Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447

Report on the sixth blind test of organic crystal-structure prediction methods

The sixth blind test of organic crystal-structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal, and a bulky flexible molecule. This blind test has seen substantial growth in the number of submissions, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and "best practices" for performing CSP calculations. All of the targets, apart from a single potentially disordered Z` = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms

Dawn of Epitranscriptomic Medicine

Medicine is at the crossroads of expanding disciplines. Prompt adaptation of medicine to each rapidly advancing research field, bridging bench to bedside, is a key step toward health improvement. Cardiovascular disease still ranks first among the mortality causes in the Western world, indicating a poor adaptation rate of cardiovascular medicine, albeit the gigantic scientific breakthroughs of this century. This urges the cardiovascular research field to explore novel concepts with promising prognostic and therapeutic potential. This review attempts to introduce the newly emerging field of epitranscriptome (or else known as RNA epigenetics) to cardiovascular researchers and clinicians summarizing its applications on health and disease. The traditionally perceived, intermediate carrier of genetic information or as contemporary revised as, occasionally, even the final product of gene expression, RNA, is dynamically subjected to >140 different kinds of chemical modifications determining its fate, which may profoundly impact the cellular responses and thus both health and disease course. Which are the most prevalent types of these RNA modifications, how are they catalyzed, how are they regulated, which role may they play in health and disease, and which are the implications for the cardiovascular medicine are few important questions that are discussed in the present review

RNA therapeutics in cardiovascular precision medicine

Since our knowledge on structure and function of messenger RNA (mRNA) has expanded from merely being an intermediate molecule between DNA and proteins to the notion that RNA is a dynamic gene regulator that can be modified and edited, RNA has become a focus of interest into developing novel therapeutic schemes. Therapeutic modulation of RNA molecules by DNA- and RNA-based therapies has broadened the scope of therapeutic targets in infectious diseases, cancer, neurodegenerative diseases and most recently in cardiovascular diseases as well. Currently, antisense oligonucleotides (ASO), small interfering RNAs (siRNAs), and microRNAs are the most widely applied therapeutic strategies to target RNA molecules and regulate gene expression and protein production. However, a number of barriers have to be overcome including instability, inadequate binding affinity and delivery to the tissues, immunogenicity, and off-target toxicity in order for these agents to evolve into efficient drugs. As cardiovascular diseases remain the leading cause of mortality worldwide, a large number of clinical trials are under development investigating the safety and efficacy of RNA therapeutics in clinical conditions such as familial hypercholesterolemia, diabetes mellitus, hypertriglyceridemia, cardiac amyloidosis, and atrial fibrillation. In this review, we summarize the clinical trials of RNA-targeting therapies in cardiovascular disease and critically discuss the advances, the outcomes, the limitations and the future directions of RNA therapeutics in precision transcriptomic medicine. © 2018 Laina, Gatsiou, Georgiopoulos, Stamatelopoulos and Stellos

Adenosine-to-Inosine RNA Editing in Health and Disease

Significance: Adenosine deamination in transcriptome results in the formation of inosine, a process that is called A-to-I RNA editing. Adenosine deamination is one of the more than 140 described RNA modifications. A-to-I RNA editing is catalyzed by adenosine deaminase acting on RNA (ADAR) enzymes and is essential for life. Recent Advances: Accumulating evidence supports a critical role of RNA editing in all aspects of RNA metabolism, including mRNA stability, splicing, nuclear export, and localization, as well as in recoding of proteins. These advances have significantly enhanced the understanding of mechanisms involved in development and in homeostasis. Furthermore, recent studies have indicated that RNA editing may be critically involved in cancer, aging, neurological, autoimmune, or cardiovascular diseases. Critical Issues: This review summarizes recent and significant achievements in the field of A-to-I RNA editing and discusses the importance and translational value of this RNA modification for gene expression, cellular, and organ function, as well as for disease development. Future Directions: Elucidation of the exact RNA editing-dependent mechanisms in a single-nucleotide level may pave the path toward the development of novel therapeutic strategies focusing on modulation of ADAR function in the disease context. Antioxid. Redox Signal. 29, 846-863. © Copyright 2018, Mary Ann Liebert, Inc. 2018

Adenosine-to-Inosine RNA Editing in Health and Disease

SIGNIFICANCE: Adenosine deamination in transcriptome results in the formation of inosine, a process that is called A-to-I RNA editing. Adenosine deamination is one of the more than 140 described RNA modifications. A-to-I RNA editing is catalyzed by adenosine deaminase acting on RNA (ADAR) enzymes and is essential for life. Recent Advances: Accumulating evidence supports a critical role of RNA editing in all aspects of RNA metabolism, including mRNA stability, splicing, nuclear export, and localization, as well as in recoding of proteins. These advances have significantly enhanced the understanding of mechanisms involved in development and in homeostasis. Furthermore, recent studies have indicated that RNA editing may be critically involved in cancer, aging, neurological, autoimmune, or cardiovascular diseases. CRITICAL ISSUES: This review summarizes recent and significant achievements in the field of A-to-I RNA editing and discusses the importance and translational value of this RNA modification for gene expression, cellular, and organ function, as well as for disease development. FUTURE DIRECTIONS: Elucidation of the exact RNA editing-dependent mechanisms in a single-nucleotide level may pave the path toward the development of novel therapeutic strategies focusing on modulation of ADAR function in the disease context. Antioxid. Redox Signal. 29, 846-863

Platelet microRNAs : From platelet biology to possible disease biomarkers and therapeutic targets

Although anucleated, platelets contain megakaryocyte-derived messenger ribonucleic acid (mRNA) which can be translated to produce protein molecules. Recently, platelets have been found to contain small (∼23 base pair) non-coding microRNAs (miRNAs) derived from hairpin-like precursors. MiRNAs can specifically silence their mRNA targets regulating mRNA translation. Platelet miRNAs are reported to bind to important platelet target mRNAs involved in platelet reactivity including P2Y12 ADP receptor, GPIIb receptor, and cyclic AMP-dependent protein kinase A. They also regulate important functions such as platelet shape change, granules secretion, and platelet activation. Platelet miRNAs were also proposed as biomarkers of arteriosclerosis, although their role in vascular inflammation needs to be elucidated. Further, the possibility of using miRNAs as therapeutic tools has emerged. Using synthetic oligo-nucleotides that antagonize miRNAs binding to their mRNAs-targets or synthetic miRNAs mimics that enhance endogenous miRNAs function potentially will ultimately lead to the manipulation of platelet miRNAs expression and function with significant effects on specific protein levels and overall platelet reactivity