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Schrödinger is excited to be participating in the International Battery Seminar & Exhibition taking place on March 12th – 15th in Orlando, Florida. Stop by our booth to speak with Schrödinger scientists.
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Regulations in chemical and materials manufacturing continue to evolve as our understanding of the impact of man-made materials on the environment and human health improves. Together with the increased focus on improved sustainability to help ensure the long-term safety of products, these concerns have caused substitute chemistry activities to grow across nearly all industries.
Given the need to change core chemistries in more and more cases, how can scientists and engineers be more effective in their search?
In this webinar we will explore:
Please note that we will host the same webinar at two different times, each with a live Q&A. Secure your participation by clicking on the registration buttons below.
8:00 AM PT / 11:00 AM ET Chemical innovation for regulatory changes: Leveraging digital simulations for efficient molecular design
1:00 PM GMT / 2:00 PM CET Chemical innovation for regulatory changes: Leveraging digital simulations for efficient molecular design
Director – Polymers and Soft Matter Schrödinger
Andrea Browning is responsible for leading efforts related to polymer and soft matter simulation. Prior to joining Schrödinger in 2017, she was a lead research engineer and project manager at The Boeing Company. She brings over a decade of experience in connecting simulations to industrial decisions.
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Schrödinger is excited to be participating in The 47th Annual Composites, Materials & Structures Conference taking place on January 21st – 25th in St. Augustine, Florida. Stop by booth #36 to speak with Schrödinger scientists.
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錬金術的な自由エネルギー計算は、タンパク質-リガンドの結合自由エネルギー計算において前例のないレベルの精度と信頼性を示し、新規で有力な化学物質を迅速に特定することを 通じて小分子薬物探索プロジェトにポジティブな影響を与えています。
タンパク質-リガンドの結合に加えて、自由エネルギー計算はタンパク質-タンパク質の結合親和性、pHセンシング、受容体の機能的応答、溶解度など、多くの高価値な薬物探索関連 エンドポイントを正確にモデル化することができます。
この講演では、FEP+メソッドの最近の拡張により、小分子結合以外の高付加価値のアプリケーションが能になった事例を紹介します。
日本時間10:00AM – 11:00AM Free Energy Calculations beyond Small Molecule Binding: Predicting Antibody Affinity, pH Sensing, Receptor Functional Response and More
Senior Vice President, Schrödinger
Lingle Wang, senior vice president, scientific development, joined Schrödinger in 2012. He is responsible for advancing Schrödinger’s physics-based computational drug discovery platform. He obtained his Ph.D. from Columbia University working with Professors Richard Friesner and Bruce Berne on methods to quantify the role of water molecules in protein-ligand binding, enhanced sampling in biomolecular simulations and free energy calculations. Lingle has published extensively in the areas of free energy methods development and applications in drug discovery.
紹介事例
【セミナー形式】
Zoom webinarを使用したオンライン形式
【お申込み方法】
▼参加のお申し込みはこちらから▼
https://schrodinger.zoom.us/webinar/register/WN_xEvIT3ElRKGUqUteJMTtLg#/registration
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参加お一人様につき一登録をお願いします。アクセスリンクの共有はご遠慮ください。
当日は、お申し込みの際に登録いただいた氏名·メールアドレスにてご参加ください。
同業他社さまにはご参加をご遠慮頂いております。申し訳ございませんが、ご理解のほど宜しくお願い致します。
※ご質問、ご不明な点がございましたら下記までお問い合わせください。
シュレーディンガー株式会社
E-mail: info-japan@schrodinger.com
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Europe’s premier platform for key opinion leaders to discuss the latest innovations & technological advancements in biologics discovery & development.
Schrödinger is excited to be participating in the Biologics 2024 conference taking place on March 13th – 15th in London, United Kingdom. Join us for a workshop by Cindy Gerson, Lead Product Manager at Schrödinger, titled “Computational approaches for engineering peptides and proteins with enhanced properties.” Stop by booth #49 to speak with Schrödinger scientists.
Workshop: Computational approaches for engineering peptides and proteins with enhanced properties
Presenters: Cindy Gerson, Lead Product Manager, Enterprise Informatics & Schrödinger Team
This workshop aims to provide valuable insights and practical approaches for leveraging computational methods in the design and optimization of therapeutic modalities.
Lead Product Manager, Enterprise Informatics & Schrödinger Team
Abstract:
The enhancement of existing properties and the introduction of new functionalities are pivotal objectives in the development of therapeutic protein modalities such as peptides, antibodies, T cell receptors and enzymes. Typically, achieving these goals involves iterative rounds of time-consuming directed evolution. However, the incorporation of computational structure-based methods, rooted in physics, can expedite this process by providing reliable predictions for the location and identities of potentially beneficial mutations. This approach resulted in targeted selection of a few productive variants, prioritized for expression, or a smaller enriched library that simplifies variant screening. Our workflow has been seamlessly integrated into the Schrödinger collaborative design platform, LiveDesign. This integration allows for the assimilation of various technologies, expediting the discovery cycle.
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Schrödinger is excited to be participating in the AI in Drug Discovery conference taking place on March 11th – 12th in London, United Kingdom. Join us for a presentation by Karl Leswing, Executive Director at Schrödinger, titled “Latest advancements in machine learning-enhanced in silico design: Impact on a pipeline of drug discovery programs”. Stop by our booth to speak with Schrödinger scientists.
Speaker: Karl Leswing, Executive Director, Machine Learning, Schrödinger
Abstract:
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Schrödinger is excited to be participating in the Lab of the Future Congress 2024 conference taking place on March 11th – 12th in Boston, Massachusetts. Join us for a presentation by Erin Davis, SVP Enterprise Informatics at Schrödinger, titled “Empowering the Future of Collaborative, Digital Drug Discovery – From Small to Large Molecules.” Stop by our booth to speak with Schrödinger scientists.
Keynote Session:
Empowering the Future of Collaborative, Digital Drug Discovery – From Small to Large Molecules
Date/Time: March 12th, 11:00 – 11:15 ET
Speaker: Erin Davis, SVP Enterprise Informatics, Schrödinger
Panel Discussion & Q&A:
Date/Time: March 12th, 11:15 – 11:35 ET
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For a drug to be effective, potent binding to the target protein is a prerequisite, but it is not sufficient. Rather, in order to produce the desired functional response, the drug must either inhibit the function of the protein or modulate the activity of the protein, most typically by modifying its conformational equilibrium. The long timescales for such protein conformational changes prohibit them from being directly modeled via physics-based simulations. However, our recent work has demonstrated that the consequences of these long-timescale processes can be accurately modeled with alchemical free energy calculations using FEP+.
In this webinar, we present a tractable and computationally efficient protocol that can accurately and reliably predict the functional response of a receptor to ligand binding, including:
The use of Absolute Binding Free Energy Perturbation (ABFEP) to score the difference of the ligand bound to active and inactive states of the receptor and accurately predict the functional response of ligand binding
Validation on a large set of systems including eight G protein-coupled receptors (GPCRs) and one nuclear receptor
How this FEP-based workflow can be used to achieve unprecedented performance in classifying ligands as agonists or antagonists in drug discovery programs
Best practices for applying this approach to your own research projects
8:00 AM PT / 11:00 AM ET / 4:00 PM GMT / 5:00 PM CET Accurate modeling of receptor functional response: GPCRs and beyond
Senior Vice President, Schrödinger
Lingle Wang, senior vice president, scientific development, joined Schrödinger in 2012. He is responsible for advancing Schrödinger’s physics-based computational drug discovery platform. He obtained his Ph.D. from Columbia University working with Professors Richard Friesner and Bruce Berne on methods to quantify the role of water molecules in protein-ligand binding, enhanced sampling in biomolecular simulations and free energy calculations. Lingle has published extensively in the areas of free energy methods development and applications in drug discovery.
Senior Scientist I, Schrödinger
Martin Vögele is a senior scientist in the life science software department at Schrödinger, Inc. in New York City. Previously, he was a postdoc in computer science at Stanford University where he worked on simulations of G-protein-coupled receptors and on machine learning for structural biology and drug discovery. Before moving to the United States, he obtained a PhD for work on diffusion and self-organization in lipid membranes at the Max Planck Institute of Biophysics in Frankfurt, Germany.
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高品質な化学物質の創製をより包括的かつ効果的に可能にする技術の開発は、薬物探索の長年の目標でした。
シュレーディンガーは近年、大規模な合成に注意を払ったde novoデザイン手法（AutoDesigner）と厳密な自由エネルギーに基づくスコアリング手法（Active Learning FEP+）を組み合わせ、小分子の効力と選択性を最適化するためのワークフローの開発を主導しています。この技術の最新の進展では、R-グループの設計を超えてコアの探索に進化し、初期のヒット同定の取り組みや代替系列の発見に拡張されました。
本セミナーでは、重要なデザインの課題を克服し、プログラムを加速させた、 de novoデザイン技術の最新事例を紹介します。
日本時間9:00am – 10:00am Pieter Bos, Principal Scientist II Sathesh Bhat, Executive Director, Therapeutics Group Zef Könst, Principal Scientist II, Therapeutics Group
Highlights
【セミナー形式】
Zoom webinarを使用したオンライン形式
【お申込み方法】
▼参加のお申し込みはこちらから▼
https://schrodinger.zoom.us/webinar/register/WN_k8iHc8W6RlajaNiThRdggQ
所属企業または所属機関のメールアドレスにて、ご登録をお願いします。
所属が明らかでない、また、個人メールアドレスでご登録の場合などは、出席をご遠慮いただく場合がございますのであらかじめご了承ください。
参加お一人様につき一登録をお願いします。アクセスリンクの共有はご遠慮ください。
当日は、お申し込みの際に登録いただいた氏名·メールアドレスにてご参加ください。
同業他社さまにはご参加をご遠慮頂いております。申し訳ございませんが、ご理解のほど宜しくお願い致します。
※ご質問、ご不明な点がございましたら下記までお問い合わせください。
シュレーディンガー株式会社
E-mail: info-japan@schrodinger.com
Date & Time Location
Schrödinger is excited to be participating in the 9th Fragment-based Drug Discovery Meeting taking place on March 3rd – 5th in Cambridge, United Kingdom at Hinxton Hall. Join us for a poster by Antonija Kuzmanic, Principal Scientist I at Schrödinger, titled “Large-scale in silico Fragment Screening Based on Absolute Free Energy Perturbation (AB-FEP+).”
Title: Large-scale in silico Fragment Screening Based on Absolute Free Energy Perturbation (AB-FEP+)
Speaker: Antonija Kuzmanic, Principal Scientist I
Abstract: Fragment screening has witnessed remarkable success with 6 FDA approved drugs and many more in clinical trials. Here we present a computational innovation to dramatically expand the scope of fragment screening, from screening typical ~3k – 30k experimental fragment libraries to screening ~200 million fragments with high hit rates. This approach involves a virtual screening funnel based on Absolute Free Energy Perturbation to rigorously score diverse fragments based on their predicted binding affinities, allowing for only a small number of fragments (~25-50) to be purchased and/or synthesized for experimental testing. This approach has already been successfully applied during the hit finding stage for several active internal drug discovery projects, resulting in potent (nM – uM), ligand efficient (LE 0.38 – 0.51) starting points from which to initiate our discovery campaigns. In the TPL2 project, five fragments hits (<100 uM) were identified from fragment screening and were expanded to develop initial SAR, which led to discovery of the hit compounds.
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Developing technologies to more comprehensively and effectively enable de novo design of high-quality chemical matter has been a long-standing goal of drug discovery.
To this end, Schrödinger has recently spearheaded the development of workflows that combine large-scale synthetically-aware de novo design methods (AutoDesigner) with rigorous free energy-based scoring methods (Active Learning FEP+) for potency and selectivity optimization of small molecules. Recent developments of this technology move beyond R-group design to core exploration, enabling its expanded application to early stage hit identification efforts and the discovery of back-up series.
In this webinar, we will describe several recent case studies from Schrödinger’s therapeutics group where these de novo design technologies have allowed teams to overcome critical design challenges and accelerate programs.
Highlights
11:00 AM – 12:00 PM EST (1 Hour) Impacting Drug Discovery Programs with Large-Scale De Novo Design
Principal Scientist II, Schrödinger
Pieter Bos is a principal scientist and product manager of AutoDesigner and De Novo Design workflows. At Schrödinger, his main focus is the research, development and optimization of automated compound design algorithms. Lead scientist for the design and execution of enumerated drug molecule libraries for internal and collaborative drug design projects. He received his Ph.D. in Synthetic Organic Chemistry from the University of Groningen in the laboratory of Prof. Ben Feringa. Prior to joining Schrödinger, he worked as a postdoctoral researcher in synthetic methodology development at Boston University (Prof. John Porco and Prof. Corey Stephenson) and small molecule drug discovery at Columbia University (Prof. Brent Stockwell.).
Executive Director, Schrödinger
Sathesh Bhat, Ph.D., executive director in the therapeutics group, joined Schrödinger in 2011. He is responsible for overseeing computational chemistry efforts on internal and partnered drug discovery programs at Schrödinger. Previously, Sathesh worked at both Merck and Eli Lilly leading computational efforts in several drug discovery programs. He obtained his Ph.D. from McGill University, which involved developing structure-based methods to predict binding free energies. Sathesh has co-authored multiple patents and publications and continues to publish on a wide variety of topics in computational chemistry.
Principal Scientist II, Schrödinger
Zef Könst is a principal scientist in the therapeutics group at Schrödinger where he is responsible for drug discovery project execution as a medicinal chemist. Zef joined Schrödinger in 2020 after working at Novartis and Nurix Therapeutics and has contributed to four compounds in clinical development. He received his Ph.D. from University of California, Irvine under Professor Vanderwal.
