Deficiencies in Molecular Dynamics Simulation-Based Prediction of Protein–DNA Binding Free Energy Landscapes

Khabiri, Morteza; Freddolino, Peter L.

doi:10.1021/acs.jpcb.6b12450

Cited by 23 publications

(47 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several approaches were developed to accurately and precisely reveal the nature of binding between a compound to a protein, a protein to a protein, and a protein to a gene, etc., [1][2][3][4] because the non-covalent reaction between two biomolecules is very important in biology. [5][6][7][8] Especially, the ligand-binding affinity is one of the most critical aspects to predict a potential inhibitor restricting the biological function of an enzyme in computer-aided drug design (CADD).…”

Section: Introductionmentioning

confidence: 99%

Estimating the ligand‐binding affinity via λ‐dependent umbrella sampling simulations

Ngo

2020

J Comput Chem

View full text Add to dashboard Cite

The umbrella sampling (US) approach has been demonstrated to be a very efficient method for estimating the ligand-binding affinity. However, most of the calculated values overestimate experimental ones that are probably caused by the inaccurate representation of the interaction between the ligand and the surrounding molecules. The issue can be resolved via the implementation aspects of λ-alteration simulation into the US approach, which we call the λ-dependent umbrella sampling (λUS) scheme. In particular, the electrostatic and van der Waals interactions were simultaneously changed by using the coupling parameter λ during λUS simulations. The mean value of obtained results, ΔG λ = 0:20 US = −11:59 AE 1:51 kcal mol −1 , is in good fitting to the mean value of respective experiments, ΔG EXP = − 11.26 ± 0.89 kcal mol −1. Moreover, the correlation between the proposed approach and experiment is quite good with a value of R λ = 0:20 US = 0:82 AE 0:10. The λUS scheme significantly enhances the calculated accuracy since the RMSE of the proposed scheme is smaller than traditional US simulations, RMSE λ = 0:20

show abstract

Section: Introductionmentioning

confidence: 99%

Estimating the ligand‐binding affinity via λ‐dependent umbrella sampling simulations

Ngo

2020

J Comput Chem

View full text Add to dashboard Cite

show abstract

“…On the other hand, high-resolution determinations of protein–DNA complex structures ( 18 ) allow one to investigate corresponding conformational dynamics by employing all-atom molecular-dynamics (MD) simulations via high-performance computing ( 19 – 21 ). Protein recognition on specific DNA has been actively examined in recent years using MD technologies ( 22 – 26 ). In comparison, protein association with nonspecific DNA has been less examined.…”

mentioning

confidence: 99%

Revealing atomic-scale molecular diffusion of a plant-transcription factor WRKY domain protein along DNA

Dai

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Transcription factor (TF) target search on genome is highly essential for gene expression and regulation. High-resolution determination of TF diffusion along DNA remains technically challenging. Here, we constructed a TF model system using the plant WRKY domain protein in complex with DNA from crystallography and demonstrated microsecond diffusion dynamics of WRKY on DNA by employing all-atom molecular-dynamics (MD) simulations. Notably, we found that WRKY preferentially binds to one strand of DNA with significant energetic bias compared with the other, or nonpreferred strand. The preferential DNA-strand binding becomes most prominent in the static process, from nonspecific to specific DNA binding, but less distinct during diffusive movements of the domain protein on the DNA. Remarkably, without employing acceleration forces or bias, we captured a complete one-base-pair stepping cycle of the protein tracking along major groove of DNA with a homogeneous poly-adenosine sequence, as individual hydrogen bonds break and reform at the protein–DNA binding interface. Further DNA-groove tracking motions of the protein forward or backward, with occasional sliding as well as strand crossing to minor groove of DNA, were also captured. The processive diffusion of WRKY along DNA has been further sampled via coarse-grained MD simulations. The study thus provides structural dynamics details on diffusion of a small TF domain protein, suggests how the protein approaches a specific recognition site on DNA, and supports further high-precision experimental detection. The stochastic movements revealed in the TF diffusion also provide general clues about how other protein walkers step and slide along DNA.

show abstract

“…A computational study by Khabiri et al, 2017 reported that changes in binding free energy do not correlate strongly with salt bridges or hydrogen bonding in protein-DNA interactions [ 43]. Contrary to their results, we show that for our peptide-DNA systems the electrostatic energy and binding free energy are correlated with the number of hydrogen bonds and salt bridges ( Figure 10), with an R 2 between binding free energy and the number of hydrogen bonds and salt bridges of -0.92 and -0.95, respectively, and an R 2 of -0.95 and -0.97 between electrostatic energy and hydrogen bonds and salt bridges, respectively.…”

Section: Contacting Surface Areamentioning

confidence: 99%

Interaction of camel Lactoferrin derived peptides with DNA: a molecular dynamics study

Pirkhezranian

Tahmurespur

Daura

et al. 2019

Preprint

View full text Add to dashboard Cite

Background: Lactoferrampin (LFampin), Lactoferricin (LFcin), and LFchimera are three well-known antimicrobial peptides derived from Lactoferrin and proposed as alternatives for antibiotics. Although the intracellular activity of these peptides has been previously demonstrated, their mode of action is not yet fully understood. Here, we performed a molecular dynamics simulation study to understand the molecular interactions between camel Lactoferrin derived peptides, including CLFampin, CLFcin, and CLFchimera, and DNA as an important intracellular target. Results: Our results indicate that all three peptides bind to DNA, albeit with different propensities, with CLFchimera showing the highest binding affinity. The secondary structures of the peptides, modeled on Lactoferrin, did not undergo significant changes during simulation, supporting their functional relevance. Main residues involved in the peptide-DNA interaction were identified based on binding free energy estimates calculated over 200 ns, which, as expected, confirmed strong electrostatic interactions between DNA phosphate groups and positively charged peptide side chains. Interaction between the different concentrations of CLFchimera and DNA revealed that after binding of four copies of CLFchimera to DNA, hydrogen bonds between the two strands of DNA start to break from one of the termini. Conclusions: Importantly, our results revealed that there is no DNA-sequence preference for peptide binding, in line with a broad antimicrobial activity. Moreover, the results showed that the strength of the interaction between DNA and CLFchimera is concentration dependent. The insight provided by these results can be used for the rational redesign of natural antimicrobial peptides targeting the bacterial DNA.

show abstract

Deficiencies in Molecular Dynamics Simulation-Based Prediction of Protein–DNA Binding Free Energy Landscapes

Cited by 23 publications

References 37 publications

Estimating the ligand‐binding affinity via λ‐dependent umbrella sampling simulations

Estimating the ligand‐binding affinity via λ‐dependent umbrella sampling simulations

Revealing atomic-scale molecular diffusion of a plant-transcription factor WRKY domain protein along DNA

Interaction of camel Lactoferrin derived peptides with DNA: a molecular dynamics study

Contact Info

Product

Resources

About