A phytochemical-based medication search for the SARS-CoV-2 infection by molecular docking models towards spike glycoproteins and main proteases.

Identifying best bioactive phytochemicals from different medicinal plants using molecular docking techniques demonstrates a potential pre-clinical compound discovery against SARS-CoV-2 viral infection. The screening of bioactive phytochemicals with the two druggable targets of SARS-CoV-2 by simple precision/extra precision molecular docking methods was used to compute binding affinity at its active sites. phyllaemblicin and cinnamtannin class of phytocompounds showed a better binding affinity range (-9.

Doxycycline prevents blood-brain barrier dysfunction and microvascular hyperpermeability after traumatic brain injury.

The main objective of this study was to determine the cellular and molecular effects of doxycycline on the blood-brain barrier (BBB) and protection against secondary injuries following traumatic brain injury (TBI). Microvascular hyperpermeability and cerebral edema resulting from BBB dysfunction after TBI leads to elevation of intracranial pressure, secondary brain ischemia, herniation, and brain death. There are currently no effective therapies to modulate the underlying pathophysiology responsible for TBI-induced BBB dysfunction and hyperpermeability.

Discovery of Anticancer Hybrid Molecules by Supervised Machine Learning Models and Validation in Drug Resistant Chronic Myeloid Leukemia Cells.

The concept of hybrid drugs for targeting multiple aberrant pathways of cancer, by combining the key pharmacophores of clinically approved single-targeted drugs, has emerged as a promising approach for overcoming drug-resistance. Here, we report the design of unique hybrid molecules by combining the two pharmacophores of clinically approved BCR-ABL inhibitor (ponatinib) and HDAC inhibitor (vorinostat) and results of studies in drug-resistant CML cells. Robust 2D-QSAR and 3D-pharmacophore machine learning supervised models were developed for virtual screening of the hybrid molecules based on their predicted BCR-ABL and HDAC inhibitory activity.

Predicting the Molecular Mechanism of EGFR Domain II Dimer Binding Interface by Machine Learning to Identify Potent Small Molecule Inhibitor for Treatment of Cancer.

Epidermal growth factor receptor (EGFR) is a transmembrane druggable target controlling cellular differentiation, proliferation, migration, survival and invasion. EGFR activation mainly occurs by its homo/hetro dimerization molecular phenomenon leading to tumor development and invasion. Several tyrosine kinase based inhibitors were discovered as potent anti-cancer drugs.

Predictive models for designing potent tyrosine kinase inhibitors in chronic myeloid leukemia for understanding its molecular mechanism of resistance by molecular docking and dynamics simulations.

BCR-ABL fusion protein drives chronic myeloid leukemia (CML) which constitutively activates tyrosine kinase involved in the initiation and maintenance of CML phenotype. Ponatinib, an oral drug, was discovered as an efficient BCR-ABL inhibitor by addressing imatinib drug resistance arising due to the point mutations at its active sites. In this study, 44 BCR-ABL kinase inhibitors, which are derivatives of ponatinib, were used to develop a robust two-dimensional quantitative structure-activity relationship (2D-QSAR) and 3D-Pharmacophore models by dividing dataset into 32 training sets and 12 test set molecules.

Multiple e-Pharmacophore modeling to identify a single molecule that could target both streptomycin and paromomycin binding sites for 30S ribosomal subunit inhibition.

The bacterial ribosome is an established target for anti-bacterial therapy since decades. Several inhibitors have already been developed targeting both defined subunits (50S and 30S) of the ribosome. Aminoglycosides and tetracyclines are two classes of antibiotics that bind to the 30S ribosomal subunit.

Structure-function studies of prothrombin Amrita, a dysfunctional prothrombin characterized by point mutation at Arg553 → Gln.

A dysfunctional prothrombin gene characterized by novel point mutation at Arg553 to Gln residue in Deep vein thrombosis (DVT) patient which we designated as "Prothrombin Amrita" was previously reported from our lab. The mutation occurred at nucleotide 20030 in exon 14 and was confirmed by restriction enzyme digestion. Arg553 has been reported as one of the key residues for the binding of cofactor Na ion in the thrombin protein.

Carboxymethylated ɩ-carrageenan conjugated amphotericin B loaded gelatin nanoparticles for treating intracellular Candida glabrata infections.

Intercellular Candida glabrata infections are difficult to treat due to poor penetration of drugs into the fungal niche. Delivering amphotericin B (Amp B) into the macrophages where the pathogen inhabits is an effective solution. We are studying the macrophage targeting proficiency of ɩ-carrageenan for the delivery of Amp B using gelatin A nanoparticles (GNPs).

Computational simulations and experimental validation of structure- physicochemical properties of pristine and functionalized graphene: Implications for adverse effects on p53 mediated DNA damage response.

Recent reports indicated DNA damaging potential of few-layer graphene in human cell systems. Here, we used computational technique to understand the interaction of both pristine (pG) or carboxyl functionalized graphene (fG) of different sizes (1, 6, and 10nm) with an important DNA repair protein p53. The molecular docking study revealed strong interaction between pG and DNA binding domains (DBD) of p53 with binding free energies (BE) varying from -12.

Epidermal growth factor receptor (EGFR) structure-based bioactive pharmacophore models for identifying next-generation inhibitors against clinically relevant EGFR mutations.

Present work elucidates identification of next generation inhibitors for clinically relevant mutations of epidermal growth factor receptor (EGFR) using structure-based bioactive pharmacophore modeling followed by virtual screening (VS) techniques. Three-dimensional (3D) pharmacophore models of EGFR and its different mutants were generated. This includes seven 3D pharmacophoric points with three different chemical features (descriptors), that is, one hydrogen bond donor, three hydrogen bond acceptors and three aromatic rings.

identification of T-type calcium channel blockers: A ligand-based pharmacophore mapping approach.

Limited progress has been made in the quest to identify both selective and non-toxic T-type calcium channel blocking compounds. The present research work was directed toward slaking the same by identifying the selective three dimensional (3D) pharmacophore map for T-type calcium channel blockers (CCBs). Using HipHop module in the CATALYST 4.