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Development and Test of PBSA Solvation Models for Drug Design

Niu, Taoyu (2024) Development and Test of PBSA Solvation Models for Drug Design. Master's Thesis, University of Pittsburgh. (Unpublished)

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The Poisson-Boltzmann Surface Area (PBSA) model was extensively used to predict solvation free energy (SFE) and protein-ligand binding free energies, as well as to study protein folding. In addition, partition coefficient (logP), which is an important physicochemical property that determines the distribution of a drug in vivo, can be derived directly from transfer free energies. Within the Statistical Assessment of the Modeling of Proteins and Ligands (SAMPL) 9 challenge, we applied the Poisson-Boltzmann (PB) surface area (SA) approach to predict toluene/water transfer free energy and partition coefficient (logPtol/wat) from SFEs. PB calculation directly adopts our previously optimized boundary definition - a set of general AMBER force field 2 (GAFF2) atom-type based sphere radii for solute atoms. For the non-polar SA model, we newly developed the solvent-related molecular surface tension parameters \gamma and offset b for toluene and cyclohexane targeting experimental SFEs. This approach yielded the highest predictive accuracy in terms of root mean squared error (RMSE) of 1.52 kcal/mol in transfer free energy for 16 small drug molecules among all 18 submissions in SAMPL9 challenge. The re-evaluation of the challenge set using multi-conformation strategies based on molecular dynamic (MD) simulations further reduces the prediction RMSE to 1.33 kcal/mol. At the same time, an additional evaluation of our PBSA method on SAMPL5 cyclohexane/water distribution coefficient (logDcyc/wat) prediction revealed that our model outperformed COSMO-RS, the best submission model with RMSEPBSA = 1.88 versus RMSECOSMO-RS = 2.11 log units. Two external logPtol/wat and logPcyc/wat datasets that contain 110 and 87 data points, respectively, are collected for extra validation and provide in-depth insight of the error source of PBSA method. Finally, to identify the best set of radius parameters which define the solute-solvent boundary, we adopted the following strategies: (1) the nonpolar term is fixed; (2) a genetic algorithm is applied to conquer the couplings between the radius parameters; (3) the new nonpolar term is reoptimized. The above three steps will be repeated until there is no further improvement on the model performance. Encouragingly, the newly tuned radii parameters conjugated with the ABCG2 charge model outperformed many widely used models and our previous results.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Niu, Taoyutan77@pitt.edutan770009-0004-2214-1397
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairGibbs, Robertgibbsr@pitt.edugibbsr
Committee MemberKoes, Daviddkoes@pitt.edudkoes
Thesis AdvisorWang, Junmeijuw79@pitt.edujuw79
Date: 2 May 2024
Date Type: Publication
Defense Date: 10 April 2024
Approval Date: 2 May 2024
Submission Date: 19 April 2024
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 72
Institution: University of Pittsburgh
Schools and Programs: School of Pharmacy > Pharmaceutical Sciences
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: SAMPL; logP; Transfer Free Energy; MM-PBSA; GAFF2; ABCG2
Date Deposited: 02 May 2024 16:17
Last Modified: 02 May 2024 16:17


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