Qing Zhang

Ailomics Therapeutics is a pharmaceutical R&D startup with a pioneering computational and experimental platform to discover novel targets and develop efficacious therapeutics for the diseases of significant unmet medical needs. Ailomics Therapeutics leverages patients-derived omics data and AI-augmented bioinformatics analytics to deeply understand disease biology and identify the targets that drive disease progressions. Learning from human disease biology, Ailomics Therapeutics develops high-translatability disease models to validate targets and screen for functional therapeutics. The human disease biology insights also enable Ailomics Therapeutics to discover high-precision biomarkers for patient stratification in clinical trials.

* Established and led a team of ~10 data scientists with expertise in bioinformatics, cheminformatics and text analytics to support drug discovery from target identification to lead discovery to early development. * Drove the development and application of Deep Learning (Machine Learning, Artificial Intelligence) methods in drug discovery. Established cheminformatics AI and bioinformatics AI capabilities with visible impacts on drug projects (compound prioritization, target validation, etc.). * Managed a department of ~20 team members in the areas of Data Science, Discovery Informatics, Laboratory Informatics and Scientific Computing. * A member of global pREDi Data Science Leadership Team. * A member of Roche Innovation Center Shanghai Leadership Team. * 1 patent [WO2023126428] on off-targets prediction of CRISPR-Cas system. * 2 peer-reviewed publications.

* Established and led Computational Chemistry function. * Pioneered computational technologies to accelerate GPCR structural biology studies. * 2 peer-reviewed publications.

* Modeling and informatics support for both small molecule and antibody drug discovery programs. * Co-led fragment-based drug discovery (FBDD) efforts at R&D China. * 2 patents covering an antibody candidate [WO2017085035] and a small molecule pre-candidate [WO2014114694]. * 2 peer-reviewed publications.

* Modeling and cheminformatics support for small molecule drug discovery programs: target tractability evaluation, assay construct design, HTS data analysis, lead series optimization. * Modeling and bioinformatics support for antibody drug discovery programs: antigen design, epitope mapping, affinity maturation. * Designed and built a TCM/CNS-flavored fragment library to support fragment-based drug discovery at R&D China. * Set up and maintained a Linux cluster for high-performance computing. * 2 patents covering two molecules past candidate selection: a small molecule for Alzheimer's Disease [WO2012076435], a monoclonal antibody for Multiple Sclerosis [patent pending].

Adviser: Prof. Arthur J. Olson * Fragment-based lead discovery, protein-ligand docking, algorithm development (collaborator: Prof. Charles D. Stout, X-ray crystallographer) Developed a docking-based program to automate interpretation of X-ray density maps from fragment screening. Applied it to HIV protease. * Signaling pathway, GPCR modeling, protein-peptide docking, molecular dynamics (collaborator: Prof. Wolfram Ruf, biologist, dept. of immunology) Built a homology model of protease-activated receptor PAR-2 and modeled its interactions with extracellular proteins to understand its signaling pathway. * Protein-protein interaction, algorithm development (collaborator: Prof. Michel Sanner, software developer) Developed a multi-resolution Gaussian surface and studied the effects of surface smoothing on shape complementarity of protein-protein complexes. * Developed software: MapDock (Python), ShapeFit (Python) * 3 peer-reviewed publications.

Adviser: Prof. Tamar Schlick * Macroscopic modeling, Brownian dynamics and Monte Carlo simulations, algorithm development Developed a protein bead model for modeling flexible histone tails of nucleosome to enable computer simulations of chromatin fiber. Mentored one Ph.D. and two students. * Microscopic modeling, molecular dynamics simulation, free energy calculation (collaborator: Prof. Suse Broyde, biologist, department of biology) Interpreted the stereochemistry and position-dependent effects of carcinogen benzo[a]pyrene on transcription initiation-required TATA-TBP binding. * Mesoscopic modeling, implicit-solvent electrostatics, algorithm development Generalized the Discrete Surface Charge Optimization (DiSCO) algorithm, which simplifies electrostatic representations of macromolecules, by developing an irregular surface building method. * Developed software: PCCMD (Perl), DiSCO (C), ViewModel (Matlab). * 6 peer-reviewed publications.

Certificate: Programmer Rank of Computer Software (national), P. R. China, 1997. 1 peer-reviewed publication.