[{"content":" About Journey Software Skills I\u0026rsquo;m a final-year Ph.D. candidate in the Durrant Lab at the University of Pittsburgh, working in computational structural biology and machine learning for drug discovery. I\u0026rsquo;m now seeking industry roles in computational drug discovery, ML for chemistry, and cheminformatics / scientific software. Here is how I got here.\nJourney # 2017 Education Education Entered Zewail City of Science and Technology Giza, Egypt Began undergraduate studies in Biomedical Sciences, drawn to the overlap of biology and computation. Transition Declared Computational Biology \u0026amp; Genomics Giza, Egypt Committed to computational approaches over traditional wet-lab work. Research Undergraduate genomics projects Giza, Egypt Built genomics tools from scratch in R, Python, and C++ — SNP calling, a diabetes SNP detector, a UPGMA tree builder, and a genomic-mismatch pipeline. Research Research internships Giza, Egypt Collected and analyzed EEG and facial-expression data for the Lumiere concentration-detection project, then interpreted variants and ran enrichment analysis (g:Profiler, KEGG) for an Alzheimer\u0026rsquo;s GWAS study. Research Undergraduate Thesis — AML drug sensitivity Giza, Egypt Trained Random Forest models to predict drug sensitivity from AML transcriptomic profiles, identifying markers linked to differential drug response. Advised by Dr. Eman Badr; graduated Cum Laude. Transition Moved to the U.S. to pursue drug discovery Pittsburgh, PA My thesis clarified the gap between finding genomic markers and knowing how a patient actually responds to a drug. To work on that gap, I moved to Pittsburgh for a PhD in Molecular, Cellular \u0026amp; Developmental Biology, focused on computational structural biology and drug design. Research First-year rotations Pittsburgh, PA Completed three ten-week rotations spanning the structural-biology spectrum: the VanDemark Lab (wet-lab structural biology — testing small-molecule inhibitors of the profilin–actin interaction by fluorescence anisotropy), the Durrant Lab (computational structural biology and drug design), and the Levin Lab (comparative genomics). Transition Joined the Durrant Lab Pittsburgh, PA Chose the Durrant Lab for my dissertation, focusing on structure-based drug design and open-source scientific software. Began developing LIGNOVA, an automated pipeline that docks bioactive PubChem compounds against experimental protein structures to build large-scale receptor-bound datasets for machine-learning — now over 232 million docked poses across 240,124 ligands and 10,851 structures, backed by a competitive NSF ACCESS allocation. Research Passed the comprehensive examination Pittsburgh, PA Defended an independent research proposal in an NIH F31 format to my committee, clearing the PhD comprehensive exam. Research Genomics collaboration — PNAS 2025 Pittsburgh, PA Extended my Levin Lab rotation into a co-first-author study of how a hypermutable hotspot drives rapid recognition-gene evolution in Dictyostelium. Led the computational genomics, genome assembly, QC, and targeted annotation across ten chromosome-length genomes. Published in PNAS (2025). Teaching Undergraduate Research Mentor — TECBio REU Pittsburgh, PA Co-mentored an undergraduate on a ten-week project applying AlphaFold2 to explore HIV protease conformations for drug design, culminating in a research poster. Present Advanced to PhD Candidacy Pittsburgh, PA Proposed my dissertation work to my committee and was admitted to candidacy. Now wrapping up my PhD (expected April 2027) and seeking industry roles in computational drug discovery, ML for chemistry, and cheminformatics. For the full record, see my CV and publications.\nSoftware # LIGNOVA durrantlab/lignova Automated pipeline to generate high-quality docked protein–ligand complexes at scale. Lead developer. ● Python · Bash · SLURM reqadence durrantlab/reqadence Async foundation for REST API clients with retries, rate limiting, and response caching. Lead developer. ● Python dicty_genomes teralevin/dicty_genomes Long-read assembly, genome annotation, QC, and targeted tgrBC locus analysis in Dictyostelium genomes. The pipeline behind the PNAS paper. Contributor. ● Python · Bash · SLURM Skills # Cheminformatics \u0026amp; Modeling GNINAGlideAutoDock VinaFoldseekRDKitPDB2PQRGypsum-DLOpen BabelMeekoMGLToolsAlphaFold Genomics \u0026amp; Bioinformatics FastQCFlyeminimap2BWAsamtoolsbcftoolsbedtoolsBLASTBUSCOMCScanXCRAQGenome assembly (Nanopore / Illumina)Variant callingGWAS Scientific Computing NumPySciPypandasPolarsPyArrowBiopythonMDAnalysis Machine Learning PyTorchscikit-learnRandom ForestGraph Neural NetworksFeature EngineeringModel Evaluation Programming PythonBashRMATLAB Tools \u0026amp; Infrastructure Git / GitHubLinuxHPC / SLURMpixi Languages Arabic — nativeEnglish — fluent ","externalUrl":null,"permalink":"/about/","section":"May Ahmed","summary":"","title":"About Me","type":"page"},{"content":"","externalUrl":null,"permalink":"/authors/","section":"Authors","summary":"","title":"Authors","type":"authors"},{"content":"","externalUrl":null,"permalink":"/categories/","section":"Categories","summary":"","title":"Categories","type":"categories"},{"content":"Two versions depending on what you\u0026rsquo;re after: The full academic record, or a focused industry résumé.\nAcademic CV ↓Research, publications, teaching \u0026 service Industry Résumé ↓Focused computational \u0026 ML summary Education # Ph.D., Molecular, Cellular \u0026amp; Developmental Biology Expected Apr 2027 University of Pittsburgh — Durrant Lab Computational structural biology and machine learning for drug discovery. B.S., Computational Biology \u0026amp; Genomics (Biomedical Sciences) 2017–2021 Zewail City of Science and Technology Graduated Cum Laude\nUndergraduate thesis under Dr. Eman Badr: Investigating the correlation between molecular variations within Acute Myeloid Leukemia (AML) patients and drug sensitivity.\nAwards \u0026amp; Honors # NSF ACCESS Allocation (BIO260240) 2026 Competitive national computing allocation (Purdue Anvil + TAMU ACES) awarded to scale the LIGNOVA pipeline. GPSG Travel Grant 2026 University of Pittsburgh — Graduate \u0026amp; Professional Student Government, for presenting at the Computational Medicinal Chemistry School conference. Elizabeth Baranger Excellence in Teaching Award — nominated 2024 \u0026amp; 2026 University of Pittsburgh — A\u0026amp;S Graduate Student Organization, recognizing excellence in graduate-student teaching across Arts \u0026amp; Sciences; awardees are nominated by their undergraduate students. Nominated for teaching Biochemistry. Provost\u0026rsquo;s Honors Roll 2021 Zewail City of Science and Technology, recognizing the top 5 students by cumulative GPA. Spring 2021. Zewail City Merit Scholarship (90%) 2017–2021 Full merit scholarship for undergraduate studies, awarded for academic excellence. ","externalUrl":null,"permalink":"/cv/","section":"May Ahmed","summary":"","title":"CV","type":"page"},{"content":"Final-year PhD, currently seeking industry roles in computational drug discovery, ML for chemistry, and cheminformatics / scientific software.\n","externalUrl":null,"permalink":"/","section":"May Ahmed","summary":"","title":"May Ahmed","type":"page"},{"content":"You can also check out my Google Scholar profile.\nAll Papers Posters Talks Poster Upcoming LIGNOVA: An automated pipeline for large-scale generation of high-quality protein–ligand complexes Computational Medicinal Chemistry School · Cambridge, MA · October 2026 Ahmed, M., Durrant, J. D. LIGNOVA docks bioactive PubChem compounds into their known protein targets with GNINA, then filters for physically plausible poses to build large-scale receptor-bound data for training next-generation ML models — 125M+ poses across 175,200 compounds and 4,180 protein structures so far, with an NSF ACCESS allocation to scale it nationally. My role: lead developer. Paper In prep Benchmarking consensus rescoring against explicit water in protein–ligand pose prediction Manuscript in preparation · 2026 Ahmed, M., Maldonado, A. M., Durrant, J. D. Benchmarked molecular docking methods under three hydration conditions to pinpoint when consensus-based rescoring can replace expensive explicit-water modeling — preserving the throughput needed for virtual screening. My role: lead author. Talk Putting the pieces together in silico to build drugs from fragments MCDB Noon Seminar Series · Durrant Lab, University of Pittsburgh · Jan 2026 Ahmed, M. Department seminar on assembling fragment-based drug design components into an end-to-end in silico pipeline. Paper Co-first author Hypermutable hotspot enables the rapid evolution of self/non-self recognition genes in Dictyostelium PNAS · 2025 · 122(51) Holland, M., Ahmed, M., Young, J. M., Drurey, J. R., McFadyen, S., Ostrowski, E. A., Levin, T. C. Investigated how the social amoeba Dictyostelium discoideum maintains the extreme genetic diversity its self/non-self recognition system requires. We found that the recognition genes tgrB1 and tgrC1 sit in a hypermutable genomic hotspot that generates new alleles faster than selection can fix any one of them — resolving Crozier\u0026rsquo;s paradox, a long-standing puzzle in the evolution of kin recognition. My role: co-first author where I led the computational genomics, genome assembly, QC, and targeted annotation across 10 chromosome-length genomes. Talk DeepFrag meets LIGNOVA: Transforming drug design with fragment-based lead optimization MCDB Noon Seminar Series · Durrant Lab, University of Pittsburgh · Nov 2024 Ahmed, M. Department seminar connecting the data generated from the LIGNOVA pipeline with DeepFrag for fragment-based lead optimization. Poster Beyond the Blueprint: A Novel Database for Innovative Drug Design and Discovery Gordon Research Conference on Computational Chemistry · Portland, ME · 2024 Ahmed, M., Durrant, J. D. Presented the database concept behind LIGNOVA — docking PubChem compounds into PDB targets with ComBind rescoring — validated on human aldose reductase and anaplastic lymphoma kinase. Talk Beyond the Blueprint: A Novel Database for Innovative Drug Design and Discovery MCDB Noon Seminar Series · Durrant Lab, University of Pittsburgh · Jan 2024 Ahmed, M. Department seminar presenting the database concept behind LIGNOVA. Paper MolModa: accessible and secure molecular docking in a web browser Nucleic Acids Research · 2024 · 52(W1), W498–W506 Kochnev, Y., Ahmed, M., Maldonado, A. M., Durrant, J. D. MolModa is a web-based molecular docking tool that makes protein–ligand docking more accessible, secure, and efficient — running docking workflows directly in the browser, with no installation or advanced technical skills required, while preserving data privacy and reproducibility. Paper Review From byte to bench to bedside: molecular dynamics simulations and drug discovery BMC Biology · 2023 · 21(1), 299 Ahmed, M., Maldonado, A. M., Durrant, J. D. A review of how advances in molecular dynamics (MD) simulations — and their integration with machine learning and quantum approaches — can bridge the gap between computational modeling and experimental drug discovery. Poster Augmenting Protein–Ligand Complex Databases with PubChem for Enhanced Drug Discovery Gordon Research Conference \u0026amp; Seminar on Computer-Aided Drug Design · West Dover, VT · 2023 Ahmed, M., Durrant, J. D. Presented a workflow assembling ~350,000 modeled protein–ligand complexes from PubChem to expand ML training data, demonstrated on the oncogenic kinase CLK2. Talk Testing the impact of a newly built receptor–ligand dataset on DeepFrag accuracy MCDB Noon Seminar Series · Durrant Lab, University of Pittsburgh · Sep 2022 Ahmed, M. Department seminar evaluating how a newly generated receptor–ligand dataset affects DeepFrag\u0026rsquo;s predictive accuracy. 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