In silico Methods for Design of Kinase Inhibitors as Anticancer Drugs

Rational drug design implies usage of molecular modeling techniques such as pharmacophore modeling, molecular dynamics, virtual screening, and molecular docking to explain the activity of biomolecules, define molecular determinants for interaction with the drug target, and design more efficient drug candidates. Kinases play an essential role in cell function and therefore are extensively studied targets in drug design and discovery. Kinase inhibitors are clinically very important and widely used antineoplastic drugs. In this review, computational methods used in rational drug design of kinase inhibitors are discussed and compared, considering some representative case studies

Comparative amino acid decomposition analysis of potent type I p38α inhibitors

Background and purpose of the study: p38α is a member of mitogen-activated protein kinases (MAPK) considered as a prominent target in development of anti-inflammatory agents. Any abnormality in the phosphorylation process leads to the different human diseases such as cancer, diabetes and inflammatory diseases. Several small molecule p38α inhibitors have been developed up to now. In this regard, structural elucidation of p38 inhibitors needs to be done enabling us in rational lead development strategies. Methodes: Various interactions of three potent inhibitors with p38α active site have been evaluated in terms of binding energies and bond lengths via density function theory and MD simulations. Results: Our comparative study showed that both ab initio and MD simulation led to the relatively similar results in pharmacophore discrimination of p38α inhibitors. Conclusion: The results of the present study may find their usefulness in pharmacophore based modification of p38α inhibitors

VIRTUAL SCREENING FOR JNK INHIBITORS AND PREDICTION OF PXR ACTIVITY USING COMPUTATIONAL MODELS

Ph.DDOCTOR OF PHILOSOPH

In Silico Strategies for Prospective Drug Repositionings

The discovery of new drugs is one of pharmaceutical research's most exciting and challenging tasks. Unfortunately, the conventional drug discovery procedure is chronophagous and seldom successful; furthermore, new drugs are needed to address our clinical challenges (e.g., new antibiotics, new anticancer drugs, new antivirals).Within this framework, drug repositioning—finding new pharmacodynamic properties for already approved drugs—becomes a worthy drug discovery strategy.Recent drug discovery techniques combine traditional tools with in silico strategies to identify previously unaccounted properties for drugs already in use. Indeed, big data exploration techniques capitalize on the ever-growing knowledge of drugs' structural and physicochemical properties, drug–target and drug–drug interactions, advances in human biochemistry, and the latest molecular and cellular biology discoveries.Following this new and exciting trend, this book is a collection of papers introducing innovative computational methods to identify potential candidates for drug repositioning. Thus, the papers in the Special Issue In Silico Strategies for Prospective Drug Repositionings introduce a wide array of in silico strategies such as complex network analysis, big data, machine learning, molecular docking, molecular dynamics simulation, and QSAR; these strategies target diverse diseases and medical conditions: COVID-19 and post-COVID-19 pulmonary fibrosis, non-small lung cancer, multiple sclerosis, toxoplasmosis, psychiatric disorders, or skin conditions

Prediction of Selective Neuroprotective JNK3 Inhibitory Activity of Plumbagin and Its derivatives using Insilico Computational Methods

In the present work, rational approach combining e- pharmacophore modelling and structure based virtual screening was employed on the target JNK3 to identify potential JNK3 inhibitors. The pharmacophore-based approaches are well known for their strength to propose a diverse set of molecules having diverse molecular frameworks but owing to a desired biological activity for one target. The hits were further analyzed and ranked by using dock score, binding energy, ADME parameters and MD simulations. Plumbagin derivatives have shown good potential of binding with the targeted protein as indicated by ΔGbind score. They also possessed desired ADME properties. Thereafter, MD simulation studies were carried out two best docked complexes. Based on the key amino acid residues interactions, molecular dynamics simulation sindicates that the docked complex of 5-Methoxy-2-methyl-(4(trifluoromethyl) benzylamino) naphthalene1, 4-dione and shikonin with JNK3 protein (3OY1) have a good stability in the binding pocket. The significant interaction with residue MET 149 was observed in both molecular docking and molecular dynamics simulations studies. By confirm the binding affinities of the ligand and the accurate interactions, molecular dynamics simulations valid the results of molecular docking. The results showed that the best classified compounds 5-Methoxy- 2-methyl-3-(4(trifluoromethyl)benzylamino) naphthalene1, 4-dione and shikonin with highest docking score and binding affinity and stable hydrogen bond with MET149 and hydrophobic interactions with Met146, Val79, Val145, Leu144, Ala91, Ile92, Ile124, and Leu128. relative to reference compounds. The outcome reveal that this study provides evidence for the consideration of plumbagin derivatives as pontential JNK3 inhibitors. Therefore, reliable computer-aided drug design methods could play an increasingly important role in the future drug discovery process. The Insilico studies results revealed that 5-Methoxy-2-methyl-3-(4 (trifluoromethyl) benzylamino) naphthalene1,4-dione and Shikonin as a potent, selective JNK3 inhibitors. This was found out by screening of generated pharmacophore hypothesis, molecular docking and molecular dynamics study of plumbagin and its derivatives. Further, in vitro evaluation of 5-Methoxy-2-methyl-3-(4-(trifluoromethyl) benzylamino) naphthalene1,4-dione and Shikonin is the futuristic requirement in order to perceive additional activity validation

Protein kinases: Structure modeling, inhibition, and protein-protein interactions

Human protein kinases belong to a large and diverse enzyme family that contains more than 500 members. Deregulation of protein kinases is associated with many disorders, and this is why protein kinases are attractive targets for drug discovery. Due to the high conservation of the ATP binding pocket among this family, designing specific and/or selective inhibitors against certain member(s) is challenging. Several studies have been conducted on protein kinases to validate them as suitable drug targets. Although there are numerous target-validated protein kinases, the efforts to develop small molecule inhibitors have so far led to only a limited number of therapeutic agents and drug candidates. In our studies, we tried to understand the basic structural features of protein kinases using available computational tools. There are wide structural variations between different states of the same protein kinase that affect the enzyme specificity and inhibition. Many protein kinases do not yet have an available X-ray crystal structure and have not yet been validated to be drug targets. For these reasons, we developed a new homology modeling approach to facilitate modeling non-crystallized protein kinases and protein kinase states. Our homology modeling approach was able to model proteins having long amino acid sequences and multiple protein domains with reliable model quality and a manageable amount of computational time. Then, we checked the applicability of different docking algorithms (the routinely used computational methodology in virtual screening) in protein kinase studies. After performing the basic study of kinase structure modeling, we focused our research on cyclin dependent kinase 2 (CDK2) and glycogen synthase kinase-3β (GSK-3β). We prepared a non-redundant database from 303 available CDK2 PDB structures. We removed all structural anomalies and proceeded to use the CDK2 database in studying CDK2 structure in its different states, upon ATP, ligand and cyclin binding. We clustered the database based on our findings, and the CDK2 clusters were used to generate protein ligand interaction fingerprints (PLIF). We generated a PLIF-based pharmacophore model which is highly selective for CDK2 ligands. A virtual screening workflow was developed making use of the PLIF-based pharmacophore model, ligand fitting into the CDK2 active site and selective CDK2 shape scoring. We studied the structural basis for selective inhibition of CDK2 and GSK-3β. We compared the amino acid sequence, the 3D features, the binding pockets, contact maps, structural geometry, and Sphoxel maps. From this study we found 1) the ligand structural features that are required for the selective inhibition of CDK2 and GSK-3β, and 2) the amino acid residues which are essential for ligand binding and selective inhibition. We used the findings of this study to design a virtual screening workflow to search for selective inhibitors for CDK2 and GSK-3β. Because protein–protein interactions are essential in the function of protein kinases, and in particular of CDK2, we used protein–protein docking knowledge and binding energy calculations to examine CDK2 and cyclin binding. We applied this study to the voltage dependent calcium channel 1 (VDAC1) binding to Bax. We were able to provide important data relevant to future experimental researchers such as on the possibility of Bax to cross biological membranes and the most relevant amino acid residues in VDAC1 that interact with Bax

Sensitizing triple negative breast cancer to approved therapies: Design, synthesis and biological activity of MNK inhibitors

La desregulació de la síntesi de proteïnes és comuna en càncer. Un factor clau en el control de la traducció de proteïnes és el factor d'inici de la traducció 4E (eIF4E) que es troba regulat per les cinases MNK1/2 (MAP kinase interacting kinases 1 i 2) mitjançant fosforilació. En els últims anys, l’eIF4E s'ha descrit com un factor de pronòstic independent associat amb la progressió maligna i el desenvolupament de resistència. A més, l’eIF4E es troba sobreexpressat en càncer d'ovari, mama, pulmó, bufeta i pròstata. La fosforilació de l'eIF4E és necessària per a la transformació tumoral però és prescindible per al desenvolupament normal. Per tant, la inhibició farmacològica de les MNKs pot proporcionar una estratègia no tòxica i eficaç per al tractament del càncer, especialment en combinació amb els tractaments aprovats. En aquest projecte, es proposen els sistemes pirazolo[3,4-b]piridínics com a possibles candidats a inhibidors de MNK degut a la seva similitud amb inhibidors coneguts. S'han estudiat les possibilitats sintètiques que ofereixen aquestes estructures, definint metodologies generals per introduir substitucions selectives i controlades en 6 punts diferents de la molècula. A més, s'han descrit els mecanismes de reacció. S'han estudiat 5 famílies de compostos basades en les pirazolo[3,4-b]piridines i una de les famílies ha mostrat una activitat interessant en els assajos preliminars. S'han identificat tres compostos (EB1-3), amb valors micromolars de IC50 (0.7-4 μM), que inhibeixen de forma completa i selectiva les MNKs (entre 2.5 i 5 μM) i sense presentar citotoxicitat en cèl·lules de càncer de mama triple negatiu (MDA-MB-231). A més, el co tractament amb EB1 augmenta la sensibilitat de les cèl·lules MDA-MB-231 a la doxorubicina, millorant la seva eficàcia d'inhibir el creixement cel·lular. S'ha fet servir una estratègia de disseny basada en estructura per estudiar el mecanisme d'interacció dels diferents candidats. S'han creat models de les formes actives i inactives de MNK1 que s'han fet servir per predir la manera d'unió dels candidats. EB1 s'ha definit com un inhibidor de tipus II que s'uneix selectivament la forma inactiva de MNK1 i interacciona amb el motiu DFD (Asp-Phe-Asp), característic de les MNKs.La desregulación de la síntesis de proteínas es común en cáncer. Un factor clave en el control de la traducción de proteínas es el factor de inicio de la traducción 4E (eIF4E) cuya función está modulada por las quinasas MNK1/2 (MAP kinase interacting kinases 1 y 2) mediante fosforilación. En los últimos años, el eIF4E se ha descrito como un factor de pronóstico independiente asociado con la progresión maligna y el desarrollo de resistencia. Además, el eIF4E se encuentra sobreexpresado en cáncer de ovario, mama, pulmón, vejiga y próstata. La fosforilación del eIF4E es necesaria para la transformación tumoral pero es prescindible para el desarrollo normal. Por lo tanto, la inhibición farmacológica de las MNKs puede proporcionar una estrategia no tóxica y eficaz para el tratamiento del cáncer, especialmente en combinación con los tratamientos aprobados. En este proyecto, se proponen los sistemas pirazolo[3,4-b]piridínicos como posibles candidatos a inhibidores de MNK debido a su similitud con inhibidores conocidos. Se han estudiado las posibilidades sintéticas que ofrecen estas estructuras, definiendo metodologías generales para introducir sustituciones selectivas y controladas en 6 puntos diferentes de la molécula. Además, se han descrito los mecanismos de reacción. Se han estudiado 5 familias de compuestos basados en los compuestos pirazolo[3,4-b]piridínicos y una de las familias ha mostrado una actividad interesante en los ensayos preliminares. Se han identificado tres compuestos (EB1-3), con valores micromolares de IC50 (0.7 a 4 μM), que inhiben de forma completa y selectiva las MNKs (entre 2.5 y 5 μM) y sin presentar citotoxicidad en células de cáncer de mama triple negativo (MDA-MB-231). Además, el co-tratamiento con EB1 aumenta la sensibilidad de las células MDA-MB-231 a la doxorrubicina, mejorando su eficacia de inhibir el crecimiento celular. Se ha usado una estrategia de diseño basada en estructura para estudiar el mecanismo de interacción de los diferentes candidatos. Se han creado modelos de las formas activas e inactivas de MNK1 que se han usado para predecir el modo de unión de los hits. EB1 se ha definido como un inhibidor de tipo II que se une selectivamente la forma inactiva de MNK1 e interacciona con el motivo DFD (Asp-Phe-Asp), característico de las MNKs.Deregulation of protein synthesis is a common event in cancer. A key player in translational control is eIF4E whose function is modulated by the MAP kinase interacting kinases 1 and 2 (MNK1/2) through phosphorylation of a conserved serine (Ser209). In the recent years, eIF4E has been described as an independent prognostic factor associated with malignant progression and development of resistance. Moreover, eIF4E is found to be overexpressed in ovarian, breast, lung, colon, bladder and prostate cancer. eIF4E phosphorylation is necessary for oncogenic transformation while dispensable for normal development. Hence, pharmacologic MNK inhibitors may provide a non-toxic and effective anti-cancer strategy, especially in combination with approved treatments. In this project, the pyrazolo[3,4-b]pyridinic systems have been proposed as potential candidates as MNK inhibitors due to their similarity with known effective inhibitors. During this project, the synthetic possibilities offered by these scaffolds have been deeply studied defining general methodologies to achieve selective and controlled substitutions in 6 different points of the central core. Moreover, the reaction mechanisms have been described. Up to 5 families of compounds based on the pyrazolo[3,4-b]pyridine scaffold were studied and one of the families showed interesting activity on the preliminary assays. Three compounds (EB1-3), with IC50 values in the low μM range (0.7 to 4 μM), showed a complete and selective inhibition of MNKs (between 2.5 and 5 μM) and no significant cell toxicity in the triple negative breast cancer cell line MDA-MB-231. Moreover, co-treatment with EB1 clearly increased the sensitivity of MDA-MB 231 cells to doxorubicin improving the efficacy of the drug in inhibiting cell growth. A structure-based drug design strategy was applied to understand the mechanism of interaction of the different candidates. Models of the active/inactive forms of MNK1 were created and used to predict the binding mode of the hits. EB1 seems to be a type II inhibitor which selectively binds to the inactive form of MNK1 and interacts with the DFD (Asp-Phe-Asp) motif, a unique feature of MNKs