h
hmalik2470

Azan

@hmalik2470

Computational Drug Discovery Expert, Bioinformatics and Academic Outreach

Bangladesh
Bengaals, Engels
Sommige informatie wordt in het Engels weergegeven.
Over mij
I am Mahedi Hassan, a researcher in Biochemistry & Bioinformatics. I specialize in Computational Drug Design (CADD) & Academic Strategy. 🔬 Research: Expert in MD Simulations (GROMACS, AMBER) up to 100ns, Molecular Docking (AutoDock Vina), & MM-PBSA analysis. I use Linux/Python for data precision. 🎓 Outreach: I provide Academic Lead Generation, helping scholars find potential PIs/Professors with verified email databases & Cold Email strategies for PhD applications. ✍️ Deliverables: 3D Molecular Renderings (PyMOL) & scientific reports. Let's accelerate your research and academic journey! ... Lees meer

Skills

h
hmalik2470
Azan
offline • 
Gemiddelde reactietijd: 1 uur

Bekijk mijn diensten

Programmering en technologie
I will run up to 100ns molecular dynamics simulation of a protein ligand complex
Data
I will perform molecular docking with full analysis

Portfolio

Werkervaring

Founder

InSilico Scholars Hub • Fulltime

Dec 2025 - Present5 mos

Role: Founder & Lead Researcher (In-Silico Drug Discovery) At InSilico Scholars Hub, I focus exclusively on advanced computational research and bioinformatics to accelerate the drug discovery process. My work involves high-throughput screening and molecular modeling to identify potent therapeutic candidates. Key In-Silico Research Topics & Expertise: MERS-CoV & Viral Targeting: Conducting specialized In-silico research to identify bioactive phytocompounds that target essential proteins of MERS-CoV. This involves large-scale virtual screening and molecular docking. Combatting Antimicrobial Resistance (MRSA): Using computational tools to target Methicillin-resistant Staphylococcus aureus (MRSA). I focus on identifying novel lead compounds that can effectively bypass existing bacterial resistance mechanisms. Molecular Dynamics (MD) Simulation: Performing extensive simulations (e.g., 30ns to 500ns) using GROMACS to study the stability, binding affinity, and structural behavior of protein-ligand complexes. Bioinformatics Pipeline Development: Designing and implementing specialized workflows for analyzing structural data, ensuring high precision in predicting molecular interactions. Data Visualization: Creating high-resolution 3D renderings and interaction maps using tools like PyMOL, VMD, and Discovery Studio for detailed research reporting.

Research Assistant

Genexa Foundation • Fulltime

May 2025 - Dec 20257 mos

Role: Research Assistant During my tenure as a Research Assistant, I focused on cutting-edge drug discovery projects targeting high-priority pathogens. My work integrated computational biology with experimental validation to identify novel therapeutic candidates. Key Research Areas & Contributions: MERS-CoV & Viral Inhibition: Investigated the therapeutic potential of bioactive phytocompounds against MERS-CoV. I conducted molecular docking and stability analysis to identify compounds that effectively interfere with viral replication. Targeting Methicillin-Resistant Bacteria (MRSA): Addressed the challenge of antimicrobial resistance by screening natural inhibitors against Methicillin-resistant Staphylococcus aureus (MRSA) and other resistant bacterial strains. In-Vitro Laboratory Trials: Validated in-silico predictions through rigorous in-vitro experiments. I performed laboratory trials to determine the efficacy of selected compounds in inhibiting bacterial growth and viral activity. Cell Culture Studies: Managed and executed protocols for various cell culture models. I evaluated the cytotoxicity and bioactivity of phytocompounds, ensuring their safety and effectiveness in biological systems. Data Integration: Analyzed experimental data to bridge the gap between computational models and benchwork, providing a comprehensive understanding of ligand-target interactions. Technical Expertise: Molecular Docking, Cell Line Maintenance, In-Vitro Assays, Phytochemistry, and Antibacterial Resistance Profiling.