Molecular Interpretation Research Articles

A Cross-Sectional Study of Variant Interpretation and Reporting of NGS Data Using Tertiary Analysis Software: Navify® Mutation Profiler.

Personalized medicine has revolutionized the clinical management of patients with solid tumors. However, the large volumes of molecular data derived from next-generation sequencing (NGS) and the lack of harmonized bioinformatics pipelines drastically impact the clinical management of patients with solid tumors. A possible solution to streamline the molecular interpretation and reporting of NGS data would be to adopt automated data analysis software. In this study, we tested the clinical efficiency of the Navify Mutation Profiler (nMP) software in improving the interpretation of NGS data analysis in diagnostic routine samples from patients with solid tumors. This study included one coordinating institution (Federico II University of Naples) and five other Italian institutions. Variant call format (VCF) files from reference standard samples previously tested by the coordinating institution and from n = 8 diagnostic routine samples (n = 2 from colorectal carcinoma; n = 2 from non-small cell lung cancer; n = 2 from advanced melanoma; and n = 2 from patients with gastrointestinal stromal tumors)and previously analyzed by each participating institution (n = 5) with standardized internal analysis workflows were uploaded onto the Navify® Mutation Profiler (nMP) system (Roche Sequencing Solutions, Pleasanton, CA, USA) for automated analysis and interpretation of DNA and RNA molecular alterations analytical parameters, molecular profiling, and clinical interpretation were carried out by the nMP system and compared with the standard workflow data analyzed by the participating institutions. Overall, all VCF files were successfully submitted and interpreted by the nMP system. A concordance agreement rate of 89.6% was observed between the automated and standard workflow systems. In particular, DNA and RNA molecular profiles obtained with the nMP system matched those obtained with standardized approaches in 44 out of 48 patients (91.7%) and in 11 out of 12 (91.7%) cases, respectively. In addition, the nMP system evidenced wild-type variants in 6 out of 7 (85.7%) cases. The nMP system represents a valid, easily manageable, and clinically useful system to interpret NGS data on diagnostic routine samples from patients with solid tumors.

The Perils of Molecular Interpretations from Vibrational Spectra of Complex Samples.

Vibrational spectroscopy is a widely used technique for chemical characterizations across various analytical sciences. Its applications are increasingly extending to the analysis of complex samples such as biofluids, providing high-throughput molecular profiling. While powerful, the technique suffers from an inherent limitation: The overlap of absorption information across different spectral domains hinders the capacity to identify individual molecular substances contributing to measured signals. Despite the awareness of this challenge, the difficulty of analyzing multi-molecular spectra is often underestimated, leading to unsubstantiated molecular interpretations. Here, we examine the prevalent overreliance on spectral band assignment and illuminate the pitfalls of correlating spectral signals to discrete molecular entities or physiological states without rigorous validation. Focusing on blood-based infrared spectroscopy, we provide examples illustrating how peak overlap among different substances, relative substance concentrations, and preprocessing steps can lead to erroneous interpretations. We advocate for a viewpoint shift towards a more careful understanding of complex spectra, which shall lead to either accepting their fingerprinting nature and leveraging machine learning analysis - or involving additional measurement modalities for robust molecular interpretations. Aiming to help translate and improve analytical practices within the field, we highlight the limitations of molecular interpretations and feature their viable applications.

Assignment of a Physical Energy Scale for the Dimensionless Interaction Energies within the PRIME20 Peptide Model.

We present a calibration scheme to determine the conversion factors from a coarse-grained stochastic approximation Monte Carlo approach using the PRIME20 peptide interaction model to atomistic force-field interaction energies at full explicit aqueous solvation. The conversion from coarse-grained to atomistic structures was performed according to our previously established inverse coarse-graining protocol. We provide a physical energy scale for both the backbone hydrogen bonding interactions and the sidechain interactions by correlating the dimensionless energy descriptors of the PRIME20 model with the energies averaged over molecular dynamics simulations. The conversion factor for these interactions turns out to be around 2 kJ/mol for the backbone interactions, and zero for the sidechain interactions. We discuss these surprisingly small values in terms of their molecular interpretation.

A simplified method for theoretical sum frequency generation spectroscopy calculation and interpretation: The "pop model".

Existing methods to compute theoretical spectra are restricted to the use of time-correlation functions evaluated from accurate atomistic molecular dynamics simulations, often at the abinitio level. The molecular interpretation of the computed spectra requires additional steps to deconvolve the spectroscopic contributions from local water and surface structural populations at the interface. The lack of a standard procedure to do this often hampers rationalization. To overcome these challenges, we rewrite the equations for spectra calculation into a sum of partial contributions from interfacial populations, weighted by their abundance at the interface. We show that SFG signatures from each population can be parameterized into a minimum dataset of reference partial spectra. Accurate spectra can then be predicted by just evaluating the statistics of interfacial populations, which can be done even with force field simulations as well as with analytic models. This approach broadens the range of simulation techniques from which theoretical spectra can be calculated, opening toward non-atomistic and Monte Carlo simulation approaches. Most notably, it allows constructing accurate theoretical spectra for interfacial conditions that cannot even be simulated, as we demonstrate for the pH-dependent SFG spectra of silica/water interfaces.

Hidden charm decays of Y(4626) in a Ds*+Ds1(2536)− molecular frame

In this work, we investigate the hidden charm decays properties of Y(4626), where Y(4626) is assigned as a S−wave Ds*+Ds1(2536)− molecular state with JPC=1−−. The partial widths of the processes Y(4626)→J/ψη, J/ψη′, ηcϕ, and χcJϕ,(J={0,1,2}) are estimated by employing the effective Lagrangian approach. The present estimations indicate that the partial widths of the J/ψη and J/ψη′ channels are of the order of 1 MeV, while the one of χc1ϕ is of the order of 0.1 MeV. Thus, we propose to further examine the molecular interpretation of Y(4626) by searching it in the cross sections for the e+e−→J/ψη(′) processes, which should be accessible by the BES III and Belle II. Published by the American Physical Society 2024

Studying the Ξ(2030) as a predominantly K¯*Σ molecular state

Since its discovery in 1977, the spin parity of Ξ(2030) has not been fully determined experimentally. The latest Particle Data Group listing suggests it may be a baryon with J=5/2. Therefore, studying the mass spectrum and decay properties of Ξ(2030) has become a current hot topic to definitively establish its spin parity. As the three-quark model fails to explain Ξ(2030), we previously proposed it may be a molecule primarily composed of K¯*Σ with JP=5/2+, based on its mass spectrum study. To verify its molecular state interpretation, this work proposes studying the strong decays of Ξ(2030) assuming it is a P-wave JP=5/2+ meson-baryon molecule predominantly composed of K¯*Σ. We calculated all experimentally measured two-body and three-body final state decay widths of Ξ(2030), including Ξ(2030)→K¯Λ,K¯Σ,πΞ,πΞ*, and Ξ(2030)→ππΞ,πK¯Σ,πK¯Λ. The results indicate that both the total decay width and partial decay widths agree well with experimental values within the error margins. This supports that Ξ(2030) is a molecule with spin-parity JP=5/2+, predominantly composed of K¯*Σ. Compared to the experimental central values, our results are slightly smaller, which suggests that Ξ(2030) may contain additional components besides meson-baryon molecular components, such as three-quark structures. Published by the American Physical Society 2024

AlphaFold2 Predicts Alternative Conformation Populations in Green Fluorescent Protein Variants.

Artificial intelligence-based protein structure prediction methods such as AlphaFold2 have emerged as powerful tools for characterizing proteins sequence-structure relationship offering unprecedented opportunities for the molecular interpretation of biological and biochemical phenomena. While initially confined to providing a static representation of proteins through their global free-energy minimum, AlphaFold2 has demonstrated the ability to partially sample conformational landscapes, providing insights into protein dynamics, which is fundamental for interpreting and potentially tuning the function of natural and artificial proteins. In this study, we show that targeted column masking of AlphaFold2's multiple sequence alignment enables the characterization and estimation of the population ratio of the two main conformations of engineered green fluorescent proteins with alternative β-strands. The possibility of quickly estimating relative populations through AlphaFold2 predictions is expected to speed-up the computational design of related systems for sensing applications.

QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm

ABSTRACT Ionic liquids (ILs) have attracted considerable interest due to their unique properties and prospective uses in various industries. However, their potential toxicity, particularly regarding enzyme inhibition, has become a growing concern. In this study, a QSAR model was proposed to predict the enzyme inhibition toxicity of ILs. A dataset of diverse ILs with corresponding toxicity data against three enzymes was compiled. Molecular descriptors that capture the physicochemical, structural, and topological properties of the ILs were calculated. To optimize the selection of descriptors and develop a robust QSAR model, the chaotic spotted hyena optimization algorithm, a novel nature-inspired metaheuristic, was employed. The proposed algorithm efficiently searches for an optimal subset of descriptors and model parameters, enhancing the predictive performance and interpretability of the QSAR model. The developed model exhibits excellent predictive capability, with high classification accuracy and low computation time. Sensitivity analysis and molecular interpretation of the selected descriptors provide insights into the critical structural features influencing the toxicity of ILs. This study showcases the successful application of the chaotic spotted hyena optimization algorithm in QSAR modelling and contributes to a better understanding of the toxicity mechanisms of ILs, aiding in the design of safer alternatives for industrial applications.

How Fe-La-CS microspheres have selective adsorption capacity for As(V) over a wide pH range: Coupling molecular scale interpretation with experiments

In this study, an Fe-La-CS adsorbent with a reticulated structure was prepared by an in situ method, which was able to adsorb arsenate efficiently over a wide pH range of 3–11. The incorporation of iron and lanthanum ions broadened the tolerant pH range of the adsorbent compared with chitosan beads (CS). Arsenic was mainly present in the pH range of 3–9 as two forms, H2AsO4− and HAsO42−. Calculations using the density-functional theory (DFT) showed that in the Ligand interactions and electrostatic interactions dominate in the pH range, with surface precipitation, and hydrogen bonding interactions playing a facilitating role. The background ions mainly compete with arsenic adsorption for electrostatic interaction sites. However, due to the different valence states of the background ions, the competition intensity is different. Such as low valence state representative ions Na+, K+ competitiveness is weak, and arsenic competition adsorption first occupy different adsorption sites, therefore, from the quantum chemistry and molecular dynamics point of view of Na+, K+ on arsenic adsorption almost no effect. Cl−, SO42− will have some influence on arsenic adsorption because of the same charge with arsenic, but the charged amount is smaller than arsenic and the molecular structure is different from that of arsenic, so the influence is not very big. In summary, the material design of Fe-La-CS adsorbent has great potential and theoretical significance for selective purification of heavy metal wastewater at wide pH.

Engineering Bis-Pyridine N-Functionalized Cellulose Aerogel for Efficient Extraction of Cu2+ from High-Acidity Wastewaters: Coupling Molecular Scale Interpretation with Experiment.

In order to address the issue of protonation of functional groups and structural instability on the surface of aerogel due to strong acidic wastewater, a three-dimensional bis-pyridine N cellulose aerogel [PEIPD/carboxymethyl cellulose (CMC)] with protonation resistance was prepared in this paper by grafting pyridine onto polyethylenimine. The adsorption capacity for Cu2+ of the as-prepared aerogel is as high as 1.64 mmol/g (pH 5) and is maintained well in high-acidity solutions (1.15 mmol/g at pH = 2). It reveals high selectivity, splendid anti-interference ability, and also reliable on the recycle performance. Through the zeta potential tests, this adsorbent reveals a rather low zero charge point (pHpzc = 2.2). The adsorption of Cu2+ on the adsorbent is consistent with the pseudo-second-order kinetic model and the Langmuir model, suggesting that the adsorption process is dominated by chemisorption in a monolayer. The characterizations by Fourier transform infrared spectrometry and X-ray photoelectron spectroscopy proved pyridine N as responsible binding sites, based on which two possible mechanisms are proposed, including chelation and cation-π interaction. Density functional theory calculations are further used to precisely investigate the pathway. By comparing the binding energies, molecular electrostatic potentials, electron densities, and differential charge densities, the bis-pyridine N functional group is finally determined to be of much higher affinity to Cu2+ following chelation reaction as designated. By integrating bis-pyridine N with the CMC and understanding their crucial roles, this will provide significant insights into the rational design of aerogel adsorbents to enhance the recovery of Cu from strongly acidic wastewaters.

Forensic species identification: practical guide for animal and plant DNA analysis

The importance of non-human DNA in the forensic field has increased greatly in recent years, together with the type of applications. The molecular species identification of animal and botanical material may be crucial both for wildlife trafficking and crime scene investigation. However, especially for forensic botany, several challenges slow down the implementation of the discipline in the routine.Although the importance of molecular analysis of animal origin samples is widely recognized and the same value is acknowledged to the botanical counterpart, the latter does not find the same degree of application.The availability of molecular methods, especially useful in cases where the material is fragmented, scarce or spoiled preventing the morphological identification, is not well known. This work is intended to reaffirm the relevance of non-human forensic genetics (NHFG), highlighting differences, benefits and pitfalls of the current most common molecular analysis workflow for animal and botanical samples, giving a practical guide. A flowchart describing the analysis paths, divided in three major working areas (inspection and sampling, molecular analysis, data processing and interpretation), is provided. More real casework examples of the utility of non-human evidence in forensic investigations should be shared by the scientific community, especially for plants. Moreover, concrete efforts to encourage initiatives in order to promote quality and standardization in the NHFG field are also needed.

A Fast and Efficient Molecular Networking Approach for Reactivity of Natural Products Exploration in Plant Extracts: Application to Diterpene Esters from Euphorbia dendroides.

Natural products represent a rich source of bioactive compounds, covering a large chemical space. Even if challenging, this diversity can be extended by applying chemical modifications. However, these studies generally require multigram amounts of isolated natural products and face frequent testing failures. To overcome this limitation, we propose a rapid and efficient approach that uses molecular networking (MN) to visualize the new chemical diversity generated by simple chemical modifications of natural extracts. Moreover, the strategy deployed enables the most appropriate reagents to be defined quickly upstream of a reaction on a pure compound, in order to maximize chemical diversity. This methodology was applied to the latex extract of Euphorbia dendroides to follow the reactivity toward a series of Brønsted and Lewis acids of three class of diterpene esters identified in this species: jatrophane, terracinolide, and phorbol. Through the molecular networking interpretation, with the aim to illustrate our approach, BF3·OEt2 was selected for chemical modification on isolated jatrophane esters. Three rearranged compounds (3-5) were obtained, showing that the most appropriate reagents can be selected by MN interpretation.

Impedance of nanocapacitors from molecular simulations to understand the dynamics of confined electrolytes

Nanoelectrochemical devices have become a promising candidate technology across various applications, including sensing and energy storage, and provide new platforms for studying fundamental properties of electrode/electrolyte interfaces. In this work, we employ constant-potential molecular dynamics simulations to investigate the impedance of gold-aqueous electrolyte nanocapacitors, exploiting a recently introduced fluctuation-dissipation relation. In particular, we relate the frequency-dependent impedance of these nanocapacitors to the complex conductivity of the bulk electrolyte in different regimes, and use this connection to design simple but accurate equivalent circuit models. We show that the electrode/electrolyte interfacial contribution is essentially capacitive and that the electrolyte response is bulk-like even when the interelectrode distance is only a few nanometers, provided that the latter is sufficiently large compared to the Debye screening length. We extensively compare our simulation results with spectroscopy experiments and predictions from analytical theories. In contrast to experiments, direct access in simulations to the ionic and solvent contributions to the polarization allows us to highlight their significant and persistent anticorrelation and to investigate the microscopic origin of the timescales observed in the impedance spectrum. This work opens avenues for the molecular interpretation of impedance measurements, and offers valuable contributions for future developments of accurate coarse-grained representations of confined electrolytes.

Deep-PK: deep learning for small molecule pharmacokinetic and toxicity prediction.

Evaluating pharmacokinetic properties of small molecules is considered a key feature in most drug development and high-throughput screening processes. Generally, pharmacokinetics, which represent the fate of drugs in the human body, are described from four perspectives: absorption, distribution, metabolism and excretion-all of which are closely related to a fifth perspective, toxicity (ADMET). Since obtaining ADMET data from in vitro,in vivo or pre-clinical stages is time consuming and expensive, many efforts have been made to predict ADMET properties via computational approaches. However, the majority of available methods are limited in their ability to provide pharmacokinetics and toxicity for diverse targets, ensure good overall accuracy, and offer ease of use, interpretability and extensibility for further optimizations. Here, we introduce Deep-PK, a deep learning-based pharmacokineticand toxicity prediction, analysis and optimization platform. We applied graph neural networks and graph-based signatures as a graph-level feature to yield the best predictive performance across 73 endpoints, including 64 ADMET and 9 general properties. With these powerful models, Deep-PK supports molecular optimization and interpretation, aiding users in optimizing and understanding pharmacokinetics and toxicity for given input molecules. The Deep-PK is freely available athttps://biosig.lab.uq.edu.au/deeppk/.

Enhancing property and activity prediction and interpretation using multiple molecular graph representations with MMGX

Graph Neural Networks (GNNs) excel in compound property and activity prediction, but the choice of molecular graph representations significantly influences model learning and interpretation. While atom-level molecular graphs resemble natural topology, they overlook key substructures or functional groups and their interpretation partially aligns with chemical intuition. Recent research suggests alternative representations using reduced molecular graphs to integrate higher-level chemical information and leverages both representations for model. However, there is a lack of studies about applicability and impact of different molecular graphs on model learning and interpretation. Here, we introduce MMGX (Multiple Molecular Graph eXplainable discovery), investigating the effects of multiple molecular graphs, including Atom, Pharmacophore, JunctionTree, and FunctionalGroup, on model learning and interpretation with various perspectives. Our findings indicate that multiple graphs relatively improve model performance, but in varying degrees depending on datasets. Interpretation from multiple graphs in different views provides more comprehensive features and potential substructures consistent with background knowledge. These results help to understand model decisions and offer valuable insights for subsequent tasks. The concept of multiple molecular graph representations and diverse interpretation perspectives has broad applicability across tasks, architectures, and explanation techniques, enhancing model learning and interpretation for relevant applications in drug discovery.

Disease-Causing TIMP3 Variants and Deep Phenotyping of Two Czech Families with Sorsby Fundus Dystrophy Associated with Novel p.(Tyr152Cys) Mutation.

We aim to report the ocular phenotype and molecular genetic findings in two Czech families with Sorsby fundus dystrophy and to review all the reported TIMP3 pathogenic variants. Two probands with Sorsby fundus dystrophy and three first-degree relatives underwent ocular examination and retinal imaging, including optical coherence tomography angiography. The DNA of the first proband was screened using a targeted ocular gene panel, while, in the second proband, direct sequencing of the TIMP3 coding region was performed. Sanger sequencing was also used for segregation analysis within the families. All the previously reported TIMP3 variants were reviewed using the American College of Medical Genetics and the Association for Molecular Pathology interpretation framework. A novel heterozygous variant, c.455A>G p.(Tyr152Cys), in TIMP3 was identified in both families and potentially de novo in one. Optical coherence tomography angiography documented in one patient the development of a choroidal neovascular membrane at 54 years. Including this study, 23 heterozygous variants in TIMP3 have been reported as disease-causing. Application of gene-specific criteria denoted eleven variants as pathogenic, eleven as likely pathogenic, and one as a variant of unknown significance. Our study expands the spectrum of TIMP3 pathogenic variants and highlights the importance of optical coherence tomography angiography for early detection of choroidal neovascular membranes.

Comparative study on Perfluoro(2-methyl-3-oxahexanoic) acid removal by quaternary ammonium functionalized silica gel and granular activated carbon from batch and column experiments and molecular simulation-based interpretation

Removing perfluoro(2-methyl-3-oxahexanoic) acid (HFPO-DA) in water treatment is hindered by its hydrophobicity and negative charge. Two adsorbents, quaternary-ammonium-functionalized silica gel (Qgel), specifically designed for anionic hydrophobic compounds, and conventional granular activated carbon (GAC) were investigated for HFPO-DA removal. ANOVA results (p ≪ 0.001) revealed significant effects on initial concentration, contact time, and adsorbent type. Langmuir model-derived capacities were 285.019 and 144.461 mg/g for Qgel and GAC, respectively, with Qgel exhibiting higher capacity irrespective of pH. In column experiments, selective removal of HFPO-DA removal with Qgel was observed; specifically, in the presence of NaCl, the breakthrough time was extended by 10 h from 26 to 36 h. Meanwhile, the addition of NaCl decreased the breakthrough time from 32 to 14 h for GAC. However, in the presence of carbamazepine, neither of the adsorbents significantly changed the breakthrough time for HFPO-DA. Molecular simulations were also used to compare the adsorption energies and determine the preferential interactions of HFPO-DA and salts or other chemicals with Qgel and GAC. Molecular simulations compared adsorption energies, revealing preferential interactions with Qgel and GAC. Notably, HFPO-DA adsorption energy on GAC surpassed other ions during coexistence. Specifically, with Cl− concentrations from 1 to 10 times, Qgel showed lower adsorption energy for HFPO-DA (−62.50 ± 5.44 eV) than Cl− (−52.89 ± 2.59 eV), a significant difference (p = 0.036). Conversely, GAC exhibited comparable or higher adsorption energy for HFPO-DA (−18.33 ± 40.38 eV) than Cl- (−32.36 ± 29.89 eV), with no significant difference (p = 0.175). This suggests heightened selectivity of Qgel for HFPO-DA removal compared to GAC. Consequently, our study positions Qgel as a promising alternative for effective HFPO-DA removal, contributing uniquely to the field. Additionally, our exploration of molecular simulations in predicting micropollutant removal adds novelty to our study.

On the simulation and interpretation of substrate-water exchange experiments in photosynthetic water oxidation.

Water oxidation by photosystem II (PSII) sustains most life on Earth, but the molecular mechanism of this unique process remains controversial. The ongoing identification of the binding sites and modes of the two water-derived substrate oxygens ('substrate waters') in the various intermediates (Si states, i = 0, 1, 2, 3, 4) that the water-splitting tetra-manganese calcium penta-oxygen (Mn4CaO5) cluster attains during the reaction cycle provides central information towards resolving the unique chemistry of biological water oxidation. Mass spectrometric measurements of single- and double-labeled dioxygen species after various incubation times of PSII with H218O provide insight into the substrate binding modes and sites via determination of exchange rates. Such experiments have revealed that the two substrate waters exchange with different rates that vary independently with the Si state and are hence referred to as the fast (Wf) and the slow (WS) substrate waters. New insight for the molecular interpretation of these rates arises from our recent finding that in the S2 state, under special experimental conditions, two different rates of WS exchange are observed that appear to correlate with the high spin and low spin conformations of the Mn4CaO5 cluster. Here, we reexamine and unite various proposed methods for extracting and assigning rate constants from this recent data set. The analysis results in a molecular model for substrate-water binding and exchange that reconciles the expected non-exchangeability of the central oxo bridge O5 when located between two Mn(IV) ions with the experimental and theoretical assignment of O5 as WS in all S states. The analysis also excludes other published proposals for explaining the water exchange kinetics.

Spectrum of the molecular tetraquarks: Unraveling the Tcs0(2900) and Tcs¯0a(2900)

We relate the interactions of the D¯(*)K* and D(*)K* systems to those of D(*)D(*) and D(*)D¯(*) respectively, considering the residual strong interactions at the near-threshold energy is too weak to excite the strange quarks inside the hadrons. We propose an effective model to describe the low-energy S-wave interactions that are undertaken by the light u, d quarks between two separated heavy hadrons. We find that the existence of molecules in the heavy-(anti)heavy sectors will naturally lead to the emergence of molecular states in D¯(*)K* and D(*)K* systems. The recently observed Tcs0(2900) and Tcs¯0a(2900) can be well identified as the 0(0+) and 1(0+) partners of Tcc(3875) and Zc(3900) in the charmed strange sector, respectively. We also predict their members under the (c and s) quark symmetry and SU(2) flavor symmetry. Most of them are very good molecule candidates, for example, (i) the 0(1+) states in D*D*, D¯K*, D¯*K*; (ii) the 0(+)(2+(+)) states in D*D¯*, D¯*K*, D*K*; (iii) the 1−(0++) state in D*D¯* and 1(1+) state in D*K*. The 0+(0++) state in DD¯ and the 0(1+) state in DK* might also exist as virtual states, and the 0(1+) DK* can serve as a key to infer the existence of 0+(0++) DD¯. The Dsπ invariant mass spectrum of Tcs¯0a(2900) is also studied within the coupled-channel approach, and the molecular interpretation of Tcs¯0a(2900) is consistent with the experimental data. Searching for the predicted states in experiments is crucial to discriminate the different pictures for interpreting these near-threshold exotica. Published by the American Physical Society 2024

Solvation Thermodynamics and Its Applications.

In this article, we start by describing a few "definitions" of the solvation processes, which were used in the literature until about 1980. Then, we choose one of these definitions and show that it has a simple molecular interpretation. This fact led to a new definition of the solvation process and the corresponding thermodynamic quantities. The new measure of the solvation Gibbs energy has a simple interpretation. In addition, the thermodynamic quantities associated with the new solvation process have several other advantages over the older measures. These will be discussed briefly in the third section. In the fourth section, we discuss a few applications of the new solvation process.