Andy Vinter Memorial Meeting
Andy was one of the driving forces in the creation of the Molecular Graphics and Modelling Society (MGMS), which has recently celebrated its 40th anniversary. The Society is still very vibrant in serving the community, organising conferences and events (for example, the annual Young Modellers’ Forum) and awarding prizes (such as the annual Frank Blaney Prize for early career researchers). Andy’s role in the establishment of the MGMS will be described, and a summary of the Society’s current activities will be given.
Steve Maginn is currently the Membership Secretary of the MGMS and co-organiser of their annual Young Modellers’ Forum events. These are voluntary roles – for his 'day job', he works part-time in marketing at Chemical Computing Group, having originally set up the company’s presence in the UK back in 2002. He has spent his career on the interface between academia and industry, and as such crossed paths with Andy several times over the years.
It is now twenty years since the founding of Cresset, and more than thirty-five years since Andy developed the obsession with molecular interactions that would define his career. In this talk, I look back over Andy’s many achievements, from the XED force field, to new ways of looking at molecular electrostatics, to his fascination with GPCR signalling.
Mark graduated from the University of Tasmania in 1992 with a BSc in Chemistry, Physics and Mathematics. Between 1988 and 1992 Mark was awarded the following accolades: Chemistry Honors Prize at University of Tasmania; Dean’s citation for outstanding undergraduate and Honors achievements; University Medal from University of Tasmania; ICI Australia Ltd Prize for third year chemistry; Masson Memorial Prize for top chemistry graduate in Australia.
In 1993 Mark moved to the University of Cambridge where he was awarded his PhD in 1997. It was during his time at Cambridge that Mark first worked with Dr Andy Vinter, founder of Cresset. Upon completion of his PhD Mark worked as a Molecular Modeler and Senior Research Scientist for Napp Pharmaceuticals and Merck Sharp & Dohme respectively.
In 2002 Dr Vinter invited Mark to join him as a founder member of Cresset. Mark has designed and added fundamental science to tools that are now accepted and used by many pharmaceutical, agrochemical and academic institutions across the world. In 2010 Mark was appointed as CSO of Cresset.
Mark is a Fellow of the Royal Society of Chemistry.
Designing new drug molecules is an important task in drug discovery. The utilization of artificial intelligence (AI) technology is expected to improve the efficiency of current drug development. On the other hand, the application of AI to structure generation (i.e., de novo molecular design) has not yet achieved sufficient results. One of the reasons is the lack of quantitative and qualitative training data of successful drug development data. In this presentation, I will present the current status and limitations of structure generation techniques using known data, and discuss the attempts to bridge the gap between the model imperfections and med chem's knowledge and experience in the early stages of AI development. Finally, I will also discuss the usefulness of pharmacophore-based approaches to this end.
Kazuyoshi Ikeda obtained his Ph.D. in Bioinformatics at Tokyo University of Pharmacy and Life Science in 2005. After a year as a Post Doc in Computational Biology Research Center, AIST Tokyo, he then worked as a principal researcher at Pharma Design Inc.
He moved to EMBL-EBI (European Bioinformatics Institute, Cambridge, UK), ChEMBL team for 3 years. During the time he was involved in developing drug discovery databases and applications. He is currently a project associate professor at the Faculty of Pharmacy, Keio University as well as working for an AI drug discovery project at RIKEN in Japan.
‘Bioisostere’ replacement has been popular in medicinal chemistry ever since it was introduced by Harris Friedman in 1950 and later broadened by Burger in 1991.1 As practice grew with numerous reported case studies in lead optimization, the community gained insights into the nuances involved in a successful bioisostere replacement.2 Parameters such as size, shape, electronic distribution, aromaticity, polarizability, dipole, polarity, lipophilicity, pKa etc. play as much important roles as the interactions in protein-ligand complex.3 The advances in computational methods and tools in this area has expanded its application towards identifying non-obvious bioosisteres.4,5 Availability of virtual fragments originating from reagents, real and virtual compound libraries6,7 enables the generation of many diverse and interesting ideas based on stereoelectronic factors. Although these tools use frequency of occurrence and other means of feasibility assessment,8 synthetic feasibility is one of the major challenges to convert them to practice, especially ideas from rarely occurring and theoretically generated fragments. From a computational perspective, three dimensional geometry, conformational preference of the isostere as compared to the original active structure and relative strength of the key non-covalent interactions are some of the challenges experienced. A few examples will be discussed.
References: 1) Burger A, 'Isosterism and bioisosterism in drug design.' Progress Drug Res 1991, 37, 288–362. 2) Meanwell N. A. “The Influence of Bioisosteres in Drug Design: Tactical Applications to Address Developability Problems”. Top Med Chem, 2013. Springer-Verlag Berlin Heidelberg. 3) Tu et al., 'Exploring Aromatic Chemical Space with NEAT: Novel and Electronically Equivalent Aromatic Template', J. Chem. Inf. Model., 2012, 52, 1114-1123. 4) Cheeseright T. et al. 'Molecular Field Extrema as Descriptors of Biological Activity: Definition and Validation.' J. Chem. Inf. Model. 2006, 46, 665-676. 5) BROOD 184.108.40.206: OpenEye Scientific Software, Santa Fe, NM. 6) Bento, A.P. et al. 'The ChEMBL bioactivity database: an update.' Nucleic Acids Res.,2014, 42, 1083-1090. 7) Walters, W. P. 'Virtual Chemical Libraries' J. Med. Chem. 2019, 62, 1116-1124. 8) Boda, K. et al., Structure and reaction- based evaluation of synthetic accessibility, J. Comp.-Aided Mol. Des., 2007, 21, 311-325.
Manoranjan Panda currently holds the position of Scientific Associate Director at Bristol Myers Squibb (BMS), Biocon BMS Research Center (BBRC), Bangalore and heading the computer aided drug design (CADD) group at BBRC. More than seventeen years of experience in multi-national pharmaceutical industry R&D in early and late stage drug discovery programs.
Electrostatic interactions play a key role in molecular recognition and their characterisation and modulation is at the heart of structure-based drug design (SBDD). This presentation showcases a number of SBDD case studies where electrostatic potential (ESP) analysis and the subsequent ESP modulation has been used to optimise protein-ligand electrostatic complementarity and to modulate intramolecular interactions in order to stabilise the ligand bioactive conformation. The presentation also touches on recent developments, using a Graph-Convolutional Deep Neural Network, to rapidly generate high quality ESP surfaces with the potential to make ESP tools more accessible to medicinal chemists.
Gianni Chessari is Vice President and Head of Medicinal Chemistry at Astex. Gianni has extensive experience of fragment-based and structure-based drug design and has contributed to the discovery of a number of small molecule drug candidates that have entered into human clinical trials. Gianni obtained his PhD in Chemistry from the University of Sheffield (UK) where he worked with Professor Chris Hunter and Dr Andy Vinter on the parametrisation of the XED force-field. Gianni has authored more than 70 publications and patents.
Drug re-profiling or repurposing is an established means to more rapidly develop therapies, often utilised for the treatment of rare or orphan diseases. The benefits of re-profiling largely stem from the known data on an existing therapeutic, such as safety profile, side-effects and known drug-drug interactions. The benefits are seen in an accelerated approvals process, as well as opportunities for 'off label' treatment of rare diseases in a controlled clinical setting. In this talk we illustrate a re-profiling example, from target identification through to setting up initial clinical validation. The active agent was uncovered as a result of computational screening, which reduced to a handful the number of compounds needing to be screened before an initial hit was identified.
Dr Arkasubhra Ghosh obtained his PhD in Molecular Medicine from the University of Missouri-Columbia, School of Medicine where he focused on developing AAV vectors for gene therapy. He subsequently worked on discovering how inflammation is regulated by telomeric proteins at IMCB, Singapore. His current research focuses on understanding the genetic and molecular signaling mechanisms driving pathogenesis of ocular disorders and cancers, particularly the signal cascades that determine the course and severity of the disorders for applications in early clinical diagnosis and identification of novel therapeutic targets. These are identified from an established biorepository of primary patient samples by genetics, transcriptomic analyses, protein biochemistry, mass spectrometry and flow cytometric methods followed relevant in vitro cell culture and in vivo animal model studies. Information from such experiments is used for developing new diagnostic and therapeutic approaches with an emphasis on drug repurposing. The GROW laboratory is part of a teaching hospital and collaborates continuously with clinicians to develop novel diagnostics and advanced therapeutic applications. A database of mutations and genes associated with genetic diseases within the Indian population has been established for future recombinant vector based gene therapy and cell replacement modalities. His Gene Therapy platform focuses on recombinant Adeno-associated virus (AAV) as the transfer vehicle utilizing multiple pseudotyped capsids for efficient delivery for targeted treatment of inherited diseases. Further, transgene engineering tools and a clinical grade gene therapy vector production platform has now been developed at GROW lab and various functional genetics studies are being done with the aim of starting human clinical gene therapy trials in India. He is actively involved in mentoring graduate scholars, clinical fellows and post doctoral fellows. He has published over a hundred research articles and serves on numerous research committees and journal editorial boards.
Dr Robert Scoffin is an experienced entrepreneur and senior executive within the life sciences software industry. Following a D.Phil gained from Oxford University, Rob worked for eight years at Oxford Molecular, seeing the company grow from 15 to 250 people and a successful floatation on the London Stock Exchange. In 1998 he joined CambridgeSoft where he was responsible for running the European team, and oversaw the growth of the business unit to more than $5m in annual turnover, and contributing to the development and growth in use of ELN's within pharma and biotech. Rob joined Cresset as CEO in 2010 and now also serves as Chairman of Cresset. During the time he has been leading the team, Cresset has further developed its software and contract research divisions from a very solid customer base, into a high-growth and profitable business. Rob also serves as co-Chairman for Torx Software, a collaboration between Cresset and Elixir Software.
Enabling chemistry technologies can aid the successful development of new therapeutic agents by reducing cycle time, reducing cost of goods and ultimately improving overall probability of success. However, it is important to note that new technology introductions should be developed to meet the needs of a particular challenge. What works for one company may not work for another. In this context, in this talk I focus on the development of key 'fit for purpose' technology that was appropriate to advance one major Pharma's medicinal chemistry research paradigm. These innovations include automated robotic systems for parallel synthesis and purification, fully automated integrated synthesis-purification- bioassay platform (BIOSIP) and ChemBead technology for High Throughput Experimentation applications.
Dr Stevan Djuric is currently a member of the faculty in the School of Pharmacy at the University of Kansas at Lawrence, USA and President of a Medicinal Chemistry Consulting company.
Previously, he was Vice President, Discovery Chemistry and Technology, Global Pharmaceutical Research and Development at AbbVie, Illinois, USA and head of their global Medicinal Chemistry Leadership Team and was also responsible for the Discovery Chemistry and Technology organization within their Discovery organization and chemistry outsourcing activities. That group’s efforts were focused on new initiatives in the areas of high throughput synthesis and purification, hit to lead chemistry, chemical biology including target identification proteomics and new enabling technology identification and development.
He was named an AbbVie Distinguished Research Fellow in 2015 and was a member of their governing Scientific Advisory Board During his tenure at Abbott/AbbVie Laboratories, Dr Djuric was a Project Leader for groups in the Immunoscience, Metabolic Disease, Antiinfective and CNS areas. Several of these programs have advanced compounds into clinical development (e.g DPPIV inhibitor ABT-279) and to the market including Abbott’s proprietary rapamycin analog, Zotarolimus, currently licensed to Medtronics for use on their vascular stents, marketed in the United States and Europe. More recently, compounds from his team’s medicinal chemistry efforts have entered clinical trials (Phase 2 and 3) in the CNS and Cystic Fibrosis areas.
Dr Djuric has over 180 scientific publications, presentations and patents/ applications pending. He has also given over 45 invited lectures at universities and scientific meetings. He currently is a member of several Editorial Advisory Boards including the Journal of Medicinal Chemistry and is an Associate Editor for ACS Medicinal Chemistry Letters. He also serves on the Scientific Advisory Boards of several pharma/biopharma companies.
In addition, he also holds an Adjunct Professorship in the School of Pharmacy at the High Point University, NC.
Unusual circumstances often reveal the most incredible opportunities. One of mine as the first chemist assigned to Novartis’ first PI 3-kinase drug-discovery effort. I will describe why it was a right-place, right-time moment in time, leaning heavily on inspiration from the three Peters, Ertl, Finan and Gedeck. The journey along Main Street is described with the tails of avoiding termination, seeing a burning flame (one if by land, two if by sea, three if via e-mail), Rae and David’s unbroken promise, losing $90K on a CD, seeing some blueprints over coffee in secret Flour, almost calling the FBI to report a crime, ending with partners in Times Square suggesting a virtual screen.
Lewis was raised and educated on Merseyside, Fife & Hampshire, having had the misfortune to miss his footballing trial at Liverpool F.C. due to family vacation. He made an unfashionable decision to postdoc in industry at a Swiss pharmaceutical company in West Sussex and moved initially to Morris and rapidly to Middlesex counties in New Jersey and Massachusetts respectively when barely anyone had heard of Kendall Square, let alone wanted to work there, or walk the streets after 6 pm. Lewis plays sweeper for The Blast on Monday night, and as a striker for Spartak Somerville on Thursday. He lives on Boston’s North Shore, in sight, sound and smell of the Atlantic Ocean, with wife Louise and cats George and Mildred.
The design-make-test-analyze (DMTA) cycle in drug discovery is supported at Alkermes by a customized microservice architecture of calculation engines for in silico predictions of relevant parameters that are retrieved by different frontend applications such as Torx and ALKSketch. Several global and automatically updating local predictive models for absorption, distribution, metabolism, excretion, and toxicity (ADMET) endpoints have been enabled. Target-specific optimization objectives are supported through asynchronous compute services such as compound docking and alignment, density functional theory (DFT) calculations of molecular interaction energies, and free binding energy calculations. Different multi-parameter optimization (MPO) strategies are supported depending on the stage of the drug discovery project. The use of in silico positional analog scanning (PSA) through thermodynamic integration will be exemplified. Opportunities from using generative modeling artificial intelligence (AI) methods will be discussed. Finally, thoughts on using in silico dose predictions as holistic parameter to prioritize compound ideas will be shared.
Ingo Mügge is an Executive Director and Head of Modeling & Informatics at Alkermes in Waltham, Massachusetts. His research interests include drug design, predictive modeling, cheminformatics, bioinformatics, and functional genomics. He previously served a variety of leadership roles in drug discovery at Boehringer Ingelheim in Ridgefield, Connecticut, and Bayer in West Haven, Connecticut. He earned a Diploma in Physics at Humboldt University in Berlin, Germany, and a Doctorate in Computational Chemistry at Free University in Berlin, Germany. He completed postdoctoral studies at the University of Southern California in Los Angeles, California, and Abbott Laboratories in Abbott Park, Illinois. He has published 66 scientific papers and book chapters, co-organized scientific conferences, and serves on the editorial advisory board of Molecular Informatics.
Andy Vinter was a huge advocate for the Cambridge Structural Database. In particular he was interested in how the CSD could inform on intermolecular interactions. Molecular recognition is driven by strong interactions between chemical entities. Since the original identification of the hydrogen bonds, there have been many attempts to characterize and understand interactions and indeed many have been given specific names (for example, halogen bonds, chalcogen bonds, pnictogen bonds). Some have proposed making use of such interactions in molecular design for protein-ligand binding. In this presentation, we will present an overview of how the CSD and the PDB have been used to inform chemists regarding interactions for medicinal chemistry design using data-driven methods both from a visualisation perspective and from an ‘importance’ perspective.
Dr Jason Cole has a BSc in chemistry from the University of Bristol and a PhD in small molecule crystallography from the University of Durham. His research at Durham focused on CSD studies of the effects of symmetry on packing and space group selection, but he also wrote software for controlling diffractometers and in the area of structural analysis of potential organic non-linear optical compounds. He joined the CCDC in 1994 on completion of his PhD, and has been central to the CCDC's software development since then. In his early years at the CCDC, Jason was the lead developer on their IsoStar library of intermolecular interactions; a product now well established in the CCDC's portfolio. He also worked on a tool to use IsoStar for probing interaction sites in protein structures (SuperStar). He went on to design the initial prototype of the CCDC's knowledge base of intramolecular data, Mogul.
For many years, Jason was the lead developer for the CCDC's docking program, GOLD. He improved the performance of the initial system and developed many additional features, including an API to allow for support of multiple scoring functions and methods for applying a variety of constraints during docking - now central to the use of GOLD in virtual screening. Jason has also contributed to the development of other life science-oriented tools including CSD-CrossMiner.
Having then had a 6 year period in top level management overseeing scientific and technical development at CCDC, Jason has now stepped into a more research-focussed role and as the Senior Research Fellow is responsible for collaborative efforts to develop innovative new methods that take advantage of the wealth of structural data available for scientific benefit.
The Open Force Field Initiative, an open science collaboration hosted by the Open Molecular Software Foundation, aims to (1) engineer a modern, open, sustainable, extensible, and well-supported framework for automated force field improvement and application; (2) use this to release rapid iteratively improved versions of an AMBER-compatible small molecule force field we have developed to take advantage of modern cheminformatics; (3) produce entirely new comprehensive force fields that break free of legacy accuracy limitations while maintaining compatibility with existing simulation software, providing dramatically improved accuracy for modeling predictions in diverse applications ranging from predictions of binding affinity, selectivity, and drug resistance, to partitioning, solubility, kinetics, and other properties; and (4) work closely with industry partners to ensure the development path follows that most relevant to R&D needs. In this talk, we will give an overview of the Initiative and its progress to date, including the development of a new small molecule force field that delivers increased accuracy for protein-ligand modeling, and highlight some of the applications in real-world projects, such as the COVID Moonshot.
John Chodera received his BS in Biology from Caltech and his PhD in Biophysics from UCSF. He was a postdoctoral fellow with Vijay Pande at Stanford, who founded the Folding@home distributed computing project, and subsequently a QB3-Berkeley Independent Postdoctoral Fellow at the University of California, Berkeley. In 2012, he started his laboratory at the Sloan Kettering Institute, the basic science arm of the Memorial Sloan Kettering Cancer Center in NYC. There, his lab focuses on the development of new methodologies integrating physical modeling with machine learning to accelerate structure-based drug discovery, with a focus on developing high-quality open source software that facilitates both algorithmic development and application to real problems in drug discovery. He is passionate about supporting a healthy open source software ecosystem in drug discovery and biomolecular modeling, and is a member of the Folding@home Consortium, co-develops the GPU-accelerated molecular simulation code OpenMM, co-founded the Open Force Field Consortium and Open Free Energy Consortium, and helped create the new Open Molecular Software Foundation that seeks to help open source software communities in the biomolecular sciences achieve sustainable funding and governance models.