Goverdhan Lanka

Pharmacophore-based virtual screening, 3D QSAR, Docking, ADMET, and MD simulation studies: An in silico perspective for the identification of new potential HDAC3 inhibitors

Goverdhan Lanka, Darakhshan Begum, Suvankar Banerjee et al. · Computers in Biology and Medicine · 2023 · 98 citations

Medicinal Chemistry, Virtual Screening, Silico Perspective +13

Structure-based identification of potential novel inhibitors targeting FAM3B (PANDER) causing type 2 diabetes mellitus through virtual screening

Goverdhan Lanka, Revanth Bathula, Mahendar Dasari et al. · Journal of Receptors and Signal Transduction · 2019 · 25 citations

Drug Target, Engineering, Insulin Signaling +24

Fragment-based discovery of new potential DNMT1 inhibitors integrating multiple pharmacophore modeling, 3D-QSAR, virtual screening, molecular docking, ADME, and molecular dynamics simulation approaches

Goverdhan Lanka, Suvankar Banerjee, Nilanjan Adhikari et al. · Molecular Diversity · 2024 · 22 citations

Multiple Pharmacophore Modeling, Medicinal Chemistry, Drug Target +10

Identification of potential Aurora kinase-C protein inhibitors: an amalgamation of energy minimization, virtual screening, prime MMGBSA and AutoDock

Revanth Bathula, Goverdhan Lanka, Narasimha Muddagoni et al. · Journal of Biomolecular Structure and Dynamics · 2019 · 19 citations

Glide Docking, Autodock, Binding Free Energy and Drug-Likeness Studies for Prediction of Potential Inhibitors of Cyclin-Dependent Kinase 14 Protein in Wnt Signaling Pathway

Revanth Bathula, Narasimha Muddagoni, Goverdhan Lanka et al. · Biointerface Research in Applied Chemistry · 2021 · 18 citations · Full text

Drug Target, Engineering, Molecular Biology +23