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Gheta SKO, Bonin A, Gerlach T, Göller AH. Predicting absolute aqueous solubility by applying a machine learning model for an artificially liquid-state as proxy for the solid-state. J Comput Aided Mol Des 2023; 37:765-789. [PMID: 37878216 DOI: 10.1007/s10822-023-00538-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 10/02/2023] [Indexed: 10/26/2023]
Abstract
In this study, we use machine learning algorithms with QM-derived COSMO-RS descriptors, along with Morgan fingerprints, to predict the absolute solubility of drug-like compounds. The QM-derived descriptors account for the molecular properties of the solute, i.e., the solute-solute interactions in an artificial-liquid-state (super-cooled liquid), and the solute-solvent interactions in solution. We employ two main approaches to predict solubility: (i) a hypothetical pathway that involves melting the solute at room temperature T = T¯ ([Formula: see text]) and mixing the artificially liquid solute into the solvent ([Formula: see text]). In this approach [Formula: see text] is predicted using machine learning models, and the [Formula: see text] is obtained from COSMO-RS calculations; (ii) direct solubility prediction using machine learning algorithms. The models were trained on a large number of Bayer in-house compounds for which water solubility data is available at physiological pH of 6.5 and ambient temperature. We also evaluated our models using external datasets from a solubility challenge. Our models present great improvements compared to the absolute solubility prediction with the QSAR model for the artificial liquid state as implemented in the COSMOtherm software, for both in-house and external datasets. We are furthermore able to demonstrate the superiority of QM-derived descriptors compared to cheminformatics descriptors. We finally present low-cost alternative models using fragment-based COSMOquick calculations with only marginal reduction in the quality of predicted solubility.
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Affiliation(s)
- Sadra Kashef Ol Gheta
- Bayer AG, Pharmaceuticals, R&D, Computational Molecular Design, 42096, Wuppertal, Germany
| | - Anne Bonin
- Bayer AG, Pharmaceuticals, R&D, Computational Molecular Design, 42096, Wuppertal, Germany
| | - Thomas Gerlach
- Bayer AG, Crop Science, R&D, Digital Transformation, 40789, Monheim, Germany
- Bayer AG, Engineering & Technology, Thermal Separation Technologies, 51368, Leverkusen, Germany
| | - Andreas H Göller
- Bayer AG, Pharmaceuticals, R&D, Computational Molecular Design, 42096, Wuppertal, Germany.
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2
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Minetti CA, Remeta DP. Forces Driving a Magic Bullet to Its Target: Revisiting the Role of Thermodynamics in Drug Design, Development, and Optimization. Life (Basel) 2022; 12:1438. [PMID: 36143474 PMCID: PMC9504344 DOI: 10.3390/life12091438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/02/2022] [Accepted: 09/03/2022] [Indexed: 11/27/2022] Open
Abstract
Drug discovery strategies have advanced significantly towards prioritizing target selectivity to achieve the longstanding goal of identifying "magic bullets" amongst thousands of chemical molecules screened for therapeutic efficacy. A myriad of emerging and existing health threats, including the SARS-CoV-2 pandemic, alarming increase in bacterial resistance, and potentially fatal chronic ailments, such as cancer, cardiovascular disease, and neurodegeneration, have incentivized the discovery of novel therapeutics in treatment regimens. The design, development, and optimization of lead compounds represent an arduous and time-consuming process that necessitates the assessment of specific criteria and metrics derived via multidisciplinary approaches incorporating functional, structural, and energetic properties. The present review focuses on specific methodologies and technologies aimed at advancing drug development with particular emphasis on the role of thermodynamics in elucidating the underlying forces governing ligand-target interaction selectivity and specificity. In the pursuit of novel therapeutics, isothermal titration calorimetry (ITC) has been utilized extensively over the past two decades to bolster drug discovery efforts, yielding information-rich thermodynamic binding signatures. A wealth of studies recognizes the need for mining thermodynamic databases to critically examine and evaluate prospective drug candidates on the basis of available metrics. The ultimate power and utility of thermodynamics within drug discovery strategies reside in the characterization and comparison of intrinsic binding signatures that facilitate the elucidation of structural-energetic correlations which assist in lead compound identification and optimization to improve overall therapeutic efficacy.
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Affiliation(s)
- Conceição A. Minetti
- Department of Chemistry and Chemical Biology, Rutgers—The State University of New Jersey, Piscataway, NJ 08854, USA
| | - David P. Remeta
- Department of Chemistry and Chemical Biology, Rutgers—The State University of New Jersey, Piscataway, NJ 08854, USA
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Tan T, Cheng H, Chen G, Song Z, Qi Z. Prediction of infinite‐dilution activity coefficients with neural collaborative filtering. AIChE J 2022. [DOI: 10.1002/aic.17789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Tian Tan
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering East China University of Science and Technology Shanghai China
| | - Hongye Cheng
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering East China University of Science and Technology Shanghai China
| | - Guzhong Chen
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering East China University of Science and Technology Shanghai China
| | - Zhen Song
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering East China University of Science and Technology Shanghai China
| | - Zhiwen Qi
- State Key Laboratory of Chemical Engineering, School of Chemical Engineering East China University of Science and Technology Shanghai China
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Kashefolgheta S, Wang S, Acree WE, Hünenberger PH. Evaluation of nine condensed-phase force fields of the GROMOS, CHARMM, OPLS, AMBER, and OpenFF families against experimental cross-solvation free energies. Phys Chem Chem Phys 2021; 23:13055-13074. [PMID: 34105547 PMCID: PMC8207520 DOI: 10.1039/d1cp00215e] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 04/28/2021] [Indexed: 12/02/2022]
Abstract
Experimental solvation free energies are nowadays commonly included as target properties in the validation of condensed-phase force fields, sometimes even in their calibration. In a previous article [Kashefolgheta et al., J. Chem. Theory. Comput., 2020, 16, 7556-7580], we showed how the involved comparison between experimental and simulation results could be made more systematic by considering a full matrix of cross-solvation free energies . For a set of N molecules that are all in the liquid state under ambient conditions, such a matrix encompasses N×N entries for considering each of the N molecules either as solute (A) or as solvent (B). In the quoted study, a cross-solvation matrix of 25 × 25 experimental value was introduced, considering 25 small molecules representative for alkanes, chloroalkanes, ethers, ketones, esters, alcohols, amines, and amides. This experimental data was used to compare the relative accuracies of four popular condensed-phase force fields, namely GROMOS-2016H66, OPLS-AA, AMBER-GAFF, and CHARMM-CGenFF. In the present work, the comparison is extended to five additional force fields, namely GROMOS-54A7, GROMOS-ATB, OPLS-LBCC, AMBER-GAFF2, and OpenFF. Considering these nine force fields, the correlation coefficients between experimental values and simulation results range from 0.76 to 0.88, the root-mean-square errors (RMSEs) from 2.9 to 4.8 kJ mol-1, and average errors (AVEEs) from -1.5 to +1.0 kJ mol-1. In terms of RMSEs, GROMOS-2016H66 and OPLS-AA present the best accuracy (2.9 kJ mol-1), followed by OPLS-LBCC, AMBER-GAFF2, AMBER-GAFF, and OpenFF (3.3 to 3.6 kJ mol-1), and then by GROMOS-54A7, CHARM-CGenFF, and GROMOS-ATB (4.0 to 4.8 kJ mol-1). These differences are statistically significant but not very pronounced, and are distributed rather heterogeneously over the set of compounds within the different force fields.
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Affiliation(s)
- Sadra Kashefolgheta
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 55 03
| | - Shuzhe Wang
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 55 03
| | - William E. Acree
- Department of Chemistry, University of North Texas1155 Union Circle Drive #305070DentonTexas 76203USA
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCICH-8093 ZürichSwitzerland+41 44 632 55 03
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5
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Kalayan J, Henchman RH. Convergence behaviour of solvation shells in simulated liquids. Phys Chem Chem Phys 2021; 23:4892-4900. [PMID: 33616583 DOI: 10.1039/d0cp05903j] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
A convenient way to analyse solvent structure around a solute is to use solvation shells, whereby solvent position around the solute is discretised by the size of a solvent molecule, leading to multiple shells around the solute. The two main ways to define multiple shells around a solute are either directly with respect to the solute, called solute-centric, or locally for both solute and solvent molecules alike. It might be assumed that both methods lead to solvation shells with similar properties. However, our analysis suggests otherwise. Solvation shells are analysed in a series of simulations of five pure liquids of differing polarity. Shells are defined locally working outwards from each molecule treated as a reference molecule using two methods: the cutoff at the first minimum in the radial distribution function and the parameter-free Relative Angular Distance method (RAD). The molecular properties studied are potential energy, coordination number and coordination radius. Rather than converging to bulk values, as might be expected for pure solvents, properties are found to deviate as a function of shell index. This behaviour occurs because molecules with larger coordination numbers and radius have more neighbours, which make them more likely to be connected to the reference molecule via fewer shells. The effect is amplified for RAD because of its more variable coordination radii and for water with its more open structure and stronger interactions. These findings indicate that locally defined shells should not be thought of as directly comparable to solute-centric shells or to distance. As well as showing how box size and cutoff affect the non-convergence, to restore convergence we propose a hybrid method by defining a new set of shells with boundaries at the uppermost distance of each locally derived shell.
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Affiliation(s)
- Jas Kalayan
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. and Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Richard H Henchman
- Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester M1 7DN, UK. and Department of Chemistry, The University of Manchester, Oxford Road, Manchester M13 9PL, UK
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Abreu CRA, Tuckerman ME. Molecular Dynamics with Very Large Time Steps for the Calculation of Solvation Free Energies. J Chem Theory Comput 2020; 16:7314-7327. [PMID: 33197180 DOI: 10.1021/acs.jctc.0c00698] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
In multiple time scale molecular dynamics, the use of isokinetic constraints along with massive thermostatting has enabled the adoption of very large integration steps, well beyond the limits imposed by resonance artifacts in standard algorithms. In this work, we present two new contributions to this topic. First, we investigate the velocity distribution and the temperature-kinetic energy relationship associated with the isokinetic Nosé-Hoover family of methods, showing how they depend on the number of thermostats attached to each atomic degree of freedom. Second, we investigate the performance of these methods in the calculation of solvation free energies, the determination of which is often key for understanding the partition of a chemical species among distinct environments. We show how one can extract this property from canonical (constant-NVT) simulations and compare the result to experimental data obtained at a specific pressure. Finally, we demonstrate that large time steps can, in fact, be used to improve the efficiency of these calculations and that attaching multiple thermostats per degree of freedom is beneficial for effectively exploring the configurational space of a molecular system.
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Affiliation(s)
- Charlles R A Abreu
- Chemical Engineering Department, Escola de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ 21941-909, Brazil
| | - Mark E Tuckerman
- Department of Chemistry, New York University, New York, New York 10003, United States.,Courant Institute of Mathematical Sciences, New York University, New York, New York 10012, United States.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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Kashefolgheta S, Oliveira MP, Rieder SR, Horta BAC, Acree WE, Hünenberger PH. Evaluating Classical Force Fields against Experimental Cross-Solvation Free Energies. J Chem Theory Comput 2020; 16:7556-7580. [DOI: 10.1021/acs.jctc.0c00688] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Affiliation(s)
- Sadra Kashefolgheta
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Marina P. Oliveira
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Salomé R. Rieder
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
| | - Bruno A. C. Horta
- Instituto de Química, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil
| | - William E. Acree
- Department of Chemistry, University of North Texas, 1155 Union Circle Drive #305070, Denton, Texas 76203, United States
| | - Philippe H. Hünenberger
- Laboratorium für Physikalische Chemie, ETH Zürich, ETH-Hönggerberg, HCI, CH-8093 Zürich, Switzerland
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Gebhardt J, Kiesel M, Riniker S, Hansen N. Combining Molecular Dynamics and Machine Learning to Predict Self-Solvation Free Energies and Limiting Activity Coefficients. J Chem Inf Model 2020; 60:5319-5330. [DOI: 10.1021/acs.jcim.0c00479] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Julia Gebhardt
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, D-70569 Stuttgart, Germany
| | - Matthias Kiesel
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, D-70569 Stuttgart, Germany
| | - Sereina Riniker
- Laboratory of Physical Chemistry, ETH Zürich, Vladimir-Prelog-Weg 2, 8093 Zürich, Switzerland
| | - Niels Hansen
- Institute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, D-70569 Stuttgart, Germany
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Abstract
The Solvent Similarity Index (SSI) is a quantitative parameter we introduce for the comparison of the solvation properties of any solvent or solvent mixture. The Surface Site Interaction Model for Liquids at Equilibrium (SSIMPLE) was used to calculate the free energy of solvation of a single Surface Site Interaction Point (SSIP) on a solute. The SSIP representation of molecular surfaces was used to calculate the free energy of solvation for all possible solute polarities, generating a unique solvation profile for any solvent or solvent mixture. Quantitative comparison of the solvation profiles of two solvents was used as the basis for calculating the solvation similarity index. Values of SSI were calculated for all pairwise comparisons of 261 pure solvents at 298 K, and the results were used to classify solvents into groups according to their solvation properties. Applications to understanding the solvation properties of binary solvent mixtures and for identification of alternative solvents are illustrated.
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Affiliation(s)
- Mark D Driver
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
| | - Christopher A Hunter
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK.
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Assessment of the SM12, SM8, and SMD Solvation Models for Predicting Limiting Activity Coefficients at 298.15 K. Processes (Basel) 2020. [DOI: 10.3390/pr8050623] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
The SMx (x = 12, 8, or D) universal solvent models are implicit solvent models which using electronic structure calculations can compute solvation free energies at 298.15 K. While solvation free energy is an important thermophysical property, within the thermodynamic modeling of phase equilibrium, limiting (or infinite dilution) activity coefficients are preferred since they may be used to parameterize excess Gibbs free energy models to model phase equilibrium. Conveniently, the two quantities are related. Therefore the present study was performed to assess the ability to use the SMx universal solvent models to predict limiting activity coefficients. Two methods of calculating the limiting activity coefficient where compared: (1) the solvation free energy and self-solvation free energy were both predicted and (2) the self-solvation free energy was computed using readily available vapor pressure data. Overall the first method is preferred as it results in a cancellation of errors, specifically for the case in which water is a solute. The SM12 model was compared to both the Universal Quasichemical Functional-group Activity Coefficients (UNIFAC) and modified separation of cohesive energy density (MOSCED) models. MOSCED was the highest performer, yet had the smallest available compound inventory. UNIFAC and SM12 exhibited comparable performance. Therefore further exploration and research should be conducted into the viability of using the SMx models for phase equilibrium calculations.
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