Literature DB >> 28520421

Examining the Feasibility of Using Free Energy Perturbation (FEP+) in Predicting Protein Stability.

Melissa Coates Ford1, Kerim Babaoglu1.   

Abstract

The importance of engineering protein stability is well-known and has the potential to impact many fields ranging from pharmaceuticals to food sciences. Engineering proteins can be both a time-consuming and expensive experimental process. The use of computation is a potential solution to mitigating some of the time and expenses required to engineer a protein. This process has been previously hindered by inaccurate force fields or energy equations and slow computational processors; however, improved software and hardware have made this goal much more attainable. Here we find that Schrödinger's new FEP+, although still imperfect, proves more successful in predicting protein stability than other simpler methods of investigation. This increased accuracy comes at a cost of computational time and resources when compared to simpler methods. This work adds to the initial testing of FEP+ by offering options for more accurately predicting protein stability in an efficient manner.

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Year:  2017        PMID: 28520421     DOI: 10.1021/acs.jcim.7b00002

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  10 in total

1.  Improving the Accuracy of Protein Thermostability Predictions for Single Point Mutations.

Authors:  Jianxin Duan; Dmitry Lupyan; Lingle Wang
Journal:  Biophys J       Date:  2020-05-29       Impact factor: 4.033

2.  A protein interaction free energy model based on amino acid residue contributions: Assessment of point mutation stability of T4 lysozyme.

Authors:  Lawrence J Williams; Brian J Schendt; Zachary R Fritz; Yonatan Attali; Robert H Lavroff; Martin L Yarmush
Journal:  Technology (Singap World Sci)       Date:  2019-04-26

3.  Water Networks and Correlated Motions in Mutant Isocitrate Dehydrogenase 1 (IDH1) Are Critical for Allosteric Inhibitor Binding and Activity.

Authors:  Jennifer M Chambers; Wade Miller; Giovanni Quichocho; Viraj Upadhye; Diego Avellaneda Matteo; Andrey A Bobkov; Christal D Sohl; Jamie M Schiffer
Journal:  Biochemistry       Date:  2020-01-13       Impact factor: 3.162

4.  Large-scale in vitro functional testing and novel variant scoring via protein modeling provide insights into alkaline phosphatase activity in hypophosphatasia.

Authors:  Guillermo Del Angel; John Reynders; Christopher Negron; Thomas Steinbrecher; Etienne Mornet
Journal:  Hum Mutat       Date:  2020-03-18       Impact factor: 4.878

5.  Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations.

Authors:  Kevin Hauser; Christopher Negron; Steven K Albanese; Soumya Ray; Thomas Steinbrecher; Robert Abel; John D Chodera; Lingle Wang
Journal:  Commun Biol       Date:  2018-06-13

6.  Role of simple descriptors and applicability domain in predicting change in protein thermostability.

Authors:  Kenneth N McGuinness; Weilan Pan; Robert P Sheridan; Grant Murphy; Alejandro Crespo
Journal:  PLoS One       Date:  2018-09-07       Impact factor: 3.240

7.  Relative Binding Affinity Prediction of Charge-Changing Sequence Mutations with FEP in Protein-Protein Interfaces.

Authors:  Anthony J Clark; Christopher Negron; Kevin Hauser; Mengzhen Sun; Lingle Wang; Robert Abel; Richard A Friesner
Journal:  J Mol Biol       Date:  2019-02-16       Impact factor: 5.469

8.  Predicting mutations deleterious to function in beta-lactamase TEM1 using MM-GBSA.

Authors:  Christopher Negron; David A Pearlman; Guillermo Del Angel
Journal:  PLoS One       Date:  2019-03-19       Impact factor: 3.240

9.  Large-scale application of free energy perturbation calculations for antibody design.

Authors:  Fangqiang Zhu; Feliza A Bourguet; William F D Bennett; Edmond Y Lau; Kathryn T Arrildt; Brent W Segelke; Adam T Zemla; Thomas A Desautels; Daniel M Faissol
Journal:  Sci Rep       Date:  2022-07-21       Impact factor: 4.996

10.  The future of biomolecular simulation in the pharmaceutical industry: what we can learn from aerodynamics modelling and weather prediction. Part 1. understanding the physical and computational complexity of in silico drug design.

Authors:  Tom Edwards; Nicolas Foloppe; Sarah Anne Harris; Geoff Wells
Journal:  Acta Crystallogr D Struct Biol       Date:  2021-10-27       Impact factor: 7.652

  10 in total

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