PARTİSYON KATSAYISI (LOG P) TAHMİNİNDE KULLANILAN YAZILIMLARIN KARŞILAŞTIRILMASI

Amaç: Sentezlenecek ilaç etken maddesi adayı bileşiklerin vücut dokularına ulaşabilmesi ve ulaştığında da toksik etki göstermemesi gerekmektedir. Kantitatif yapı-etki ilişkilerinin fizikokimyasal parametreler başlığında yer alan partisyon katsayısı (log P), ilacın farmakokinetik özelliklerini etkilemektedir. Araştırmacılar, ilaç geliştirme çalışmalarında zaman ve maliyetten tasarruf sağlamak amacıyla log P tahmin eden yazılımlara başvurabilmektedir. Fakat bu yazılımların tamamen doğru sonuç vermediği unutulmamalıdır. Bu çalışmada, kullanılmakta olan bu yazılımların güvenilirliği test edilmiştir. Bunlardan güvenilirliği onaylanan yazılım araştırmacılara partisyon katsayısının deneysel tayininden önce fikir verebilecektir. Gereç ve Yöntem: 94 bileşikten oluşan bileşik verisetinde, literatürdeki log P değerleri ile ACD/iLab 2.0, ALOGPS 2.1 ve Molinspiration log P yazılımları aracılığıyla hesaplanan değerler karşılaştırılmış; sapma değerlerine göre bu üç yazılımdan en güvenilir olan seçilmiştir. Bileşiklerin partisyon katsayısı hesaplanırken SMILES kodları kullanılmıştır. Sonuç ve Tartışma: 94 literatür bileşiğinden elde edilen hesaplama sonuçlarına göre partisyon katsayısı (log P) hesaplamada en güvenilir yazılımın, en düşük ortalama sapmaya sahip olan Molinspiration log P olduğuna karar verilmiştir. Bu yazılımın kullanılmasıyla araştırmacılar, sentezlenen bileşiklerin partisyon katsayısı hakkında yorum yürütebilecek olup, zaman ve maliyetten tasarruf edebileceklerdir.

Anahtar Kelimeler:

ADME/Tox, Farmakokinetik, İlaç Geliştirme, Lipofiliklik, Log P

COMPARISON OF PARTITION COEFFICIENT (LOG P) PREDICTION SOFTWARES

Objective: Drug candidate compounds that are going to be synthesized have to reach body tissues and show minimum toxic effects within the body. Partition coefficient (log P), which is a physicochemical parameter of Quantitative Structure- Activity Relationship subject, effects the pharmacokinetical characteristic of the compound. In this context, researchers tend to use log P prediction softwares to save both time and resources in their drug development studies. Although, these softwares do not give a true value. In this study, softwares that have being used were tested. The one that gets approved for its accuracy can give some clues on the value of partition coefficient, before determining it experimentally. Material and Method: In the following dataset, which comprises of 94 compounds, logP values from literature and values that have been calculated with softwares such as ACD/iLab 2.0, ALOGPS 2.1 ve Molinspiration have been compared. By calculating the deviations, most reliable of these three has been selected. SMILES notations of the compounds has been used as an input for the calculation. Result and Discussion: According to the calculation results of 94 compounds, Molinspiration log P, which has the lowest average deviation value, was selected as most reliable log P prediction software. By using this software, scholars can comment on partition coefficients of their synthesized compounds. Therefore, hopefully they can save both time and resources.

Keywords:

ADME/Tox, Drug Development, Lipophilicity, Log P, Pharmacokinetics,

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