In Silico Studies of Tumor Targeted Peptide-Conjugated Natural Products for Targeting Over-Expressed Receptors in Breast Cancer Cells Using Molecular Docking, Molecular Dynamics and MMGBSA Calculations

Molecular docking, MMGBSA, and ADMET studies of phytoconstituents of Ocimum gratissimum on multiple breast cancer targets

O. gratissimum is one of the most common medicinal plants in every community in Nigeria. This plant has been presumed to be useful in the management of diseases including breast cancer, which is one the commonest cancers affecting women globally. Hence, this study aimed to computationally investigate the phytochemicals present in O. gratissimum by elucidate their binding dynamics against five selected molecular targets of breast cancer and predict their pharmacokinetics properties. Molecular docking, MMGBSA calculation and ADMET prediction were used. The results showed that isovitexin has the highest binding affinity of -9.11 kcal/mol and -9.80 kcal/mol for Human Epidermal Growth Factor Receptor 2 (HER2) and Epidermal Growth Factor Receptor (EGFR) respectively. Rosmarinic acid has the highest binding affinity of -12.15 kcal/mol for Phosphatidylinositol 3-kinase (PI3K), Nepetoidin A has the highest binding affinity of -9.14 kcal/mol for oestrogen receptor (ER), and Vitexin has the highest binding affinity of -12.90 kcal/mol for Progesterone receptor (PR). MMGBSA provided total binding energy that confirmed the stability of the complexes under physiological conditions. The ADMET profiles showed that O. gratissimum top phytochemicals identified would be safe for oral administration with no hepatoxicity. Overall, this study identified isovitexin, vitexin, rosmarinic acid, nepetoidin A and luteolin among others, as compounds that exhibit strong anti-cancer properties against breast cancer cells.

In silico designing of an epitope-based peptide vaccine cocktail against Nipah virus: an Indian population-based epidemiological study

Nipah virus, a zoonotic virus from the family Paramyxoviridae has led to significant loss of lives till date with the most recent outbreak in India reported in Kerala. The virus has a considerably high mortality rate along with lack of characteristic symptoms which results in the delay of the virus detection. No specific vaccine is available for the virus although monoclonal antibody treatment has been seen to be effective along with favipiravir. The high mortality and complications caused by the virus underscores the necessity to develop alternative modes of vaccination. One such method has been designed in this study using peptide cocktail consisting of the immunologically important epitopes for use as vaccine. The human leucocytic antigens that are used for the study were analyzed for their presence in various ethnic Indian populations. This study may serve as a new avenue for development of more efficient peptide cocktail vaccines in recent future based on the population genetics and ethnicity.

Pharmacophore based virtual screening for identification of effective inhibitors to combat HPV 16 E6 driven cervical cancer

Targeting HPV16 E6 has emerged as an effective drug target for the treatment/management of cervical cancer. We utilized pharmacophore-based virtual screening, molecular docking, absorption, distribution, metabolism and excretion (ADME) prediction, and molecular dynamics simulation approach for identifying potential inhibitors of HPV16 E6. Initially, we generated a ligand-based pharmacophore model based on the features of four known HPV16 E6 inhibitors (CA24, CA25, CA26, and CA27) via the PHASE module implanted in the Schrödinger suite. We constructed four-point pharmacophore features viz., three hydrogen bond acceptors (A) and one aromatic ring (R). The common pharmacophore feature further employed as a query for virtual screening against the ASINEX database via Schrödinger suite. The pharmacophore-based virtual screening filtered out top 2000 hits, based on the fitness score. We then applied the high throughput virtual screening (HTVS), standard precision (SP) and extra precision (XP). 1000 compounds were obtained from HTVS docking. Based on the glide score, they were further filtered to 500 hits by employing docking in standard precision mode. Finally, the best four hits and a negative molecule were identified using docking in XP mode. The four lead compounds and a negative molecule were then further subjected to ADME profile prediction by engaging Qikprop module. The ADME properties of the four lead molecules indicate good pharmacokinetic (PK) properties rather than the negative molecule. The binding stability of the HPV16 E6-hit complexes were investigated at a different time scale (100 ns) by using the desmond package and the results were examined using Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF) and it revealed the stability of the protein-ligand complex throughout the simulation. Key residues, CYS 51 and GLN 107, also play a crucial role in enhancing the stability of the protein-ligand complex during the simulation. Furthermore, the binding free energy of the HPV16 E6-leads complexes was analyzed by prime which revealed that the ΔGbind coulomb and ΔGbind vdW interactions are crucially contributes to the binding affinity. In order to validate the computational findings, the efficacy of benzoimidazole and benzotriazole were ascertained for regulating ME180 cervical cancer cell survival, migration and ability to release MMP-2.