scholarly journals The repetitive local sampling and the local distribution theory

2021 ◽  
Author(s):  
PU TIAN
Keyword(s):  
Molecular Simulation ◽  
Structure Prediction ◽  
Materials Science ◽  
Molecular System ◽  
Potential Of Mean Force ◽  
Distribution Theory ◽  
Local Distribution ◽  
Structural Refinement ◽  
Molecular Systems ◽  
Local Sampling

Molecular simulation is a mature and versatile tool set widely utilized in many subjects with more than 30,000 publications each year. However, its methodology development has been struggling with a tradeoff between accuracy/resolution and speed, significant improvement of both beyond present state of the art is necessary to reliably substitute many expensive and laborious experiments in molecular biology, materials science and nanotechnology. Previously, the ubiquitous issue regarding severe wasting of computational resources in all forms of molecular simulations due to repetitive local sampling was raised, and the local free energy landscape approach was proposed to address it. This approach is derived from a simple idea of first learning local distributions, and followed by dynamic assembly of which to infer global joint distribution of a target molecular system. When compared with conventional explicit solvent molecular dynamics simulations, a simple and approximate implementation of this theory in protein structural refinement harvested acceleration of about six orders of magnitude without loss of accuracy. While this initial test revealed tremendous benefits for addressing repetitive local sampling, there are some implicit assumptions need to be articulated. Here, I present a more thorough discussion of repetitive local sampling; potential options for learning local distributions; a more general formulation with potential extension to simulation of near equilibrium molecular systems; the prospect of developing computation driven molecular science; the connection to mainstream residue pair distance distribution based protein structure prediction/refinement; and the fundamental difference of utilizing averaging from conventional molecular simulation framework based on potential of mean force. This more general development is termed the local distribution theory to release the limitation of strict thermodynamic equilibrium in its potential wide application in general soft condensed molecular systems.

ROLE OF MOLECULAR MODELLING IN DRUG DESIGN

2016 ◽  
Vol 1 (02) ◽  
Author(s):  
M. Lakshmi Prabha ◽  
N. Pradeepa
Keyword(s):  
Molecular Modeling ◽  
Drug Design ◽  
Materials Science ◽  
Molecular System ◽  
Biological Molecules ◽  
Computational Techniques ◽  
Molecular Systems ◽  
Chemical Systems ◽  
Individual Unit

Molecular modeling includes all theoretical methods and computational techniques used to model or mimic the behavior of molecules. The techniques are used in the fields of computational chemistry, drug design, computational biology and materials science for studying molecular systems ranging from small chemical systems to large biological molecules and material assemblies. One can perform simplest calculation manually. But the computers are required to perform molecular modeling of any complex or reasonably sized system. Atomic level description of molecular system is the common feature of molecular modeling techniques. This may include treating atoms as the smallest individual unit (the Molecular mechanics approach), or explicitly modeling electrons of each atom (Parsons et al., 2005).

Development of the ChIMES Force Field for Reactive Molecular Systems: Carbon Monoxide at Extreme Conditions

2019 ◽  
Author(s):  
Rebecca Lindsey ◽  
Nir Goldman ◽  
Laurence E. Fried ◽  
Sorin Bastea
Keyword(s):  
Carbon Monoxide ◽  
Molecular System ◽  
Interaction Model ◽  
System Size ◽  
Single Atom ◽  
Reactive System ◽  
Extreme Conditions ◽  
Ambient Conditions ◽  
Molecular Systems ◽  
Three Body

<p>The interatomic Chebyshev Interaction Model for Efficient Simulation (ChIMES) is based on linear combinations of Chebyshev polynomials describing explicit two- and three-body interactions. Recently, the ChIMES model has been developed and applied to a molten metallic system of a single atom type (carbon), as well as a non-reactive molecular system of two atom types at ambient conditions (water). Here, we continue application of ChIMES to increasingly complex problems through extension to a reactive system. Specifically, we develop a ChIMES model for carbon monoxide under extreme conditions, with built-in transferability to nearby state points. We demonstrate that the resulting model recovers much of the accuracy of DFT while exhibiting a 10<sup>4</sup>increase in efficiency, linear system size scalability and the ability to overcome the significant system size effects exhibited by DFT.</p>

The initial reaction mechanism and thermal sensitivity of a fluoropolymer-containing energetic molecular system: the coupling effect of interfacial interactions and free radical reactions

CrystEngComm ◽  
2021 ◽  
Vol 23 (16) ◽  
pp. 3006-3014
Author(s):  
Wen Qian
Keyword(s):  
Free Radical ◽  
Coupling Effect ◽  
Molecular System ◽  
Thermal Sensitivity ◽  
Radical Reactions ◽  
Initial Reaction ◽  
Interfacial Interactions ◽  
Free Radical Reactions ◽  
Molecular Systems ◽  
Reactive Molecular Dynamics

A strategy combining classic and reactive molecular dynamics is applied to find the coupling effect of interfacial interactions and free radical reactions during the initial thermal decomposition of fluoropolymer-containing molecular systems.

Graph theory approach

1983 ◽  
Vol 48 (8) ◽  
pp. 2097-2117 ◽  
Author(s):  
Vladimír Kvasnička
Keyword(s):  
Organic Chemistry ◽  
Computer Simulation ◽  
Graph Theory ◽  
Chemical Reaction ◽  
Molecular System ◽  
Theory Approach ◽  
Molecular Systems

A graph-theory formalism of the organic chemistry is suggested. The molecular system is considered as a multigraph with loops, the vertices are evaluated by their mapping onto the vocabulary of vertex labels (e.g. atomic symbols). A multiedge of multiplicity t corresponds to a t-tuple (single, double, triple, etc) bond. The chemical reaction of molecular systems is treated by the transformation of graphs. The suggested graph-theory approach allows to formalize many notions and concepts that are naturally emerging in the computer simulation of organic chemistry.

scholarly journals "Dividing and Conquering" and "Caching" in Molecular Modeling

2021 ◽  
Author(s):  
Xiaoyong Cao ◽  
Pu Tian
Keyword(s):  
Molecular Modeling ◽  
Degrees Of Freedom ◽  
Materials Science ◽  
Force Fields ◽  
Coarse Graining ◽  
Divide And Conquer ◽  
Collective Variables ◽  
Molecular Systems ◽  
State Models ◽  
Molecular Science

Molecular modeling is widely utilized in subjects including but not limited to physics, chemistry, biology, materials science and engineering. Impressive progress has been made in development of theories, algorithms and software packages. To divide and conquer, and to cache intermediate results have been long standing principles in development of algorithms. Not surprisingly, Most of important methodological advancements in more than half century of molecule modeling are various implementations of these two fundamental principles. In the mainstream classical computational molecular science based on force fields parameterization by coarse graining, tremendous efforts have been invested on two lines of algorithm development. The first is coarse graining, which is to represent multiple basic particles in higher resolution modeling as a single larger and softer particle in lower resolution counterpart, with resulting force fields of partial transferability at the expense of some information loss. The second is enhanced sampling, which realizes "dividing and conquering" and/or "caching" in configurational space with focus either on reaction coordinates and collective variables as in metadynamics and related algorithms, or on the transition matrix and state discretization as in Markov state models. For this line of algorithms, spatial resolution is maintained but no transferability is available. Deep learning has been utilized to realize more efficient and accurate ways of "dividing and conquering" and "caching" along these two lines of algorithmic research. We proposed and demonstrated the local free energy landscape approach, a new framework for classical computational molecular science and a third class of algorithm that facilitates molecular modeling through partially transferable in resolution "caching" of distributions for local clusters of molecular degrees of freedom. Differences, connections and potential interactions among these three algorithmic directions are discussed, with the hope to stimulate development of more elegant, efficient and reliable formulations and algorithms for "dividing and conquering" and "caching" in complex molecular systems.

scholarly journals Density functional theory in the solid state

2014 ◽  
Vol 372 (2011) ◽  
pp. 20130270 ◽  
Author(s):  
Philip J. Hasnip ◽  
Keith Refson ◽  
Matt I. J. Probert ◽  
Jonathan R. Yates ◽  
Stewart J. Clark ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Density Functional Theory ◽  
Solid State ◽  
Structure Prediction ◽  
Density Functional ◽  
Materials Science ◽  
Difficult Problem ◽  
Structure Property ◽  
Defect States ◽  
Functional Theory

Density functional theory (DFT) has been used in many fields of the physical sciences, but none so successfully as in the solid state. From its origins in condensed matter physics, it has expanded into materials science, high-pressure physics and mineralogy, solid-state chemistry and more, powering entire computational subdisciplines. Modern DFT simulation codes can calculate a vast range of structural, chemical, optical, spectroscopic, elastic, vibrational and thermodynamic phenomena. The ability to predict structure–property relationships has revolutionized experimental fields, such as vibrational and solid-state NMR spectroscopy, where it is the primary method to analyse and interpret experimental spectra. In semiconductor physics, great progress has been made in the electronic structure of bulk and defect states despite the severe challenges presented by the description of excited states. Studies are no longer restricted to known crystallographic structures. DFT is increasingly used as an exploratory tool for materials discovery and computational experiments, culminating in ex nihilo crystal structure prediction, which addresses the long-standing difficult problem of how to predict crystal structure polymorphs from nothing but a specified chemical composition. We present an overview of the capabilities of solid-state DFT simulations in all of these topics, illustrated with recent examples using the CASTEP computer program.

The evaluation of the hyperfine interaction tensor components in molecular systems

1977 ◽  
Vol 354 (1677) ◽  
pp. 223-244 ◽  
Keyword(s):  
Angular Momentum ◽  
Hyperfine Interaction ◽  
Metal Ion ◽  
Molecular System ◽  
Slater Type Orbital ◽  
Molecular Systems ◽  
Principal Axes ◽  
Interaction Tensor ◽  
Electronic Wavefunction ◽  
General Method

In this paper a general method is developed to evaluate the nine hyperfine interaction tensor components, A αβ , arising from the electron orbital angular momentum and the electron spin dipolar-nuclear spin angular momentum interactions of an electron associated dominantly with one nucleus coupling with a nucleus with a non-zero magnetic moment, where the electronic wavefunction is described by a Slater-type orbital. The method handles long range and short range coupling including the free atom case. From the results the degree of non-coincidence of the principal axes of the g and A tensors and the n.m.r. shifts are evaluated. As an illustration the molecular system examined is a molecule containing a d 1 transition metal ion in a strong crystal field.

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