ALMOST: An all atom molecular simulation toolkit for protein structure determination

Almost ( al l atom mo lecular s imulation t oolkit) is an open source computational package for structure determination and analysis of complex molecular systems including proteins, and nucleic acids. Almost has been designed with two primary goals: to provide tools for molecular structure determination using various types of experimental measurements as conformational restraints, and to provide methods for the analysis and assessment of structural and dynamical properties of complex molecular systems. The methods incorporated in Almost include the determination of structural and dynamical features of proteins using distance restraints derived from nuclear Overhauser effect measurements, orientational restraints obtained from residual dipolar couplings and the structural restraints from chemical shifts. Here, we present the first public release of Almost , highlight the key aspects of its computational design and discuss the main features currently implemented. Almost is available for the most common Unix‐based operating systems, including Linux and Mac OS X. Almost is distributed free of charge under the GNU Public License, and is available both as a source code and as a binary executable from the project web site at http://www.open‐almost.org . Interested users can follow and contribute to the further development of Almost on http://sourceforge.net/projects/almost . © 2014 Wiley Periodicals, Inc.     

HTMoL: full-stack solution for remote access,visualization, and analysis of molecular dynamics trajectory data

Research on biology has seen significant advances with the use of molecular dynamics (MD) simulations. The MD methodology enables explanation and discovery of molecular mechanisms in a wide range of natural processes and biological systems. The need to readily share the ever-increasing amount of MD data has been hindered by the lack of specialized bioinformatic tools. The difficulty lies in the efficient management of the data, i.e., in sending and processing 3D information for its visualization. In this work, we present HTMoL, a plug-in-free, secure GPU-accelerated web application specifically designed to stream and visualize MD trajectory data on a web browser. Now, individual research labs can publish MD data on the Internet, or use HTMoL to profoundly improve scientific reports by including supplemental MD data in a journal publication. HTMoL can also be used as a visualization interface to access MD trajectories generated on a high-performance computer center directly. Furthermore, the HTMoL architecture can be leveraged with educational efforts to improve learning in the fields of biology, chemistry, and physics.     

Global and local relative convexity and oriented relative convexity; application to molecular shapes in external fields

The concepts of global and local relative convexity and oriented relative convexity are described and proposed as tools for the characterization of molecular shapes. The usual concept of convexity is a special case of the generalization described. Oriented relative convexity is suitable for the characterization of molecular shapes in external fields, such as magnetic fields or fields representing cavity regions of various enzymes or zeolite catalysts. Potential applications include new approaches to computer-based drug design and molecular engineering.     

Structure and growth of self-assembling monolayers

The structural phases and the growth of self-assembled monolayers (SAMs) are reviewed from a surface science perspective, with emphasis on simple model systems. The concept of self-assembly is explained, and different self-assembling materials are briefly discussed. A summary of the techniques used for the study of SAMs is given. Different general scenarios for structures obtained by self-assembly are described. Thiols on Au(1 1 1) surfaces are used as an archetypal system to investigate in detail the structural phase diagram as a function of temperature and coverage, the specific structural features on a molecular level, and the effect of changes of the molecular backbone and the end group on the structure of the SAM. Temperature effects including phase transitions are discussed. Concepts for the preparation of more complex structures such as multi-component SAMs, laterally structured SAMs, and heterostructures, also with inorganic materials, are outlined. The growth and ways to control it are discussed in detail. Solution and gas phase deposition and the impact of various parameters such as temperature, concentration (in solution) or partial pressure (in the gas phase) are described. The kinetics and the energetics of self-assembly are analyzed. Several more complex issues of the film formation process including non-equilibrium issues are discussed. Some general conclusions are drawn concerning the impact of various molecular features on the growth behavior and concerning the relationship between growth and structural phase diagram. Finally, the potential of self-assembly as a route for the preparation of monolayers with pre-designed properties and SAMs as building blocks in heterostructures as well as application strategies are discussed.     

Artificial Intelligence for Autonomous Molecular Design: A Perspective

Domain-aware artificial intelligence has been increasingly adopted in recent years to expedite molecular design in various applications, including drug design and discovery. Recent advances in areas such as physics-informed machine learning and reasoning, software engineering, high-end hardware development, and computing infrastructures are providing opportunities to build scalable and explainable AI molecular discovery systems. This could improve a design hypothesis through feedback analysis, data integration that can provide a basis for the introduction of end-to-end automation for compound discovery and optimization, and enable more intelligent searches of chemical space. Several state-of-the-art ML architectures are predominantly and independently used for predicting the properties of small molecules, their high throughput synthesis, and screening, iteratively identifying and optimizing lead therapeutic candidates. However, such deep learning and ML approaches also raise considerable conceptual, technical, scalability, and end-to-end error quantification challenges, as well as skepticism about the current AI hype to build automated tools. To this end, synergistically and intelligently using these individual components along with robust quantum physics-based molecular representation and data generation tools in a closed-loop holds enormous promise for accelerated therapeutic design to critically analyze the opportunities and challenges for their more widespread application. This article aims to identify the most recent technology and breakthrough achieved by each of the components and discusses how such autonomous AI and ML workflows can be integrated to radically accelerate the protein target or disease model-based probe design that can be iteratively validated experimentally. Taken together, this could significantly reduce the timeline for end-to-end therapeutic discovery and optimization upon the arrival of any novel zoonotic transmission event. Our article serves as a guide for medicinal, computational chemistry and biology, analytical chemistry, and the ML community to practice autonomous molecular design in precision medicine and drug discovery.     

Evaluation of ForenSeq™ Signature Prep Kit B on predicting eye and hair coloration as well as biogeographical ancestry by using Universal Analysis Software (UAS) and available web‐tools

This study examined 266 individuals from various populations including African American, East Asian, South Asian, European, and mixed populations to evaluate the ForenSeq? Signature Prep Kit Primer Mix B. Focus was placed on phenotypic and biogeographical ancestry predictions by Illumina's Universal Analysis Software (UAS). These outcomes were compared to those obtained through web‐tools developed at the Erasmus Medical Center (EMC) and available from the Forensic Resource/Reference on Genetics‐knowledge base (FROG‐kb), as well as to eye color predictions by the 8‐plex system. Due to drop‐outs, predictions for eye and hair color by UAS failed for various samples in each run. By including reads below thresholds, predictions could be obtained for all samples through the web‐tools. Eye and hair color predictions for African Americans, East Asians, and South Asians showed no errors. Difficulties however, were noted in intermediate (neither blue nor brown) eye color predictions. These were mitigated by the 8‐plex system through exclusion of one eye color (e.g. “not brown”). Additionally, notable discrepancies were observed in hair color predictions, where some black/dark‐brown haired individuals were predicted to have blond hair. Overall, ancestry predictions were more accurate by FROG‐kb compared to UAS, which did not predict South Asian ancestry, particularly Indian individuals.     

CHARMM-GUI: a web-based graphical user interface for CHARMM

CHARMM is an academic research program used widely for macromolecular mechanics and dynamics with versatile analysis and manipulation tools of atomic coordinates and dynamics trajectories. CHARMM-GUI, http://www.charmm-gui.org, has been developed to provide a web-based graphical user interface to generate various input files and molecular systems to facilitate and standardize the usage of common and advanced simulation techniques in CHARMM. The web environment provides an ideal platform to build and validate a molecular model system in an interactive fashion such that, if a problem is found through visual inspection, one can go back to the previous setup and regenerate the whole system again. In this article, we describe the currently available functional modules of CHARMM-GUI Input Generator that form a basis for the advanced simulation techniques. Future directions of the CHARMM-GUI development project are also discussed briefly together with other features in the CHARMM-GUI website, such as Archive and Movie Gallery.     

Molecular Design in Practice: A Review of Selected Projects in a French Research Institute That Illustrates the Link between Chemical Biology and Medicinal Chemistry

Chemical biology and drug discovery are two scientific activities that pursue different goals but complement each other. The former is an interventional science that aims at understanding living systems through the modulation of its molecular components with compounds designed for this purpose. The latter is the art of designing drug candidates, i.e., molecules that act on selected molecular components of human beings and display, as a candidate treatment, the best reachable risk benefit ratio. In chemical biology, the compound is the means to understand biology, whereas in drug discovery, the compound is the goal. The toolbox they share includes biological and chemical analytic technologies, cell and whole-body imaging, and exploring the chemical space through state-of-the-art design and synthesis tools. In this article, we examine several tools shared by drug discovery and chemical biology through selected examples taken from research projects conducted in our institute in the last decade. These examples illustrate the design of chemical probes and tools to identify and validate new targets, to quantify target engagement in vitro and in vivo, to discover hits and to optimize pharmacokinetic properties with the control of compound concentration both spatially and temporally in the various biophases of a biological system.     

Synthesis and Investigation of Electro-Optical Properties of H-Shape Dibenzofulvene Derivatives

We have synthetized two classes of dibenzofulvene-arylamino derivatives with an H-shape design, for a total of six different molecules. The molecular structures consist of two D-A-D units connected by a thiophene or bitiophene bridge, using diarylamino substituents as donor groups anchored to the 2,7- (Group A) and 3,6- (Group B) positions of the dibenzofulvene backbone. The donor units and the thiophene or bithiophene bridges were used as chemico-structural tools to modulate electro-optical and morphological-electrical properties. A combination of experiments, such as absorption measurements (UV-Vis spectroscopy), cyclic voltammetry, ellipsometry, Raman, atomic force microscopy, TD-DFT calculation and hole-mobility measurements, were carried out on the synthesized small organic molecules to investigate the differences between the two classes and therefore understand the relevance of the molecular design of the various properties. We found that the anchoring position on dibenzofulvene plays a crucial key for fine-tuning the optical, structural, and morphological properties of molecules. In particular, molecules with substituents in 2,7 positions (Group A) showed a lower structural disorder, a larger molecular planarity, and a lower roughness.     

A virtual vibrational self-consistent-field method for efficient calculation of molecular vibrational partition functions and thermal effects on molecular properties

A new method is described for the calculation of molecular vibrational partition functions and thermal effects on molecular properties including an explicit account of anharmonicity. The approach is based on the vibrational self-consistent-field method. Partition functions and thermal averages of the energies calculated with the new method are generally in good agreement with the result of more accurate methods. At lower temperatures the method gives in addition good results for thermal averages of dipole moments and polarizabilities. The new method is much more efficient than explicit sum-over-states approaches previously used for calculation of thermal averages. Unlike the standard sum-over-states approach, the newly developed method is feasible for larger systems despite the formal exponential increase in the number of states with the size of the system. Thus, it is presently the only practical way for including an explicit treatment of anharmonicity in vibrational wave function based calculations of molecular vibrational partition functions and thermally averaged properties of larger molecules.     

Structures behind the amyloid aggregation of α-synuclein: an NMR based approach

The misfolding of proteins into a toxic conformation is proposed to be at the molecular foundation of a number of neurodegenerative disorders including Alzheimer's and Parkinson's diseases. Evidence that α-synuclein amyloidogenesis plays a causative role in the development of Parkinson's disease is furnished by a variety of genetic, neuropathological and biochemical studies. There is a major interest in understanding the structural and toxicity features of the various species populated along the aggregation pathway of this protein. The development of multidimensional nuclear magnetic resonance (NMR) spectroscopy in liquid and solid state over the last decade has significantly increased the scope of molecules that are amenable for structural studies. The aim of this review is to provide a picture of how NMR tools were used in concert to decipher the structural and dynamic properties of the intrinsically disordered protein α-synuclein in its native, oligomeric, fibril and membrane-bound states. Understanding the structural and molecular basis behind the aggregation pathway of α-synuclein is key to advance in the design of a therapeutic strategy.     

Microsystem technology as a road from macro to nanoworld

Tremendous progress of microelectronic technology observed within last 40 years is closely related to even more remarkable progress of technological tools. It is important to note however, that these new tools may be used for fabrication of diverse multifunctional structures as well. Such devices, called MEMS (Micro-Electro-Mechanical-System) and MOEMS (Micro-Electro-Opto-Mechanical-System) integrate microelectronic and micromechanical structures in one system enabling interdisciplinary application, with most interesting and prospective being bio-medical investigations. Development of these applications requires however cooperation of multidisciplinary team of specialists, covering broad range of physics, (bio) chemistry and electronics, not mentioning medical doctors and other medical specialists. Thus, dissemination, of knowledge about existing processing capabilities is of key importance. In this paper, examples of various applications of microelectronic technology for fabrication of Microsystems which may be used for medicine and chemistry, will be presented. Besides, information concerning a design and technology potential available in poland and new, emerging opportunities will be given.     

PlantPIs--an interactive web resource on plant protease inhibitors

PlantPIs is a web querying system for a database collection of plant protease inhibitors data. Protease inhibitors in plants are naturally occurring proteins that inhibit the function of endogenous and exogenous proteases. In this paper the design and development of a web framework providing a clear and very flexible way of querying plant protease inhibitors data is reported. The web resource is based on a relational database, containing data of plants protease inhibitors publicly accessible, and a graphical user interface providing all the necessary browsing tools, including a data exporting function. PlantPIs contains information extracted principally from MEROPS database, filtered, annotated and compared with data stored in other protein and gene public databases, using both automated techniques and domain expert evaluations. The data are organized to allow a flexible and easy way to access stored information. The database is accessible at http://www.plantpis.ba.itb.cnr.it/.     

SPE and purification of DNA using magnetic particles

Superparamagnetic particles have been attractive for molecular diagnostics and analytical chemistry applications due to their unique magnetic properties and their ability to interact with various biomolecules of interest. This paper presents a critical overview of magnetic nano ‐ and microparticles used as a solid phase for extraction and purification of DNAs. The mechanisms of DNA binding to the surface of functionalised magnetic particles are described. The most widely used materials including silica supports, organic polymers and other materials, mostly containing magnetite or paramagnetic metallic elements are reviewed. The main application areas of magnetic particles for DNA separation are briefly described.     

分子基材料聚集态结构的场发射性质研究

场发射在扫描电子显微镜、平面显示器、压力传感器、加速度传感器以及电子束可寻址记忆器件等许多领域中得到了广泛的应用,分子基材料由于其结构和能带可设计,性质可调和柔性易加工等显著特点,被认为是新一代的场发射材料。本文综述了近年来分子基材料聚集态结构的场发射性质研究的新进展,特别是分子基材料的结构和聚集态形貌和尺寸对场发射性质的影响以及通过对分子基材料的杂化优化其场发射的性质,展望了分子基材料聚集态结构场发射的应用前景和发展趋势。     

STOCK: Structure mapper and online coarse‐graining kit for molecular simulations

We present a web toolkit STructure mapper and Online Coarse‐graining Kit for setting up coarse‐grained molecular simulations. The kit consists of two tools: structure mapping and Boltzmann inversion tools. The aim of the first tool is to define a molecular mapping from high, for example, all‐atom, to low, that is, coarse‐grained, resolution. Using a graphical user interface it generates input files, which are compatible with standard coarse‐graining packages, for example, Versatile Object‐oriented Toolkit for Coarse‐graining Applications and DL_CGMAP. Our second tool generates effective potentials for coarse‐grained simulations preserving the structural properties, for example, radial distribution functions, of the underlying higher resolution model. The required distribution functions can be provided by any simulation package. Simulations are performed on a local machine and only the distributions are uploaded to the server. The applicability of the toolkit is validated by mapping atomistic pentane and polyalanine molecules to a coarse‐grained representation. Effective potentials are derived for systems of TIP3P (transferable intermolecular potential 3 point) water molecules and salt solution. The presented coarse‐graining web toolkit is available at http://stock.cmm.ki.si . © 2014 Wiley Periodicals, Inc.     

定量结构-性质关系在分析化学中的应用研究进展

定量结构-性质关系研究应用理论计算方法和各种统计分析工具相结合,研究系列化合物的结构与其生物学性质和各种物理化学性质之间的定量函数关系．它不仅可以建立预测化合物的各种物理化学性质以及生物活性的理论,而且还可以发现和确定对化合物的各种性质起决定作用的结构因素,从而在分子水平上了解物质的微观结构对各种宏观性质的影响,在很多领域得到了广泛的应用．主要介绍定量结构—性质关系在分析化学中的应用研究,主要包括在色谱分析、毛细管电泳分析中的应用两大部分．