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ikram_ullah183

Ikramullah

@ikram_ullah183

Medical Writer, CADD and Drug Discovery, Cheminformatics, Clinical Research

Pakistan
Inglese, Urdu
Alcune informazioni sono riportate in lingua inglese.
Chi sono
I am a motivated Doctor of Pharmacy (PharmD) candidate with over one year of experience in medical and research writing. I effectively combine a robust scientific background with meticulous attention to detail to produce high-quality annotated datasets essential for the development of computer vision models.... Continua a leggere

Competenze

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ikram_ullah183
Ikramullah
offline • 
Tempo di risposta medio: 1 ora

Consulta i miei servizi

Articoli educativi e informativi
I will write patient education and healthcare website content
A partire da10 USD / progettoMaggiori dettagli
Programmazione e tecnologia
I will analyse protein ligand interactions for drug discovery
A partire da15 USD / progettoMaggiori dettagli

Portfolio

Esperienza lavorativa

Fiverr

Content Writer

Fiverr • Freelance

Jan 2025 - Present • 1 yr 9 mos

Google

Google

Part time • 2 mos

Advanced Chemoinformatic

Jul 2026 - Aug 2026 • 1 mo

Completed a two-day Advanced Chemoinformatics Masterclass covering Python, RDKit, molecular descriptors, drug-likeness assessment, Lipinski’s Rule of Five, Veber’s rules, and cheminformatics workflows for drug discovery.

Computer aided drug designing

Jun 2026 - Jul 2026 • 1 mo

Selected for Cohort 5 of The Insilico Lab’s 3-Week Virtual Research Training in Computer-Aided Drug Design (CADD), focused on structure-based and AI-assisted drug discovery. Completed computational projects involving protein preparation, binding-site analysis, molecular docking, ligand screening, ADMET evaluation, protein–ligand interaction analysis, and AlphaFold3-based structure prediction. DHFR (PDB: 1U72): Evaluated curcumin, gefitinib, and kaempferol using SwissADME, PyRx/AutoDock Vina, PyMOL, DoGSiteScorer, UCSF Chimera, and Discovery Studio. Curcumin showed the strongest predicted binding, while kaempferol demonstrated the most balanced predicted ADMET profile. Generated an AlphaFold3 DHFR model showing strong agreement with the experimental structure (RMSD: 0.392 Å across 186 residues). Carbonic Anhydrase II (PDB: 3HS4): Compared acetazolamide, methazolamide, ethoxzolamide, dorzolamide, and brinzolamide through a structured CADD workflow. Acetazolamide and dorzolamide showed the most balanced predicted ADMET profiles. Generated an AlphaFold3 CA II model with a pTM score of 0.97 and RMSD of 0.173 Å across 257 residues.