Evaluation of CDK6 and p16/INK4a-Derived Peptides Interaction

doi:10.4236/cmb.2013.33007

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Computational Molecular Bioscience, 2013, 3, 53-57

http://dx.doi.org/10.4236/cmb.2013.33007 Published Online September 2013 (http://www.scirp.org/journal/cmb)

Evaluation of CDK6 and p16/INK4a-Derived

Peptides Interaction

Andrey Kazennov1, Andrey Alekseenko1, Vladimir Bozhenko2,

Tatiana Kulinich2, Nikolay Shuvalov1, Y ar os la v Khol od ov1

1Department of Computational Mathematics, Moscow Institute of Physics and Technology,

Dolgoprudny, Russia

2Russian Scientific Center of Roentgenoradiology, Moscow, Russia

Email: [email protected]

Received May 22, 2013; revised June 22, 2013; accepted June 30, 2013

cense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ABSTRACT

The goal of this work is the development of novel peptides with high efficacy of inhibiting activity of CDK6/CyclinD

complex. The peptides were derived from primary sequence of P16 protein and its homologues. The interactions be-

tween CDK6 and P16/INK4a-derived peptides are studied with molecular dynamics simulation employing umbrella

sampling method. The SASA implicit solvent model was used for simulation, which was accelerated using NVIDIA

GPUs.

Keywords: Cyclin-Dependent Kinases; Molecular Dynamics; Umbrella Sampling; GPU; SASA

1. Introduction

Cyclin-dependent kinases (CDKs) play a major role in

cell cycle regulation and cell division progression. The

correct performance of various cyclin-dependent kinases

secures the sequential progression of numerous meta-

bolic processes required for cell division. CyclinD-acti-

vated kinases CDK4 and CDK6 are quintessential for

cell progression from growth phase (G1) to synthesis

phase (S). The CyclinD-CDK4/6 complex activity is re-

gulated by proteins of CKI (Cyclin-dependent kinase

inhibitors) family. Many pathological processes includ-

ing malignant tumors of various locations associated with

abnormalities in cell division process are caused by de-

fects in CyclinD-CDK4/6 complex functioning, which

are conditioned by hyperexpression of CyclinD or CDK-

4/6, mutation of intracellular inhibitors or a number of

other processes. CDK4 and CDK6 are attractive molecu-

lar targets since it was shown that pharmacological inhi-

bition of CDK4/6 leads to growth suppression in tumors

having declension in CDK4/6-involving control pathway.

Currently, numerous low-molecular CDK inhibitors

are known [1]. However, their major disadvantage is low

selectivity since they are mimicking ATP and are com-

peting with it for binding sites, which are homologous in

most kinases, thus the problem of cross-reactivity arises

[2]. More preferable from our point of view is the use of

peptides derived from natural CKI proteins. In vivo and

in vitro experiments have shown that short (up to 10 re-

sidues) peptides from p16/INK4a, p18/INK4c, p21/

WAF1 and p27/Kip1 proteins have inhibitory properties

comparable with activity of full-sized protein [3]. The

use of peptides as pharmaceutical intracellular drugs be-

came possible after discovery advancement of “cell pene-

trating peptides” (CPP) technology [4], allowing delivery

of almost-arbitrary peptide sequence into intracellular

compartments with nearly 100% efficacy. The combina-

tion of CPP technology with highly selective functional

sequences derived from natural regulatory proteins ap-

pears to be a promising approach for development of

targeted drugs.

Numerical modeling is routinely used as a way to

lower the drug developments costs by significantly re-

ducing the number of potential pharmaceutical com-

pounds. However there is no mastered methodology for

evaluation of peptide drugs.

In this work protein docking and molecular dynamics

methods are applied to the problem of predicting the ef-

ficacy of given peptides. The CDK6 protein is used as

drug target, and the tested peptides were derived from

p16/INK4a protein sequence.

A. KAZENNOV ET AL.

2. Numerical Model

To calculate the free energy of protein-peptide interac-

tion we use SASA implicit solvent model implemented

in GPU-accelerated MDis package [5]. Since the main

task is to bolt out the most of a priory ineffective pep-

tides the use of such simplified model is justified.

MDis package implements a CHARMM19 forcefield

[6] in conjunction with SASA implicit solvent model [7-

9].

3. Biological System

The major role in cell division control pathway is played

by Retinoblastoma protein (pRb) (Figure 1). In activated

(non-phosphorylated) state this protein suppresses cell

cycle progression by inhibiting E2F transcription factor.

In healthy cell ready for division, the phosphorylation

(deactivation) of pRb is performed by complex of cyclin-

dependent kinases CDK4 and CDK6 with cyclinD pro-

teins (D1, D2, D3). The cancer cells often exhibit the

mutations in one or more proteins involved in this path-

way [10-14]. The natural inhibitors of CDK4 and CDK6

bound to CyclinD are proteins of INK4 family, including

P16/INK4a protein, whose functioning is also known to

be disrupted in cancerous cell [11,12]. The introduction

of P16 protein into cell has been shown to arrest cell cy-

cle progression from G1 to S phase.

The clinical use of P16, however, is not practical due

to its relatively large size (156 amino acid residues). It

might be more practical to develop shorter (up to 10

amino acid residues long) peptides with inhibitory activ-

ity on level with full-length P16.

As a foundation for this study we used the works of

Fåhraeus et al. [15,16] measuring in vitro and in vivo the

efficiency of CDK6 and CDK4 inhibition by various

Figure 1. CDK4/6 regulatory pathway schematics.

parts of P16 protein and its homologues.

The first series of experiments [15] measures the sta-

bility of complex formed by CDK6 and 20-residue-long

peptides derived from all subsequences of P16 with 15-

residue step. Afterwards, the activity of CDK6 was mea-

sured in vitro in presence of same peptides, as well as

their effect on cell cycle progression in vivo. In all of

these experiments the peptide codenamed “p6” (residues

84 - 103 of full-sized P16) have shown best results.

Reference [16] describes the experiments measuring

the efficiency of various mutations of “p6” peptide, in-

cluding its shortening.

The main goal of this work is to reproduce the results

of [15,16] in silico to approbate the suggested protocol.

4. Methodology

The proteins of INK4 family are allosteric inhibitors [17,

18]. However, the characteristic times of structural tran-

sitions in proteins are of order of milliseconds which is

beyond what is currently reachable by all-atom molecular

dynamics simulations. So an assumption was made that

the stable complex formation is required for peptide in-

hibitory activity since otherwise it would be unable to

cause sufficient structural change. For this reason the

energy profiles of association of CDK6 with peptides

were studied.

Initial protein structures were taken from Protein Data

Bank (CDK6: 1BLX [19], P16: 1BI7 [20]). Each struc-

ture was minimized with steepest-descend algorithm in

MDis package.

In this work peptides codenamed P2-P9 from [15] are

studied. The structure of peptides was obtained by cut-

ting them from 3D structure of whole protein and subse-

quent equilibration for 5 ns at 300 K temperature.

Initial conformations of peptides bound to CDK6 were

obtained using Autodock Vina software [21]. For each

peptide ten most energetically favorable conformations

were chosen, from which from 2 to 4 significantly dif-

ferent ones were chosen for further investigation.

To measure interaction energy the umbrella sampling

technique [22] was used. The distance between peptide

and protein centers of mass was taken as reaction coor-

dinate. For each conformation in consideration the gen-

eration of initial trajectory was performed by pulling

peptide apart from the protein with force applied to pep-

tides center of mass and Cα atoms of CDK6 restrained

(Langevin integrator with T = 300 K, γ = 0.15, Δt = 1 fs,

harmonic restraint on Cα atoms of CDK6 16 kcal/mol/Å2,

pulling speed 5 Å/ns, pulling spring constant 2 kcal/mol/

Å2). The trajectories were used to extract initial confor-

mations for further sampling. The conformations were

taken with 0.5 Å step of reaction coordinate. For each

sampling window the 30 ns of equilibration simulation

A. KAZENNOV ET AL.

energy compared to in vitro results from [15,16]. As

could be seen in Figure 4 although numerical modeling

yields correct interaction energy it is not always directly

related to inhibition efficiency.

was performed with additional harmonic restraint applied

to reaction coordinate (Langevin integrator with T = 300

K, γ = 0.15, Δt = 1 fs; umbrella spring constant 1 kcal/

mol /Å2; restraint on Cα atoms of CDK6 2.4 kcal/mol/Å2).

After analyzing resulting trajectories with weighted

histogram analysis method (WHAM) [23] the free energy

profiles were obtained. We used implementation of

WHAM by A. Grossfield [24].

The free energy difference between bound state and

the highest point of energy barrier separating bound and

unbound states were chosen as resulting value for each

peptide studied.

5. Results and Discussion

The conformations obtained from protein docking study

are shown in Figure 2, and the primary sequences of

peptides are listed in the Table 1. As one can see, all

peptides prefer hydrophobic pockets between two lobes

of CDK6 which coheres with proposed structural model

of CDK4/6 inhibition by proteins of INK4 family [17]. Figure 2. CDK6 (black) and peptides (red) bound confor-

mations as predicted by Autodock Vina [21].

Figures 3 and 4 show the obtained results for binding

Figure 3. The comparison of in silico (blue) and in vitro (yellow) results for the first series of experiments. For in silico, the

energy of binding obtained with Umbrella sampling is shown. For in vitro, the data on relative binding on agarose gel is

shown.

Figure 4. The comparison of in silico (blue) and in vitro (yellow, green) results for the second series of experiments. For in

silico, the energy of binding obtained with Umbrella sampling is shown. For in vitro, the data on relative binding on agarose

el (yellow) and relative kinase activity in presence of studied peptide (green) is shown. g

A. KAZENNOV ET AL.

Table 1. Studied peptides.

Peptide Sequence Source

P2 RVEEVRALLEAGANPNAPNS [15]

P3 NAPNSYGRRPIQVMMMGSAR [15]

P4 MGSARVAELLLLHGAEPNCA [15]

P5 EPNCADPATLTRPVHDAARE [15]

P6 DAAREGFLDTLVVLHRAGAR [15]

P7 RAGARLDVRDAWGRLPVDLA [15]

P8 PVDLAEELGHRDVARYLRAA [15]

P9 YLRAAAGGTRGSNHARIDAA [15]

P10 DAARAGFLDTLQTLLEFQAD [15]

P11 DAAREGFLDTLVVLHRAGAR [15]

R1 DAAREGFLDTLVVLHRAG [16]

R4 DAAREGFLDTLVVLHR [16]

R5 AREGFLDTLVVLHRAGAR [16]

R6 EGFLDTLVVLHRAGAR [16]

R7 FLDTLVVLHR [16]

R8 RVEEVRALLEAGANPNAPNS [16]

R11 NAPNSYGRRPIQVMMMGSAR [16]

6. Conclusion

The result of this work is the approbation of methodol-

ogy for numerical evaluation of binding energy of given

peptides with chosen target protein. The results could be

improved at the expense of increased simulation wall

time by using more accurate implicit solvent models (e.g.

GB/SA [25] or FACTS [26]) or explicit solvent. Alterna-

tive approach to improve the accuracy is to use more

initial conformations.

7. Acknowledgements

The work was supported by grants from Ministry of Sci-

ence and Education of Russian Federation #14.A18.21.

1871 and #14.A18.21.1239.

The “Lomonosov” supercomputer installed in Super-

computing complex of Moscow State University was

used to perform simulations.

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