プロフィール詳細

プロジェクトを作成

★★★★★

☆☆☆☆☆

★★★★★

☆☆☆☆☆

Dr. Dr.Selvaraj S.に依頼

India

Computational Chemist | AI-Driven Drug Discovery | Molecular Modeling | QM/MM & MD Simulations

プロフィール概要

I am a computational chemist with extensive experience in molecular modeling, AI-driven drug discovery, and enzyme engineering. My research integrates quantum chemical simulations, molecular dynamics, and machine learning approaches to design and optimize biomolecules, catalysts, and therapeutic compounds. I completed my PhD at the University of Gdansk, Poland, where I developed computational frameworks for functional materials and nanoscale systems. I have also conducted research at leading international institutions including KTH Royal Institute of Technology (Sweden), the University of Rome (Italy), and Ewha Womans University (South Korea). My work focuses on combining quantum mechanics (QM), QM/MM simulations, molecular dynamics (MD), and machine learning techniques to study reaction mechanisms, protein–ligand interactions, enzyme engineering, and catalytic processes. I have experience with high-performance computing environments and widely used computational chemistry software such as Gaussian, GAMESS, AMBER, GROMACS, CP2K, and MODELLER. I have published multiple peer-reviewed articles in journals such as ACS Nano, International Journal of Molecular Sciences, Journal of Physical Chemistry B, and others. My research interests include computational drug discovery, enzyme engineering, catalysis, nanomaterial modeling, and AI-assisted molecular design. I can assist clients with molecular modeling studies, computational drug discovery, docking and molecular dynamics simulations, quantum chemical calculations, QSAR/QSPR modeling, and scientific manuscript preparation.

専門分野

• ☆ Catalysis
• ☆ Biocatalysis
• ☆ Molecular Modeling
• ☆ Chemoinformatics
• ☆ Quantum Chemistry
• ☆ Theoretical Chemistry
• ☆ Computational Chemistry

サービス

• Writing
• Research
• Consulting
• Data & AI

Writing Medical Writing, Technical Writing, General Proofreading & Editing

Research User Research, Meta-Research, Scientific and Technical Research

Consulting Digital Strategy Consulting, Healthcare Consulting, Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-ML, Data Mining, Data Processing, Data Insights

職務経験

AI Researcher

Turing Inc.

1月 2026 - 現在

Associate Manager

Biocon Limited

3月 2023 - 7月 2024

学歴

Post-Doc

Ewha Women's University - Korea, Republic of

12月 2020 - 10月 2023

認定資格

• AMBER Molecular Dynamics Simulation Workshop

  AMBER Developers

  6月 2013 - 現在

• EMBO Biomolecular Simulation Training

  European Molecular Biology Organization

  7月 2010 - 現在

出版物

JOURNAL ARTICLE

Selvaraj Sengottiyan, Alicja Mikolajczyk, Karolina Jagiełło, Marta Swirog, Tomasz Puzyn (2023). Core, Coating, or Corona? The Importance of Considering Protein Coronas in nano-QSPR Modeling of Zeta Potential . ACS Nano.

Selvaraj Sengottiyan, Alicja Mikolajczyk, Tomasz Puzyn (2023). How Does the Study MD of pH-Dependent Exposure of Nanoparticles Affect Cellular Uptake of Anticancer Drugs? . International Journal of Molecular Sciences.

Selvaraj Sengottiyan, Alicja Mikolajczyk, Tomasz Puzyn (2023). How Does the Study MD of pH-Dependent Exposure of Nanoparticles Affect Cellular Uptake of Anticancer Drugs? . International Journal of Molecular Sciences.

Selvaraj Sengottiyan, Kakoli Malakar, Arunkumar Kathiravan, Marappan Velusamy, Alicja Mikolajczyk, Tomasz Puzyn(2022). Integrated Approach to Interaction Studies of Pyrene Derivatives with Bovine Serum Albumin: Insights from Theory and Experiment . The Journal of Physical Chemistry B. American Chemical Society ({ACS})

Arunkumar Kathiravan, Selvaraj Sengottiyan, Tomasz Puzyn, Pushparathinam Gopinath, Kanagachidambaresan Ramasubramanian, Praveen Ayyappan Susila, Mariadoss Asha Jhonsi(2022). Rapid colorimetric discrimination of cyanide ions – mechanistic insights and applications . Analytical Methods. Royal Society of Chemistry ({RSC})

Sengottiyan Selvaraj, Selvan Nehru (2021). Integrating electronic properties of Prodan by parameterization: Combining theory with experimentation . Journal of Molecular Structure.