[COMMODE] a large-scale database of molecular descriptors using compounds from PubChem

BACKGROUND: Molecular descriptors have been extensively used in the field of structure-oriented drug design and structural chemistry. They have been applied in QSPR and QSAR models to predict ADME-Tox properties, which specify essential features for drugs. Molecular descriptors capture chemical and structural information, but investigating their interpretation and meaning remains very challenging. RESULTS: This paper introduces a large-scale database of molecular descriptors called COMMODE containing more than 25 million compounds originated from PubChem. About 2500 DRAGON-descriptors have been calculated for all compounds and integrated into this database, which is accessible through a web interface at http://commode.i-med.ac.at

QSAR-driven screening uncovers and designs novel pyrimidine-4,6-diamine derivatives as potent JAK3 inhibitors

This study presents a robust and integrated methodology that harnesses a range of computational techniques to facilitate the design and prediction of new inhibitors targeting the JAK3/STAT pathway. This methodology encompasses several strategies, including QSAR analysis, pharmacophore modeling, ADMET prediction, covalent docking, molecular dynamics (MD) simulations, and the calculation of binding free energies (MM/GBSA). An efficacious QSAR model was meticulously crafted through the employment of multiple linear regression (MLR). The initial MLR model underwent further refinement employing an artificial neural network (ANN) methodology aimed at minimizing predictive errors. Notably, both MLR and ANN exhibited commendable performance, showcasing R2 values of 0.89 and 0.95, respectively. The model's precision was assessed via leave-one-out cross-validation (CV) yielding a Q2 value of 0.65, supplemented by rigorous Y-randomization. , The pharmacophore model effectively differentiated between active and inactive drugs, identifying potential JAK3 inhibitors, and demonstrated validity with an ROC value of 0.86. The newly discovered and designed inhibitors exhibited high inhibitory potency, ranging from 6 to 8, as accurately predicted by the QSAR models. Comparative analysis with FDA-approved Tofacitinib revealed that the new compounds exhibited promising ADMET properties and strong covalent docking (CovDock) interactions. The stability of the new discovered and designed inhibitors within the JAK3 binding site was confirmed through 500 ns MD simulations, while MM/GBSA calculations supported their binding affinity. Additionally, a retrosynthetic study was conducted to facilitate the synthesis of these potential JAK3/STAT inhibitors. The overall integrated approach demonstrates the feasibility of designing novel JAK3/STAT inhibitors with robust efficacy and excellent ADMET characteristics that surpass Tofacitinib by a significant margin

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

Pharmacolog

To what extent do cell-penetrating peptides selectively cross the blood-brain barrier?

The blood-brain barrier protects the brain from toxic compounds. Its selective permeability is essential for the optimal function of the central nervous system. Some peptides can cross the blood-brain barrier. On the other hand, cell-penetrating peptides are able to overcome the cell membrane. During this research project, it was investigated whether these cell-penetrating peptides also can cross the blood-brain barrier. The chemical diversity of the already reported cell-penetrating peptides was investigated and a unified response for the extent of cellular uptake of peptides was introduced. Based on this study, a set of cell-penetrating peptides was rationally selected for further research. In order to more objectively compare the quantitative data on the blood-brain barrier influx of peptides, a classification system for blood-brain barrier influx was established. The purity of the selected synthetized cell-penetrating peptides was also investigated, which is essential for obtaining reliable research conclusions. Different chromatographic systems were compared for the analysis of the selected peptides. The investigated cell-penetrating peptides crossed the blood-brain barrier to a different extent. The influx varied from very low to very high and some peptides showed efflux out of the brain. There was no correlation observed between the blood-brain barrier transport kinetics and the extent of cellular uptake. During the aging process, the blood-brain barrier shows an increased permeability and, together with other age-related functional changes, should be taken into account during the development of medicines used by the elderly. Therefore, the current regulatory status of the development of geriatric medicines was investigated

Poly(2-oxazoline)-based polymeric micelle platform for drug delivery

Polymeric micelles (PMs) have been extensively utilized as drug delivery platform. Particularly, potent hydrophobic small molecules were encapsulated in the PMs to alleviate toxicity issues and improve therapeutic outcomes. We attempt to provide detailed information on PMs for hydrophobic small molecules, such as the design of block copolymers (BCP) and current clinical outcomes from PMs. In particular, we aim to describe advanced analytical approaches for elucidating molecular interactions for effective solubilization. This dissertation includes a novel computer-aided strategy for rational design of PMbased delivery systems for poorly soluble drugs. We have developed novel descriptors of drug polymer complexes that were employed to build models to predict both drug loading efficiency (LE) and loading capacity (LC). These models were used for virtual screening of drug libraries and eight drugs for the experimental validation. Three putative true positive as well as three putative negative hits were confirmed (implying 75% prediction accuracy). The success of the computational strategy suggests its broad utility for rational design of drug delivery systems. This dissertation involves the study of poly(2-oxazoline) micelles (POx) for treatment of medulloblastoma. For patients with SHH-subgroup medulloblastoma, SHH-pathway inhibition may be more effective and less toxic than current non-targeted therapy. We successfully solubilized SHH-pathway inhibitor, vismodegib, in POx micelles (POx-vismo) and showed the PM formulation improved drug efficacy, demonstrated in the treatment of medulloblastoma animal model. Mechanistic studies revealed that POx-vismo decreased vismodegib binding to serum proteins and improved brain and tumor drug penetration without penetration of the nanoparticle carrier into the CNS. This dissertation also includes the development of novel poly(2-oxazoline)-based block copolymer with the aromatic heterocyclic side chains and demonstration of its application as a drug delivery platform. The copolymer was synthesized via the condensation of N,N dimethylbiguanide with the methyl ester side chain in poly(2-methoxycarboxyethyl-2-oxazoline) block (PMestOx). Successful encapsulation into these micelles has been demonstrated for several poorly soluble drugs. The capability of this new copolymer to solubilize a uniquely diverse set of active pharmaceutical ingredients suggests potential applications in drug delivery. In summary, poly(2-oxazoline)-based PM platforms are versatile drug delivery platform and exhibit the broad potential for ideal drug delivery of therapeutic small molecules.Doctor of Philosoph

Pharmacophore analysis, design and in vitro testing of multi-target ligands as potentially effective therapeutics of complex neurological and mental disorders

Disfunkcija serotoninske i dopaminske neurotransmisije u mozgu je u osnovi patofiziologijebrojnih neuroloških i mentalnih oboljenja. Definisanje protokola koji integriše in silico i in vitrometode, u cilju prouĉavanja farmakofore multi-potentnih jedinjenja koja deluju na nivou centralnognervnog sistema (CNS), predstavlja vaţan korak u racionalizaciji procesa otkrivanja novih lekova.Primenom simulacija molekulske dinamike i molekulskog dokinga, kao i analize kvantitativnogodnosa strukture i aktivnosti (eng. 3D-Quantitative Structure Activity Relationship, 3D-QSAR)definisane su kljuĉne strukturne karakteristike dualnih antagonista 5-HT2A i D2 receptora, sasmanjenim afinitetom za H1 receptor. Na osnovu dobijenih rezultata izvršeno je pretraţivanje bazafragmenata primenom metode virtuelnog skrininga (eng. Virtual Screening, VS) u cilju dizajniranjapotencijalno bezbednijih i efikasnijih liganada sa višestrukim delovanjem (eng. multi-target),pruţajući smernice za razvoj novih lekova u terapiji sloţenih CNS oboljenja. 3D-QSAR analizombicikliĉnih α-iminofosfonata definisana je struktura farmakofore selektivnih liganadaimidazolinskih I2 receptora, kao potencijalno novih lekova za leĉenje kognitivnih poremećaja. Invitro paralelni test permeabilnosti na veštaĉkim membranama (eng. Parallel Artificial MembranePermeability Assay, PAMPA) je korišćen za odreĊivanje efektivne permeabilnosti (logPe) krozkrvno-moţdanu barijeru (KMB) jedinjenja koja utiĉu na modulaciju aktivnosti serotoninskog idopaminskog sistema u mozgu. Dobijeni rezultati su korišćeni u analizi kvantitativnog odnosastrukture i osobina (eng. Quantitative Structure-Property Relationship, QSPR) u cilju razumevanjastrukturnih karakteristika koje najviše utiĉu na prolazak jedinjenja kroz KMB. Model formiranprimenom metode podrţavajućih vektora (eng. Support-Vector Machine, SVM) i validiranopseţnom statistiĉkom analizom, je korišćen za predviĊanje logPe vrednosti dizajniranih dualnihantagonista i liganada I2 receptora, svrstavajući ih u grupu visoko permeabilnih jedinjenja. Sa ciljemda se dodatno analizira i vizuelizuje proces permeabilnosti centralnodelujućih jedinjenja kroz KMBna molekulskom nivou, korišćene su simulacije usmerene molekulske dinamike (eng. SteeredMolecular Dynamics, SMD).Disturbances in serotoninergic and dopaminergic neurotransmissions in the central nervoussystem (CNS) play a key role in the pathophysiology of various neurological and mental disorders.Developing an integrative approach through application of in silico and in vitro methods, in order toanalyse pharmacophore of multi-target neuroactive compounds, presents a promising strategy inrationalization of drug design process. Molecular dynamics simulations and molecular dockingmethods in combination with 3D-quantitative structure activity relationship analysis (3D-QSAR)were used to evaluate crucial structural features of potent dual antagonists of 5-HT2A i D2 receptors,with lower antagonistic activity on H1 receptors. The virtual screening of the available fragmentlibraries was performed with the aim to design novel multi-target compounds with a more effectiveand safer profile, laying a good foundation for the therapy of complex brain diseases. Moreover,3D-QSAR analysis of bicyclic α-iminophosphonates was used to reveal the pharmacophorestructure of selective imidazoline I2 receptor (I2-IR) ligands, as potentially new drugs for thetreatment of cognitive disorders. In vitro parallel artificial membrane permeability assay (PAMPA)was further employed to examine the effective permeability (logPe) through blood brain barrier(BBB) of compounds that affect serotonin and dopamine levels in the CNS. Based on the obtainedresults, quantitative structure-property relationship (QSPR) analysis was performed with the aim todefine structural features that mostly affect the permeability of compounds through BBB. Support-vector machine (SVM) method was used to create predictable and reliable QSPR model that wasfurther employed to predict logPe values of new designed dual antagonists of 5-HT2A/D2 receptorsand I2-IR ligands, classifying them into a group of highly permeable compounds. Steered moleculardynamics (SMD) simulations have been carried out to additionally explain and visualize the entireBBB permeation pathway at the molecular level

A multiscale biophysical platform for charting design-specific interactions of nanoparticles with model cellular membranes

In this thesis, we outline the development of a multiscale physics-based platform for exploring and ultimately predicting the design-specific interaction of ~1-10 nm particles with model cellular membranes. Nanoparticles (NP) are ever-present in foods and beverages, cosmetics, packaging, cooking products, fertilizers, pesticides, and novel pharmaceuticals, and pose significant challenges related to their increased consumer, occupational, and environmental exposure and their unique bioactivity relative to small molecules and large colloids. Thanks to rapidly advancing fabrication and characterization techniques, NPs are highly tunable in physicochemical properties such as size, surface chemistry, shape, elasticity, roughness, and crystallinity. Currently, however, the influence of these NP design parameters is highly underdeveloped, and difficult to reproducibly demonstrate in in vivo, in vitro, and even model experiments. Specifically, NP interactions with and passive transport across cellular membranes play a significant role in pharmacological and consumer product performance (biodistribution) as well as adverse outcome pathways in toxicology. We thus focus on the fundamental problem of design-specific interactions between NPs and cellular membranes, modeled to a first approximation as lipid bilayers.To provide accurate, efficient, and robust predictions for a range of NP designs, we construct a first-of-its kind, multiscale physics-based platform linking detailed molecular dynamics (MD) simulations, continuum mechanical theory, and multi-compartment modeling. Using this platform, we examine the two most influential design parameters--size and surface chemistry--and through two main case studies: (1) the membrane permeability of sub-nanometer particles and (2) the thermodynamic stability of larger-scale, ~1-10 nm particle-membrane interactions. Within (1), we first simulate the NP-membrane interactions and transport in full detail to test the validity of Overton's Rule, a longstanding structure-property relationship, and the inhomogeneous solubility-diffusion (ISD) model, a microscopic mechanistic continuum model for transport. We show that Overton's Rule is overly simplified for describing transport across a fluctuating lipid bilayer membrane, yet that ISD model holds for small enough particles. Within this range of particles where the solubility-diffusion mechanism holds, we directly link the impact of particle chemistry in the MD simulations to transient (time-dependent) transport outcomes in the macroscopic multi-compartmental models. This allows us to both compare with and evaluate models used in experimental permeability assays and close the orders of magnitude gap between simulation-predicted and experimentally-calculated permeabilities. We also leverage our platform to construct improved structure-property relationships for the steady-state membrane permeability and structure-kinetic relationships, accounting for a wider range of particle chemistries and highlighting the imperative of time in dictating the design rules for membrane permeation.Within case study (2), we probe larger NP-membrane interactions that implicate macroscopic membrane deformations and restructuring. Using the molecular simulations, we map out in particle size and chemistry space the putative NP-membrane interaction configurations, some of which resemble and agree with small-scale solubility-diffusion theory or large-scale membrane elastic theory (e.g. for lipid bilayer or monolayer wrapping of the NP) in stability limits and free energies and some of which require closer examination in the simulation to explain the thermodynamics. We also discover an entirely novel mechanism of interaction for ~4 nm, rough crystalline hydrophobic particles that we call "asymmetric leaflet hopping," wherein the particle preferentially inserts in one bilayer leaflet, forming a pre-pore in the membrane and inducing large-scale membrane curvature, and flips to the other leaflet over extended time scales.We conclude with preliminary phenomenologies to outline the phase behavior of ~1-10 nm particles of varying chemistry, as well as other areas where our platform shows great promise. By accounting for a vast range of NP designs, natural lipid diversity (lipidomics), and variable compartmental size, boundary layer, and transient conditions, this platform has the potential to more intuitively and effectively inform systems-level physiologically-based pharmacokinetic models for NP biodistribution predictions, as well as structure-activity relationships for direct predictions of product efficacy and toxicity. The end result of this multiscale platform is that we can directly link a NP's microscopic physicochemical properties to its macroscopic outcomes in a dynamic biodistribution setting

Pharmacophore analysis, design and in vitro testing of multi-target ligands as potentially effective therapeutics of complex neurological and mental disorders

Disfunkcija serotoninske i dopaminske neurotransmisije u mozgu je u osnovi patofiziologije brojnih neuroloških i mentalnih oboljenja. Definisanje protokola koji integriše in silico i in vitro metode, u cilju prouĉavanja farmakofore multi-potentnih jedinjenja koja deluju na nivou centralnog nervnog sistema (CNS), predstavlja vaţan korak u racionalizaciji procesa otkrivanja novih lekova. Primenom simulacija molekulske dinamike i molekulskog dokinga, kao i analize kvantitativnog odnosa strukture i aktivnosti (eng. 3D-Quantitative Structure Activity Relationship, 3D-QSAR) definisane su kljuĉne strukturne karakteristike dualnih antagonista 5-HT2A i D2 receptora, sa smanjenim afinitetom za H1 receptor. Na osnovu dobijenih rezultata izvršeno je pretraţivanje baza fragmenata primenom metode virtuelnog skrininga (eng. Virtual Screening, VS) u cilju dizajniranja potencijalno bezbednijih i efikasnijih liganada sa višestrukim delovanjem (eng. multi-target), pruţajući smernice za razvoj novih lekova u terapiji sloţenih CNS oboljenja. 3D-QSAR analizom bicikliĉnih α-iminofosfonata definisana je struktura farmakofore selektivnih liganada imidazolinskih I2 receptora, kao potencijalno novih lekova za leĉenje kognitivnih poremećaja. In vitro paralelni test permeabilnosti na veštaĉkim membranama (eng. Parallel Artificial Membrane Permeability Assay, PAMPA) je korišćen za odreĊivanje efektivne permeabilnosti (logPe) kroz krvno-moţdanu barijeru (KMB) jedinjenja koja utiĉu na modulaciju aktivnosti serotoninskog i dopaminskog sistema u mozgu. Dobijeni rezultati su korišćeni u analizi kvantitativnog odnosa strukture i osobina (eng. Quantitative Structure-Property Relationship, QSPR) u cilju razumevanja strukturnih karakteristika koje najviše utiĉu na prolazak jedinjenja kroz KMB. Model formiran primenom metode podrţavajućih vektora (eng. Support-Vector Machine, SVM) i validiran opseţnom statistiĉkom analizom, je korišćen za predviĊanje logPe vrednosti dizajniranih dualnih antagonista i liganada I2 receptora, svrstavajući ih u grupu visoko permeabilnih jedinjenja. Sa ciljem da se dodatno analizira i vizuelizuje proces permeabilnosti centralnodelujućih jedinjenja kroz KMB na molekulskom nivou, korišćene su simulacije usmerene molekulske dinamike (eng. Steered Molecular Dynamics, SMD).Disturbances in serotoninergic and dopaminergic neurotransmissions in the central nervous system (CNS) play a key role in the pathophysiology of various neurological and mental disorders. Developing an integrative approach through application of in silico and in vitro methods, in order to analyse pharmacophore of multi-target neuroactive compounds, presents a promising strategy in rationalization of drug design process. Molecular dynamics simulations and molecular docking methods in combination with 3D-quantitative structure activity relationship analysis (3D-QSAR) were used to evaluate crucial structural features of potent dual antagonists of 5-HT2A i D2 receptors, with lower antagonistic activity on H1 receptors. The virtual screening of the available fragment libraries was performed with the aim to design novel multi-target compounds with a more effective and safer profile, laying a good foundation for the therapy of complex brain diseases. Moreover, 3D-QSAR analysis of bicyclic α-iminophosphonates was used to reveal the pharmacophore structure of selective imidazoline I2 receptor (I2-IR) ligands, as potentially new drugs for the treatment of cognitive disorders. In vitro parallel artificial membrane permeability assay (PAMPA) was further employed to examine the effective permeability (logPe) through blood brain barrier (BBB) of compounds that affect serotonin and dopamine levels in the CNS. Based on the obtained results, quantitative structure-property relationship (QSPR) analysis was performed with the aim to define structural features that mostly affect the permeability of compounds through BBB. Support- vector machine (SVM) method was used to create predictable and reliable QSPR model that was further employed to predict logPe values of new designed dual antagonists of 5-HT2A/D2 receptors and I2-IR ligands, classifying them into a group of highly permeable compounds. Steered molecular dynamics (SMD) simulations have been carried out to additionally explain and visualize the entire BBB permeation pathway at the molecular level

Statistical learning approaches for predicting pharmacological properties of pharmaceutical agents

Ph.DDOCTOR OF PHILOSOPH