BAGIM is an active community of Boston area scientists bringing together people from diverse fields of modeling and informatics to impact life and health sciences. BAGIM strives to create a forum for great scientific discussions covering a wide range of topics including data management, visualization, computational chemistry, drug discovery, protein structure, molecular modeling, structure-based drug design, data mining, software tools, and the sharing of goals and experiences. Our community is made up of participants from academia, government, and industry whose goal is to engage in the discussion of science involving a synthesis of theory and technology. Discussions sponsored by BAGIM are targeted to the needs and interests of informatics scientists, computational chemists, medicinal chemists, and statisticians. BAGIM also provides opportunities for networking within these disciplines as well as an arena for the dissemination of information of specific interest to the membership.

Friday, December 20, 2019

Correction: BAGIM Event: Andrew Kernytsky

Please join us in the New Year for an amazing talk by Andrew Kernytsky entitled "Predicting and Detecting CRISPR Edits: On Target and Off."

Andrew Kernytsky heads up the Computational Biology and Genomics work at CRISPR Therapeutics by staring at edited DNA sequencing data and occasionally making some sense of it. Previously, he brought order to a swarm of cancer genomics data at Agios Pharmaceuticals and saw how it factored into metabolic pathways and drug targets.
Previously, Andrew dove into next-generation sequencing at the Broad Institute of MIT and Harvard. There, he contributed to the creation of a leading system for detecting DNA variants (SNPs and short indels) as well as GATK, a generalized toolkit for analyzing massive genomic data. Some key applications of this toolkit that Andrew has led or contributed to include: detecting de novo mutations in sequenced mother-father-child trios, detecting systematic errors in sequencing data, creating tools that decrease the negative downstream effects of these errors, and optimizing the protocols by which sequencing is targeted to specific areas of the genome.
Before joining the Broad, Andrew completed his Ph.D. at Columbia University in the Burkhard Rost Lab. There, he used genetic algorithms to select combinations of features from a complex space in order to predict protein function. Andrew’s undergraduate work included majors in Chemistry and Biochemistry at La Salle University. During that time, he had the opportunity to work extensively with custom microarray gene expression platforms and Affymetrix arrays at Rhone-Poulenc Rorer and Merck Research Labs. In this work, Andrew split his time between doing laboratory research and computational data exploration and tool development.

This event will be held on Thursday, January 16th, 2020 at 6:00pm at RelayTX.

Please note, this event is capped at 60 people. In order to attend, we need full names for the check list. No one will be admitted after 6:15. Please update your Meetup with your full name or email bagimcommunications@gmail.com.

Additionally, I would like to sincerely apologize for the confusion. The previous announcement was made in error, and was a result of a misread email.

The entire BAGIM team thanks you all for your continued support and for your understanding.

Happy Holidays

Tuesday, November 12, 2019

BAGIM Event: Rebecca Swett

Please join us as we hear an amazing talk by Rebecca Swett entitled "Effective Simulations, Effective Team."

This event will be held on Thursday, November 21st at 6:00pm at Novartis.

Dr. Swett graduated from Wayne State University in Detroit, where she applied molecular dynamics to the development and optimization of covalent inhibitors of the Clostridium Difficile toxins, and developed methods to apply interference in protein-protein recognition as a mechanism of inhibition, leading to her first patent. Additionally, she developed software connect genotypes to phenotypes by gene region of interest, in a hypothesis-driven manner and validated the results with simulations and in vitro experiments. She then completed a postdoc at Novartis with an academic mentor at Stanford. Here, she worked on applying ultra-fine print molecular dynamics to the use of solvation in lead optimization, application of Markov State Modeling to the identification of targetable metastable protein states for the development of flu treatments, and developed predictive models to discriminate between ligand effects on correlated protein motions in high throughput MD. She currently is at Vertex Pharmaceuticals where she uses an array of ligand and structure based methods, as well as predictive modeling and molecular dynamics, to pursue treatments for Cystic Fibrosis and other targets

Friday, October 11, 2019

BAGIM Event: Pat Walters

First BAGIM event of the season! Please join us on Monday, October 21st at Relay Therapeutics (399 Binney Street) to hear Pat Walters on the "Applications of Artificial Intelligence in Drug Discovery- Separating Hype from Utility." 

Pat Walters heads the Computation & Informatics group at Relay Therapeutics in Cambridge, MA. His group focuses on novel applications of computational methods that integrate computer simulations and experimental data to provide insights that drive drug discovery programs. Prior to joining Relay, he spent more than 20 years at Vertex Pharmaceuticals where he was Global Head of Modeling & Informatics. Pat is a member of the editorial advisory board for the Journal of Medicinal Chemistry, and previously held similar roles with Molecular Informatics, and Letters in Drug Design & Discovery. Pat received his Ph.D. in Organic Chemistry from the University of Arizona where he studied the application of artificial intelligence in conformational analysis. Prior to obtaining his Ph.D., he worked at Varian Instruments as both a chemist and a software developer. Pat received his B.S. in Chemistry from the University of California, Santa Barbara.

Monday, April 1, 2019

BAGIM Event: Mike Bower

Please join us on April 25th at 6:00 pm at Verizon Alley (10 Ware St, Cambridge) for a talk by Mike Bower entitled: PXR Mitigation and Structure-Based Design

Upregulation of CYP450 3A4 via activation of the pregnane X receptor (PXR) is an active and growing concern for pharmaceutical discovery and development, as it can lead to unpredictable and potentially dangerous drug-drug interactions.  I will introduce a novel molecular descriptor, Smallest Maximum Interatomic Distance (SMID), which correlates with PXR activation.  I will also present a method for using the descriptor to guide chemists in modifying their lead compounds to decrease PXR activation. 

The presenter, Mike Bower, received a BS in Chemistry from the University of Delaware. During undergrad, Mike had his first computational chemistry job as an intern at DuPont Merck Pharmaceutical Co (28 years ago). Mike received a PhD in Pharmaceutical Chemistry from the University of California at San Francisco, where he worked in Fred Cohen’s lab on homology modeling and sidechain modeling using his program, SCWRL.  Since then, Mike has worked at Chiron pharmaceuticals, SmithKline Beecham/GlaxoSmithKline, Incyte Corporation, and now Vertex Pharmaceuticals.  He spent four years as the communication/social media officer for BAGIM.

Friday, March 1, 2019

BAGIM Event: Yifan Song

Please Join Us on Thursday March 14th at 6pm at Shire on Binney Street for a talk entitled:
Got Structure?
by Yifan Song

Most computational methods that can be applied to drug discovery require a protein structure. Ideally, such structures are derived from experimental approaches such as X-ray, EM or NMR. However, frequently, an experimental structure of the specific protein of interest is not available. In such a case we turn to homology modeling.

The state-of-the-art for homology model prediction has progressed tremendously over the past two decades. Whereas useful HM models were initially only available in cases where a high-similarity homolog was available in the PDB, it is now often possible to predict such models even when the best homologs have only 15-25% similarity to the sequence whose structure is being predicted. The dramatic improvement in what is possible with HM is due to several factors, including: adoption of methods that can identify suitable low similarity templates on the basis of Markov Models, familial and other deep analysis of sequence space; the ability to incorporate multiple low-similarity templates to broadly span a target sequence; powerful approaches to model building that can handle missing structure due to lack of template, insertions and deletions; and the availability of massive compute power through processor clusters and parallelization. In many cases, the HM models that can be generated are so good—not only in terms of backbone trace, but also in such fine details as hydrogen bonding network, salt bridges, disulphide bonds, etc.—that they are suitable for downstream modeling methods.

We will present the history of HM approaches, culminating in a description of the state-of-the-art Rosetta HM workflow.

Friday, January 25, 2019

BAGIM Event: Michael Hoemann

Please join us on Feb 28th at 6pm at Le Meridien for a talk entitled:

Design at AbbVie in the 21 st Century
Michael Hoemann
in collaboration with: Maria Argiriadi, Eric Breinlinger, Kevin Cusack, Jeremy Edmunds and Michael Friedman

This talk will cover the various computational tools that we use at AbbVie at all stages of small molecule drug design. In particular, methods for the analysis of large numbers of virtual compounds through docking (i.e. Glide, Gold etc), clustering (i.e. tSNE), similarity analysis (i.e. Rocs Overlay™ and Cresset Torch™) and sorting through fingerprints (i.e. SIFT) of ligand-protein interactions will be discussed. In addition, it is recognized that protein-ligand complexes are not static solid state structures, but are dynamic and fluid. Therefore, this talk will talk about some of the early work we have been doing at AbbVie to utilize dynamic simulations (MM-GBSA, Desmond MD, MetaDynamics and FEP+) to prioritize compounds for synthesis. These tools when combined together can provide validated workflows to improve the efficiency of small molecule drug discovery.