プロフィール詳細

プロジェクトを作成

★★★★★

☆☆☆☆☆

★★★★★

☆☆☆☆☆

Dr. Sharoon A.に依頼

United States

Computational Structural Biologist | GPU-Accelerated MD Simulations, AlphaFold2 & Virtual Screening

プロフィール概要

If you need a protein structure modeled, a binding interaction characterized, or a compound library screened against your target — and you need it done on dedicated GPU hardware with fast turnaround — I can help. I am a computational structural biologist with a PhD from Mayo Clinic, where my research focused on molecular dynamics simulations of serine proteases and cancer-relevant protein targets. I have 13 peer-reviewed publications spanning structural biology, cancer biology, and computational methods. What I deliver: • Structure prediction and homology modeling (AlphaFold2 running locally, not queued on shared servers) • All-atom molecular dynamics simulations in explicit solvent (AMBER and GROMACS, GPU-accelerated on an RTX 5090 with 32 GB VRAM) • Virtual screening and molecular docking campaigns (AutoDock Vina, ligand library preparation, ADMET filtering) • Trajectory analysis and publication-quality figures (RMSD, RMSF, hydrogen bond occupancy, free energy landscapes, rendered in PyMOL and VMD) • Automated analysis pipelines in Python for reproducible, auditable results My infrastructure is not shared or cloud-based. I run simulations on dedicated local hardware, which means faster iteration, no queue times, and full control over your data. Typical engagements range from $2,500 for a focused docking or structure prediction project to $8,000–$10,000 for multi-system MD simulation campaigns with full analysis reports. I scope every project with a written deliverables list and timeline before work begins. If you have a structural biology or drug discovery question that needs computational horsepower and scientific rigor, send me a message. I respond within 24 hours.

専門分野

• ☆ Biocatalysis
• ☆ Natural Product Chemistry
• ☆ Peptide Synthesis
• ☆ Computational Biology
• ☆ Phytochemistry
• ☆ Medicinal Plants
• ☆ Biostatistics
• ☆ Data Analysis
• ☆ Image Processing
• ☆ Computer Simulation/Computational Modeling
• ☆ Predictive Modeling & Analytics
• ☆ Data Processing
• ☆ Data Collection
• ☆ Machine Learning
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Pharmacy
• ☆ Clinical Pharmacy
• ☆ Drug Discovery
• ☆ High Throughput Screening (HTS)
• ☆ Drug Target Identification
• ☆ Hit-to-Lead & Lead Optimization
• ☆ Medicinal Chemistry
• ☆ Drug Design
• ☆ Structure-Activity Relationship (SAR) Studies
• ☆ Pharmaceutical Manufacturing
• ☆ Bioprocess Development
• ☆ In vitro Diagnostics
• ☆ In vitro Diagnostic Validation
• ☆ In vitro Diagnostic Design
• ☆ Biomarker Analysis
• ☆ Pharmacovigilance/Drug Safety Monitoring
• ☆ Precision Medicine
• ☆ Hematology
• ☆ Hematology-Oncology
• ☆ Leukemia & Lymphoma
• ☆ Cancer Research
• ☆ Cancer Biology
• ☆ Drug Delivery Technologies
• ☆ Liposomes
• ☆ Quality Assurance & Quality Control (QA/QC)
• ☆ Hypothesis
• ☆ Peer Review
• ☆ Research Methodology
• ☆ Survey Design & Methodology
• ☆ Meta-Research
• ☆ Literature Search
• ☆ Regulatory Writing
• ☆ NDA/BLA Applications
• ☆ Nonclinical Study Documentation
• ☆ Clinical Trial Documentation
• ☆ Clinical Trial Protocol Writing
• ☆ Clinical Study Reports
• ☆ Medical Writing
• ☆ Medical Content Writing
• ☆ Research Summaries & Abstracts
• ☆ Investigational New Drug (IND) Application Writing
• ☆ Technical & Scientific Writing
• ☆ Manuscript & Journal Article Writing
• ☆ Experimental Protocols
• ☆ SOP & Protocol Writing
• ☆ Spec Sheets
• ☆ Literature Review
• ☆ Traditional/Narrative Literature Review
• ☆ Systematic Literature Review
• ☆ Scientific Proofreading & Editing
• ☆ Proofreading & Editing
• ☆ Language Translation
• ☆ Creative Writing
• ☆ Speechwriting
• ☆ Grant Writing
• ☆ Small Business
• ☆ Data-Driven Decision Making
• ☆ Entrepreneurship

サービス

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

Writing Clinical Trial Documentation, Medical Writing, Non-Medical Regulatory Writing, Technical Writing, Business & Legal Writing, Copywriting, Creative Writing, Newswriting, General Proofreading & Editing, Translation

Research User Research, Meta-Research, Feasibility Study, Gray Literature Search, Scientific and Technical Research, Systematic Literature Review, Secondary Data Collection

Consulting Business Strategy Consulting, Scientific and Technical Consulting, Regulatory Consulting, Manufacturing Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

Product Development Formulation, Recipe Development, Product Evaluation, Product Validation, Manufacturing, Quality Assurance & Control (QA/QC), Product Compliance , Concept Development, Prototyping

職務経験

PhD Researcher

Mayo Clinic

8月 2020 - 現在

Clinical Research Coordinator

Mayo Clinic

1月 2020 - 8月 2020

Research Technologist

Mayo Clinic

10月 2014 - 1月 2020

Special Project Associate

Mayo Clinic

7月 2012 - 10月 2014

Biology and Chemistry Teacher

Beaconhouse School System

8月 2011 - 5月 2012

QA/QC Chemist

Xenon Pharamaceutical Pvt. Ltd.

7月 2008 - 9月 2008

学歴

PhD. (Biochemistry and Molecular Biology)

Mayo Clinic in Florida

8月 2020 - 現在

MPhil (Biotechnology)

Forman Christian College

10月 2009 - 11月 2011

BSc Hon (Chemistry )

Forman Christian College

9月 2005 - 6月 2009

認定資格

• Ingenuity Pathway Analysis

  Qaigen

  3月 2024 - 現在

• Certified Clinical Research Coordinator

  CITI Program

  3月 2020 - 現在

• RCR For Research Administrators

  CITI Program

  3月 2020 - 現在

• Bronze Quality Essentials Certification

  Mayo Clinic

  5月 2019 - 現在

• GCP for Clinical Trials with Investigational Drugs and Medical Devices (U.S. FDA Focus) - GCP

  Citi Protam

  7月 2019 - 7月 2022

出版物

JOURNAL ARTICLE

Sharoon Akhtar, Joshua W. Ogony, Laura M. Pacheco-Spann, Amanda Arnold, Jennifer V. Cabezas, Nicole Cruz-Reyes, Camila Pacheco Erak, Pria J. Westerman, Savanna A. Touré, Stacey J. Winham, et al. (2025). A STAT1-GBP1 axis modulates epithelial proliferation in postpartum breast tissue by repressing CDKI expression . Breast Cancer Research.

(2020). Novel tumor-targeted liposomes comprised of an MDM2 antagonist plus proteasome inhibitor display anti-tumor activity in a xenograft model of bortezomib-resistant Waldenstrom macroglobulinemia . Leukemia & Lymphoma.

(2019). Targeting CD38 Enhances the Antileukemic Activity of Ibrutinib in Chronic Lymphocytic Leukemia . Clinical Cancer Research.

(2018). Comparative Analysis on the Anti-Tumor Activity of Venetoclax and Obinutuzumab (VO) Versus Venetoclax and Rituximab (VR) in Primary CLL Cells, Ex Vivo . Blood.

(2018). Targeting CD38 with daratumumab is lethal to Waldenström macroglobulinaemia cells . British Journal of Haematology.

(2017). Waldenstrom macroglobulinemia cells devoid of BTKC481S or CXCR4WHIM-like mutations acquire resistance to ibrutinib through upregulation of Bcl-2 and AKT resulting in vulnerability towards venetoclax or MK2206 treatment . Blood Cancer Journal.

(2016). Drug Resistance Alters CD38 Expression and in Vitro Response to Daratumumab in Waldenstrom Macroglobulinemia Cells . Blood.

(2016). Coinhibition of the deubiquitinating enzymes, USP14 and UCHL5, with VLX1570 is lethal to ibrutinib- or bortezomib-resistant Waldenstrom macroglobulinemia tumor cells . Blood Cancer Journal.

(2016). The proteasome deubiquitinase inhibitor VLX1570 shows selectivity for ubiquitin-specific protease-14 and induces apoptosis of multiple myeloma cells . Scientific Reports.

(2015). Induction of Resistance to Proteasome Inhibition Preferentially Switches Survival Dependence from Bcl-2 to XIAP in Preclinical Models of Waldenstrom Macroglobulinemia: Pre-Clinical Rationale for Early Clinical Sequencing of ABT199 . Blood.

(2015). Targeted inhibition of the deubiquitinating enzymes, USP14 and UCHL5, induces proteotoxic stress and apoptosis in Waldenström macroglobulinaemia tumour cells . British Journal of Haematology.

(2015). Immunophenotyping of Waldenströms Macroglobulinemia Cell Lines Reveals Distinct Patterns of Surface Antigen Expression: Potential Biological and Therapeutic Implications . PLOS ONE.

(2014). Nimbolide targets BCL2 and induces apoptosis in preclinical models of Waldenströms macroglobulinemia . Blood Cancer Journal.

(2014). AT-101 downregulates BCL2 and MCL1 and potentiates the cytotoxic effects of lenalidomide and dexamethasone in preclinical models of multiple myeloma and Waldenström macroglobulinaemia . British Journal of Haematology.

(2012). In vitro dephytinization and bioavailability of essential minerals in several wheat varieties . Journal of Cereal Science.