Implicit Solvent Approach Research Articles

From Implicit to Explicit: An Interaction-Reorganization Approach to Molecular Solvation Energy.

Accurate calculation of solvation energies has long fascinated researchers, but complex interactions within bulk water molecules pose significant challenges. Currently, molecular solvation energy calculations are mostly based on implicit solvent approximations in which the solvent molecules are treated as continuum dielectric media. However, the implicit solvent approach is not ideal because it lacks certain real solvation effects, such as that of the first solvation shell, etc. Here, we propose an explicit solvent approach, interaction-reorganization solvation (IRS) method, for molecular solvation energy calculations. The IRS approach achieves predictive accuracy comparable to that of the widely recognized solvation model based on the density (SMD) method and is significantly more accurate than that of the Poisson-Boltzmann/generalized Born surface area (PB/GBSA) methods. This is demonstrated in both the correlation coefficient and the mean absolute error (MAE) with respect to the experimental data. The IRS method is based on molecular dynamics simulation in explicit solvent and does not need to solve Poisson-Boltzmann or Schrödinger equations. On the other hand, the accuracy of the IRS method does depend on the accuracy of the molecular force field used in MD simulations. We expect that the IRS method will be very useful for the solvation energy calculations of molecules.

Comparison of different thermostat settings in the implicit solvent approach for nanoparticles through brush-decorated nanopores.

Nanoparticles (NPs) that are forcefully driven through a brush-decorated nanochannel form a nonequilibrium system with a rich physical behavior, including a dynamical phase transition between two modes of propagation that correspond to either separate clusters of NPs or a continuous flow channel. The peculiar properties of this system make it an ideal benchmark candidate for a comparison of three thermostat settings, the dissipative particle dynamics (DPD), the Langevin (LGV)dynamics, and a modified LGV setup, denoted as LGV^{-}, in which the thermostatting is disabled in the direction of the driving force. We demonstrate that the choice of the thermostat has little influence on the conformations of NPs, and that, due to differences in the dissipation modes, notable differences arise in their dynamical properties, such as effective friction constants and average velocities. This also includes differences in the coupling between NP clusters and the surrounding brush and affects the corresponding phase diagrams of the two propagation modes. We conclude that the conventional DPD and LGV thermostats yield results that display a reasonable degree of coincidence, but we cannot recommend the use of the LGV^{-} algorithm for the present system.

Unraveling the effect of molecular medium on the fluorosolvatochromism of the biphenyl- salicylate derivative drug Diflunisal: Experimental and computational study

Understanding the photochemical behavior of a photosensitive drug through its molecular properties is crucial for assessing potential phototoxicity. In this study, we examine how the molecular microenvironment influences the physicochemical and photochemical properties of Diflunisal (DIF), an organofluorine salicylate derivative drug. To elucidate the photophysical properties of DIF, we employed absorption and fluorescence spectroscopy techniques combined with various DFT-based computational methods. The solvatochromic and fluorescence behaviors of DIF were investigated employing various neat solvents of various polarity and hydrogen bonding (HB) capabilities. The molecular behavior of DIF exhibited mixed fluorosolvatochromism, where a negative fluorosolvatochromism is noted as solvent polarity increases, where DIF exhibited positive fluorosolvatochromism within the examined set of protic polar solvents. These fluorosolvatochromic behaviors suggest that a combination of factors, including solvent polarity, hydrogen bonding capacity, and specific solvation effects, influences the fluorosolvatochromic properties of DIF. To elucidate the impact of specific and non-specific interactions between DIF and solvent on the fluorosolvatochromism of DIF, we utilized Catalán’s four empirical scales model. The results revealed that the solvent’s acidity, basicity, and polarizability had approximately equivalent and notable impacts on the fluorosolvatochromic behavior of DIF. For a molecular-level explanation of the experimental spectral properties, we employed DFT and TD-DFT/B3LYP/6–31 + G(d) computational methods, incorporating the IEFPCM implicit solvation approach. It is also revealed that the negative fluorosolvatochromism of DIF is attributed to the solvent’s impact on the main electronic transition, namely HOMO → LUMO. It is revealed as well that not only the salicylate moiety is affected by the solvent, but also the biphenyl moiety can exhibit a major contribution to the observed behavior. The results presented here offer insights into the photochemical behavior of DIF within various microenvironments at the molecular level. This understanding could inform future endeavors aimed at mitigating induced toxicity and side effects of DIF.

Combined experimental and computational investigations of the fluorosolvatochromism of chromeno[4,3-b]pyridine derivatives: Effect of the methoxy substitution

Extensive research has been conducted on the spectral properties of chromeno[4,3-b]pyridine derivatives, owing to their potential applications in sensing, optoelectronic devices, and drug discovery. This study presents a comprehensive investigation into the fluorosolvatochromism of selected chromeno[4,3-b]pyridine derivatives, with a particular emphasis on the impact of methoxy substitution. Three derivatives were synthesized and subjected to spectral analysis: chromeno[4,3-b]pyridine-3-carboxylate (I) as the parent compound, and its 7-methoxy (II) and 8-methoxy (III) substituted derivatives.The UV–Vis absorption spectra of all derivatives exhibited a broad band with a maximum absorption wavelength that remained unaffected by the surrounding medium. However, distinct fluorescence properties were observed among them. Specifically, derivative II displayed notable fluorescence, while derivatives I and III exhibited no fluorescence properties. Furthermore, derivative II exhibited a fluorescence spectrum that is significantly influenced by the polarity of the medium. To investigate the fluorosolvatochromic behavior in depth, we conducted a comprehensive analysis using various neat solvents with different polarities and hydrogen bonding capabilities. The results obtained revealed a significant positive fluorosolvatochromism, with a bathochromic shift in the fluorescence spectrum as the solvent polarity increased. To understand how specific and non-specific interactions between the solute and the solvent affected the fluorosolvatochromism of II, we employed the four empirical scales model of Catalán. The obtained results demonstrated that intramolecular charge transfer played a crucial role in the fluorescence behavior of II. To provide a molecular-level explanation for the experimental spectral properties, we utilized the DFT and TD-DFT/B3LYP/6-31 + G(d) computational methods with the IEFPCM implicit solvation approach. The spectral differences between II and III were rationalized in terms of the frontier molecular orbitals (FMOs: the HOMO and LUMO), where distinct natures were observed among the examined derivatives. This study offers valuable insights into the impact of methoxy substitution on the physical and chemical properties of chromeno[4,3-b]pyridine derivatives, specifically concerning their spectral properties as elucidated by their fluorosolvatochromic behavior.

Implicit solvent approach based on generalized Born and transferable graph neural networks for molecular dynamics simulations.

Molecular dynamics simulations enable the study of the motion of small and large (bio)molecules and the estimation of their conformational ensembles. The description of the environment (solvent) has, therefore, a large impact. Implicit solvent representations are efficient but, in many cases, not accurate enough (especially for polar solvents, such as water). More accurate but also computationally more expensive is the explicit treatment of the solvent molecules. Recently, machine learning has been proposed to bridge the gap and simulate, in an implicit manner, explicit solvation effects. However, the current approaches rely on prior knowledge of the entire conformational space, limiting their application in practice. Here, we introduce a graph neural network based implicit solvent that is capable of describing explicit solvent effects for peptides with different compositions than those contained in the training set.

Effect of Cosolutes on the Aggregation of a Tau Fragment: A Combined Experimental and Simulation Approach.

The intrinsically disordered protein Tau represents the main component of neurofibrillary tangles that are a hallmark of Alzheimer's disease. A small fragment of Tau, known as paired helical filament 6 (PHF6), is considered to be important for the formation of the β-structure core of the fibrils. Here we study the aggregation of this fragment in the presence of different cosolutes, including urea, TMAO, sucrose and 2-hydroxypropyl-β-cyclodextrin (2-HPβCD), using both experiments and molecular dynamics simulations. A novel implicit solvation approach (MIST - Model with Implicit Solvation Thermodynamics) is used, where an energetic contribution based on the concept of transfer free energies describes the effect of the cosolutes. The simulation predictions are compared to thioflavin-T and atomic force microscopy results, and the good agreement observed confirms the predictive ability of the computational approach herein proposed. Both simulations and experiments indicate that PHF6 aggregation is inhibited in the presence of urea and 2-HPβCD, while TMAO and sucrose stabilize associated conformations. The remarkable ability of HPβCD to inhibit aggregation represents an extremely promising result for future applications, especially considering the widespread use of this molecule as a drug carrier to the brain and as a solubilizer/excipient in pharmaceutical formulations.

Comparison of Implicit and Explicit Solvent Approaches in Ab Initio Evaluation of Thermochemistry in Solution: Application in Studying Boron Isotope Fractionation in Water

Evaluation of thermochemistry in solution plays a key role in numerous fields. For this task, the solvent effects are commonly included in theoretical computations based on either implicit or explicit solvent approaches. In the present study, we evaluate and compare the performance of some of the most widely applied methods based on these two approaches. For studying the solvent effect on thermochemistry with an explicit solvent, we demonstrate that partial normal mode analysis with frozen geometry of solvent molecules for multiple solute-solvent configurations can yield quite accurate and reliable results for a drastically reduced computational cost. As a case study, we consider the evaluation of the equilibrium constant for the boron isotope exchange between boric acid and borate (k3-4) in pure and saline water which is of high geochemical importance. Employing three different rigorous and high-precision theoretical approaches, we provide a reliable estimation of k3-4 which is a value within 1.028 to 1.030 for both pure and saline water which is in excellent agreement with experimental data.

Electronic structures of zwitterionic and protonated forms of glycine betaine in water: Insights into solvent effects from ab initio simulations

Glycine betaine (GB), a naturally occurring osmolyte, has many biological functions and is used in food supplements, pharmaceuticals, and animal feed. GB usually exists as a zwitterion in aqueous solutions. Due to the hygroscopic property of GB, protonated form of GB, GBH+ (noted as GBH) is often used. In order to understand the hydration structures of GB and GBH at the atomic and electronic-structure level, a combination of ab initio molecular dynamics simulations and electronic structure calculations based on density functional theory (DFT), single-excitation configuration interaction method, and coupled-cluster ansatz was utilized. A hybrid explicit–implicit solvation model was used to elucidate solvent effects. Within the hybrid scheme, microsolvated structures of GB and GBH with up to 100 water molecules were obtained, showing that water molecules bind to GB and GBH in a dramatically different manner. By calculating the molecular electron-density distributions at PBE0-D4/def2-TZVP level, it shows that the variation of electron density for GB is more significant than GBH, suggesting that GB can interact with more water molecules than GBH. The interaction energies of GB–(H2O)n and GBH–(H2O)n systems (n = 1–6) at DLPNO-CCSD(T)/cc-pVQZ level highlight the difference from an energy point of view. Using the microsolvated structures of GB and GBH, the features of experimental K-edge spectra can be reproduced using the efficient PNO-ROCIS/B3LYP method, implying the reliability of the hybrid explicit–implicit solvation approach. The results suggest that complementary insights into the geometries and electronic structures of GB and GBH could be obtained through combined methods, which provides a methodological approach for understanding the hydration structures of zwitterionic and charged molecules.

Bridging the Experiment-Calculation Divide: Machine Learning Corrections to Redox Potential Calculations in Implicit and Explicit Solvent Models.

Prediction of redox potentials is essential for catalysis and energy storage. Although density functional theory (DFT) calculations have enabled rapid redox potential predictions for numerous compounds, prominent errors persist compared to experimental measurements. In this work, we develop machine learning (ML) models to reduce the errors of redox potential calculations in both implicit and explicit solvent models. Training and testing of the ML correction models are based on the diverse ROP313 data set with experimental redox potentials measured for organic and organometallic compounds in a variety of solvents. For the implicit solvent approach, our ML models can reduce both the systematic bias and the number of outliers. ML corrected redox potentials also demonstrate less sensitivity to DFT functional choice. For the explicit solvent approach, we significantly reduce the computational costs by embedding the microsolvated cluster in implicit bulk solvent, obtaining converged redox potential results with a smaller solvation shell. This combined implicit-explicit solvent model, together with GPU-accelerated quantum chemistry methods, enabled rapid generation of a large data set of explicit-solvent-calculated redox potentials for 165 organic compounds, allowing detailed investigation of the error sources in explicit solvent redox potential calculations.

Accurate Description of Protein-Protein Recognition and Protein Aggregation with the Implicit-Solvent-Based PACSAB Protein Model.

We used the PACSAB protein model, based on the implicit solvation approach, to simulate protein–protein recognition and study the effect of helical structure on the association of aggregating peptides. After optimization, the PACSAB force field was able to reproduce correctly both the correct binding interface in ubiquitin dimerization and the conformational ensemble of the disordered protein activator for hormone and retinoid receptor (ACTR). The PACSAB model allowed us to predict the native binding of ACTR with its binding partner, reproducing the refolding upon binding mechanism of the disordered protein.

Optimization of covalent docking for organophosphates interaction with Anopheles acetylcholinesterase

Organophosphates (OPs) used as potent insecticides for malaria vector control, covalently phosphorylate the catalytic serine residue of Anopheles gambiae AChE (AgAChE) in a reaction that liberates their leaving groups. In the recent 10-year insecticide use assessment, OPs were the most frequently used World Health Organization prequalified insecticides. Molecular modelling programs are best suited to display molecular interactions between ligands and the target proteins. The docking modes that generate ligand poses closer to the binding site show high accuracy in predicting the ligand binding mode. The implicit solvation approach such as molecular mechanics-generalized born surface area (MM-GBSA) is a more reliable method to predict ligand onformations and binding affinities. Apart from covalent docking studies being scarce, current molecular docking programs do not adequately possess the covalent docking reaction algorithm to display the molecular mechanism of OPs at the AgAChE catalytic site. This results into OP docking studies commonly being conducted through noncovalent pannels. The aim of this study was to establish the optimim covalent docking system for OPs through manual customization of Schrödinger's Glide covalent docking reaction algorithm. To achieve this, a newly customized covalent reaction algorithm was assessed on a set of ligands covering aromatic, non-aromatic and hydrophobic OPs and compared to the noncovalent docking results in terms of reliability based on the reported X-ray diffraction molecular interactions and crystal poses. The study established that by virtue of omitting the well-known OP hydrolysis, noncovalent mode suggested molecular interactions that were further from the catalytic triad and could not otherwise occur when the molecule is hydrolyzed as in the customized covalent docking mode. Moreover, the MM-GBSA concurred with the optimized covalent docking in eliminating such inaccurate molecular interactions. Additionally, the covalent docking mode confined the interactions and ligand poses to the catalytic site indicating relatively high accuracy and reliability. This study reports the optimized covalent docking panel that effectively confirmed the molecular mechanisms of OPs, as well as indentifying the corresponding amino acid residues required to stabilize the aromatic, non-aromatic and hydrophobic OPs at the AgAChE catalytic site in line with the reported X-ray diffraction studies. As such, the proposed manual customization of the Schrödinger's Glide covalent docking platform can be used to reliably predict molecular interactions between OPs and AgAChE target.

GridSolvate: A Web Server for the Prediction of Biomolecular Hydration Properties.

We present a novel web server, named gridSolvate, dedicated to the prediction of biomolecular hydration properties. Given a solute in atomic representation, such as a protein or protein–ligand complex, the server determines positions and excess chemical potential of buried and first hydration shell water molecules. Calculations are based on our semiexplicit hydration model that provides computational efficiency close to implicit solvent approaches, yet captures a number of physical effects unique to explicit solvent representation. The model was introduced and validated before in the context of bulk hydration of drug-like solutes and determination of protein hydration sites. Current methodological developments merge those two avenues into a single, easily accessible tool. Here, we focus on the server’s ability to predict water distribution and affinity within protein–ligand interfaces. We demonstrate that with possibly minimal user intervention the server correctly predicts the locations of 77% of interface water molecules in an external set of test structures. The server is freely available at https://gsolvate.biomod.cent.uw.edu.pl.

Optimization of Molecular Dynamics Simulations of c-MYC1-88-An Intrinsically Disordered System.

Many of the proteins involved in key cellular regulatory events contain extensive intrinsically disordered regions that are not readily amenable to conventional structure/function dissection. The oncoprotein c-MYC plays a key role in controlling cell proliferation and apoptosis and more than 70% of the primary sequence is disordered. Computational approaches that shed light on the range of secondary and tertiary structural conformations therefore provide the only realistic chance to study such proteins. Here, we describe the results of several tests of force fields and water models employed in molecular dynamics simulations for the N-terminal 88 amino acids of c-MYC. Comparisons of the simulation data with experimental secondary structure assignments obtained by NMR establish a particular implicit solvation approach as highly congruent. The results provide insights into the structural dynamics of c-MYC1-88, which will be useful for guiding future experimental approaches. The protocols for trajectory analysis described here will be applicable for the analysis of a variety of computational simulations of intrinsically disordered proteins.

Experimental and DFT/TD-DFT computational investigations of the solvent effect on the spectral properties of nitro substituted pyridino[3,4-c]coumarins

The UV/Vis absorption characteristics of newly synthesized pyridino[3,4-c] coumarins in different neat solvents were investigated experimentally and computationally. It is noted that the nitro-substituted pyridocoumarins can exhibit spectral features with characteristic band in the visible region, which in turn is solvent's polarity dependent with negative solvatochromic behavior. Using the Kamet-Taft approach, the obtained results (R = 0.991) revealed that this negative solvatochromic behavior is dominantly influenced by the solvents' polarizability and hydrogen bonding capability. The experimental results of the spectral properties in solution were interpreted at the molecular level with aid of the DFT and TD-DFT/CAM-B3LYP/6-31+G(d) computational methods with IEFPCM implicit solvation approach. Per benchmarking the TD-DFT simulated spectra with the experimental one, it is demonstrated that the nitro group can induce an intramolecular charge transfer to afford two resonance structures of distinctive spectral features. Such difference in spectral features is interpreted in terms of molecular orbitals, where the two potential resonance structures exhibit different natures for the frontier molecular orbitals, namely the HOMO and LUMO with a significant difference in the corresponding energy gaps. Moreover, the electrostatic potential surfaces of both structures indicate relatively different accessibility toward intermolecular hydrogen bonding with the solvent molecules. The achieved results would provide valuable insights concerning the noteworthy influence of the substituents of pyridocoumarins on their spectral properties and correspondingly their solvatochromic behaviors at the molecular level in different media.

Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study.

Implicit solvent models are a computationally efficient method of representing solid/liquid interfaces prevalent in electrocatalysis, energy storage, and materials science. However, electronic structure changes induced at the metallic surface by the dielectric continuum are not fully understood. To address this, we perform DFT calculations for the Pt(111)/water interface, in order to compare Poisson-Boltzmann continuum solvation methods with ab initio molecular dynamics (AIMD) simulations of explicit solvent. We show that the implicit solvent cavity can be parametrized in terms of the electric dipole moment change at the equilibrated explicit Pt/water interface to obtain the potential of zero charge (PZC). We also compare the accuracy of aqueous enthalpies of adsorption of phenol on Pt(111) using geometry and charge density based dielectric cavitation methods. The ability to parametrize the cavity according to individual atoms, as afforded in the geometry based approach, is key to obtaining accurate enthalpy changes of adsorption under aqueous conditions. We also show that the electronic structure changes induced by explicit solvent and our proposed implicit solvent parametrization scheme yield comparable density difference profiles and d-band projected density of states. We therefore demonstrate the capability of implicit solvent approaches to capture both the energetics of adsorption processes and the main electronic effects of aqueous solvent on the metallic surface. This work therefore provides a scheme for computationally efficient simulations of interfacial processes for applications in areas such as heterogeneous catalysis and electrochemistry.

Oenin/Syringic Acid Copigmentation: Insights From a Theoretical Study.

On the basis of the dispersion-corrected density functional theory, a computational model is proposed to describe the oenin/syringic acid copigmentation and to explore the non-covalent interaction between the anthocyanin and the copigment in the framework of implicit solvent approach. The predicted binding free energy and visible spectrum shift of this copigmentation complex are in accordance with the experimental observations. The used model provides a good structural description of oenin/syringic acid complex and suggests that the intermolecular hydrogen bonding, in which the hydroxyl-rich sugar moiety in oenin plays a key role, may be the determinant for the formation and nature of the copigmentation complex.

Implicit solvent effects in the determination of Brønsted-Evans-Polanyi relationships for heterogeneously catalyzed reactions.

Heterogeneously catalyzed reactions take place at the catalyst surface where, depending on the conditions and process, the reacting molecules are either in the gas or liquid phase. In the latter case, computational heterogeneous catalysis studies usually neglect solvent effects. In this work, we systematically analyze how the electrostatic contribution to solvent effects influences the atomic structure of the reactants and products as well as the adsorption, activation, and reaction energy for the dissociation of water on several planar and stepped transition metal surfaces. The solvent effects were accounted for through an implicit model that describes the effect of electrostatics, cavitation, and dispersion on the interaction between the solute and solvent. The present study shows that the activation energy barriers are only slightly influenced by the inclusion of the electrostatic solvent effects accounted for in a continuum solvent approach, whereas the adsorption energies of the reactants or products are significantly affected. Encouragingly, the linear equations corresponding to the Brønsted-Evans-Polanyi relationships (BEPs), relating the activation energies for the dissociation reaction with a suitable descriptor, e.g. the adsorption energies of the products of the reaction on the difference surfaces, are similar in the presence or in the absence of the solvent. Despite the associated uncertainties, this suggests that BEP relationships derived without the implicit consideration of the solvent are still valid for predicting the activation energy barriers of catalytic reactions from a reaction descriptor.

Soft-Sphere Continuum Solvation in Electronic-Structure Calculations

We present an implicit solvation approach where the interface between the quantum-mechanical solute and the surrounding environment is described by a fully continuous permittivity built up with atomic-centered "soft" spheres. This approach combines many of the advantages of the self-consistent continuum solvation model in handling solutes and surfaces in contact with complex dielectric environments or electrolytes in electronic-structure calculations. In addition it is able to describe accurately both neutral and charged systems. The continuous function, describing the variation of the permittivity, allows to compute analytically the nonelectrostatic contributions to the solvation free energy that are described in terms of the quantum surface. The whole methodology is computationally stable, provides consistent energies and forces, and keeps the computational efforts and runtimes comparable to those of standard vacuum calculations. The capabilitiy to treat arbitrary molecular or slab-like geometries as well as charged molecules is key to tackle electrolytes within mixed explicit/implicit frameworks. We show that, with given, fixed atomic radii, two parameters are sufficient to give a mean absolute error of only 1.12 kcal/mol with respect to the experimental aqueous solvation energies for a set of 274 neutral solutes. For charged systems, the same set of parameters provides solvation energies for a set of 60 anions and 52 cations with an error of 2.96 and 2.13 kcal/mol, respectively, improving upon previous literature values. To tackle elements not present in most solvation databases, a new benchmark scheme on wettability and contact angles is proposed for solid-liquid interfaces and applied to the investigation of the stable terminations of a CdS (112̅0) surface in an electrochemical medium.

Explicit Solvent Hydration Benchmark for Proteins with Application to the PBSA Method.

Explicit and implicit solvent models have a proven record of delivering hydration free energies of small, druglike solutes in reasonable agreement with experiment. Hydration of macromolecules, such as proteins, is to a large extent uncharted territory, with few results shedding light on quantitative consistency between different solvent models, let alone their ability to reproduce real water. In this work, based on extensive explicit solvent simulations employing TIP3P and SPC/E water models we analyze hydration free energy changes between fixed conformations of 5 diverse proteins, including large multidomain structures. For the two solvent models we find better agreement in electrostatic rather than nonpolar contributions (RMSE of 2.3 and 2.7 kcal/mol, respectively), even though absolute values of the latter are typically an order of magnitude smaller. We also highlight the importance of finite size corrections to relative protein hydration free energies, which turn out to be rather large, on the order of several kcal/mol, and are necessary for proper interpretation of results obtained under periodic boundary conditions. We further compare gathered data with predictions of the implicit solvent approach based on the Poisson equation and the surface or volume based nonpolar term. We find definitely lesser consistency than between the two explicit models (RMSE between implicit and TIP3 results of 11.3 and 8.4 kcal/mol for electrostatic and nonpolar contributions, respectively). In the process we determine the value of the protein dielectric constant and the geometric model for the dielectric boundary that provide for the best agreement. Finally, we evaluate the usefulness of surface and volume based models of nonpolar contributions to hydration free energy of large biomolecules.

Implementation of INDO/SCI with COSMO Implicit Solvation and Benchmarking for Solvatochromic Shifts.

Accurate and rapid quantum mechanical prediction of solvatochromic shifts, particularly in systems where charge transfer plays a significant role, is important for many aspects of molecular and material design. Although the semiempirical INDO/SCI approach is computationally efficient and performs well for charge-transfer states, the availability of implicit solvent approaches has been limited. Here, we implement the COSMO solvent model with a perturbative state-specific correction to the excited-state energies with the INDO/SCI method. We show that for a series of prototypical π-conjugated molecules, our newly implemented INDO/SCI/COSMO model yields more accurate absorption energies and comparably accurate solvatochromic shifts to those computed using TD-ωB97XD and CIS with COSMO solvation at a substantially lower computational cost.