scholarly journals Binding affinity and conformational preferences influence kinetic stability of short oligonucleotides on carbon nanotubes

2020 ◽  
Author(s):  
Ali Alizadehmojarad ◽  
Xingcheng Zhou ◽  
Abraham G Beyene ◽  
Kevin Chacon ◽  
Younghun Sung ◽  
...  

DNA-wrapped single walled carbon nanotubes (SWNTs) have found a widespread use in a variety of nanotechnology applications. Yet, the relationship between structural conformation, binding affinity and kinetic stability of these polymers on SWNTs remains poorly understood. Here, we used molecular dynamics (MD) simulations and experiments to explore this relationship for short oligonucleotides adsorbed on SWNTs. First, using classical MD simulations of oligonucleotide-(9,4)-SWNT hybrid complexes, we explored the relationship between ssDNA and ssRNA surface conformation and sequence chemistry. We screened the conformation of 36 sequences of short ssDNA and ssRNA polymers on (9,4) SWNT, where the contour lengths were selected so the polymers can, to a first approximation, wrap once around the SWNT circumference. From these screens, we identified structural motifs that we broadly classified into rings and non-rings. Then, several sequences were selected for detailed investigations. We used temperature replica exchange MD calculations to compute two-dimensional free energy landscapes characterizing the conformations of select sequences. Ring conformations seemed to be driven primarily by sequence chemistry. Specifically, strong (n,n+2) nucleotide interactions and the ability of the polymer to form compact structures, as for example, through sharp bends in the nucleotide backbone, correlated with ring-forming propensity. However, ring-formation probability was found to be uncorrelated with free energy of oligonucleotide binding to SWNTs (∆Gbind). Conformational analyses of oligonucleotides, computed free energy of binding of oligonucleotides to SWNTs, and experimentally determined kinetic stability measurements show that ∆Gbind is the primary correlate for kinetic stability. The probability of the sequence to adopt a compact, ring-like conformation is shown to play a secondary role that still contributes measurably to kinetic stability. For example, sequences that form stable compact rings (C-rich sequences) could compensate for their relatively lower ∆Gbind and exhibit kinetic stability, while sequences with strong ∆Gbind (such as (TG)3(GT)3) were found to be kinetically stable despite their low ring formation propensity. We conclude that the stability of adsorbed oligonucleotides is primarily driven by its free energy of binding and that if ring-like structural motifs form, they would contribute positively to stability.

2020 ◽  
Vol 7 (15) ◽  
pp. 2000353 ◽  
Author(s):  
Ali A. Alizadehmojarad ◽  
Xingcheng Zhou ◽  
Abraham G. Beyene ◽  
Kevin E. Chacon ◽  
Younghun Sung ◽  
...  

2011 ◽  
Vol 697-698 ◽  
pp. 487-490
Author(s):  
M.Y. Zhou ◽  
Yan Ling Tian ◽  
Z. Ren ◽  
H.Y. Zheng ◽  
R.B. Wei

Molecular dynamics (MD) simulations were used to investigate the elastic properties of carbon nanotubes (CNTs). Displacements were loaded to CNTs on the tension deformation simulations. In order to better understand the relationship between Young’s modulus and the structure of the CNTs, different chiralities and diameters were involved. It is found that the Young’s modulus will be no more sensitive as in the single-walled carbon nanotubes (SWCNTs) with increasing walls. The tension deformation results also indicate that SWCNTs have better elastic property compared to multi-walled carbon nanotubes (MWCNTs).


2020 ◽  
Vol 10 (6) ◽  
pp. 20190133
Author(s):  
S. J. Zasada ◽  
D. W. Wright ◽  
P. V. Coveney

In recent years, it has become possible to calculate binding affinities of compounds bound to proteins via rapid, accurate, precise and reproducible free energy calculations. This is imperative in drug discovery as well as personalized medicine. This approach is based on molecular dynamics (MD) simulations and draws on sequence and structural information of the protein and compound concerned. Free energies are determined by ensemble averages of many MD replicas, each of which requires hundreds of cores and/or GPU accelerators, which are now available on commodity cloud computing platforms; there are also requirements for initial model building and subsequent data analysis stages. To automate the process, we have developed a workflow known as the binding affinity calculator. In this paper, we focus on the software infrastructure and interfaces that we have developed to automate the overall workflow and execute it on commodity cloud platforms, in order to reliably predict their binding affinities on time scales relevant to the domains of application, and illustrate its application to two free energy methods.


2020 ◽  
Author(s):  
E. Prabhu Raman ◽  
Thomas J. Paul ◽  
Ryan L. Hayes ◽  
Charles L. Brooks III

<p>Accurate predictions of changes to protein-ligand binding affinity in response to chemical modifications are of utility in small molecule lead optimization. Relative free energy perturbation (FEP) approaches are one of the most widely utilized for this goal, but involve significant computational cost, thus limiting their application to small sets of compounds. Lambda dynamics, also rigorously based on the principles of statistical mechanics, provides a more efficient alternative. In this paper, we describe the development of a workflow to setup, execute, and analyze Multi-Site Lambda Dynamics (MSLD) calculations run on GPUs with CHARMm implemented in BIOVIA Discovery Studio and Pipeline Pilot. The workflow establishes a framework for setting up simulation systems for exploratory screening of modifications to a lead compound, enabling the calculation of relative binding affinities of combinatorial libraries. To validate the workflow, a diverse dataset of congeneric ligands for seven proteins with experimental binding affinity data is examined. A protocol to automatically tailor fit biasing potentials iteratively to flatten the free energy landscape of any MSLD system is developed that enhances sampling and allows for efficient estimation of free energy differences. The protocol is first validated on a large number of ligand subsets that model diverse substituents, which shows accurate and reliable performance. The scalability of the workflow is also tested to screen more than a hundred ligands modeled in a single system, which also resulted in accurate predictions. With a cumulative sampling time of 150ns or less, the method results in average unsigned errors of under 1 kcal/mol in most cases for both small and large combinatorial libraries. For the multi-site systems examined, the method is estimated to be more than an order of magnitude more efficient than contemporary FEP applications. The results thus demonstrate the utility of the presented MSLD workflow to efficiently screen combinatorial libraries and explore chemical space around a lead compound, and thus are of utility in lead optimization.</p>


2017 ◽  
Vol 14 (10) ◽  
pp. 1122-1137 ◽  
Author(s):  
Nivedita Singh ◽  
Parameswaran Saravanan ◽  
M.S. Thakur ◽  
Sanjukta Patra

Background: Phosphodiesterases 9A (PDE9A) is one of the prominent regulating enzymes of the signal transduction pathway having highest catalytic affinity for second messenger, cGMP. When the cGMP level is lowered, an uncontrolled expression of PDE9A may lead to various neurodegenerative diseases. To regulate the catalytic activity of PDE9A, potent inhibitors are needed. Objective: The primary objective of the present study was to develop new xanthine based inhibitors targeting PDE9A. This study was an attempt to bring structural diversification in PDE9A inhibitor development because most of the existing inhibitors are constructed over pyrazolopyrimidinone scaffold. Methods: Manual designing and parallel molecular docking approach were used for the development of xanthine derivatives. In this study, N1, N3, N9 and C8 positions of xanthine scaffold were selected as substitution sites to design 200 new compounds. Reverse docking and pharmaceutical analyses were used for final validation of most promising compounds. Results: By keeping free energy of binding cut-off of -6.0 kcal/mol, 52 compounds were screened. The compounds with substitution at N1, N3 and C8 positions of xanthine showed good occupancy in PDE9A active site pocket with a significant interaction pattern. This was further validated by screening different factors such as free energy of binding, inhibition constant and interacting active site residues in the 5Å region. Substitution at C8 position with phenyl substituent determined the inhibition affinity of compounds towards PDE9A by establishing a strong hydrophobic - hydrophobic interaction. The alkyl chain at N1 position generated selectivity of compounds towards PDE9A. The aromatic fragment at N3 position increased the binding affinity of compounds. Thus, by comparative docking study, it was found that compound 39-42 formed selective interaction towards PDE9A over other members of the PDE superfamily. Conclusion: From the present study, N1, N3 and C8 positions of xanthine were concluded as the best sites for substitution for the generation of potent PDE9A inhibitors.


Author(s):  
A. M. Savchenko ◽  
Yu. V. Konovalov ◽  
A. V. Laushkin

The relationship of the first and second laws of thermodynamics based on their energy nature is considered. It is noted that the processes described by the second law of thermodynamics often take place hidden within the system, which makes it difficult to detect them. Nevertheless, even with ideal mixing, an increase in the internal energy of the system occurs, numerically equal to an increase in free energy. The largest contribution to the change in the value of free energy is made by the entropy of mixing, which has energy significance. The entropy of mixing can do the job, which is confirmed in particular by osmotic processes.


2009 ◽  
Vol 35 (10-11) ◽  
pp. 986-997 ◽  
Author(s):  
Abdallah Sayyed-Ahmad ◽  
Himanshu Khandelia ◽  
Yiannis N. Kaznessis

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