Pharmacoinformatics elucidation of potential drug targets against migraine to target ion channel protein KCNK18

FMO-guided design of darunavir analogs as HIV-1 protease inhibitors

The prevalence of HIV-1 infection continues to pose a significant global public health issue, highlighting the need for antiretroviral drugs that target viral proteins to reduce viral replication. One such target is HIV-1 protease (PR), responsible for cleaving viral polyproteins, leading to the maturation of viral proteins. While darunavir (DRV) is a potent HIV-1 PR inhibitor, drug resistance can arise due to mutations in HIV-1 PR. To address this issue, we developed a novel approach using the fragment molecular orbital (FMO) method and structure-based drug design to create DRV analogs. Using combinatorial programming, we generated novel analogs freely accessible via an on-the-cloud mode implemented in Google Colab, Combined Analog generator Tool (CAT). The designed analogs underwent cascade screening through molecular docking with HIV-1 PR wild-type and major mutations at the active site. Molecular dynamics (MD) simulations confirmed the assess ligand binding and susceptibility of screened designed analogs. Our findings indicate that the three designed analogs guided by FMO, 19-0-14-3, 19-8-10-0, and 19-8-14-3, are superior to DRV and have the potential to serve as efficient PR inhibitors. These findings demonstrate the effectiveness of our approach and its potential to be used in further studies for developing new antiretroviral drugs.

Targeting ion channels with ultra-large library screening for hit discovery

Ion channels play a crucial role in a variety of physiological and pathological processes, making them attractive targets for drug development in diseases such as diabetes, epilepsy, hypertension, cancer, and chronic pain. Despite the importance of ion channels in drug discovery, the vastness of chemical space and the complexity of ion channels pose significant challenges for identifying drug candidates. The use of in silico methods in drug discovery has dramatically reduced the time and cost of drug development and has the potential to revolutionize the field of medicine. Recent advances in computer hardware and software have enabled the screening of ultra-large compound libraries. Integration of different methods at various scales and dimensions is becoming an inevitable trend in drug development. In this review, we provide an overview of current state-of-the-art computational chemistry methodologies for ultra-large compound library screening and their application to ion channel drug discovery research. We discuss the advantages and limitations of various in silico techniques, including virtual screening, molecular mechanics/dynamics simulations, and machine learning-based approaches. We also highlight several successful applications of computational chemistry methodologies in ion channel drug discovery and provide insights into future directions and challenges in this field.

In-silico drug design for the novel Karachi-NF001 strain of brain-eating amoeba: Naegleria fowleri

Naegleria fowleri (N. fowleri) is a free-living thermophilic amoeba of fresh water and soil. The amoeba primarily feeds on bacteria but can be transmitted to humans upon contact with freshwater sources. Furthermore, this brain-eating amoeba enters the human body through the nose and travels to the brain to cause primary amebic meningoencephalitis (PAM). N. fowleri has been reported globally since its discovery in 1961. Recently a new strain of N. fowleri named Karachi-NF001 was found in a patient who had traveled from Riyadh, Saudi Arabia to Karachi in 2019. There were 15 unique genes identified in the genome of the Karachi-NF001 strain compared to all the previously reported strains of N. fowleri worldwide. Six of these genes encode well-known proteins. In this study, we performed in-silico analysis on 5 of these 6 proteins, namely, Rab family small GTPase, NADH dehydrogenase subunit 11, two Glutamine-rich protein 2 proteins (locus tags: 12086 and 12110), and Tigger transposable element-derived protein 1. We conducted homology modeling of these 5 proteins followed by their active site identification. These proteins were subjected to molecular docking against 105 anti-bacterial ligand compounds as potential drugs. Subsequently, the 10 best-docked compounds were determined for each protein and ranked according to the number of interactions and their binding energies. The highest binding energy was recorded for the two Glutamine-rich protein 2 proteins with different locus tags, and results have shown that the protein-inhibitor complex was stable throughout the simulation run. Moreover, future in-vitro studies could validate the findings of our in-silico analysis and identify potential therapeutic drugs against N. fowleri infections.

Identification of repurposing therapeutics toward SARS-CoV-2 main protease by virtual screening

SARS-CoV-2 causes the current global pandemic coronavirus disease 2019. Widely-available effective drugs could be a critical factor in halting the pandemic. The main protease (3CL^pro) plays a vital role in viral replication; therefore, it is of great interest to find inhibitors for this enzyme. We applied the combination of virtual screening based on molecular docking derived from the crystal structure of the peptidomimetic inhibitors (N3, 13b, and 11a), and experimental verification revealed FDA-approved drugs that could inhibit the 3CL^pro of SARS-CoV-2. Three drugs were selected using the binding energy criteria and subsequently performed the 3CL^pro inhibition by enzyme-based assay. In addition, six common drugs were also chosen to study the 3CL^pro inhibition. Among these compounds, lapatinib showed high efficiency of 3CL^pro inhibition (IC₅₀ value of 35 ± 1 μM and K_i of 23 ± 1 μM). The binding behavior of lapatinib against 3CL^pro was elucidated by molecular dynamics simulations. This drug could well bind with 3CL^pro residues in the five subsites S1’, S1, S2, S3, and S4. Moreover, lapatinib’s key chemical pharmacophore features toward SAR-CoV-2 3CL^pro shared important HBD and HBA with potent peptidomimetic inhibitors. The rational design of lapatinib was subsequently carried out using the obtained results. Our discovery provides an effective repurposed drug and its newly designed analogs to inhibit SARS-CoV-2 3CL^pro.

Recent Advances in Diagnostic and Therapeutic Approaches for Breast Cancer: A Comprehensive Review

A silent monster, breast cancer, is a challenging medical task for researchers. Breast cancer is a leading cause of death in women with respect to other cancers. A case of breast cancer is diagnosed among women every 19 seconds, and every 74 seconds, a woman dies of breast cancer somewhere in the world. Several risk factors, such as genetic and environmental factors, favor breast cancer development. This review tends to provide deep insights regarding the genetics of breast cancer along with multiple diagnostic and therapeutic approaches as problem-solving negotiators to prevent the progression of breast cancer. This assembled data mainly aims to discuss omics-based approaches to provide enthralling diagnostic biomarkers and emerging novel therapies to combat breast cancer. This review article intends to pave a new path for the discovery of effective treatment options.

KCNK18 Biallelic Variants Associated with Intellectual Disability and Neurodevelopmental Disorders Alter TRESK Channel Activity

The TWIK-related spinal cord potassium channel (TRESK) is encoded by KCNK18, and variants in this gene have previously been associated with susceptibility to familial migraine with aura (MIM #613656). A single amino acid substitution in the same protein, p.Trp101Arg, has also been associated with intellectual disability (ID), opening the possibility that variants in this gene might be involved in different disorders. Here, we report the identification of KCNK18 biallelic missense variants (p.Tyr163Asp and p.Ser252Leu) in a family characterized by three siblings affected by mild-to-moderate ID, autism spectrum disorder (ASD) and other neurodevelopment-related features. Functional characterization of the variants alone or in combination showed impaired channel activity. Interestingly, Ser252 is an important regulatory site of TRESK, suggesting that alteration of this residue could lead to additive downstream effects. The functional relevance of these mutations and the observed co-segregation in all the affected members of the family expand the clinical variability associated with altered TRESK function and provide further insight into the relationship between altered function of this ion channel and human disease.

Molecular docking analyses of CYP450 monooxygenases of Tribolium castaneum (Herbst) reveal synergism of quercetin with paraoxon and tetraethyl pyrophosphate: in vivo and in silico studies

Pest management in stored grain industry is a global issue due to the development of insecticide resistance in stored grain insect pests. Excessive use of insecticides at higher doses poses a serious threat of food contamination and residual toxicity for grain consumers. Since the development of new pesticide incurs heavy costs, identifying an effective synergist can provide a ready and economical tool for controlling resistant pest populations. Therefore, the synergistic property of quercetin with paraoxon and tetraethyl pyrophosphate has been evaluated against the larvae and adults of Tribolium castaneum (Herbst). Comparative molecular docking analyses were carried out to further identify the possible mechanism of synergism. It was observed that quercetin has no insecticidal when applied at the rate of 1.5 and 3.0 mg/g; however, a considerable synergism was observed when applied in combination with paraoxon. The comparative molecular docking analyses of CYP450 monooxygenase (CYP15A1, CYP6BR1, CYP6BK2, CYP6BK3) family were performed with quercetin, paraoxon and tetraethyl pyrophosphate which revealed considerable molecular interactions, predicting the inhibition of CYP450 isoenzyme by all three ligands. The study concludes that quercetin may be an effective synergist for organophosphate pesticides depending upon the dose and type of the compound. In addition, in silico analyses of the structurally diversified organophosphates can effectively differentiate the organophosphates which are synergistic with quercetin.

The Role of TRESK in Discrete Sensory Neuron Populations and Somatosensory Processing

Two-pore domain K⁺ (K_2P) channels generate K⁺ leak current, which serves a vital role in controlling and modulating neuronal excitability. This diverse family of K⁺ channels exhibit distinct expression and function across neuronal tissues. TWIK-related spinal cord K⁺ channel (TRESK) is a K_2P channel with a particularly enriched role in sensory neurons and in vivo pain pathways. Here, we explored the role of TRESK across molecularly distinct sensory neuron populations and assessed its contribution to different sensory modalities. We found TRESK mRNA only in select populations of C- and A-δ nociceptors, in addition to low threshold D-hair afferents. Neurons from mice in which TRESK has been ablated demonstrated marked hyperexcitability, which was amplified under inflammatory challenge. Detailed behavioral phenotyping of TRESK knockout mice revealed specific deficits in somatosensory processing of noxious and non-noxious stimuli. These results demonstrate novel roles of TRESK in somatosensory processing and offer important information to those wishing to target the channel for therapeutic means.

Pharmacoinformatics and molecular docking reveal potential drug candidates against Schizophrenia to target TAAR6

Schizophrenia (SZ) is a complex disabling disorder that leads to the mental disability and afflicts 1% of the world's total population and placed in top ten medical disorders. In current work, bioinformatics analyses were carried out on Trace amine (TA)-associated receptor 6 (TAAR6) to recognize the potential drugs and compounds against SZ. Comparative modeling and threading-based approaches were utilized for the structure prediction of TAAR6. Fifty-nine predicted structures were evaluated by various model assessment techniques and final model having only eight amino acids in the outlier region and 98.5% overall quality factor was chosen for further pharmacoinformatics and molecular docking analyses. From an extensive literature review, 11 Food and Drug Administration (FDA) approved drugs were analyzed by computational techniques and Aripiprazole was found as the most effective drug against SZ by targeting TAAR6. Here, we report five novel molecules which exhibited the highest binding affinity, effective drug properties, and interestingly, observed better results than the approved selected drugs against SZ by targeting TAAR6. The docking analyses revealed that Arg-92, Trp-98, Gln-191, Thr-192, Ala-290, Cys-291, Tyr-293, and Glu-294 residues were observed as critical interacting residues in receptor-ligand interactions. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, Lipinski rule of five, highest binding affinity coupled with virtual screening (VS), and pharmacophore modeling approach illustrated that aripiprazole (-8.6 kcal/mol) and TAAR6_0094 (-9.3 kcal/mol) are potential inhibitors for targeting TAAR6. It is suggested that schizophrenic patients have to use Aripiprazole for the medication of SZ by targeting TAAR6 and develop effective therapies by utilizing scrutinized novel compound.

Current Therapeutic Molecules and Targets in Neurodegenerative Diseases Based on in silico Drug Design

Abstract: Background

As the number of elderly persons increases, neurodegenerative diseases are becoming ubiquitous. There is currently a great need for knowledge concerning management of old-age neurodegenerative diseases; the most important of which are: Alzheimer’s disease, Parkinson’s disease, Amyotrophic Lateral Sclerosis, and Huntington’s disease.

Objective

To summarize the potential of computationally predicted molecules and targets against neurodegenerative diseases.

Method

Review of literature published since 1997 against neurodegenerative diseases, utilizing as keywords: in silico, Alzheimer’s disease, Parkinson’s disease, Amyotrophic Lateral Sclerosis ALS, and Huntington’s disease was conducted.

Results and Conclusion

Due to the costs associated with experimentation and current ethical law, performing experiments directly on living organisms has become much more difficult. In this scenario, in silico techniques have been successful and have become powerful tools in the search to cure disease. Researchers use the Computer Aided Drug Design pipeline which: 1) generates 3-dimensional structures of target proteins through homology modeling 2) achieves stabilization through molecular dynamics simulation, and 3) exploits molecular docking through large compound libraries. Next generation sequencing is continually producing enormous amounts of raw sequence data while neuroimaging is producing a multitude of raw image data. To solve such pressing problems, these new tools and algorithms are required. This review elaborates precise in silico tools and techniques for drug targets, active molecules, and molecular docking studies, together with future prospects and challenges concerning possible breakthroughs in Alzheimer’s, Parkinson’s, Amyotrophic Lateral Sclerosis, and Huntington’s disease.

Pharmacoinformatics, Adaptive Evolution, and Elucidation of Six Novel Compounds for Schizophrenia Treatment by Targeting DAOA (G72) Isoforms

Studies on Schizophrenia so far reveal a complex picture of neurological malfunctioning reported to be strongly associated with DAOA. Detailed sequence analyses proved DAOA as a primate specific gene having conserved gene desert region on both upstream and downstream region. The analyses of 10 MB chromosomal region of primates, birds, rodents, and reptiles having DAOA evidenced the conserved part in primates and in the rest of species, while DAOA is only present in primates. DAOA has four isoforms having one interaction partner DAO. Protein-protein analyses of four DAOA isoforms with DAO were performed individually and find potential interacting residues computationally. It was observed that molecular docking of approved FDA drugs revealed efficient results but there was no common drug with effective binding to all DAOA isoforms. Library of compounds was constructed by virtual screening of 2D similarity search against recommended SZ drugs in conjunction with their physiochemical properties. Molecular docking resulted in six novel compounds exhibiting maximum binding affinity with selected four DAOA isoforms. However not the entire schizophrenic population responds to the single drug and interestingly in this study six novel compounds having promising results and same binding site to that DAOA that may be used to interact with DAO against four DAOA isoforms were observed.

Pharmacoinformatic and molecular docking studies reveal potential novel antidepressants against neurodegenerative disorders by targeting HSPB8

Charcot-Marie-Tooth (CMT) disease is an inherited peripheral neuromuscular disorder characterized by length-dependent and progressive degeneration of peripheral nerves, leading to muscular weakness. Research has shown that mutated HSPB8 may be responsible for depression, neurodegenerative disorders, and improper functioning of peripheral nerves, resulting in neuromuscular disorders like CMT. In the current work, a hybrid approach of virtual screening and molecular docking studies was followed by homology modeling and pharmacophore identification. Detailed screening analyses were carried out by 2-D similarity search against prescribed antidepressant drugs with physicochemical properties. LigandScout was employed to ascertain novel molecules and pharmacophore properties. In this study, we report three novel compounds that showed maximum binding affinity with HSPB8. Docking analysis elucidated that Met37, Ser57, Ser58, Trp60, Thr63, Thr114, Lys115, Asp116, Gly117, Val152, Val154, Leu186, Asp189, Ser190, Gln191, and Glu192 are critical residues for ligand-receptor interactions. Our analyses suggested paroxetine as a potent compound for targeting HSPB8. Selected compounds have more effective energy scores than the selected drug analogs. Additionally, site-directed mutagenesis could be significant for further analysis of the binding pocket. The novel findings based on an in silico approach may be momentous for potent drug design against depression and CMT.

Activation of TRESK channels by the inflammatory mediator lysophosphatidic acid balances nociceptive signalling

In dorsal root ganglia (DRG) neurons TRESK channels constitute a major current component of the standing outward current IK_SO. A prominent physiological role of TRESK has been attributed to pain sensation. During inflammation mediators of pain e.g. lysophosphatidic acid (LPA) are released and modulate nociception. We demonstrate co-expression of TRESK and LPA receptors in DRG neurons. Heterologous expression of TRESK and LPA receptors in Xenopus oocytes revealed augmentation of basal K⁺ currents upon LPA application. In DRG neurons nociception can result from TRPV1 activation by capsaicin or LPA. Upon co-expression in Xenopus oocytes LPA simultaneously increased both depolarising TRPV1 and hyperpolarising TRESK currents. Patch-clamp recordings in cultured DRG neurons from TRESK[wt] mice displayed increased IK_SO after application of LPA whereas under these conditions IK_SO in neurons from TRESK[ko] mice remained unaltered. Under current-clamp conditions LPA application differentially modulated excitability in these genotypes upon depolarising pulses. Spike frequency was attenuated in TRESK[wt] neurons and, in contrast, augmented in TRESK[ko] neurons. Accordingly, excitation of nociceptive neurons by LPA is balanced by co-activation of TRESK channels. Hence excitation of sensory neurons is strongly controlled by the activity of TRESK channels, which therefore are good candidates for the treatment of pain disorders.