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Molecular Pharmacology Internship Topics

Browse all focused areas across all internship categories under this field.

Molecular Pharmacology Internships with Accommodation

Choose an internship topic, then explore accommodation-enabled internship options at active NTHRYS branch locations in India.

Showing 1–10 of 10 internship topics
Protein-Ligand Binding Prediction Using Deep Learning
Interns will develop and train neural network models to predict binding affinities between drug candidates and target proteins using molecular docking data and structural information. They will work with datasets like PDBbind and learn to implement graph neural networks and convolutional architectures for molecular interaction prediction.
Machine Learning Signal Transduction Drug ResearchView internship →
Signal Transduction Pathway Classification and Network Analysis
Interns will analyze gene expression data and phosphoproteomic profiles to classify active signaling pathways in diseased cells using machine learning algorithms. They will construct and visualize signal transduction networks to identify key nodes and therapeutic targets in disease progression.
Machine Learning Signal Transduction Drug ResearchView internship →
Drug Response Prediction in Cell-Based Assays
Interns will build predictive models using machine learning to forecast cellular responses to pharmaceutical compounds based on transcriptomic and proteomic signatures. They will process high-throughput screening data and develop models for drug efficacy and toxicity assessment.
Machine Learning Signal Transduction Drug ResearchView internship →
Molecular Feature Engineering for ADMET Properties
Interns will extract and engineer molecular descriptors and fingerprints from chemical structures to predict drug absorption, distribution, metabolism, excretion, and toxicity properties. They will implement feature selection techniques and train regression models to optimize drug-likeness criteria.
Machine Learning Signal Transduction Drug ResearchView internship →
Kinase Inhibitor Selectivity Profiling and Mechanism Discovery
Interns will apply machine learning to kinase screening data to predict inhibitor selectivity profiles across the kinome and identify off-target effects. They will use classification models and structural bioinformatics to elucidate mechanism of action and optimize drug specificity.
Machine Learning Signal Transduction Drug ResearchView internship →
Phytochemical Isolation and Characterization
Interns will learn extraction techniques and chromatographic methods to isolate bioactive compounds from plant materials. They will use HPLC, LC-MS, and NMR spectroscopy to identify and characterize natural product structures for pharmacological evaluation.
Natural Product Bioactive ScreeningView internship →
High-Throughput Bioactivity Screening
Interns will conduct systematic screening of natural product libraries against relevant molecular targets using cell-based and biochemical assays. They will develop and optimize screening protocols, analyze data, and identify lead compounds with therapeutic potential.
Natural Product Bioactive ScreeningView internship →
Receptor Binding and Molecular Docking Studies
Interns will perform computational and experimental studies to evaluate how natural products interact with drug targets at the molecular level. They will use molecular docking software, surface plasmon resonance, and fluorescence assays to determine binding affinities and mechanisms.
Natural Product Bioactive ScreeningView internship →
Cytotoxicity and Cellular Mechanism Evaluation
Interns will assess the antiproliferative and cytotoxic effects of bioactive natural products on cancer and diseased cell lines using MTT assays, flow cytometry, and apoptosis detection methods. They will investigate cellular mechanisms including cell cycle arrest, apoptosis pathways, and oxidative stress responses.
Natural Product Bioactive ScreeningView internship →
Natural Product Structure-Activity Relationship (SAR) Analysis
Interns will design and synthesize structural analogs or derivatives of lead natural products to establish SAR profiles. They will correlate chemical modifications with changes in bioactivity using quantitative data analysis to optimize pharmacological properties.
Natural Product Bioactive ScreeningView internship →
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