Prioritizing Computational Cocrystal Prediction Methods for Experimental Researchers: A Review to Find Efficient, Cost-Effective, and User-Friendly Approaches

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(22), P. 12045 - 12045

Published: Nov. 9, 2024

Pharmaceutical cocrystals offer a versatile approach to enhancing the properties of drug compounds, making them an important tool in formulation and development by improving therapeutic performance patient experience pharmaceutical products. The prediction involves using computational theoretical methods identify potential cocrystal formers understand interactions between active ingredient coformers. This process aims predict whether two or more molecules can form stable structure before performing experimental synthesis, thus saving time resources. In this review, commonly used are first overviewed then evaluated based on three criteria: efficiency, cost-effectiveness, user-friendliness. Based these considerations, we suggest researchers without strong experiences which tools should be tested as step workflow rational design cocrystals. However, optimal choice depends specific needs resources, combining from different categories powerful approach.

Language: Английский

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Enhancing the Screening Efficiency of Chiral Cocrystals for the Separation of Praziquantel through the Use of Coformer Derivatives

Crystal Growth & Design, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 8, 2025

Cocrystallization has become an increasingly attractive method for the separation of chiral active pharmaceutical ingredients (API). However, screening process coformers (CFs) that are capable cocrystallizing with API and further producing cocrystals suitable enantiomeric resolution is often time-consuming may not always give desired results. One promising approaches involves prediction CF structures based on modification structure a known successful particular target molecule. This can lead to formation new different space groups be more resolution. In this study, we propose four similar malic acid, which been shown form diastereomeric praziquantel (PZQ), including tartaric methylsuccinic 2,3-dimethylsuccinic 2,2-dimethylsuccinic acid. Our findings demonstrated these CFs generate cocrystal PZQ some crystallized in Sohncke group, allows only enantiomerically pure crystal structure. Notably, meso-2,3-dimethylsuccinic acid shows potential forming rare conglomerate cocrystal. Furthermore, energetic was revealed by DFT calculation.

Language: Английский

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Progress in the understanding of traditional and nontraditional molecular interactions

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

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Pharmaceutical Cocrystals for Drug Delivery

Burger's Medicinal Chemistry and Drug Discovery, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 62

Published: May 26, 2025

Abstract Pharmaceutical cocrystals offer the ability to tune solubility, permeability, tableting, and bioavailability of a solid, oral drug formulation without changing chemical structure molecule. Crystal engineering pharmaceutical salts via supramolecular heterosynthons with acceptable generally recognized as safe (GRAS) coformers provides platform technology for improving efficacy optimal delivery. With almost 90% drugs in Biopharmaceutics Classification System (BCS) class II IV suffering from low‐solubility and/or low‐permeability challenges, have provided an opportune intervention populating pipeline over past decade. From prototype cocrystal itraconazole‐succinic acid first salt‐cocrystal complex Entresto containing valsartan‐sacubitril, this review covers origins subject early 2000s peak growth curve model systems between 2005 2015, successful lab‐to‐market translation witnessed The combined application machine learning neural network tools is bringing speed accuracy research exercise designing drug–coformer therapeutic properties. This article snapshot summary latest trends leading discovery, development, continuous manufacturing.

Language: Английский

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Resources for Accelerating Medicine Discovery

Burger's Medicinal Chemistry and Drug Discovery, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 57

Published: May 26, 2025

Abstract Using artificial intelligence and machine learning, computational tools are increasingly accelerating new medicine discovery. Applications to the stages of drug discovery, including target identification, hit lead optimization, developability assessment, described. This chapter provides a compilation databases, software packages, web‐based applications for evaluation, optimization molecules.

Language: Английский

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Conformation, virtual cocrystal screening, synthesis and determination of dipyridamole

Journal of Molecular Structure, Journal Year: 2024, Volume and Issue: 1318, P. 139259 - 139259

Published: July 10, 2024

Language: Английский

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