Mohamed Diwan Abdulhameed Email & Phone Number

Frederick, Md

Principal investigator in computational toxicology/drug discovery projects with a focus on developing cheminformatics methodologies and tools to assist in hit prioritization and ADMET prediction.* Managing countermeasure discovery project focused on muscarinic receptors* Developing machine learning models and methods to improve ligand-based virtual screening approach* Toxicogenomic data analysis to understand mechanisms of toxicity* Developed correction based on shuffling (CBOS) approach that improves the performance of 3D ligand-based virtual screening* Supervise the development of software applications to aid in hit prioritization* Manage collaborations with experimental groups from Alchem, Fl, and Vanderbilt University, TNToxProfiler:- Created tool to predict chemical-toxicity target interaction: https://toxpro.bhsai.org/loginLiver Steatosis:- Developing a computational tool to predict liver steatosis using integrated cheminformatics and toxicogenomics approachesADME/TOX models:- Developed predictive, species-specific (rat/human) pregnane X receptor (PXR) QSAR models using the Bayesian approach - Utilized chemical similarity networks to explore the chemical space- SME for developing DoD BHSAI cheminformatics systemAcute Kidney Injury (AKI):- Generated the first compendium of gene co-expression modules in rat kidney tissue after exposure to diverse toxicants- Utilized machine learning approaches and developed a gene expression-based classification model that can predict the future onset of acute kidney injury.- Identified for the first time the involvement of immunoproteasomes in acute kidney injuryLiver Fibrosis:- Developed a computational protocol to integrate gene expression data with protein-protein interaction networks and identify de novo toxicity pathways- Identified new gene signature for detecting liver fibrosis and experimentally validated it animal exposure studies (U.S. patent)

Maryland

- Developed a novel ligand-based target fishing approach for exploring polypharmacology profile of drugs. - Involved in anti-bacterial drug design- Discovered new lead molecules for bacterial targets: FabI (Francisella tularensis) and CapD (Bacillus anthracis)- Carried out drug repurposing screens against FabI and identified dicumarol as a new hit- Participated in generation of metabolism and toxicity reports for lead optimization- Participated in multi-center, collaborative (including GE) effort to create countermeasure discovery pipeline. Carried out target prioritization, rapid virtual screening, and identified hits against multiple, species-specific targets (Chikungunya virus, Francisella tularensis)- Participated in collaborative work with Moulder Center for Drug Discovery Research. Carried out off-target profiling and contributed to lead prioritization of natural product-based anti-cancer agents.- Involved in identification of biomarkers for traumatic brain injury by using systems biology approaches.

Lexington, Kentucky

- Dissertation: Computational design of new anti-cancer agents. 3-Phosphoinositide dependent kinase-1 - Carried out small molecule drug design for a number of important therapeutic targets implicated in cancer, inflammation, Alzhemier's disease and nicotine addiction. The different targets I worked on include PDK1, mPGES-1, LMP2, BChE and CYP2A6. - Developed hierarchical virtual screening protocol for screening large databases. Used a combination of approaches like docking, ligand-based screening, de novo design, molecular dynamics simulations and binding free energy calculations to identify the new leads.- Discovered two new lead molecules for 3-Phosphoinositide dependent kinase-1 (PDK1) with in vitro activity against cancer cell lines- Identified a novel binding mode of celecoxib - PDK1 interaction without kinase hinge hydrogen bonds. I reported the first computational model for kinase inhibitors without hinge hydrogen bonds before such binding mode X-ray crystal structure were published. - Discovered the molecular basis for selectivity of first, LMP2 subunit-specific immunoproteasome inhibitor- Played a major role in developing the first 3D structural model of mPGES-1 (Published as Cover Article). Developed predictive 3D-QSAR model for microsomal prostaglandin E synthase-1 (mPGES-1) inhibitors.Identified the binding mode of mPGES-1 inhibitors by using a novel approach of integrating ligand-based contour plots with structural modeling- Developed a natural products database and integrated natural products with computational screening. I identified a natural product from Mangifera species, as an inhibitor of PDK1- Developed ligand based, predictive 3D-QSAR models for PDK1

Teaching Assitant in Biochemistry and Medicinal chemistry courses for Pharmacy students at UKY.

Chennai Area, India

- Involved in computer-aided anti-microbial and anti-inflammatory drug discovery

Ph.D., Computational Drug Design Of Anti-Cancer Agents

M.Pharm, Medicinal And Pharmaceutical Chemistry

B.Pharm, Pharmacy

Activities and Societies: Indian Pharmacy Graduates Association -Organized State-level National Pharmacy Week celebrations