Computer Simulations of Nonlinear Optical Chromophore Containing Polypeptides

1993 ◽  
Vol 330 ◽  
Author(s):  
Ruth Pachter ◽  
Steven B. Fairchild ◽  
James A. Lupo ◽  
Brian S. Sennett ◽  
Robert L. Crane ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Structure Prediction ◽  
Nonlinear Optical ◽  
Integrated Approach ◽  
Genetically Engineered ◽  
Spatial Proximity ◽  
Tertiary Structures ◽  
Eglin C ◽  
Nonlinear Optical Chromophores ◽  
Dynamics Simulations

ABSTRACTIn our continuing efforts towards the design of nonlinear (NLO) optical chromophore containing polypeptides we present an integrated computational approach, in which the design of biomolecular materials with defined secondary and tertiary structures is investigated by means of novel predictive tools, while the effects of the nonlinear optical chromophores are studied with molecular dynamics simulations. A neural network that was trained to predict the spatial proximity of Cα atoms that are less than a given threshold apart, is applied. The double-iterated Kalman filter (DIKF) technique is then employed with a constraints set that includes these pairwise atomic distances, and the distances and angles that define the structure as it is known from the protein's sequence. The results for test cases, particularly Crambin and genetically engineered Eglin-C, demonstrate that this integrated approach is useful for structure prediction at an intermediate resolution. Defined structural motifs of NLO chromophore containing polypeptides are investigated by using molecular dynamics techniques, particularly for the design of coil coiled amphiphatic biopolymers.

scholarly journals Systematic Finite-Temperature Reduction of Crystal Energy Landscapes.

2020 ◽  
Author(s):  
Nicholas Francia ◽  
Louise S. Price ◽  
Jonas Nyman ◽  
Sarah (Sally) Price ◽  
Matteo Salvalaglio
Keyword(s):  
Molecular Dynamics ◽  
Finite Temperature ◽  
Structure Prediction ◽  
Lattice Energy ◽  
Biased Sampling ◽  
Energy Landscapes ◽  
Polymorphic Transformations ◽  
Temperature And Pressure ◽  
Dynamics Simulations ◽  
The Impact

<p>Crystal structure prediction methods are prone to overestimate the number of potential polymorphs of organic molecules. In this work, we aim to reduce the overprediction by systematically applying molecular dynamics simulations and biased sampling methods to cluster subsets of structures that can easily interconvert at finite temperature and pressure. Following this approach, we rationally reduce the number of predicted putative polymorphs in CSP-generated crystal energy landscapes. This uses an unsupervised clustering approach to analyze independent finite-temperature molecular dynamics trajectories and hence identify a representative structure of each cluster of distinct lattice energy minima that are effectively equivalent at finite temperature and pressure. Biased simulations are used to reduce the impact of limited sampling time and to estimate the work associated with polymorphic transformations. We demonstrate the proposed systematic approach by studying the polymorphs of urea and succinic acid, reducing an initial set of over 100 energetically plausible CSP structures to 12 and 27 respectively, including the experimentally known polymorphs. The simulations also indicate the types of disorder and stacking errors that may occur in real structures.<br></p>

scholarly journals Reducing Crystal Structure Overprediction of Ibuprofen with Large Scale Molecular Dynamics Simulations

2021 ◽  
Author(s):  
Nicholas Francia ◽  
Louise Price ◽  
Matteo Salvalaglio
Keyword(s):  
Crystal Structure ◽  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Crystal Structures ◽  
Finite Temperature ◽  
Structure Prediction ◽  
Large Scale ◽  
Lattice Energy ◽  
Racemic Mixture ◽  
Dynamics Simulations

<p>The control of the crystal form is a central issue in the pharmaceutical industry. The identification of putative polymorphs through Crystal Structure Prediction (CSP) methods is based on lattice energy calculations, which are known to significantly over-predict the number of plausible crystal structures. A valuable tool to reduce overprediction is to employ physics-based, dynamic simulations to coalesce lattice energy minima separated by small barriers into a smaller number of more stable geometries once thermal effects are introduced. Molecular dynamics simulations and enhanced sampling methods can be employed in this context to simulate crystal structures at finite temperature and pressure. </p><p>Here we demonstrate the applicability of approaches based on molecular dynamics to systematically process realistic CSP datasets containing several hundreds of crystal structures. The system investigated is ibuprofen, a conformationally flexible active pharmaceutical ingredient that crystallises both in enantiopure forms and as a racemic mixture. By introducing a hierarchical approach in the analysis of finite-temperature supercell configurations, we can post-process a dataset of 555 crystal structures, identifying 65% of the initial structures as labile, while maintaining all the experimentally known crystal structures in the final, reduced set. Moreover, the extensive nature of the initial dataset allows one to gain quantitative insight into the persistence and the propensity to transform of crystal structures containing common hydrogen-bonded intermolecular interaction motifs.</p>

scholarly journals Molecular Dynamics Simulations for Biological Systems

2017 ◽  
pp. 1044-1071 ◽  
Author(s):  
Prerna Priya ◽  
Minu Kesheri ◽  
Rajeshwar P. Sinha ◽  
Swarna Kanchan
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Molecular Dynamics Simulations ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Biological Molecules ◽  
Dynamics Simulation ◽  
Ligand Docking ◽  
Protein Protein Interaction ◽  
Dynamics Simulations

Molecular dynamics simulation is an important tool to capture the dynamicity of biological molecule and the atomistic insights. These insights are helpful to explore biological functions. Molecular dynamics simulation from femto seconds to milli seconds scale give a large ensemble of conformations that can reveal many biological mysteries. The main focus of the chapter is to throw light on theories, requirement of molecular dynamics for biological studies and application of molecular dynamics simulations. Molecular dynamics simulations are widely used to study protein-protein interaction, protein-ligand docking, effects of mutation on interactions, protein folding and flexibility of the biological molecules. This chapter also deals with various methods/algorithms of protein tertiary structure prediction, their strengths and weaknesses.

Molecular Dynamics Simulations for Biological Systems

2016 ◽  
pp. 286-313 ◽  
Author(s):  
Prerna Priya ◽  
Minu Kesheri ◽  
Rajeshwar P. Sinha ◽  
Swarna Kanchan
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Molecular Dynamics Simulations ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Biological Molecules ◽  
Dynamics Simulation ◽  
Ligand Docking ◽  
Protein Protein Interaction ◽  
Dynamics Simulations

Molecular dynamics simulation is an important tool to capture the dynamicity of biological molecule and the atomistic insights. These insights are helpful to explore biological functions. Molecular dynamics simulation from femto seconds to milli seconds scale give a large ensemble of conformations that can reveal many biological mysteries. The main focus of the chapter is to throw light on theories, requirement of molecular dynamics for biological studies and application of molecular dynamics simulations. Molecular dynamics simulations are widely used to study protein-protein interaction, protein-ligand docking, effects of mutation on interactions, protein folding and flexibility of the biological molecules. This chapter also deals with various methods/algorithms of protein tertiary structure prediction, their strengths and weaknesses.

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