difference in virtual screening enrichment using … · 5. d.a. case, et al., amber 2017, 2017,...

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DIFFERENCE IN VIRTUAL SCREENING ENRICHMENT USING POLAR AND NON- POLAR INTERACTIONS OF MM-PB/GBSA METHODS XIAO HU 1 , ALESSANDRO CONTINI 1, § § DEPARTMENT OF PHARMACEUTICAL SCIENCE, UNIVERSITY OF MILAN Introduction MM-PB/GBSA free energy calculation has been suggested a better tool than most scoring functions. Both MM-PBSA and MM-GBSA binding energy calculation on docked poses yield moderate to good correlations to experimental data. Previous studies demonstrated that improvements in docking and virtual screening using MM-PB/GBSA methods were observed with increased internal dielectric value. 1,2 In our work, we assessed rescoring performance of MM-PB/GBSA methods on three test sets, each with the size of around 20 receptor proteins. We noticed no qualitative improvements in electrostatic estimation were observed by increasing the internal dielectric values for virtual screening. By using higher internal dielectrics, it quantitatively decreases the enrichment impairing effects from electrostatic and polar interactions to the total binding free energy prediction. Hence, future improvements in electrostatics can possibly improve the over all performance of MM-PB/GBSA calculations. Reference 1. T. Yang, et al., Proteins, 2011, 79(6), 1940-1951 2. H, Sun, et al., Phys. Chem. Chem. Phys., 2014, 16, 22035 3. K. Sommer, et al., J. Chem. Inf. Model., 2016, 56, 1105-1111 4. O. Korb, et al., J. Chem. Inf. Model., 2009, 49, 84-96 5. D.A. Case, et al., AMBER 2017, 2017, University of California, San Francisco Acknowledgement This work and X.H. are supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 675527. Docking & Virtual Screening: UNICON 3 was used to generate the top-scored tautomer and protonation states. PLANTS 4 was applied with PLANTS chemplp scoring function using a modified protocol. MM-PBSA rescoring: MMPBSA.py included in AMBERTools15 5 is applied for MM-PBSA rescoring. The docked poses of ligands were minimised briefly before rescoring. Internal dielectric constants of 1, 2, 4, and 6 were tested. Correlations of ROC AUC results between different internal dielectric constants Different distributions in KDE probability Density 13 out of 19 systems showed that increasing the internal dielectric values quantitatively decrease the deteriorating effects from electrostatic and polar energies on the overall binding free energy estimations. Table 1: ROC AUC correlation data for MM-GBSA energy compositions with different internal dielectrics (2, 4, and 6) to results using internal dielectric = 1. The AM1-BCC charging method was applied. MM-GBSA energy compositions Internal dielectric = 2 Internal dielectric = 4 Internal dielectric = 6 ! " # * $** % ** ! " # * $** % ** ! " # * $** % ** Ele + polar solvation 0.9996 1.0019 0.0014 0.9951 1.0040 0.0011 0.9870 1.0154 0.0020 VDW + non-polar solvation 0.9981 1.0168 -0.0141 0.9924 1.0111 -0.0090 0.9857 1.0140 -0.0124 Total binding free energy 0.9061 0.8523 0.1214 0.3562 0.4572 0.4060 0.0685 0.2127 0.5775 * Pearson correlation coefficient squared ** $ and % are the fitted parameter to a linear equation of the form & =$)+% Table 2: ROC AUC correlation data for MM-PBSA energy compositions with different internal dielectrics (2, 4, and 6) to results using internal dielectric = 1. The Gasteiger charging method was applied. MM-PBSA energy compositions Internal dielectric = 2 Internal dielectric = 4 Internal dielectric = 6 ! " # * $** % ** ! " # * $** % ** ! " # * $** % ** Ele + polar solvation 0.9870 0.9954 0.0180 0.9386 0.9598 0.0501 0.8742 0.9152 0.0769 VDW + non-polar solvation 0.9952 0.9982 -0.0033 0.9869 1.0098 -0.0078 0.9854 1.0194 -0.0114 Total binding free energy 0.3728 0.6109 0.3293 0.0628 0.2598 0.5636 0.0228 0.1595 0.6261 * Pearson correlation coefficient squared ** $ and % are the fitted parameter to a linear equation of the form & =$)+% ACES CDK2 ESR1 HIVPR KDE Probability Density Calculated Free Energy (score), kcal.mol -1 Figure 1: ROC AUC correlation graphs of MM-PBSA decomposed energies with different internal dielectric values (2, 4, and 6) to results using internal dielectric = 1. The fitted linear equation and the squared Pearson correlation coefficients are as dieplayed. Worsened correlations were observed with total binding free energy predictions (G-I), but not when considering polar (A-C) or non-polar (D–F) energies alone. y = 0.9819x + 0.0138 r p ² = 0.9794 0.00 0.50 1.00 0.00 0.50 1.00 ROC AUC ELE , Int diel = 2 y = 0.9542x + 0.0387 r p ² = 0.9282 0.00 0.50 1.00 0.00 0.50 1.00 ROC AUC ELE , Int diel = 4 ROC AUC ELE , Int diel = 1 y = 0.8991x + 0.0735 r p ² = 0.8758 0.00 0.50 1.00 0.00 0.50 1.00 ROC AUC ELE , Int diel = 6 y = 0.9836x + 0.0154 r p ² = 0.9838 0.00 0.50 1.00 0.00 0.50 1.00 ROC AUC npol , Int diel = 2 ROC AUC , Int diel = 1 y = 1.0052x + 0.0019 r p ² = 0.9664 0.00 0.50 1.00 0.00 0.50 1.00 ROC AUC npol , Int diel = 4 ROC AUC npol , Int diel = 1 y = 1.0063x + 0.003 r p ² = 0.9609 0.00 0.50 1.00 0.00 0.50 1.00 ROC AUC npol , Int diel = 6 y = 0.5065x + 0.4194 r p ² = 0.3896 0.00 0.50 1.00 0.00 0.50 1.00 1.50 ROC AUC tot , Int diel = 2 y = 0.2023x + 0.6302 r p ² = 0.059 0.00 0.50 1.00 0.00 0.50 1.00 1.50 ROC AUC tot , Int diel = 4 ROC AUC tot , Int diel = 1 y = 0.1001x + 0.6931 r p ² = 0.014 0.00 0.50 1.00 0.00 0.50 1.00 1.50 ROC AUC tot , Int diel = 6 A B C D E F G H I Non-polar Polar Total MM-PBSA Figure 2: Examples of the KDE plots of actives and inactives of receptors within the test set. 13 out of 19 systems showed the distributions similar to those of ACES and HIVPR when increasing the internal dielectric values. Only 3 out of 19 were observed with the trends similar to ESR1.

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Page 1: DIFFERENCE IN VIRTUAL SCREENING ENRICHMENT USING … · 5. D.A. Case, et al., AMBER 2017, 2017, University of California, San Francisco Acknowledgement This work and X.H. are supported

DIFFERENCE IN VIRTUAL SCREENING ENRICHMENT USING POLAR AND NON-POLAR INTERACTIONS OF MM-PB/GBSA METHODS

XIAO HU1, ALESSANDRO CONTINI1,§§DEPARTMENT OF PHARMACEUTICAL SCIENCE, UNIVERSITY OF MILAN

Introduction

MM-PB/GBSA free energy calculation has been suggested a better tool than most scoring functions. Both MM-PBSA and MM-GBSA binding energycalculation on docked poses yield moderate to good correlations to experimental data. Previous studies demonstrated that improvements in dockingand virtual screening using MM-PB/GBSA methods were observed with increased internal dielectric value.1,2 In our work, we assessed rescoringperformance of MM-PB/GBSA methods on three test sets, each with the size of around 20 receptor proteins. We noticed no qualitative improvements inelectrostatic estimation were observed by increasing the internal dielectric values for virtual screening. By using higher internal dielectrics, it quantitativelydecreases the enrichment impairing effects from electrostatic and polar interactions to the total binding free energy prediction. Hence, futureimprovements in electrostatics can possibly improve the over all performance of MM-PB/GBSA calculations.

Reference1. T. Yang, et al., Proteins, 2011, 79(6), 1940-19512. H, Sun, et al., Phys. Chem. Chem. Phys., 2014, 16, 220353. K. Sommer, et al., J. Chem. Inf. Model., 2016, 56, 1105-11114. O. Korb, et al., J. Chem. Inf. Model., 2009, 49, 84-965. D.A. Case, et al., AMBER 2017, 2017, University of California, San Francisco

AcknowledgementThis work and X.H. are supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 675527.

Docking & Virtual Screening: UNICON3 was used to generate the top-scored tautomer and protonation states. PLANTS4 was applied withPLANTSchemplp scoring function using a modified protocol.

MM-PBSA rescoring: MMPBSA.py included in AMBERTools155 is applied for MM-PBSA rescoring. The docked poses of ligands were minimised brieflybefore rescoring. Internal dielectric constants of 1, 2, 4, and 6 were tested.

Correlations of ROC AUC results between different internaldielectric constants

Different distributions in KDEprobability Density13 out of 19 systemsshowed that increasing theinternal dielectric valuesquantitatively decrease thedeteriorating effects fromelectrostatic and polarenergies on the overallbinding free energyestimations.

Table 1: ROC AUC correlation data for MM-GBSA energy compositions with different internal dielectrics (2, 4, and 6) to results using internal dielectric = 1. The AM1-BCC charging method was applied.

MM-GBSA energy compositions

Internal dielectric = 2 Internal dielectric = 4 Internal dielectric = 6 !"#* $** %** !"#* $** %** !"#* $** %**

Ele + polar solvation 0.9996 1.0019 0.0014 0.9951 1.0040 0.0011 0.9870 1.0154 0.0020 VDW + non-polar solvation 0.9981 1.0168 -0.0141 0.9924 1.0111 -0.0090 0.9857 1.0140 -0.0124 Total binding free energy 0.9061 0.8523 0.1214 0.3562 0.4572 0.4060 0.0685 0.2127 0.5775

* Pearson correlation coefficient squared ** $ and % are the fitted parameter to a linear equation of the form & = $) +% Table 2: ROC AUC correlation data for MM-PBSA energy compositions with different internal dielectrics (2, 4, and 6) to results using internal dielectric = 1. The Gasteiger charging method was applied.

MM-PBSA energy compositions

Internal dielectric = 2 Internal dielectric = 4 Internal dielectric = 6 !"#* $** %** !"#* $** %** !"#* $** %**

Ele + polar solvation 0.9870 0.9954 0.0180 0.9386 0.9598 0.0501 0.8742 0.9152 0.0769 VDW + non-polar solvation 0.9952 0.9982 -0.0033 0.9869 1.0098 -0.0078 0.9854 1.0194 -0.0114 Total binding free energy 0.3728 0.6109 0.3293 0.0628 0.2598 0.5636 0.0228 0.1595 0.6261

* Pearson correlation coefficient squared ** $ and % are the fitted parameter to a linear equation of the form & = $) +%

ACES

CDK2

ESR1

HIV

PRKD

E Pr

obab

ility

Den

sity

Calculated Free Energy (score), kcal.mol-1

Figure 1: ROC AUC correlation graphs of MM-PBSA decomposedenergies with different internal dielectric values (2, 4, and 6) to resultsusing internal dielectric = 1. The fitted linear equation and the squaredPearson correlation coefficients are as dieplayed. Worsened correlationswere observed with total binding free energy predictions (G - I), but notwhen considering polar (A - C) or non-polar (D – F) energies alone.

y = 0.9819x + 0.0138rp² = 0.97940.00

0.50

1.00

0.00 0.50 1.00

RO

C A

UC

ELE, I

ntdi

el =

2

ROC AUCELE, Int diel = 1

y = 0.9542x + 0.0387rp² = 0.92820.00

0.50

1.00

0.00 0.50 1.00

RO

C A

UC

ELE, I

ntdi

el =

4

ROC AUCELE, Int diel = 1

y = 0.8991x + 0.0735rp² = 0.87580.00

0.50

1.00

0.00 0.50 1.00

RO

C A

UC

ELE, I

ntdi

el =

6

ROC AUCELE, Int diel = 1

y = 0.9836x + 0.0154rp² = 0.98380.00

0.50

1.00

0.00 0.50 1.00

RO

C A

UC

npol, I

ntdi

el =

2

ROC AUCnpol, Int diel = 1

y = 1.0052x + 0.0019rp² = 0.96640.00

0.50

1.00

0.00 0.50 1.00

RO

C A

UC

npol, I

ntdi

el =

4

ROC AUCnpol, Int diel = 1

y = 1.0063x + 0.003rp² = 0.96090.00

0.50

1.00

0.00 0.50 1.00

RO

C A

UC

npol, I

ntdi

el =

6

ROC AUCnpol, Int diel = 1

y = 0.5065x + 0.4194rp² = 0.38960.00

0.50

1.00

0.00 0.50 1.00 1.50

RO

C A

UC

tot,

Intd

iel =

2

ROC AUCtot, Int diel = 1

y = 0.2023x + 0.6302rp² = 0.0590.00

0.50

1.00

0.00 0.50 1.00 1.50

RO

C A

UC

tot,

Intd

iel =

4

ROC AUCtot, Int diel = 1

y = 0.1001x + 0.6931rp² = 0.0140.00

0.50

1.00

0.00 0.50 1.00 1.50

RO

C A

UC

tot,

Intd

iel =

6

ROC AUCtot, Int diel = 1

A B C

D E F

G H I

Non

-pol

arPo

lar

Tota

l MM

-PBS

A

Figure 2: Examples of theKDE plots of actives andinactives of receptors withinthe test set. 13 out of 19systems showed thedistributions similar to thoseof ACES and HIVPR whenincreasing the internaldielectric values. Only 3 outof 19 were observed withthe trends similar to ESR1.