As an accomplished Computational Chemist, I specialize in lead optimization and the application of advanced computational techniques to enhance drug discovery processes. With a strong foundation in molecular dynamics simulations, free energy perturbation calculations, and both ligand- and structure-based drug design, I bring a wealth of expertise and innovation to the field.During my tenure at the Voelz Lab at Temple University, I utilized open-source MD frameworks through Folding@Home to conduct all-atom, long-timescale molecular dynamics simulations, evaluating the binding mechanisms and kinetics of protein-ligand complexes as well as evaluating Expanded Ensemble free energy calculations for thousands of compounds in partnership with the COVID Moonshot mission.At Nested Therapeutics, I contributed to multiple programs using a diverse array of tools ranging from literature- and modeling-based target assessment, deploying ligand FEP to evaluate binding affinities, stability- and affinity-based Protein FEP to predict resistance mutations, conducting SAR trend analyses to inform prospective design, matched pair analyses, and ADME property predictions.I have also worked to reconcile simulated structures with experimental observables (HDX/NMR) and re-weight simulated ensembles and generate relevant conformers to bolster understanding of protein dynamics.My technical skills encompass:Software Programming (Python & Bash)GNU/Unix, HPC, AWS ExpertiseSchrodinger Suite, D360, KNIMEAll-Atom Molecular Dynamics SimulationsFree Energy CalculationsMachine-Learning / Generative AIIn addition to my core expertise, I have a keen interest in:Incorporating generative deep-learning methods to design novel and optimized drug candidates.Integrating GPU acceleration into computational methods.Developing virtual and augmented reality applications for molecular modeling and drug design.Exploring breakthroughs in Natural Language Processing and refinement of LLMs.With strong project and cluster administration skills, I have overseen software upgrades, expanded scientific workflow documentation, and mentored team members. My interpersonal communication abilities further enhance my collaborative and leadership capabilities.I am passionate about pushing the boundaries of computational chemistry and drug discovery, constantly seeking innovative solutions and staying abreast of the latest advancements in the field.
-
Scientist IiVidavinci, Inc.Cambridge, Ma, Us -
ScientistStealth Biotech Nov 2024 - Present -
ScientistNested Therapeutics Sep 2022 - Nov 2024Cambridge, Ma, UsAssisted in lead optimization by validating and optimizing free energy perturbation (FEP) maps, (absolute & relative) towards prioritization of candidate compounds on a vector-specific basis.Enumeration of designs, assessed via docking and ADME property prediction resulted in a streamlined filtering ahead of FEP.Managed datasets for post-synthesis tracking of virtual compounds, increasing enrichment of synthesis queue.Deployed stability- and affinity-based Protein FEP to predict resistance for all proximal single-codon mutations.Initiated short time-scale MD simulations to generate working structure-based hypotheses to correlate with observed selectivity.Uncovered SAR trends through R-group decomposition and matched pair analyses using D360 to inform prospective design.Deployed long timescale MD simulations to establish differential dynamics and pocket formation across Zn-compromising p53 mutations.Reconciled simulated structures with experimental HDX observables using ensemble re-weighting to generate relevant conformers. Aided the platform team in evaluating prospective protein targets based on pre-existing literature, modeling, and pocket identification.Oversaw upgrading and testing of new software installations, presenting recent releases to the broader team.Expanded existing documentation for scientific workflows and HPC cluster administration tasks. -
Research AssistantTemple University Aug 2015 - Oct 2022Philadelphia, Pennsylvania, UsResearch Projects:Reconciling experimental observables with simulation data towards structure prediction of cyclic peptidomimetics using Bayesian inference.Conformational stability assessment of fluorinated peptoids via ab initio quantum mechanics calculations of molecular orbital interactions.Estimation of protein-ligand binding kinetics, pathways, and state populations from molecular dynamics using dimensionality reduction methods and Markov state models.Deployment and analysis of high-throughput absolute free energy simulations towards binding affinity predictions for small molecular inhibitors of SARS-CoV-2 on Folding@home as part of the Postera Moonshot Consortium.Development of a novel ligand restraint protocol and optimization of expanded ensemble enhanced sampling methodology.Participation in SAMPL9 host-guest challenge for estimating thermodynamics of binding interactions.Installation, administration, and maintenance of Folding@home work servers.Folding@home community outreach, moderation, and mentorship.TA assignments:General Chemistry Lab I/IIGeneral Chemistry II RecitationPhysical Chemistry of BiomoleculesTechniques of Chemical Measurement IIEmerging STEM Scholars I/II
Matt Hurley Education Details
-
Temple UniversityChemistry -
Fordham UniversityChemistry
Frequently Asked Questions about Matt Hurley
What company does Matt Hurley work for?
Matt Hurley works for Vidavinci, Inc.
What is Matt Hurley's role at the current company?
Matt Hurley's current role is Scientist II.
What schools did Matt Hurley attend?
Matt Hurley attended Temple University, Fordham University.
Free Chrome Extension
Find emails, phones & company data instantly
Aero Online
Your AI prospecting assistant
Select data to include:
0 records × $0.02 per record
Download 750 million emails and 100 million phone numbers
Access emails and phone numbers of over 750 million business users. Instantly download verified profiles using 20+ filters, including location, job title, company, function, and industry.
Start your free trial