Most Monogenic Disorders Are Caused by Mutations Altering Protein Folding Free Energy

Revealing the molecular effect that pathogenic missense mutations have on the corresponding protein is crucial for developing therapeutic solutions. This is especially important for monogenic diseases since, for most of them, there is no treatment available, while typically, the treatment should be provided in the early development stages. This requires fast targeted drug development at a low cost. Here, we report an updated database of monogenic disorders (MOGEDO), which includes 768 proteins and the corresponding 2559 pathogenic and 1763 benign mutations, along with the functional classification of the corresponding proteins. Using the database and various computational tools that predict folding free energy change (ΔΔG), we demonstrate that, on average, 70% of pathogenic cases result in decreased protein stability. Such a large fraction indicates that one should aim at in silico screening for small molecules stabilizing the structure of the mutant protein. We emphasize that knowledge of ΔΔG is essential because one wants to develop stabilizers that compensate for ΔΔG, but do not make protein over-stable, since over-stable protein may be dysfunctional. We demonstrate that, by using ΔΔG and predicted solvent exposure of the mutation site, one can develop a predictive method that distinguishes pathogenic from benign mutations with a success rate even better than some of the leading pathogenicity predictors. Furthermore, hydrophobic-hydrophobic mutations have stronger correlations between folding free energy change and pathogenicity compared with others. Also, mutations involving Cys, Gly, Arg, Trp, and Tyr amino acids being replaced by any other amino acid are more likely to be pathogenic. To facilitate further detection of pathogenic mutations, the wild type of amino acids in the 768 proteins mentioned above was mutated to other 19 residues (14,847,817 mutations), the ΔΔG was calculated with SAAFEC-SEQ, and 5,506,051 mutations were predicted to be pathogenic.

Variation in the Chemical Composition of Endemic Specimens of Hedychium coronarium J. Koenig from the Amazon and In Silico Investigation of the ADME/Tox Properties of the Major Compounds

Four species of the genus Hedychium can be found in Brazil. Hedychium coronarium is a species endemic to India and Brazil. In this paper, we collected six specimens of H. coronarium for evaluation of their volatile chemical profiles. For this, the essential oils of these specimens were extracted using hydrodistillation from plant samples collected in the state of Pará, Brazil, belonging to the Amazon region in the north of the country. Substance compounds were identified with GC/MS. The most abundant constituent identified in the rhizome and root oils was 1,8-cineole (rhizome: 35.0-66.1%; root: 19.6-20.8%). Leaf blade oil was rich in β-pinene (31.6%) and (E)-caryophyllene (31.6%). The results from this paper allow for greater knowledge about the volatile chemical profile of H. coronarium specimens, in addition to disseminating knowledge about the volatile compounds present in plant species in the Amazon region.

Molecular docking, QSAR, pharmacophore modeling, and dynamics studies of some chromone derivatives for the discovery of anti-breast cancer agents against hormone-dependent breast cancer

In search of new anti-breast cancer agents, the present study envisaged the design and synthesis of a series of benzopyran-chalcones. All the synthesized compounds were assayed for their in-vitro anticancer activity against ER + MCF-7 and triple-negative MDA-MB-231 breast cancer cell lines using SRB assay. The synthesized compounds were found active against ER + MCF-7 cell lines. Based on the in-vitro data, in-silico analysis was performed using hormone-dependent breast cancer targets such as hER-α and aromatase because the compounds showed activity against MCF-7 cells and none was active against MDA-MB-231. The in-silico results supported the in-vitro anticancer activity suggesting the affinity of compounds toward hormone-dependant breast cancer. Compounds 4A1 to 4A3 were found to be most cytotoxic to MCF-7 cells with IC50 values of 31.87, 22.95, and 20.34 μg/ml, respectively (Doxorubicin IC50: <10 μg/ml). In addition, they showed the interactions with the amino acid residues of a binding cavity of an hER-α. Furthermore, quantitative structure-activity relationship (QSAR) studies were performed to reveal the vital structural features required for anticancer activity against breast cancer. Molecular dynamic simulation studies of hER-α and 4A3 in comparison with the raloxifene complex ensure the appropriate refinement of compounds in the dynamic system. Additionally, a generated pharmacophore model explored the essential pharmacophoric features of the synthesized scaffolds with respect to clinically used drug molecules for optimal hormone-dependant anti-breast cancer activity.Communicated by Ramaswamy H. Sarma.

Synthesis of new diphenyl urea-clubbed imine analogs and its Implications in diabetic management through in vitro and in silico approaches

Type II diabetes mellitus (T2DM) is a global health issue with high rate of prevalence. The inhibition of α-glucosidase enzyme has prime importance in the management of T2DM. This study was established to synthesize Schiff bases of 1,3-dipheny urea (3a-y) and to investigate their in vitro anti-diabetic capability via inhibiting α-glucosidase, a key player in the catabolism of carbohydrates. The structures of all compounds were confirmed through various techniques including, Fourier-transform infrared spectroscopy (FTIR) and nuclear magnetic resonance (NMR) and mass-spectrometry (MS) methods. Interestingly all these compounds displayed potent inhibition IC₅₀ values in range of 2.14-115 µM as compared to acarbose used as control. Additionally, all the compounds were docked at the active site of α-glucosidase to predict their mode of binding. The docking results indicates that Glu277 and Asn350 play important role in the stabilization of these compounds in the active site of enzyme. These molecules showed excellent predicted pharmacokinetics, physicochemical and drug-likeness profile. The anti-diabetic potential of these molecules signifies their medical importance and provide insights into prospective therapeutic options for the treatment of T2DM.

Identification of hydantoin based Decaprenylphosphoryl-β-D-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools

Tuberculosis (TB) is one of the emerging infectious diseases in the world. DprE1 (Decaprenylphosphoryl-β-D-ribose 2'-epimerase), an enzyme accountable for mycobacterial cell wall synthesis was the first drug gable target based on discoveries of inhibitors via HTS (high throughput screening). Since then, many literature reports have been published so far enlightening varieties of chemical scaffolds acting as inhibitors of DprE1. Herein, in our present study, we have developed statistically robust GA-MLR (genetic algorithm multiple linear regression), atom-based as well as field based-3D-QSAR models. Both atom-based as well as field based-3D-QSAR models (internally as well as externally validated) were obtained with robust Training set, R² > 0.69 and Test set, Q² > 0.50. We have also developed top ranked 5 point hypothesis AAAHR_1 among 14 CPHs (common pharmacophore hypotheses). We found that our dataset molecule had more docking score (XP mode = - 9.068 kcal/mol) than the standards isoniazid and ethambutol; when docked into binding pockets of enzyme 4P8C with Glide module. We further queried our best docked dataset molecule 151 for ligand based virtual screening using "SwissSimilarity" platform. Among 9 identified hits, we found ZINC12196803 had best binding energies and docking score (docking score = - 9.437 kcal/mol, MMGBSA dgBind = - 70.508 kcal/mol). Finally, our molecular dynamics studies for 1.2-100 ns depicts that these complexes are stable. We have also carried out in-silico ADMET predictions, Cardiac toxicity, 'SwissTargetPredictions' and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) binding energy calculations for further explorations of dataset as well as hit molecules. Our current studies showed that the hit molecule ZINC12196803 may enlighten the path for future developments of DprE1 inhibitors.

3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Dynamics Simulations for the Identification of Spleen Tyrosine Kinase Inhibitors

Spleen tyrosine kinase (SYK) is an essential mediator of immune cell signaling and has been anticipated as a therapeutic target for autoimmune diseases, notably rheumatoid arthritis, allergic rhinitis, asthma, and cancers. Significant attempts have been undertaken in recent years to develop SYK inhibitors; however, limited success has been achieved due to poor pharmacokinetics and adverse effects of inhibitors. The primary goal of this research was to identify potential inhibitors having high affinity, selectivity based on key molecular interactions, and good drug-like properties than the available inhibitor, fostamatinib. In this study, a 3D-QSAR model was built for SYK based on known inhibitor IC₅₀ values. The best pharmacophore model was then used as a 3D query to screen a drug-like database to retrieve hits with novel chemical scaffolds. The obtained compounds were subjected to binding affinity prediction using the molecular docking approach, and the results were subsequently validated using molecular dynamics (MD) simulations. The simulated compounds were ranked according to binding free energy (ΔG), and the binding affinity was compared with fostamatinib. The binding mode analysis of selected compounds revealed that the hit compounds form hydrogen bond interactions with hinge region residue Ala451, glycine-rich loop residue Lys375, Ser379, and DFG motif Asp512. Identified hits were also observed to form a desirable interaction with Pro455 and Asn457, the rare feature observed in SYK inhibitors. Therefore, we argue that identified hit compounds ZINC98363745, ZINC98365358, ZINC98364133, and ZINC08789982 may help in drug design against SYK.