Literature DB >> 30276503

An explicit-solvent hybrid QM and MM approach for predicting pKa of small molecules in SAMPL6 challenge.

Samarjeet Prasad1,2, Jing Huang3, Qiao Zeng4, Bernard R Brooks4.   

Abstract

In this work we have developed a hybrid QM and MM approach to predict pKa of small drug-like molecules in explicit solvent. The gas phase free energy of deprotonation is calculated using the M06-2X density functional theory level with Pople basis sets. The solvation free energy difference of the acid and its conjugate base is calculated at MD level using thermodynamic integration. We applied this method to the 24 drug-like molecules in the SAMPL6 blind pKa prediction challenge. We achieved an overall RMSE of 2.4 pKa units in our prediction. Our results show that further optimization of the protocol needs to be done before this method can be used as an alternative approach to the well established approaches of a full quantum level or empirical pKa prediction methods.

Entities:  

Keywords:  Explicit solvent; Hybrid QM and MM; SAMPL6; pKa prediction

Mesh:

Substances:

Year:  2018        PMID: 30276503      PMCID: PMC6342563          DOI: 10.1007/s10822-018-0167-1

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  45 in total

1.  Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation.

Authors:  Araz Jakalian; David B Jack; Christopher I Bayly
Journal:  J Comput Chem       Date:  2002-12       Impact factor: 3.376

2.  A blind challenge for computational solvation free energies: introduction and overview.

Authors:  J Peter Guthrie
Journal:  J Phys Chem B       Date:  2009-04-09       Impact factor: 2.991

3.  pKa measurements for the SAMPL6 prediction challenge for a set of kinase inhibitor-like fragments.

Authors:  Mehtap Işık; Dorothy Levorse; Ariën S Rustenburg; Ikenna E Ndukwe; Heather Wang; Xiao Wang; Mikhail Reibarkh; Gary E Martin; Alexey A Makarov; David L Mobley; Timothy Rhodes; John D Chodera
Journal:  J Comput Aided Mol Des       Date:  2018-11-07       Impact factor: 3.686

4.  Toward the accurate calculation of pKa values in water and acetonitrile.

Authors:  James T Muckerman; Jonathan H Skone; Ming Ning; Yuko Wasada-Tsutsui
Journal:  Biochim Biophys Acta       Date:  2013-04-06

5.  Constant pH molecular dynamics with proton tautomerism.

Authors:  Jana Khandogin; Charles L Brooks
Journal:  Biophys J       Date:  2005-04-29       Impact factor: 4.033

6.  Accurate Calculation of Hydration Free Energies using Pair-Specific Lennard-Jones Parameters in the CHARMM Drude Polarizable Force Field.

Authors:  Christopher M Baker; Pedro E M Lopes; Xiao Zhu; Benoît Roux; Alexander D Mackerell
Journal:  J Chem Theory Comput       Date:  2010-03-01       Impact factor: 6.006

Review 7.  Overview of the SAMPL5 host-guest challenge: Are we doing better?

Authors:  Jian Yin; Niel M Henriksen; David R Slochower; Michael R Shirts; Michael W Chiu; David L Mobley; Michael K Gilson
Journal:  J Comput Aided Mol Des       Date:  2016-09-22       Impact factor: 3.686

8.  Correcting for the free energy costs of bond or angle constraints in molecular dynamics simulations.

Authors:  Gerhard König; Bernard R Brooks
Journal:  Biochim Biophys Acta       Date:  2014-09-16

Review 9.  The SAMPL4 host-guest blind prediction challenge: an overview.

Authors:  Hari S Muddana; Andrew T Fenley; David L Mobley; Michael K Gilson
Journal:  J Comput Aided Mol Des       Date:  2014-03-06       Impact factor: 3.686

10.  AUTOMATED FORCE FIELD PARAMETERIZATION FOR NON-POLARIZABLE AND POLARIZABLE ATOMIC MODELS BASED ON AB INITIO TARGET DATA.

Authors:  Lei Huang; Benoît Roux
Journal:  J Chem Theory Comput       Date:  2013-08-13       Impact factor: 6.006

View more
  7 in total

1.  Standard state free energies, not pKas, are ideal for describing small molecule protonation and tautomeric states.

Authors:  M R Gunner; Taichi Murakami; Ariën S Rustenburg; Mehtap Işık; John D Chodera
Journal:  J Comput Aided Mol Des       Date:  2020-02-12       Impact factor: 3.686

2.  Improving Small Molecule pK a Prediction Using Transfer Learning With Graph Neural Networks.

Authors:  Fritz Mayr; Marcus Wieder; Oliver Wieder; Thierry Langer
Journal:  Front Chem       Date:  2022-05-26       Impact factor: 5.545

3.  Multi-phase Boltzmann weighting: accounting for local inhomogeneity in molecular simulations of water-octanol partition coefficients in the SAMPL6 challenge.

Authors:  Andreas Krämer; Phillip S Hudson; Michael R Jones; Bernard R Brooks
Journal:  J Comput Aided Mol Des       Date:  2020-02-14       Impact factor: 3.686

4.  SAMPL7 blind challenge: quantum-mechanical prediction of partition coefficients and acid dissociation constants for small drug-like molecules.

Authors:  Basak Koca Fındık; Zeynep Pinar Haslak; Evrim Arslan; Viktorya Aviyente
Journal:  J Comput Aided Mol Des       Date:  2021-06-24       Impact factor: 3.686

5.  A deep learning approach for the blind logP prediction in SAMPL6 challenge.

Authors:  Samarjeet Prasad; Bernard R Brooks
Journal:  J Comput Aided Mol Des       Date:  2020-01-30       Impact factor: 3.686

6.  Overview of the SAMPL6 pKa challenge: evaluating small molecule microscopic and macroscopic pKa predictions.

Authors:  Mehtap Işık; Ariën S Rustenburg; Andrea Rizzi; M R Gunner; David L Mobley; John D Chodera
Journal:  J Comput Aided Mol Des       Date:  2021-01-04       Impact factor: 3.686

7.  Evaluation of log P, pKa, and log D predictions from the SAMPL7 blind challenge.

Authors:  Teresa Danielle Bergazin; Nicolas Tielker; Yingying Zhang; Junjun Mao; M R Gunner; Karol Francisco; Carlo Ballatore; Stefan M Kast; David L Mobley
Journal:  J Comput Aided Mol Des       Date:  2021-06-24       Impact factor: 3.686

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.