Seq12, Seq12m, and Seq13m, peptide analogues of the spike glycoprotein shows antiviral properties against SARS-CoV-2: An in silico study through molecular docking, molecular dynamics simulation, and MM-PB/GBSA calculations.

At the very beginning of the new decade, the COVID-19 pandemic has badly hit modern human societies. SARS-CoV-2, the causative agent of COVID-19 acquiring mutations and circulating as new variants. Herein, we have found three new antiviral peptides (AVPs) against the SARS-CoV-2. These AVPs are analogous to the spike glycoprotein of the SARS-CoV-2. Antiviral peptides, i.e., Seq12, Seq12m, and Seq13m, can block the receptor-binding domain (RBD) of the SARS-CoV-2, which is necessary for communicating with the angiotensin-converting enzyme 2 (ACE2). Also, these AVPs sustain their antiviral properties, even after the insertion of 25 mutations in the RBD (Rosetta and FoldX based). Further, Seq12 and Seq12m showed negligible cytotoxicity. Besides, the binding free energies calculated using MM-PB/GBSA method are also in agreement with the molecular docking studies. The molecular interactions between AVPs and the viral membrane protein (M) also showed a favorable interaction suggesting it could inhibit the viral re-packaging process. In conclusion, this study suggests Seq12, Seq12m, and Seq13m could be helpful to fight against SARS-CoV-2. These AVPs could also aid virus diagnostic tools and nasal spray against SARS-CoV-2 in the future.

Homology modeling and in silico design of novel and potential dual-acting inhibitors of human histone deacetylases HDAC5 and HDAC9 isozymes.

Histone deacetylases (HDACs) are a group of enzymes that have prominent and crucial effect on various biological systems, mainly by their suppressive effect on transcription. Searching for inhibitors targeting their respective isoforms without affecting other targets is greatly needed. Some histone deacetylases have no crystal structures, such as HDAC5 and HDAC9. Lacking proper and suitable crystal structure is obstructing the designing of appropriate isoform selective inhibitors. Here in this study, we constructed human HDAC5 and HDAC9 protein models using human HDAC4 (PDB:2VQM_A) as a template by the means of homology modeling approach. Based on the Z-score of the built models, model M0014 of HDAC5 and model M0020 of HDAC9 were selected. The models were verified by MODELLER and validated using the Web-based PROCHECK server. All selected known inhibitors displayed reasonable binding modes and equivalent predicted Ki values in comparison to the experimental binding affinities (Ki/IC50). The known inhibitor Rac26 showed the best binding affinity for HDAC5, while TMP269 showed the best binding affinity for HDAC9. The best two compounds, CHEMBL2114980 and CHEMBL217223, had relatively similar inhibition constants against HDAC5 and HDAC9. The built models and their complexes were subjected to molecular dynamic simulations (MD) for 100 ns. Examining the MD simulation results of all studied structures, including the RMSD, RMSF, radius of gyration and potential energy suggested the stability and reliability of the built models. Accordingly, the results obtained in this study could be used for designing de novo inhibitors against HDAC5 and HDAC9. Communicated by Ramaswamy H. Sarma.

Structure-based virtual screening for novel potential selective inhibitors of class IIa histone deacetylases for cancer treatment.

The fundamental cause of human cancer is strongly influenced by down- or up-regulations of epigenetic factors. Upregulated histone deacetylases (HDAC) have been shown to be effectively neutralized by the action of HDACs inhibitors (HDACi). However, cytotoxicity has been reported in normal cells because of non-specificity of several available HDACis that are in clinical use or at different phases of clinical trials. Because of the high amino acid sequence and structural similarity among HDAC enzymes, it is believed to be a challenging task to obtain isoform-selectivity. The essential aim of the present research work was to identify isoform-selective inhibitors against class IIa HDACs via structure-based drug design. Based on the highest binding affinity and isoform-selectivity, the top-ranked inhibitors were in silico tested for their absorption, distribution, metabolism, elimination, and toxicity (ADMET) properties, which were classified as drug-like compounds. Later, molecular dynamics simulation (MD) was carried out for all compound-protein complexes to evaluate the structural stability and the biding mode of the inhibitors, which showed high stability throughout the 100 ns simulation. Free binding energy predictions by MM-PBSA method showed the high binding affinity of the identified compounds toward their respective targets. Hence, these inhibitors could be used as drug candidates or as lead compounds for more in silico or in vitro optimization to design safe isoform-selective HDACs inhibitors.

Homology modeling of human GABA-AT and devise some novel and potent inhibitors via computer-aided drug design techniques.

γ-aminobutyric acid aminotransferase (GABA-AT) is a pyridoxal 5'-phosphate (PLP)-dependent enzyme which degrades γ-aminobutyric (GABA) in the brain. GABA is an important inhibitory neurotransmitter that plays important neurological roles in the brain. Therefore, GABA-AT is an important drug target which regulates the GABA level. Novel and potent drug development to inhibit GABA-AT is still very challenging task. In this study, we aimed to devise novel and potent inhibitors against GABA-AT using computer-aided drug design (CADD) tools. However, the human GABA-AT crystal structure is not available yet, and we built the 3D structure of human GABA-AT based on the crystal structure of pig's liver (Sus Scrofa) enzyme as a template. The generated model was validated with numerous tools such as ProSA and PROCHECK. A set of selected well-known inhibitors have been tested against the modeled GABA-AT. Molecular docking studies have been accomplished via application of Genetic Optimization for Ligand Docking (GOLD), Vina and Autodock 4.2 software to search for potent inhibitors. The best two candidate inhibitors have been computationally examined for absorption, distribution, metabolism, elimination and toxicity descriptors (ADMET) and Lipinski's rule of 5. Lastly, molecular dynamics (MD) simulations were carried out to inspect the ligands' binding mode and stability of the active site of human GABA-AT over time. The top ranked ligands exhibited reliable stability throughout the MD simulation. The selected compounds are promising candidates and might be tested experimentally for the inhibition of human GABA-AT enzyme. Communicated by Ramaswamy H. Sarma.

Discovery of novel isoform-selective histone deacetylases 5 and 9 inhibitors through combined ligand-based pharmacophore modeling, molecular mocking, and molecular dynamics simulations for cancer treatment.

Class IIa histone deacetylases (HDACs) 5 and 9 play crucial roles in several human disorders such as cancer, making them important targets for drug design. Continuous research is pursed to overcome the cytotoxicity side effect that comes with the currently available broad-spectrum HDACs inhibitors. Herein, common features of active HDACs inhibitors in clinical trials and use have been calculated to generate the best pharmacophore hypothesis. Guner-Henry scoring system was used to validate the generated hypotheses. Hypo1 of HDAC5 and Hypo2 of HDAC9 exhibited the most statistically significance hypotheses. Compounds with fit value of 3 and more were examined by QuickVina 2 docking tool to calculate their binding affinity toward all class IIa HDACs. A total of 6 potential selective compounds were subjected to 100 molecular dynamics (MD) simulation to examine their binding modes. The free binding energy calculations were computed according to the MM-PBSA method. Proposed selective compounds displayed good stability with their targets and thus they may offer potent leads for the designing of HDAC5 and HDAC9 isoform selective inhibitors.

Drug repurposing for coronavirus (COVID-19): in silico screening of known drugs against coronavirus 3CL hydrolase and protease enzymes.

In December 2019, COVID-19 epidemic was described in Wuhan, China, and the infection has spread widely affecting hundreds of thousands. Herein, an effort was made to identify commercially available drugs in order to repurpose them against coronavirus by the means of structure-based virtual screening. In addition, ZINC15 library was used to identify novel leads against main proteases. Human TMPRSS2 3D structure was first generated using homology modeling approach. Our molecular docking study showed four potential inhibitors against Mpro enzyme, two available drugs (Talampicillin and Lurasidone) and two novel drug-like compounds (ZINC000000702323 and ZINC000012481889). Moreover, four promising inhibitors were identified against TMPRSS2; Rubitecan and Loprazolam drugs, and compounds ZINC000015988935 and ZINC000103558522. ADMET profile showed that the hits from our study are safe and drug-like compounds. Furthermore, molecular dynamic (MD) simulation and binding free energy calculation using the MM-PBSA method was performed to calculate the interaction energy of the top-ranked drugs.Communicated by Ramaswamy H. Sarma.

ß-Globin Mutations in Egyptian Patients With ß-Thalassemia.

ß-thalassemia is a common hereditary disorder, particularly in Middle Eastern countries. More than 200 mutations in the ß globin gene have been reported; most are point mutations in functionally important regions (HBB; OMIM #141900)). The spectrum of mutations varies significantly between different geographical regions; only a few common mutations of ß-globin cause ß-thalassemia in each population. The aim of this study was to determine the spectrum of mutations that cause ß-thalassemia in the North Coast of Egypt and to investigate their correlation with the phenotypic severity of ß-thalassemia. We carried out our study with a total of 47 Egyptian patients (25 male and 22 female) confirmed to have ß-thalassemia. Evaluation of ß-thalassemia mutations revealed the presence of 10 ß-globin mutations. The most frequently encountered mutations were intronic: IVS 1.6 [T>C] (27.66%) and IVS 1.110 [G>A] (22.35%), followed by IVS 2.848 [C>A], IVS 1.1 (G>A), and IVS 2.745 [C>G]. We observed the exonic and promoter mutations less frequently. A homozygous mutation was found in 24 patients (51%) and compound heterozygous mutations were found in 13 patients (28%). However, in 9 patients (19%), we identified only 1 mutation. In 1 patient (2%), we detected no mutation. The detection rate of the method that we used in our population was 88% (83 of the tested 94 alleles). The results we obtained did not reveal any correlation between genotype and phenotype among patients with ß-thalassemia.