MolOpt: A Web Server for Drug Design using Bioisosteric Transformation

Exploring novel Apalutamide analogues as potential therapeutics for prostate cancer: design, molecular docking investigations and molecular dynamics simulation

Introduction: Prostate cancer (PC) ranks as the second most frequent type of cancer in men and is the fourth largest cause of mortality worldwide. Androgenic hormones such as testosterone and dihydrotestosterone are crucial for the development and progression of the prostate gland. Androgenic hormones bind to androgen receptors (AR) and trigger the synthesis of many genes that stimulate the growth of prostate cells, initiating PC growth. Apalutamide (APL) is a non-steroidal antiandrogen drug used to treat PC; however, it also causes a variety of toxicities and resistance during the treatment. Methods: The purpose of this study was to computationally identify new and safer analogues of APL, focusing on improved pharmacokinetic properties and reduced toxicity. Drug likeness (DL) and drug score (DS) were also calculated. Docking studies on the designed analogues were conducted to predict their binding affinities and compare their orientations with the ligands in the original crystal structure. Molecular dynamics (MD) simulation of docked ligands was done using Schrödinger suite. Results: We generated a total of 1,415 analogues for different groups of APL using the bioisosteric approach. We selected 80 bioisosteres based on pharmacokinetic profiles, DL and DS score predictions, and found that the designed APL bioisosteres were optimal to good compared to APL. Analogues APL19, APL35, APL43, APL76, and APL80, formed hydrogen bonds with protein (PDB ID: 5T8E) which is similar hydrogen bonding to the standard (APL). The MD simulation result confirmed that APL43 and APL80 complexes were stable during the 100 nS run. Discussion: The results suggest that the APL analogues, particularly APL43 and APL80, are predicted to be potential antiandrogen drugs for the treatment of prostate cancer.

OptADMET: a web-based tool for substructure modifications to improve ADMET properties of lead compounds

Lead optimization is a crucial step in the drug discovery process, which aims to design potential drug candidates from biologically active hits. During lead optimization, active hits undergo modifications to improve their absorption, distribution, metabolism, excretion and toxicity (ADMET) profiles. Medicinal chemists face key questions regarding which compound(s) should be synthesized next and how to balance multiple ADMET properties. Reliable transformation rules from multiple experimental analyses are critical to improve this decision-making process. We developed OptADMET ( https://cadd.nscc-tj.cn/deploy/optadmet/ ), an integrated web-based platform that provides chemical transformation rules for 32 ADMET properties and leverages prior experimental data for lead optimization. The multiproperty transformation rule database contains a total of 41,779 validated transformation rules generated from the analysis of 177,191 reliable experimental datasets. Additionally, 146,450 rules were generated by analyzing 239,194 molecular data predictions. OptADMET provides the ADMET profiles of all optimized molecules from the queried molecule and enables the prediction of desirable substructure transformations and subsequent validation of drug candidates. OptADMET is based on matched molecular pairs analysis derived from synthetic chemistry, thus providing improved practicality over other methods. OptADMET is designed for use by both experimental and computational scientists.

BioisoIdentifier: an online free tool to investigate local structural replacements from PDB

Within the realm of contemporary medicinal chemistry, bioisosteres are empirically used to enhance potency and selectivity, improve adsorption, distribution, metabolism, excretion and toxicity profiles of drug candidates. It is believed that bioisosteric know-how may help bypass granted patents or generate novel intellectual property for commercialization. Beside the synthetic expertise, the drug discovery process also depends on efficient in silico tools. We hereby present BioisoIdentifier (BII), a web server aiming to uncover bioisosteric information for specific fragment. Using the Protein Data Bank as source, and specific substructures that the user attempt to surrogate as input, BII tries to find suitable fragments that fit well within the local protein active site. BII is a powerful computational tool that offers the ligand design ideas for bioisosteric replacing. For the validation of BII, catechol is conceived as model fragment attempted to be replaced, and many ideas are successfully offered. These outputs are hierarchically grouped according to structural similarity, and clustered based on unsupervised machine learning algorithms. In summary, we constructed a user-friendly interface to enable the viewing of top-ranking molecules for further experimental exploration. This makes BII a highly valuable tool for drug discovery. The BII web server is freely available to researchers and can be accessed at http://www.aifordrugs.cn/index/ . Scientific Contribution: By designing a more optimal computational process for mining bioisosteric replacements from the publicly accessible PDB database, then deployed on a web server for throughly free access for researchers. Additionally, machine learning methods are applied to cluster the bioisosteric replacements searched by the platform, making a scientific contribution to facilitate chemists' selection of appropriate bioisosteric replacements. The number of bioisosteric replacements obtained using BII is significantly larger than the currently available platforms, which expanding the search space for effective local structural replacements.

In Silico Approaches to Developing Novel Glycogen Synthase Kinase 3β (GSK-3β)

Alzheimer's disease (AD) is caused by plaque agglomeration and entanglement in several areas of the neural cells, which leads to apoptosis. The main etiology of AD is senile dementia, which is linked to amyloid-beta (Aβ) deregulation and tau perivascular pathogeny. Hyperphosphorylated tau has a propensity for microtubules, which elevate the instability and tau-protein congregates, leading to accumulation of neurofibrillary tangles (NFTs). Tau hyperphosphorylation is susceptible to GSK-3, which has led to an emerging hypothesis regarding the pathogenesis of AD. Accordingly, attempts have been made to conduct investigations and achieve further advancements on new analogues capable of inhibiting the GSK-3 protein, which are currently in the clinical trials. In this analysis, we have evaluated certain GSK-3 inhibitor variants utilising scaffolding and framework devised techniques with pharmacological characteristics, accompanied by computational screenings (pharmacokinetics and docking). The structure-based designed analogues interacted effectively with the active amino acids of GSK-3β target protein. The in silico pharmacokinetic studies revealed their drug-like properties. The analogues with best interactions and binding scores will be considered in the future to completely demonstrate their potential relevance as viable GSK-3 inhibitors.

Recent Development of Novel Aminoethyl-Substituted Chalcones as Potential Drug Candidates for the Treatment of Alzheimer's Disease

No drug on the market, as a single entity, participates in different pathways involved in the pathology of Alzheimer's disease. The current study is aimed at the exploration of multifunctional chalcone derivatives which can act on multiple targets involved in Alzheimer's disease. A series of novel aminoethyl-substituted chalcones have been developed using in silico approaches (scaffold morphing, molecular docking, and ADME) and reported synthetic methods. The synthesized analogs were characterized and evaluated biologically using different in vitro assays against AChE, AGEs, and radical formation. Among all compounds, compound PS-10 was found to have potent AChE inhibitory activity (IC50 = 15.3 nM), even more than the standard drug (IC50 = 15.68 nM). Further, the in vivo evaluation of PS-10 against STZ-induced dementia in rats showed memory improvement (Morris Water Maze test) in rats. Also, PS-10 inhibited STZ-induced brain AChE activity and oxidative stress, further strengthening the observed in vitro effects. Further, the molecular dynamic simulation studies displayed the stability of the PS-10 and AChE complex. The novel aminoethyl-substituted chalcones might be considered potential multifunctional anti-Alzheimer's molecules.

Scaffold Morphing and In Silico Design of Potential BACE-1 (β-Secretase) Inhibitors: A Hope for a Newer Dawn in Anti-Alzheimer Therapeutics

Alzheimer's disease (AD) is the prime cause of 65-80% of dementia cases and is caused by plaque and tangle deposition in the brain neurons leading to brain cell degeneration. β-secretase (BACE-1) is a key enzyme responsible for depositing extracellular plaques made of β-amyloid protein. Therefore, efforts are being applied to develop novel BACE-1 enzyme inhibitors to halt plaque build-up. In our study, we analyzed some Elenbecestat analogues (a BACE-1 inhibitor currently in clinical trials) using a structure-based drug design and scaffold morphing approach to achieve a superior therapeutic profile, followed by in silico studies, including molecular docking and pharmacokinetics methodologies. Among all the designed compounds, SB306 and SB12 showed good interactions with the catalytic dyad motifs (Asp228 and Asp32) of the BACE-1 enzyme with drug-likeliness properties and a high degree of thermodynamic stability confirmed by the molecular dynamic and stability of the simulated system indicating the inhibitory nature of the SB306 and SB12 on BACE 1.

Identified Isosteric Replacements of Ligands' Glycosyl Domain by Data Mining

Biologically equivalent replacements of key moieties in molecules rationalize scaffold hopping, patent busting, or R-group enumeration. Yet, this information may depend upon the expert-defined space, and might be subjective and biased toward the chemistries they get used to. Most importantly, these practices are often informatively incomplete since they are often compromised by a try-and-error cycle, and although they depict what kind of substructures are suitable for the replacement occurrence, they fail to explain the driving forces to support such interchanges. The protein data bank (PDB) encodes a receptor-ligand interaction pattern and could be an optional source to mine structural surrogates. However, manual decoding of PDB has become almost impossible and redundant to excavate the bioisosteric know-how. Therefore, a text parsing workflow has been developed to automatically extract the local structural replacement of a specific structure from PDB by finding spatial and steric interaction overlaps between the fragments in endogenous ligands and particular ligand fragments. Taking the glycosyl domain for instance, a total of 49 520 replacements that overlap on nucleotide ribose were identified and categorized based on their SMILE codes. A predominately ring system, such as aliphatic and aromatic rings, was observed; yet, amide and sulfonamide replacements also occur. We believe these findings may enlighten medicinal chemists on the structure design and optimization of ligands using the bioisosteric replacement strategy.

Molecular docking/dynamics simulations, MEP analysis, bioisosteric replacement and ADME/T prediction for identification of dual targets inhibitors of Parkinson's disease with novel scaffold

Monoamine oxidase B and Adenosine A2A receptors are used as key targets for Parkinson's disease. Recently, hMAO-B and hA2AR Dual-targets inhibitory potential of a novel series of Phenylxanthine derivatives has been established in experimental findings. Hence, the current study examines the interactions between 38 compounds of this series with hMAO-B and hA2AR targets using different molecular modeling techniques to investigate the binding mode and stability of the formed complexes. A molecular docking study revealed that the compounds L24 ((E)-3-(3-Chlorophenyl)-N-(4-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl) phenyl) acrylamide and L32 ((E)-3-(3-Chlorophenyl)-N-(3-(1,3-dimethyl-2,6-dioxo-2,3,6,7-tetrahydro-1H-purin-8-yl)phenyl)acrylamide) had a high affinity (S-score: -10.160 and -7.344 kcal/mol) with the pocket of hMAO-B and hA2AR targets respectively, and the stability of the studied complexes was confirmed during MD simulations. Also, the MEP maps of compounds 24 and 32 were used to identify the nucleophilic and electrophilic attack regions. Moreover, the bioisosteric replacement approach was successfully applied to design two new analogs of each compound with similar biological activities and low energy scores. Furthermore, ADME-T and Drug-likeness results revealed the promising pharmacokinetic properties and oral bioavailability of these compounds. Thus, compounds L24, L32, and their analogs can undergo further analysis and optimization in order to design new lead compounds with higher efficacy toward Parkinson's disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00139-3.

Virtual screening, optimization and molecular dynamics analyses highlighting a pyrrolo[1,2-a]quinazoline derivative as a potential inhibitor of DNA gyrase B of Mycobacterium tuberculosis

Tuberculosis is a disease that remains a significant threat to public health worldwide, and this is mainly due to the selection of strains increasingly resistant to Mycobacterium tuberculosis, its causative agent. One of the validated targets for the development of new antibiotics is DNA gyrase. This enzyme is a type II topoisomerase responsible for regulating DNA topology and, as it is essential in bacteria. Thus, to contribute to the search for new molecules with potential to act as competitive inhibitors at the active site of M. tuberculosis DNA gyrase B, the present work explored a dataset of 20,098 natural products that were filtered using the FAF-Drugs4 server to obtain a total of 5462 structures that were subsequently used in virtual screenings. The consensus score analysis between LeDock and Auto-Dock Vina software showed that ZINC000040309506 (pyrrolo[1,2-a]quinazoline derivative) exhibit the best binding energy with the enzyme. In addition, its subsequent optimization generated the derivative described as PQPNN, which show better binding energy in docking analysis, more stability in molecular dynamics simulations and improved pharmacokinetic and toxicological profiles, compared to the parent compound. Taken together, the pyrrolo[1,2-a]quinazoline derivative described for the first time in the present work shows promising potential to inhibit DNA gyrase B of M. tuberculosis.

Bioinformatics Approach on Bioisosterism Softwares to be Used in Drug Discovery and Development

Background:

In the rational drug development field, bioisosterism is a tool that improves lead compounds' performance, referring to molecular fragment substitution that has similar physical-chemical properties. Thus, it is possible to modulate drug properties such as absorption, toxicity, and half-life increase. This modulation is of pivotal importance in the discovery, development, identification, and interpretation of the mode of action of biologically active compounds.

Objective:

Our purpose here is to review the development and application of bioisosterism in drug discovery. In this study history, applications, and use of bioisosteric molecules to create new drugs with high binding affinity in the protein-ligand complexes are described.

Method:

It is an approach for molecular modification of a prototype based on the replacement of molecular fragments with similar physicochemical properties, being related to the pharmacokinetic and pharmacodynamic phase, aiming at the optimization of the molecules.

Results:

Discovery, development, identification, and interpretation of the mode of action of biologically active compounds are the most important factors for drug design. The strategy adopted for the improvement of leading compounds is bioisosterism.

Conclusion:

Bioisosterism methodology is a great advance for obtaining new analogs to existing drugs, enabling the development of new drugs with reduced toxicity, in a comparative analysis with existing drugs. Bioisosterism has a wide spectrum to assist in several research areas.

Scaffold morphing of arbidol (umifenovir) in search of multi-targeting therapy halting the interaction of SARS-CoV-2 with ACE2 and other proteases involved in COVID-19

The rapid emergence of novel coronavirus, SARS-coronavirus 2 (SARS-CoV-2), originated from Wuhan, China, imposed a global health emergency. Angiotensin-converting enzyme 2 (ACE2) receptor serves as an entry point for this deadly virus while the proteases like furin, transmembrane protease serine 2 (TMPRSS2) and 3 chymotrypsin-like protease (3CLpro) are involved in the further processing and replication of SARS-CoV-2. The interaction of SP with ACE2 and these proteases results in the SARS-CoV-2 invasion and fast epidemic spread. The small molecular inhibitors are reported to limit the interaction of SP with ACE2 and other proteases. Arbidol, a membrane fusion inhibitor approved for influenza virus is currently undergoing clinical trials against COVID-19. In this context, we report some analogues of arbidol designed by scaffold morphing and structure-based designing approaches with a superior therapeutic profile. The representative compounds A_BR4, A_BR9, A_BR18, A_BR22 and A_BR28 restricted the interaction of SARS-CoV-2 SP with ACE2 and host proteases furin and TMPRSS2. For 3CLPro, Compounds A_BR5, A_BR6, A_BR9 and A_BR18 exhibited high binding affinity, docking score and key residue interactions. Overall, A_BR18 and A_BR28 demonstrated multi-targeting potential against all the targets. Among these top-scoring molecules A_BR9, A_BR18, A_BR22 and A_BR28 were predicted to confer favorable ADME properties.

Integrated Protocol to Design Potential Inhibitors of Dipeptidyl Peptidase- 4 (DPP-4)

BACKGROUND

A strategy for the treatment of type II diabetes mellitus is the inhibition of the enzyme known as dipeptidyl peptidase-4 (DPP-4).

AIMS

This study aims to investigate the main interactions between DPP-4 and a set of inhibitors, as well as proposing potential candidates to inhibit this enzyme.

METHODS

We performed molecular docking studies followed by the construction and validation of CoMFA and CoMSIA models. The information provided from these models was used to aid in the search for new candidates to inhibit DPP-4 and the design of new bioactive ligands from structural modifications in the most active molecule of the studied series.

RESULTS

We were able to propose a set of analogues with biological activity predicted by the CoMFA and CoMSIA models, suggesting that our protocol can be used to guide the design of new DPP-4 inhibitors as drug candidates to treat diabetes.

CONCLUSION

Once the integration of the techniques mentioned in this article was effective, our strategy can be applied to design possible new DPP-4 inhibitors as candidates to treat diabetes.