Abstract
Aqueous solubility is one of the major physiochemical properties to be optimized in drug discovery. It is related to absorption and distribution in the ADME-Tox (Absorption, Distribution, Metabolism, Excretion, and Toxicity). Aqueous solubility and membrane permeability are the two key factors that affect a drugs oral bioavailability. Because of the importance of aqueous solubility, a lot of efforts have been spent on developing reliable models to predict this physiochemical property. Although some progress has been made and a lot of models have been constructed, it is concluded that accurate and reliable aqueous models targeted to predict solubility of drug-like molecules, have not emerged based on the outcome of an aqueous solubility prediction campaign sponsored by Goodman et al. In this review paper, we provide a snapshot of the latest development in the field. The challenges of developing high quality aqueous solubility models as well as the strategies of surmounting those challenges have been discussed. We conclude that the biggest challenge of modeling aqueous solubility is to collect more high quality, unskewed and drug-relevant solubility data which are sufficient diverse to cover most the chemical space of drugs. The second challenge is to develop good descriptors to account for the lattice energy of solvation. In order to develop accurate and predictable in silico solubility models, the key is to collect a sufficient number of high quality experimental data and the suspicious data must be verified. In addition, the molecular descriptors must be relevant to the energies in the solvation process (the lattice energy for crystal packing, the energy of forming cavity in solvent, and the solvation energy), and the models must be carefully cross-validated and evaluated using the external data sets.
Keywords: Solubility, solubility challenge, in silico modeling, drug design, Prediction, physiochemical properties, ADME-Tox, bioavailability, combinatorial chemistry, high-throughput screening
Combinatorial Chemistry & High Throughput Screening
Title: Recent Advances on Aqueous Solubility Prediction
Volume: 14 Issue: 5
Author(s): Junmei Wang and Tingjun Hou
Affiliation:
Keywords: Solubility, solubility challenge, in silico modeling, drug design, Prediction, physiochemical properties, ADME-Tox, bioavailability, combinatorial chemistry, high-throughput screening
Abstract: Aqueous solubility is one of the major physiochemical properties to be optimized in drug discovery. It is related to absorption and distribution in the ADME-Tox (Absorption, Distribution, Metabolism, Excretion, and Toxicity). Aqueous solubility and membrane permeability are the two key factors that affect a drugs oral bioavailability. Because of the importance of aqueous solubility, a lot of efforts have been spent on developing reliable models to predict this physiochemical property. Although some progress has been made and a lot of models have been constructed, it is concluded that accurate and reliable aqueous models targeted to predict solubility of drug-like molecules, have not emerged based on the outcome of an aqueous solubility prediction campaign sponsored by Goodman et al. In this review paper, we provide a snapshot of the latest development in the field. The challenges of developing high quality aqueous solubility models as well as the strategies of surmounting those challenges have been discussed. We conclude that the biggest challenge of modeling aqueous solubility is to collect more high quality, unskewed and drug-relevant solubility data which are sufficient diverse to cover most the chemical space of drugs. The second challenge is to develop good descriptors to account for the lattice energy of solvation. In order to develop accurate and predictable in silico solubility models, the key is to collect a sufficient number of high quality experimental data and the suspicious data must be verified. In addition, the molecular descriptors must be relevant to the energies in the solvation process (the lattice energy for crystal packing, the energy of forming cavity in solvent, and the solvation energy), and the models must be carefully cross-validated and evaluated using the external data sets.
Export Options
About this article
Cite this article as:
Wang Junmei and Hou Tingjun, Recent Advances on Aqueous Solubility Prediction, Combinatorial Chemistry & High Throughput Screening 2011; 14 (5) . https://dx.doi.org/10.2174/138620711795508331
DOI https://dx.doi.org/10.2174/138620711795508331 |
Print ISSN 1386-2073 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5402 |
Call for Papers in Thematic Issues
Artificial Intelligence Methods for Biomedical, Biochemical and Bioinformatics Problems
Recently, a large number of technologies based on artificial intelligence have been developed and applied to solve a diverse range of problems in the areas of biomedical, biochemical and bioinformatics problems. By utilizing powerful computing resources and massive amounts of data, methods based on artificial intelligence can significantly improve the ...read more
Eco-friendly Agents for Biological Control of Pathogenic Diseases
The discovery of an alternative biological approach to disease management includes work on medicinal products derived from natural sources as a starting point for the development of eco-friendly agents for these diseases and the injuries they cause, as well as reducing human contact with hazardous chemicals and their residues. We ...read more
Emerging trends in diseases mechanisms, noble drug targets and therapeutic strategies: focus on immunological and inflammatory disorders
Recently infectious and inflammatory diseases have been a key concern worldwide due to tremendous morbidity and mortality world Wide. Recent, nCOVID-9 pandemic is a good example for the emerging infectious disease outbreak. The world is facing many emerging and re-emerging diseases out breaks at present however, there is huge lack ...read more
Exploring Spectral Graph Theory in Combinatorial Chemistry
Scope of the Thematic Issue: Combinatorial chemistry involves the synthesis and analysis of a large number of diverse compounds simultaneously. Traditional methods rely on brute force experimentation, which can be time-consuming and resource-intensive. Spectral Graph Theory, a branch of mathematics dealing with the properties of graphs in relation to the ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Antiviral Activity of Bee Products
Current Pharmaceutical Design Pharmacological and Surgical Therapy for Primary Postpartum Hemorrhage
Current Pharmaceutical Design New Developments In Treatment After Lung Transplantation
Current Pharmaceutical Design Calcium Store Stability as an Antiarrhythmic Endpoint
Current Pharmaceutical Design Evaluation of the Therapeutic Properties of Mastoparan- and Sifuvirtide- Derivative Antimicrobial Peptides Using Chemical Structure-Function Relationship - in vivo and in silico Approaches
Current Drug Delivery Comparison of Chest CT and RT-PCR Assay for Indication of Disease Course of Coronavirus Disease 2019 (COVID-19) Pneumonia
Current Medical Imaging Graphical Abstracts
Letters in Drug Design & Discovery Histamine H3 Antagonists as Wake-Promoting and Pro-Cognitive Agents
Current Topics in Medicinal Chemistry World’s First Experience of the Low-Dose Radionuclide Inhalation Therapy in the Treatment of COVID-19-Associated Viral Pneumonia: Phase 1/2 Clinical Trial
Current Radiopharmaceuticals Editorial from Editor-in-Chief
Current Respiratory Medicine Reviews Information Disclosed in Patent Documents being the Source to Address Emergencies: A Strategy to Achieve Technological Developments Addressing COVID-19
Recent Patents on Biotechnology Predictive Factors for the Care and Control of Hypertension Based on the Health Belief Model Among Hypertensive Patients During the COVID-19 Epidemic in Sirjan, Iran
Current Hypertension Reviews Remote Preconditioning- Endocrine Factors in Organ Protection Against Ischemic Injury
Endocrine, Metabolic & Immune Disorders - Drug Targets Secondary Stroke Prevention in Patients with Cryptogenic Stroke and Patent Foramen Ovale
Vascular Disease Prevention (Discontinued) Therapeutic Neovascularization by the Implantation of Autologous Mononuclear Cells in Patients with Connective Tissue Diseases
Current Pharmaceutical Design The Impact of Deranged Glucose Metabolism and Diabetes in the Pathogenesis and Prognosis of the Novel SARS-CoV-2: A Systematic Review of Literature
Current Diabetes Reviews 3D-QSAR and Molecular Docking Studies of Flavonoid Derivatives as Potent Acetylcholinesterase Inhibitors
Letters in Drug Design & Discovery Neurologic Sequelae in Critical Illness: Evaluation and Outcomes
Current Respiratory Medicine Reviews Physiologically Based Pharmacokinetic Models: Integration of In Silico Approaches with Micro Cell Culture Analogues
Current Drug Metabolism Endotoxin, TLR4 Signaling and Vascular Inflammation: Potential Therapeutic Targets in Cardiovascular Disease
Current Pharmaceutical Design