# name
On the usage of lipophilic descriptors for molecular similarity evaluation

# metadata.dc.contributor.other[].value
Universitat de Barcelona. Facultat de Farmàcia i Ciències de l'Alimentació

# metadata.dc.description.abstract[].value
[eng] Three-dimensional ligand-based virtual screening methods have been used for many years in drug discovery, with a variable success depending on different factors, such as the complexity of the target system or the suitability of the molecular descriptors. New approaches are still necessary to cover the broad spectrum of relationships that a drug-like molecule may establish with the organism. In spite of the complexity of processes that modulate the activity of a drug, most tools are primarily focused on the use of shape or electrostatic descriptors. In contrast, since the importance of lipophilicity in pharmacodynamics and pharmacokinetics process, an exact representation of the 3D pattern of hydrophobic/hydrophilic regions can be a valuable guideline to enhance the molecular similarity studies.
In this scenario, PharmScreen was conceived as a tool to exploit lipophilic 3D similarity. Exploiting the MST contributions to octanol/water partition coefficients,  the  capacity to perform correct molecular overlays and distinguish between active and inactive molecules is discussed.
The overlap algorithm is validated against the AstraZeneca test, which comprises 121 experimentally derived sets of molecular overlays. The results point out the suitability of the MST-based hydrophobic parameters for generating molecular overlays, as correct predictions were obtained for 94%, 79%, and 54% of the molecules classiﬁed into easy, moderate, and hard sets, respectively. Moreover, the results point out that this accuracy is attained at a much lower degree of identity between the templates used by hydrophobic/HB ﬁelds and electrostatic/steric ones.
On the other hand, the topological hydrophobic descriptors proposed are applied over 3D-QSAR models. In this context, the Miertus–Scrocco–Tomasi-derived hydrophobic descriptors have been shown to provide models for structure–activity relationships with a predictive accuracy comparable to traditional techniques based on electrostatic/steric parameters. The results reported support the assumption that lipophilicity, supplemented by HB acceptors/donors, provides a useful signature to enrich the information that can be retrieved from
(i) molecular alignment and (ii) QSAR models, complementing the results obtained traditionally from electrostatic and steric properties. Taken together, lipophilicity is presented as a valuable alternative for the molecular similarity study.
In addition, the applicability of our descriptors in structure-based methods has been explored in order to re-evaluate the complexes constituted by docking techniques (in our case, Glide). Since (de)solvation is fundamental for the establishment of the ligand-receptor complex, it can be expected that the docked ligands in the same pocket share lipophilic characteristics, even if there are several binding modes. However, approximations that affect solvation contribution are applied in the docking score functions, and by extension, some docking programs show problems performing VS especially in hydrophobic binding pockets. Speciﬁc binding typically requires the formation of key interactions between targets and ligands. Thus, 3D similarity relative
 
to experimental binding modes could be suﬃcient to distinguish active compounds from decoys. In view of the results obtained the similarity descriptors proposed are introduced as a valid scoring function for discerning between active and inactive compounds.
These ﬁndings support the usefulness of lipophilicity as driver descriptors in molecular similarity studies promoting their use in virtual screening campaigns considering LB approaches or in combination with SB.
As conclusion, results obtained from the analysis of hydrophobic/hydrophilic descriptors presented in this thesis opens a new window to explore the vast chemical space, complementing the information derived from traditional descriptors in ligand- and structure-based approaches.

# metadata.dc.description.abstract[].value
[cat] El fet d'assumir que molècules estructuralment semblants donaran lloc a activitats biològiques similars ha estat una idea àmpliament explotada en el disseny de fàrmacs. Aquesta premissa subjau en la majoria de les aplicacions pràctiques en recerca química i farmacèutica. No obstant això, el concepte de similitud molecular és subjectiu4 i la seva interpretació pot variar segons l’ús que se’n vulgui derivar. La quantificació d’aquesta mesura de semblança molecular depèn de la representació de les característiques químiques presents en l'estructura molecular mitjançant descriptors 1D, 2D o 3D, la ponderació d'aquests descriptors i l'expressió matemàtica de la funció de similitud.      En l’àmbit de les característiques químiques utilitzades en els mètodes tridimensionals de similitud molecular, les propietats electrostàtiques i estèriques han estat dominants tradicionalment. Tanmateix, això oculta el paper fonamental exercit per altres contribucions a l'afinitat d'unió, com els canvis en la (de)solvatació del lligant i del receptor. Malgrat la seva rellevància, la lipofilicitat ocupa aparentment un paper secundari com a descriptor principal del reconeixement lligand-receptor.
Sota aquesta premissa s’ha desenvolupat una eina de cribratge virtual 3D basada en lligands (PharmScreen) que explota les relacions de similitud entre topologies hidrofòbiques derivades del model continuo de solvatació Miertus – Scrocco – Tomasi (MST).
Els estudis reportats al llarg d’aquesta tesis recolzen la utilitat de les contribucions atòmiques a la lipofilicitat com a descriptors fonamentals en estudis de similitud, complementant la informació derivada dels descriptors tradicional. PharmScreen es presenta, així, com una eina competitiva per aplicar en campanyes de cribratge virtual basada en lligand o en combinació amb tècniques basades en proteïna, obrint una nova finestra en l’ampli espai químic.

# metadata.dc.source[].value
Tesis Doctorals - Facultat - Farmàcia i Ciències de l'Alimentació

# metadata.dc.title[].value
On the usage of lipophilic descriptors for molecular similarity evaluation