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メインカンファレンスプログラム 第1日目

7:15 am Coffee and Conference Registration

8:15 Organizer’s Welcoming Remarks
Micah Lieberman, Conference Director, Cambridge Healthtech Institute

8:20 Chairperson’s Remarks
Paul Labute, Ph.D., President, Chemical Computing Group Inc.

 COMPUTATIONAL-BASED PROTEIN DESIGN

8:30 Recent Progress in Computational Protein Design: Designing Combinatorial Protein Libraries
Stephen Mayo, Ph.D., Professor of Biology and Chemistry, California Institute of Technology
Understanding the relationships between protein sequence, protein structure, and protein function remains as a central challenge in chemistry and biology. Combined computational and experimental approaches aimed at elucidating these relationships have led to a powerful method for the enhancement of naturally occurring proteins and the creation of new protein function. This presentation will cover the development of our computational protein design methodology and will focus on recent efforts to design combinatorial protein libraries that should be useful for a range of applications including the development of novel engineered antibodies.

9:00 Structure Based Design of Inhibitors of Imatinib-resistant Mutants of Bcr-Abl Kinase
David Dalgarno, Ph.D., Vice President, Research Technologies, ARIAD Pharmaceuticals Inc.
The discovery and development of imatinib (Gleevec) has proven to be an effective and successful treatment for CML and other cancers. Imatinib itself is the prototype of new classes of DFG-out binding mode kinase inhibitors. Patient relapse under imatinib treatment is often associated with the occurrence of point mutations in the Abl kinase domain, which has catalyzed the development of second and ultimately third generation Bcr-Abl kinase inhibitors capable of inhibiting many clinically relevant mutations. The T315I gatekeeper residue mutant of Abl kinase has proven particularly difficult to inhibit and is resistant to second generation kinase inhibitors such as dasatinib and nilotinib. Here I describe how the application of structural chemistry and structure-based drug design in a tightly focused discovery team has lead to the discovery of potent Src:Abl inhibitors, leading ultimately to the discovery of AP24534, a potent orally active inhibitor of the T315I mutant form of Abl kinase, currently in Phase 1 clinical testing.

 CHALLENGES OF DOCKING AND SCREENING:
SPEED, COST AND QUALITY OF RESULTS

9:30 Virtual Screening Enrichment Studies: The Devil Is in the Details
Andrew Good, Ph.D., Principal Scientist, Computer Assisted Drug Design, Bristol-Myers Squibb
Many articles have been published that attempt to provide performance benchmarks for virtual screening tools. While this research has imparted useful insights, the myriad variables controlling said studies significantly limits results interpretability. Here we highlight the effects of these variables, including analysis of calculation setup variation, the effect of target choice, active / decoy set selection (with a focus on the issue of analogue bias) and enrichment data interpretation. In addition an analysis of the DUD benchmark sets is discussed with a view to improving DUD utility, as is their augmentation through the addition of large diverse data sets collated using WOMBAT.

 10:00 Networking Coffee Break, Poster and Exhibit Viewing

 
10:45 Technology Spotlight
eHiTS Lightning Redefines the State-of-the-art for Structure-Based Virtual Screening
Zsolt Zsoldos, Co-Founder and CSO, SimBioSys
The primary goal of most virtual screening experiments is to find new lead compounds as a starting point in the drug discovery pipeline. There are two typical approaches that are sometimes combined in a screening workflow funnel: ligand-based screening (2D similarity, 3D pharmacophore, fingerprint, surface or other QSAR descriptors) and structure-based flexible ligand docking and scoring. The latter is often considered too slow for large scale screening, especially when considering databases of millions of structures, while the former does not provide 3D coordinates or estimated binding energies. The combination of flexible docking and ligand based filtering in a single software platform has proven to be among the most accurate pose prediction tools and provides one of the highest enrichment factors based on comparative evaluation studies. The software platform is called eHITS and utilizes a surface-based descriptor know as LASSO, Ligand Activity in Surface Similarity Order. Accurate binding energy estimation and activity rank ordering has historically been a very challenging task for all tools and methods in the past. Detailed scientific analysis has been carried out on a wide variety of protein targets to find the root of the elusive scoring problem. The results of this study will be presented with compelling evidence pointing towards insufficient pose prediction accuracy.

 
11:00 Co-presentation: The Fine Details Matter! Learnings & Challenges from De Novo Design & Docking
Jonathan S. Mason, Ph.D., Chief Scientist & Divisional Director, Computational Chemistry & Structural Biology, Lundbeck Research (Denmark)

Lena Tagmose, Ph.D., Head of Section, Computational Chemistry, Lundbeck Research (Denmark)
Experiences in de novo design for an aspartyl protease target and docking for several enyzme targets illustrate that “the devil is in the details” and the critical nature to success of these “fine details”. Examples will be discussed of how key opportunities for structure-based drug design can be enabled or lost, including the use of molecular interaction fields and X-ray experimental ligand complexes for de novo design and docking.

11:30 In silico Discovery and NMR Validation of Transcriptional Inhibitors: Targeting a Requisite Interface
Alan C. Rigby Ph.D., Assistant Professor of Medicine, Harvard Medical School
Several recent publications have identified transcription factors as potential drug discovery targets capable of a rheostat, tunable mechanism of re-regulating gene expression pathways that are deregulated in inflammatory diseases and cancer. Our research program is focused on leveraging the strengths of in silico structure- and ligand-based small molecule discovery partnered with NMR spectroscopy target validation for the exploration of this novel chemical space with a singular goal: the identification of small molecule inhibitors that selectively target and disrupt the transcription factor-DNA interaction interface. Small molecule inhibitors with demonstrable activity at the transcription factor-DNA interface represent an attractive therapeutic opportunity for regulating downstream gene expression profiles. We will present data that builds upon our peptidomimetic studies in which we have used in silico structure-based virtual screening (SBVS) along with stringent ligand-based virtual screening (LBVS) to identify unique small molecule inhibitors that specifically target these transcription factor-DNA interfaces as monitored using NMR spectroscopy. We have identified several chemical scaffolds that inhibit these in vitro transcribed transcription factors at levels comparable to siRNA specific for each transcription factor. Bioinformatics analysis identified that these inhibitors selectively regulate downstream gene expression profiles specific for each transcription factor in human umbilical vein endothelial cells pre-stimulated with the inflammatory cytokine, IL-1. Taken together these data support that small molecule inhibition of the transcription factor-DNA interaction interface alone or partnered with other therapeutic agents such as histone deacetylase inhibitors (HDACs) or methyltransferase inhibitors (MTIs) may provide a novel therapeutic strategy for treating inflammatory diseases and/or cancer.

12:00 pm On the Applicability of GPCR in-silico Models to Drug Discovery: A Comparison between Crystal Structure and Molecular Models of the Beta2-Adrenergic Receptor in Complex with Carazolol
Stefano Costanzi, Ph.D., Head of the Molecular Modeling Unit, Laboratory of Biological Modeling, NIH, NIDDK
For several years rhodopsin has been the only receptor with detailed 3D structural information, and has served as a template for homology modeling of G protein-coupled receptors (GPCRs). Recently, the crystal structure of the beta2-adrenergic receptor has been disclosed, finally proving that GPCRs share a structurally conserved rhodopsin-like 7TM core. The now possible comparison of in silico models and crystal structure of a GPCR/ligand complex argues in favor of the applicability of GPCR modeling to drug discovery.

12:30 Hosted Luncheon Workshop

Recent Advances in the Treatment of Receptor Flexibility for Accurate Docking and Scoring
B. Woody Sherman, Ph.D., Director, Applications Science, Schrodinger, Inc.
The ability to accurately predict the binding mode of a complex with flexibility in both the ligand and receptor is one of the key challenges in computational drug discovery. Due to the intrinsic flexibility of many protein binding sites, this can play a central role in the drug discovery process, but only if we are able to reach a sufficiently high level of confidence in our predictions. In addition to gaining insights into the important interactions that drive binding and key areas of receptor flexibility, it is also critical to obtain an accurate ligand-receptor complex before any attempt is made to predict binding energies. In this work we present the most recent advances in our Induced-fit Docking methodology. We have made significant improvements by incorporating an adaptive softening potential that allows key residues detected by the algorithm to be fully flexible while more rigid parts of the receptor are treated with less flexibility. We present a much more extensive set of cross-docking cases covering a broad range of targets and ligand and show that the new method improves substantially over our previous Induced-fit Docking method. Finally, we discuss downstream applications of this method, such as the ability to couple the induced-fit structures with a new version of Glide XP to obtain significant correlations between predicted and experimental binding free energies.

HIT AND LEAD OPTIMIZATION

 1:55 Chairperson’s Remarks
Tomi Sawyer, Ph.D., Chief Scientific Officer, AILERON Therapeutics; Editor-in-Chief, Chemical Biology & Drug Design

2:00 The Significance of Unconventional Hydrogen Bonds in Structure Based Drug Design
Gergely Toth, Ph.D., Scientist, Computational Chemistry and Biology, Elan Pharmaceuticals
The discovery and optimization of non-bonded interactions, such as van der Waals interactions, hydrogen bonds, salt bridges and the hydrophobic effect, between small molecule ligands and their receptors is one of the main challenges in rational structure based drug discovery. As the theory of molecular interactions advances more evidence accumulates that nonbonded interactions, such as unconventional hydrogen bonds (X-H...Y interactions, where X can be either C, N or O atom and Y can be either an aromatic ring system, O or F atom), contribute to ligand recognition by biological receptors. This presentation provides both an overview and novel examples of unconventional hydrogen bonds between ligands and their receptors of pharmaceutical relevance by dissecting their structure activity relationships and 3D structural elements. Gaining an understanding of the thermodynamic and the structural properties of unconventional hydrogen bonds in ligand-receptor interactions leads us to the elucidation of their practical significance. Ultimately, this enables us to consciously apply these interactions in hit and lead optimization in rational structure based drug design.

2:30 Free Energy Computations in Drug Discovery and Optimization
Matthew Clark, Ph.D., Senior Director of Scientific Computation, Locus Pharmaceuticals
Computation of ligand-protein binding free energies has been known for many years. However, until now computing accurate binding has been time consuming and complicated, taking days for a single molecule. Locus Pharmaceuticals has developed methods to quickly and accurately estimate binding free energies of complex molecules using fragment-based free energy calculations. This enables evaluation of a large number of molecules in a short time, thus allowing free energy calculations to be performed quickly enough to impact drug discovery and optimization programs. In this presentation the following aspects of free energy calcuations in drug discovery will be discussed:

 3:00 Technology Spotlight (Sponsorship Available)

 3:15 Networking Refreshment Break, Poster and Exhibit Viewing

3:45 Structure Based Design of BCR-Abl Kinase Inhibitors with Activity against the T315I Mutant
Andreas Gosberg, Ph.D., Senior Scientist II, Medicinal Chemistry, SGX Pharmaceuticals
We show that a novel, integrated approach of fragment-based lead discovery and structure-guided medicinal chemistry can be used to simultaneously target wild-type and T315-mutant BCR-Abl. Our presentation will describe the identification of an early fragment lead that remained unaffected by the gatekeeper mutation, showing a novel binding mode to the Abl kinase domain and the subsequent implementation of a successful strategy for structure-guided optimization of this series resulting in the identification of a development candidate. In particular, we will describe the use of co-crystal structures of our inhibitors bound to clinically relevant point mutations within the Abl kinase domain, including T315I, F317L, Y253F, E255K and G250E. The structural insights gained have been utilized in the design of our development candidate SGX393, a potent and selective inhibitor of wild-type and mutant T315I BCR-Abl kinase.

 4:15 Structural-Informed Discovery of CDK2 Inhibitors
José S. Duca, Ph.D., Principal Scientist, Department of Drug Design, Schering-Plough Research Institute
CDK2 inhibitors containing the related bicyclic heterocycles pyrazolopyrimidines and imidazopyrazines were discovered through high-throughput screening. Crystal structures of inhibitors with these bicyclic cores and two more related ones show that all but one have a common binding mode featuring two hydrogen bonds (H-bonds) to the backbone of the kinase hinge region. Even though ab initio computations indicated that the imidazopyrazine core would bind more tightly to the hinge, pyrazolopyrimidines gain an advantage in potency through participation of N4 in an H-bond network involving two catalytic residues and bridging water molecules. Further insight into inhibitor/CDK2 interactions was gained from analysis of additional crystal structures. Significant gains in potency were obtained by optimizing the fit of hydrophobic substituents to the gatekeeper region of the ATP binding site. The most potent inhibitors have good selectivity.

 PROTEIN-PROTEIN INTERACTIONS:
THERAPEUTIC TARGETS AND DRUG DISCOVERY

4:45 Targeting Protein-Protein Complexes from the Viral Replication Machinery through a Multidisciplinary Platform
Xavier J. Morelli, Ph.D., Principal Investigator, NMR and Drug Design, National Center for Scientific Research (CNRS)
Our Academic Platform targets viral protein-protein interaction from the replication complexes by combining i) in silico screening: 3D Pharmacophore filtering and high throughput docking, for the acceleration of the process, with ii) experimental screening: robotized BRET experiments for Hit identification/Validation and a replicon system for cellular biology assays. Three-dimensional database searching is an effective means of accelerating the discovery of lead compounds. We will see how this approach can be applied to the Non structural Proteins from the SARS coronavirus. This presentation will incorporate state of the art experimental screening using BRET and the interest of the replicon system as model of full virus, to target the replication machinery. Three French academic laboratories have joined their forces in order to make possible the emergence of a Platform that is usually developed by pharmaceutical companies. Our platform is a fast reactive multidisciplinary entity with specific knowledge and know-how from i) Structural Biology (two NMR spectrometers and X-Ray diffractometer), Molecular Modelling and Drug Design (2 clusters), ii) Biochemistry and in vitro screening with a robotized BRET experiment (TeCAN robot), and iii) original cellular biology with a replicon system of the dengue virus.

 
5:15 Stapled Helical Peptides: Novel Synthetic Biologics
Tomi Sawyer, Ph.D., Chief Scientific Officer, AILERON Therapeutics
This presentation will highlight a fast-emerging and proprietary synthetic biologics strategy for drug discovery that is known as Stapled Peptide Technology. Exemplifying this work will be studies that illustrate the capabilities of designed stapled helical peptides which have very promising drug properties relative to both cellular penetration to modulate signal transduction pathways related to apoptosis in cancer cells as well as in vivo pharmacokinetics and efficacy in disease models. Such stapled helical peptides provide new insights into chemical and biological space for a new generation of synthetic biologics having a broad scope therapeutic application to many diseases and mechanistic pathways involving helical peptide (protein substructure) molecular recognition.

 5:30 – 6:30 Networking Reception in the Exhibit Hall

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