Rational identification of small molecules derived from 9,10-dihydrophenanthrene as potential inhibitors of 3CLpro enzyme for COVID-19 therapy: a computer-aided drug design approach

Abstract

Small molecules such as 9,10-dihydrophenanthrene derivatives have remarkable activity toward inhibition of SARS-CoV-2 3CL pro and COVID-19 proliferation, which show a strong correlation between their structures and bioactivity. Therefore, these small compounds could be suitable for clinical pharmaceutical use against COVID-19. The objective of this study was to remodel the structures of 9,10-dihydrophenanthrene derivatives to achieve a powerful biological activity against 3CL pro and favorable pharmacokinetic properties for drug design and discovery. Therefore, by the use of bioinformatics techniques, we developed robust 3D-QSAR models that are capable of describing the structure–activity relationship for 46 molecules based on 9,10-dihydrophenanthrene derivatives using CoMFA/SE ( R 2 = 0.97, Q 2 = 0.81, R 2 pred = 0.95, c R 2 p = 0.71) and CoMSIA/SEHDA ( R 2 = 0.94, Q 2 = 0.76, R 2 pred = 0.91, c R 2 p = 0.65) techniques. Accordingly, 96 lead compounds were generated based on a template molecule that showed the highest observed activity in vitro (T40, pIC 50 = 5.81) and predicted their activities and bioavailability in silico. The rational screening outputs of 3D-QSAR, Molecular docking, ADMET, and MM-GBSA led to the identification of 9 novel modeled molecules as potent noncovalent drugs against SARS-CoV-2-3CL pro . Finally, by molecular dynamics simulations, the stability and structural dynamics of 3CL pro free and complex (PDB code: 6LU7) were discussed in the presence of samples of 9,10-dihydrophenanthrene derivative in an aqueous environment. Overall, the retrosynthesis of the proposed drug compounds in this study and the evaluation of their bioactivity in vitro and in vivo may be interesting for designing and discovering a new drug effective against COVID-19. Supplementary Information The online version contains supplementary material available at 10.1007/s11224-022-02004-z.

Cyclohexane-1,3-dione Derivatives as Future Therapeutic Agents for NSCLC: QSAR Modeling, In Silico ADME-Tox Properties, and Structure-Based Drug Designing Approach

“…As a result, more research is needed to discover new compounds with structural properties suitable for safe drug use that are less toxic and more effective against the growth of cancer cell lines caused by the enzymatic activity of the c-Met protein than currently available drugs. For this reason, based on QSAR modeling, in our current work, we characterize the structures of small molecules based on cyclohexane-1,3-dione and identify the most important structural properties of these molecules that influence their biological activity against NSCLC. , For QSAR modeling, we used a combination of topological, physicochemical, and electronic DFT molecular descriptors that are commonly used for geometrical structural characterization. , The DFT computations were used because of their precision in providing precise indications on the electronic properties of the studied molecules, allowing for the generation of confident QSAR models. − Furthermore, the drug-like and pharmacokinetic absorption, distribution, metabolism, excretion, toxicity (ADMET) properties of the candidate drug molecules will be examined. − On the other hand, we performed molecular docking simulations to evaluate the binding potential of the examined small molecules toward the c-Met protein active pocket. This is due to the importance of this procedure for predicting potential interactions between ligands and active amino acid residue sites inside the target protein receptor pocket. , The interactions between the investigated heterocyclic compounds and c-Met can result in a strong noncovalent binding between the two ends, which can provide a strong inhibition of c-Met protein enzymatic activity.…”

“… 30 , 31 The DFT computations were used because of their precision in providing precise indications on the electronic properties of the studied molecules, allowing for the generation of confident QSAR models. 32 − 34 Furthermore, the drug-like and pharmacokinetic absorption, distribution, metabolism, excretion, toxicity (ADMET) properties of the candidate drug molecules will be examined. 35 − 37 On the other hand, we performed molecular docking simulations to evaluate the binding potential of the examined small molecules toward the c-Met protein active pocket.…”

An in-silico pharmacophore-based molecular docking study to evaluate the inhibitory potentials of novel fungal triterpenoid Astrakurkurone analogues against a hypothetical mutated main protease of SARS-CoV-2 virus

“…It is a 33.8 kDa protein encoded by a frameshift between two open reading frames (Orfs), Orf1a and Orf1b, of the 5’ end cap region of the positive-stranded RNA genome [ 21 , 27 ]). M pro , along with papain-like protease, cleaves the polyprotein PP1a and PP1ab into 16 non-structural proteins responsible for viral replication and maturation [ 22 , [27] , [28] , [29] ]. Therefore, the main protease of coronavirus can be considered a prospective drug target [ 30 ].…”

Identification of new dihydrophenanthrene derivatives as promising anti-SARS-CoV-2 drugs through in silico investigations

“…Over the past few years, several models of quantitative structure-activity-QSAR relationships have been developed to predict potential inhibitors of SARS-CoV-2 [12][13][14][15]. This paper determines candidate inhibitors of the studied series by QSAR and molecular docking analysis.…”