Reporting to the Vice President, Computational Chemistry, the candidate will play a key role in the ongoing development of RNA structure-based design platform and drug discovery endeavors. Central to this will be the advancement of our understanding of RNA binder molecular dynamics and SAR using state of the art computational chemistry software. A key aspect of this position is teamwork and the ability to collaborate with chemists, structural biologists, and the assay group to create and maintain a cohesive strategy to drive both platform development and our medicinal chemistry efforts.


ACCOUNTABILITIES & RESPONSIBILITIES:

• Support and assist in the development of QM/MM molecular dynamics approaches to advance our structure-based design platform.
• Partner closely with a multidisciplinary team of medicinal chemists and structural biologists in active drug discovery programs to enhance our understanding of RNA modulator SAR.
• Support and drive medicinal chemistry design efforts with modern computational and chemoinformatics approaches through an understanding of the SAR, ADME properties and target biology.
• Interacting with experienced drug design team to develop novel compounds to enhance potency, selectivity, and PK properties.
• Executing structure-based drug design for lead generation and lead optimization.
• Creating pharmacophore, homology, QSAR and other empirical models.
• Accessing and manipulating sequence, crystallographic data, and homology modeling.
• Champion emerging opportunities in ligand-based (pharmacophore modeling, shape-based expansion) and structure-based design (homology modeling, virtual screening).
• Develop hypotheses of the mechanism of action and binding modes of lead compounds based on a deep understanding of current structural biology and homology models.

• PhD in computational chemistry.
• Minimum of 2 years relevant industrial research experience and/or post doctorial experience.
• Extensive experience in the use of molecular dynamics in the study of ligand / target interactions.
• Practical working experience in computational chemistry software e.g., Schrodinger, Moe, OpenEye etc.
• Passion for the application and development of MD methods in drug design and enjoy working in a fast-paced multidisciplinary team environment at the frontier of a new paradigm in drug discovery.
• Deep knowledge in the use of QM/MM mixed methods preferred.
• Relevant experience studying RNA molecular dynamics, a plus.
• Proficiency in a widely used programming/scripting language (e.g., Python /Java) a plus.

PRECISION LIFE SCIENCES