June 2016

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2016 CDAR Annual Meeting

LIW30 June 21, 2016 0

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Platform for Abused-Drugs and Neurological Diseases Association (PANDA)

PANDA is a portal for accessing the computational resources developed, disseminated and maintained by the CDAR Center, which comprises a significant expansion of the drug abuse research tools, as well as information toward establishing the link between molecular, cellular, and systemic aspects of drug abuse and associated disorders. Read more

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Cloud computing drug-abuse and neurobiological diseases domain-specific databases

These platforms are integrated with online structure search function and data analysis tools to facilitate data-sharing and information exchange among scientific research communities for target/off-target identification neurobiological drug abuse research. Read more

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Monoamine transporters: structure, intrinsic dynamics and allosteric regulation

Mary Cheng and Ivet Bahar published an invited review article in Nature Structural & Molecular Biology, addressing recent progress in the elucidation of the structural dynamics of monoamine transporters and their conformational landscape and transitions, as well as allosteric regulation mechanisms. Read more

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Targeting of dopamine transporter to filopodia requires an outward-facing conformation of the transporter

Using quantitative live-cell fluorescence microscopy (Sorkin lab; U PITT) and molecular modeling (Bahar lab), they investigated the effects of the DAT inhibitor cocaine and its fluorescent analog JHC1-64 on the plasma membrane distribution of wild-type DAT and two DAT mutants.

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A Time-Varying Group Sparse Additive Model for GWAS of Dynamic Complex Traits

Core C proposes a new approach, Linear Regression with Validated Association (LRVA) that discovers variants by utilizing the knowledge of known associations, making the variants with weaker signals easier to be identified. They have applied their method to Drug Abuse Disorders data set collected from CEDAR provided to them by Dr. Michael Vanyukov (PI of a FRP), and discovered nearly two dozen novel SNPs associated with drug abuse disorders. Literature search suggests that many of these SNPs reside in genes previously known to be involved with substance abuse. Read more

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