Leveraging Atropisomerism to Obtain a Selective Inhibitor of RET Kinase with Secondary Activities Towards EGFR Mutants

2019 ◽  
Author(s):  
Sean T. Toenjes ◽  
Valeria Garcia ◽  
Sean M. Maddox ◽  
Greg A. Dawson ◽  
Maria A. Ortiz ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Kinase Inhibitor ◽  
Potent Inhibitor ◽  
Narrow Range ◽  
Selective Inhibitor ◽  
Low Energy ◽  
Conformational Space ◽  
Drug Resistant ◽  
Compound Promiscuity

<p>Unstable atropisomerism is innate in many common scaffolds in drug discovery, commonly existing as freely rotating aryl-aryl bonds. Such compounds can access the majority of dihedral conformations around the bond axis, however most small-molecules bind their target within a narrow range of these available conformations. The remaining accessible conformations can interact with other proteins leading to compound promiscuity. Herein, we leverage atropisomerism to restrict the accessible low energy dihedral conformations available to a promiscuous kinase inhibitor and achieve highly selective and potent inhibitors of the oncogenic target RET kinase. We then evaluate our lead inhibitor against kinases that were predicted to bind compounds in a similar conformational window to RET, discovering a potent inhibitor of drug resistant EGFR mutants including L858R/T790M/C797S EGFR. Leveraging atropisomerism to restrict accessible conformational space should be a generally applicable strategy due to the prevalence of unstable atropisomerism in drug discovery.</p>

Leveraging Atropisomerism to Obtain a Selective Inhibitor of RET Kinase with Secondary Activities Towards EGFR Mutants

2019 ◽  
Author(s):  
Sean T. Toenjes ◽  
Valeria Garcia ◽  
Sean M. Maddox ◽  
Greg A. Dawson ◽  
Maria A. Ortiz ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Kinase Inhibitor ◽  
Potent Inhibitor ◽  
Narrow Range ◽  
Selective Inhibitor ◽  
Low Energy ◽  
Conformational Space ◽  
Drug Resistant ◽  
Compound Promiscuity

<p>Unstable atropisomerism is innate in many common scaffolds in drug discovery, commonly existing as freely rotating aryl-aryl bonds. Such compounds can access the majority of dihedral conformations around the bond axis, however most small-molecules bind their target within a narrow range of these available conformations. The remaining accessible conformations can interact with other proteins leading to compound promiscuity. Herein, we leverage atropisomerism to restrict the accessible low energy dihedral conformations available to a promiscuous kinase inhibitor and achieve highly selective and potent inhibitors of the oncogenic target RET kinase. We then evaluate our lead inhibitor against kinases that were predicted to bind compounds in a similar conformational window to RET, discovering a potent inhibitor of drug resistant EGFR mutants including L858R/T790M/C797S EGFR. Leveraging atropisomerism to restrict accessible conformational space should be a generally applicable strategy due to the prevalence of unstable atropisomerism in drug discovery.</p>

Understanding Conformational Entropy in Small Molecules

2020 ◽  
Author(s):  
Lucian Chan ◽  
Garrett Morris ◽  
Geoffrey Hutchison
Keyword(s):  
Small Molecules ◽  
Degrees Of Freedom ◽  
Absolute Error ◽  
Low Energy ◽  
Standard Entropy ◽  
Free Energies ◽  
Conformational Entropy ◽  
Wide Range ◽  
High Degree ◽  
Empirical Corrections

The calculation of the entropy of flexible molecules can be challenging, since the number of possible conformers grows exponentially with molecule size and many low-energy conformers may be thermally accessible. Different methods have been proposed to approximate the contribution of conformational entropy to the molecular standard entropy, including performing thermochemistry calculations with all possible stable conformations, and developing empirical corrections from experimental data. We have performed conformer sampling on over 120,000 small molecules generating some 12 million conformers, to develop models to predict conformational entropy across a wide range of molecules. Using insight into the nature of conformational disorder, our cross-validated physically-motivated statistical model can outperform common machine learning and deep learning methods, with a mean absolute error ≈4.8 J/mol•K, or under 0.4 kcal/mol at 300 K. Beyond predicting molecular entropies and free energies, the model implies a high degree of correlation between torsions in most molecules, often as- sumed to be independent. While individual dihedral rotations may have low energetic barriers, the shape and chemical functionality of most molecules necessarily correlate their torsional degrees of freedom, and hence restrict the number of low-energy conformations immensely. Our simple models capture these correlations, and advance our understanding of small molecule conformational entropy.

Aim for the Readers! Bromodomains As New Targets Against Chagas’ Disease

2019 ◽  
Vol 26 (36) ◽  
pp. 6544-6563
Author(s):  
Victoria Lucia Alonso ◽  
Luis Emilio Tavernelli ◽  
Alejandro Pezza ◽  
Pamela Cribb ◽  
Carla Ritagliati ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Chagas Disease ◽  
Causative Agent ◽  
Current Knowledge ◽  
Sequence Similarity ◽  
Lysine Acetylation ◽  
Specific Manner ◽  
Lysine Residues ◽  
Antiparasitic Drugs

Bromodomains recognize and bind acetyl-lysine residues present in histone and non-histone proteins in a specific manner. In the last decade they have raised as attractive targets for drug discovery because the miss-regulation of human bromodomains was discovered to be involved in the development of a large spectrum of diseases. However, targeting eukaryotic pathogens bromodomains continues to be almost unexplored. We and others have reported the essentiality of diverse bromodomain- containing proteins in protozoa, offering a new opportunity for the development of antiparasitic drugs, especially for Trypansoma cruzi, the causative agent of Chagas’ disease. Mammalian bromodomains were classified in eight groups based on sequence similarity but parasitic bromodomains are very divergent proteins and are hard to assign them to any of these groups, suggesting that selective inhibitors can be obtained. In this review, we describe the importance of lysine acetylation and bromodomains in T. cruzi as well as the current knowledge on mammalian bromodomains. Also, we summarize the myriad of small-molecules under study to treat different pathologies and which of them have been tested in trypanosomatids and other protozoa. All the information available led us to propose that T. cruzi bromodomains should be considered as important potential targets and the search for smallmolecules to inhibit them should be empowered.

scholarly journals Druggable Transient Pockets in Protein Kinases

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 651
Author(s):  
Koji Umezawa ◽  
Isao Kii
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Protein Kinases ◽  
Binding Sites ◽  
Kinase Inhibitors ◽  
Screening Methods ◽  
Research Attention ◽  
Folding Process ◽  
Chemical Screening ◽  
Inhibitory Mechanisms

Drug discovery using small molecule inhibitors is reaching a stalemate due to low selectivity, adverse off-target effects and inevitable failures in clinical trials. Conventional chemical screening methods may miss potent small molecules because of their use of simple but outdated kits composed of recombinant enzyme proteins. Non-canonical inhibitors targeting a hidden pocket in a protein have received considerable research attention. Kii and colleagues identified an inhibitor targeting a transient pocket in the kinase DYRK1A during its folding process and termed it FINDY. FINDY exhibits a unique inhibitory profile; that is, FINDY does not inhibit the fully folded form of DYRK1A, indicating that the FINDY-binding pocket is hidden in the folded form. This intriguing pocket opens during the folding process and then closes upon completion of folding. In this review, we discuss previously established kinase inhibitors and their inhibitory mechanisms in comparison with FINDY. We also compare the inhibitory mechanisms with the growing concept of “cryptic inhibitor-binding sites.” These sites are buried on the inhibitor-unbound surface but become apparent when the inhibitor is bound. In addition, an alternative method based on cell-free protein synthesis of protein kinases may allow the discovery of small molecules that occupy these mysterious binding sites. Transitional folding intermediates would become alternative targets in drug discovery, enabling the efficient development of potent kinase inhibitors.

scholarly journals The human Aurora kinase inhibitor danusertib is a lead compound for anti-trypanosomal drug discovery via target repurposing

2013 ◽  
Vol 62 ◽  
pp. 777-784 ◽  
Author(s):  
Stefan O. Ochiana ◽  
Vidya Pandarinath ◽  
Zhouxi Wang ◽  
Rishika Kapoor ◽  
Mary Jo Ondrechen ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Kinase Inhibitor ◽  
Aurora Kinase ◽  
Lead Compound ◽  
Aurora Kinase Inhibitor ◽  
Target Repurposing

scholarly journals Dynamical Behavior and Conformational Selection Mechanism of the Intrinsically Disordered Sic1 Kinase-Inhibitor Domain

Life ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 110 ◽  
Author(s):  
Davide Sala ◽  
Ugo Cosentino ◽  
Anna Ranaudo ◽  
Claudio Greco ◽  
Giorgio Moro
Keyword(s):  
Kinase Inhibitor ◽  
Dynamical Behavior ◽  
Md Simulations ◽  
Molecular Shape ◽  
Conformational Space ◽  
Coarse Grained ◽  
Conformational Ensemble ◽  
Selection Mechanism ◽  
Conformational Selection ◽  
Intrinsically Disordered

Intrinsically Disordered Peptides and Proteins (IDPs) in solution can span a broad range of conformations that often are hard to characterize by both experimental and computational methods. However, obtaining a significant representation of the conformational space is important to understand mechanisms underlying protein functions such as partner recognition. In this work, we investigated the behavior of the Sic1 Kinase-Inhibitor Domain (KID) in solution by Molecular Dynamics (MD) simulations. Our results point out that application of common descriptors of molecular shape such as Solvent Accessible Surface (SAS) area can lead to misleading outcomes. Instead, more appropriate molecular descriptors can be used to define 3D structures. In particular, we exploited Weighted Holistic Invariant Molecular (WHIM) descriptors to get a coarse-grained but accurate definition of the variegated Sic1 KID conformational ensemble. We found that Sic1 is able to form a variable amount of folded structures even in absence of partners. Among them, there were some conformations very close to the structure that Sic1 is supposed to assume in the binding with its physiological complexes. Therefore, our results support the hypothesis that this protein relies on the conformational selection mechanism to recognize the correct molecular partners.

scholarly journals SAR by kinetics for drug discovery in protein misfolding diseases

2018 ◽  
Vol 115 (41) ◽  
pp. 10245-10250 ◽  
Author(s):  
Sean Chia ◽  
Johnny Habchi ◽  
Thomas C. T. Michaels ◽  
Samuel I. A. Cohen ◽  
Sara Linse ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Protein Misfolding ◽  
Amyloid Beta Peptide ◽  
Oligomer Formation ◽  
Chemical Derivatives ◽  
Structure Activity ◽  
Beta Peptide ◽  
Misfolding Diseases ◽  
Aβ Oligomer

To develop effective therapeutic strategies for protein misfolding diseases, a promising route is to identify compounds that inhibit the formation of protein oligomers. To achieve this goal, we report a structure−activity relationship (SAR) approach based on chemical kinetics to estimate quantitatively how small molecules modify the reactive flux toward oligomers. We use this estimate to derive chemical rules in the case of the amyloid beta peptide (Aβ), which we then exploit to optimize starting compounds to curtail Aβ oligomer formation. We demonstrate this approach by converting an inactive rhodanine compound into an effective inhibitor of Aβ oligomer formation by generating chemical derivatives in a systematic manner. These results provide an initial demonstration of the potential of drug discovery strategies based on targeting directly the production of protein oligomers.

scholarly journals Discovery and Optimization of Selective Inhibitors of Meprin α (Part II)

2020 ◽  
Author(s):  
Chao Wang ◽  
Juan Diez ◽  
Hajeung Park ◽  
Christoph Becker-Pauly ◽  
Gregg B. Fields ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Small Molecule ◽  
Hydroxamic Acid ◽  
Therapeutic Potential ◽  
Preceding Paper ◽  
Close Relative ◽  
Specific Inhibition ◽  
Selective Inhibitors

Meprin &alpha; is a zinc metalloproteinase (metzincin) that has been implicated in multiple diseases, including fibrosis and cancers. It has proven difficult to find small molecules that are capable of selectively inhibiting meprin &alpha;, or its close relative meprin &beta;, over numerous other metzincins which, if inhibited, would elicit unwanted effects. We recently identified possible molecular starting points for meprin &alpha;-specific inhibition through an HTS effort (see part I, preceding paper). In part II we report the optimization of a potent and selective hydroxamic acid meprin &alpha; inhibitor probe which may help define the therapeutic potential for small molecule meprin &alpha; inhibition and spur further drug discovery efforts in the area of zinc metalloproteinase inhibition.

scholarly journals A New Big-Data Paradigm for Target Identification and Drug Discovery

2017 ◽  
Author(s):  
Neel S. Madhukar ◽  
Prashant K. Khade ◽  
Linda Huang ◽  
Kaitlyn Gayvert ◽  
Giuseppe Galletti ◽  
...  
Keyword(s):  
Drug Discovery ◽  
Small Molecules ◽  
Clinical Application ◽  
Small Molecule ◽  
Target Identification ◽  
Clinical Development ◽  
Data Types ◽  
Public Data ◽  
Drug Target Identification ◽  
Approved Drugs

AbstractDrug target identification is one of the most important aspects of pre-clinical development yet it is also among the most complex, labor-intensive, and costly. This represents a major issue, as lack of proper target identification can be detrimental in determining the clinical application of a bioactive small molecule. To improve target identification, we developed BANDIT, a novel paradigm that integrates multiple data types within a Bayesian machine-learning framework to predict the targets and mechanisms for small molecules with unprecedented accuracy and versatility. Using only public data BANDIT achieved an accuracy of approximately 90% over 2000 different small molecules – substantially better than any other published target identification platform. We applied BANDIT to a library of small molecules with no known targets and generated ∼4,000 novel molecule-target predictions. From this set we identified and experimentally validated a set of novel microtubule inhibitors, including three with activity on cancer cells resistant to clinically used anti-microtubule therapies. We next applied BANDIT to ONC201 – an active anti- cancer small molecule in clinical development – whose target has remained elusive since its discovery in 2009. BANDIT identified dopamine receptor 2 as the unexpected target of ONC201, a prediction that we experimentally validated. Not only does this open the door for clinical trials focused on target-based selection of patient populations, but it also represents a novel way to target GPCRs in cancer. Additionally, BANDIT identified previously undocumented connections between approved drugs with disparate indications, shedding light onto previously unexplained clinical observations and suggesting new uses of marketed drugs. Overall, BANDIT represents an efficient and highly accurate platform that can be used as a resource to accelerate drug discovery and direct the clinical application of small molecule therapeutics with improved precision.

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