Optimizing the Performance of In Silico ADMET General Models According to Local Requirements: MARS Approach. Solubility Estimations As Case Study

Inducing heat shock protein 70 expression provides a robust antithrombotic effect with minimal bleeding risk

Antithrombotic medications target coagulation factors. Their use is associated with an increased bleeding risk. Safer drugs are needed. The heat shock protein 70 (Hsp70) exhibits antithrombotic properties that do not influence bleeding. By using murine models, we aimed to test the hypothesis that overexpressing Hsp70 with CM-695, a first in class dual inhibitor of HDAC6 and phosphodiesterase 9, protects against thrombosis while leaves bleeding tendency unaltered. CM-695 was used to induce Hsp70 overexpression. Hsp70 overexpressing mice were submitted to three thrombosis-triggering procedures. The ferric chloride carotid artery model was used to compare the antithrombotic role of CM-695 and rivaroxaban, a direct oral anticoagulant. The mouse tail transection model was used to compare the bleeding tendency upon CM-695 or rivaroxaban administration. Intraperitoneal (i. p.) 20 mg/kg CM-695 increased Hsp70 expression markedly in the murine aortic tissue. This treatment delayed thrombosis in the collagen/epinephrine [p=0.04 (Log-Rank test), n=10], Rose Bengal/laser [median vessel occlusion time (OT): 58.6 vs 39.0 minutes (min) in the control group (CG), p=0.008, n≥10] and ferric chloride (OT: 14.7 vs 9.2 min in the CG, p=0.032, n≥10) models. I.p. 80 mg/kg CM-695 (n≥9) and intravenous 3 mg/kg rivaroxaban (n≥8) significantly delayed thrombosis. CM-695 did not induce bleeding [median bleeding time (BT): 8.5 vs 7.5 min in the CG, n≥10]. However, BT was dramatically increased by rivaroxaban (30.0 vs 13.7 min in the CG, p=0.001, n=10). In conclusion, CM-695 is a new antithrombotic small molecule devoid of bleeding risk that may be envisioned as a useful clinical tool.

Impact of Scaffold Exploration on Novel Dual-Acting Histone Deacetylases and Phosphodiesterase 5 Inhibitors for the Treatment of Alzheimer's Disease

A novel systems therapeutics approach, involving simultaneous inhibition of phosphodiesterase 5 (PDE5) and histone deacetylase (HDAC), has been validated as a potentially novel therapeutic strategy for the treatment of Alzheimer's disease (AD). First-in-class dual inhibitors bearing a sildenafil core have been very recently reported, and the lead molecule 7 has proven this strategy in AD animal models. Because scaffolds may play a critical role in primary activities and ADME-Tox profiling as well as on intellectual property, we have explored alternative scaffolds (vardenafil- and tadalafil-based cores) and evaluated their impact on critical parameters such as primary activities, permeability, toxicity, and in vivo (pharmacokinetics and functional response in hippocampus) to identify a potential alternative lead molecule bearing a different chemotype for in vivo testing.

Simulation of in vitro dissolution behavior using DDDPlus™

Dissolution testing is a performance test for many dosage forms including tablets and capsules. The objective of this study was to evaluate if computer simulations can predict the in vitro dissolution of two model drugs for which different dissolution data were available. Published montelukast sodium and glyburide dissolution data was used for the simulations. Different pharmacopeial and biorelevant buffers, volumes, and rotations speeds were evaluated. Additionally, a pH change protocol was evaluated using these buffers. DDDPlus™ 3, Beta version (Simulation Plus, Inc.), was used to simulate the in vitro dissolution data. The simulated data were compared with the in vitro data. A regression coefficient between predicted and observed data was used to assess the simulations. The statistical analysis of Montelukast sodium showed that there was a significant correlation between the in vitro release data and the predicted data for all cases except for one buffer. For glyburide, there was also a significant correlation between the experimental data and the predicted data using single pH conditions. Using the dynamic pH protocol, a correlation was significant for one biorelevant media. The simulations showed that both in vitro drug releases were sensitive to solubility effects which confirmed their BCS class II category. Computer simulations of the in vitro release using DDDPlus™ have the potential to estimate the in vivo dissolution at an early stage in the drug development process. This might be used to choose the most appropriate dissolution condition to establish IVIVC and to develop biorelevant in vitro performance tests to capture critical product attributes for quality control procedures in quality by design environments.

Discovery of selective ligands for telomeric RNA G-quadruplexes (TERRA) through 19F-NMR based fragment screening

Telomeric repeat-containing RNA (TERRA) is a novel and very attractive antitumoral target. Here, we report the first successful application of (19)F-NMR fragment-based screening to identify chemically diverse compounds that bind to an RNA molecule such as TERRA. We have built a library of 355 fluorinated fragments, and checked their interaction with a long telomeric RNA as a target molecule. The screening resulted in the identification of 20 hits (hit rate of 5.6%). For a number of binders, their interaction with TERRA was confirmed by (19)F- and (1)H NMR as well as by CD melting experiments. We have also explored the selectivity of the ligands for RNA G-quadruplexes and found that some of the hits do not interact with other nucleic acids such as tRNA and duplex DNA and, most importantly, favor the propeller-like parallel conformation in telomeric DNA G-quadruplexes. This suggests a selective recognition of this particular quadruplex topology and that different ligands may recognize specific sites in propeller-like parallel G-quadruplexes. Such features make some of the resulting binders promising lead compounds for fragment based drug discovery.

Prediction of physicochemical properties

Physicochemical properties are key factors in controlling the interactions of xenobiotics with living organisms. Computational approaches to toxicity prediction therefore generally rely to a very large extent on the physicochemical properties of the query compounds. Consequently it is important that reliable in silico methods are available for the rapid calculation of physicochemical properties. The key properties are partition coefficient, aqueous solubility, and pKa and, to a lesser extent, melting point, boiling point, vapor pressure, and Henry's law constant (air-water partition coefficient). The calculation of each of these properties from quantitative structure-property relationships (QSPRs) and from available software is discussed in detail, and recommendations made. Finally, detailed consideration is given of guidelines for the development of QSPRs and QSARs.

Computational medicinal chemistry in fragment-based drug discovery: what, how and when

The use of fragment-based drug discovery (FBDD) has increased in the last decade due to the encouraging results obtained to date. In this scenario, computational approaches, together with experimental information, play an important role to guide and speed up the process. By default, FBDD is generally considered as a constructive approach. However, such additive behavior is not always present, therefore, simple fragment maturation will not always deliver the expected results. In this review, computational approaches utilized in FBDD are reported together with real case studies, where applicability domains are exemplified, in order to analyze them, and then, maximize their performance and reliability. Thus, a proper use of these computational tools can minimize misleading conclusions, keeping the credit on FBDD strategy, as well as achieve higher impact in the drug-discovery process. FBDD goes one step beyond a simple constructive approach. A broad set of computational tools: docking, R group quantitative structure–activity relationship, fragmentation tools, fragments management tools, patents analysis and fragment-hopping, for example, can be utilized in FBDD, providing a clear positive impact if they are utilized in the proper scenario – what, how and when. An initial assessment of additive/non-additive behavior is a critical point to define the most convenient approach for fragments elaboration.