プロフィール詳細

プロジェクトを作成

★★★★★

☆☆☆☆☆

★★★★★

☆☆☆☆☆

Laiba S.に依頼

Pakistan

Computational Chemist | M.Phil | Published in RSC Advances 2025 | Expert in MD Simulation, Molecular Docking & 3D-QSAR

プロフィール概要

M.Phil Chemistry with publication in RSC Advances 2025 on SARS-CoV-2 Main Protease inhibitors. Completed 100+ page thesis on computational drug discovery. Led all computational work for the published study including molecular docking, Protein Flexibility Analysis using iMOD Normal Mode Analysis, MM-GBSA binding energy calculations, ADMET profiling, and 3D-QSAR modeling. Tools: Schrödinger Suite Maestro, Glide, Prime, QikProp, PerkinElmer ChemDraw, BIOVIA Discovery Studio Visualizer & iMOD Server. I help biotech startups and researchers accelerate drug discovery with accurate computational analysis and publication-ready reports.

専門分野

• ★ Molecular Docking
• ★ Drug Discovery
• ☆ Computational Chemistry
• ☆ Medicinal Chemistry
• ☆ COVID-19

サービス

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing Medical Writing, Technical Writing, Creative Writing

Research Meta-Research, Feasibility Study, Gray Literature Search, Scientific and Technical Research, Systematic Literature Review

Consulting Healthcare Consulting, Scientific and Technical Consulting, Regulatory Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Analysis, Data Visualization

Product Development Formulation, Product Validation, Concept Development

職務経験

MPhil. research scholar

Government College Women University Faisalabad

10月 2021 - 12月 2023

学歴

M.Phil. Chemistry

Government collage women university Faisalabad (GCWUF)

10月 2021 - 12月 2023

認定資格

• 認定資格の詳細は未入力です。

出版物

JOURNAL ARTICLE

Laiba Shahbaz, Shagufta Parveen, Nusrat Shafiq, Maryam Rashid, Mohamed Mohany, Mingkun Zhu (2025). An integrated theoretical study on natural alkaloids as SARS-CoV-2 main protease inhibitors: a step toward discovery of potential drug candidates with anti-COVID-19 activity . RSC Advances.