understand the pharmacokinetic properties and safety profile of the compounds. The overall results indicate that the phytochemicals from Cyperus rotundus Linn, namely β-amyrin and stigmasta-5,22-dien-3-ol, can be screened as potential inhibitors of SARS-CoV-2 M^pro.

CHK1 kinase inhibition: identification of allosteric hits using MD simulations, pharmacophore modeling, docking and MM-PBSA calculations

The CHK1 kinase plays a pivotal role in the DNA damage response pathway. Hence, inhibition of CHK1 appeared as a promising strategy to overcome the resistance problem of chemotherapeutic agents resulting from the overexpression of CHK1 that enables cancerous cells to repair their chemotherapy-induced DNA damage. In this study, different computational drug design techniques were employed to identify new CHK1 inhibitors targeting its allosteric pocket. A 1 μs MD simulation of the apo form of the enzyme was run to study its native dynamics. The resulting trajectory was analyzed to select a frame where the ATP binding pocket is most occluded while its allosteric counterpart is most exposed to be used in the design of potential allosteric inhibitors that could trap the enzyme in such nearly inactive state. Besides the selected frame, another three crystal structures of CHK1 complexed with allosteric inhibitors were utilized to generate structure-based pharmacophore models. Seven pharmacophores were generated and utilized in virtual screening of different databases. The retrieved hits were filtered and then docked into the allosteric pocket. Finally, the binding energies of the top-ranked docked hits were calculated. Twenty compounds were selected as candidates for biological evaluation against CHK1 enzyme. The biological screening results showed moderate activities where the percentage of CHK1 inhibition ranged from zero to 28.26%. Four of the tested compounds showed percentage of CHK1 inhibition greater than 20%, of which, two compounds were identified as allosteric hits that upon further optimization could be converted into lead-like compounds.

Ellagic acid: A potent glyoxalase-I inhibitor with a unique scaffold

The glyoxalase system, particularly glyoxalase-I (GLO-I), has been approved as a potential target for cancer treatment. In this study, a set of structurally diverse polyphenolic natural compounds were investigated as potential GLO-I inhibitors. Ellagic acid was found, computationally and experimentally, to be the most potent GLO-I inhibitor among the tested compounds which showed an IC50 of 0.71 mmol L-1. Its binding to the GLO-I active site seemed to be mainly driven by ionic interaction via its ionized hydroxyl groups with the central Zn ion and Lys156, along with other numerous hydrogen bonding and hydrophobic interactions. Due to its unique and rigid skeleton, it can be utilized to search for other novel and potent GLO-I inhibitors via computational approaches such as pharmacophore modeling and similarity search methods. Moreover, an inspection of the docked poses of the tested compounds showed that chlorogenic acid and dihydrocaffeic acid could be considered as lead compounds worthy of further optimization.

Design, synthesis and biological evaluation of novel glyoxalase I inhibitors possessing diazenylbenzenesulfonamide moiety as potential anticancer agents

The enzyme glyoxalase-I (Glo-I) is an essential therapeutic target in cancer treatment. Significant efforts have been made to discover competitive inhibitors of Glo-I as potential anticancer agents. Herein, we report the synthesis of a series of diazenylbenzenesulfonamide derivatives, their in vitro evaluation against Glo-I and the resulting structure-activity relationships. Among the compounds tested, compounds 9h and 9j exhibited the highest activity with IC50 1.28 µM and 1.13 µM, respectively. Docking studies to explore the binding mode of the compounds identified key moieties that may contribute to the observed activities. The active compounds will serve as suitable leads for further chemical optimization.

Tackling COVID-19: identification of potential main protease inhibitors via structural analysis, virtual screening, molecular docking and MM-PBSA calculations

The widespread of the COVID-19 disease, caused by the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), had severely affected the entire world. Unfortunately, no successful vaccines or antiviral drugs are currently available which leaves the scientific community under huge pressure to tackle this pandemic. Among the identified promising druggable targets, specific to this virus, is the main protease (M^pro) enzyme, which is vital for viral replication, transcription and packaging within the host cells. In this study, selective inhibition of the M^pro was sought via thorough analysis of its available structural data in the Protein Data Bank. To this end, COVID-19 M^pro crystal complexes were explored and the key interacting residues (KIRs) within its active site, that are expected to be vital for effective ligand binding, were identified. Based on these KIRs, 3D pharmacophore models were generated and used in virtual screening of different databases. Retrieved hits were docked into the active site of the enzyme and their MM-PBSA based free binding energies were calculated. Finally, ADMET descriptors were calculated to aid the selection of top scoring hits with best ADMET properties. Nine compounds with different chemotypes were identified as potential M^pro inhibitors. Further, MD simulations of a virtual complex of M^pro with one of the promising hits revealed stable binding which is indicative of good inhibitory potential. The identified compounds in this study are expected to support the global drug discovery efforts in fighting against this highly contagious virus by narrowing the searchable chemical space for potential effective therapeutics.Communicated by Ramaswamy H. Sarma.