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Article ; Online: Therapeutic Anti-Depressant Potential of Microbial GABA Produced by

Tette, Fernanda-Marie / Kwofie, Samuel K / Wilson, Michael D

2022 Volume 44, Issue 4, Page(s) 1434–1451

Abstract: The role of the microbiota-gut-brain (MGB) axis in mood regulation and depression treatment has gained attention in recent years, as evidenced by the growing number of animal and human studies that have reported the anti-depressive and associated gamma- ... ...

Abstract	The role of the microbiota-gut-brain (MGB) axis in mood regulation and depression treatment has gained attention in recent years, as evidenced by the growing number of animal and human studies that have reported the anti-depressive and associated gamma-aminobutyric acid-ergic (GABAergic) effects of probiotics developed from
Language	English
Publishing date	2022-03-22
Publishing country	Switzerland
Document type	Journal Article ; Review
ZDB-ID	2000024-8
ISSN	1467-3045 ; 1467-3037
ISSN (online)	1467-3045
ISSN	1467-3037
DOI	10.3390/cimb44040096
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Zs.A 5122: Show issues

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Article: Inhibiting

Sakyi, Patrick O / Kwofie, Samuel K / Tuekpe, Julius K / Gwira, Theresa M / Broni, Emmanuel / Miller, Whelton A / Wilson, Michael D / Amewu, Richard K

Pharmaceuticals (Basel, Switzerland)

2023 Volume 16, Issue 3

Abstract: The recent outlook of leishmaniasis as a global public health concern coupled with the reportage of resistance and lack of efficacy of most antileishmanial drugs calls for a concerted effort to find new leads. The study ... ...

Abstract	The recent outlook of leishmaniasis as a global public health concern coupled with the reportage of resistance and lack of efficacy of most antileishmanial drugs calls for a concerted effort to find new leads. The study combined
Language	English
Publishing date	2023-02-21
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2193542-7
ISSN	1424-8247
ISSN	1424-8247
DOI	10.3390/ph16030330
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Article ; Online: Mycolactone: A Broad Spectrum Multitarget Antiviral Active in the Picomolar Range for COVID-19 Prevention and Cure.

Asiedu, Seth Osei / Gupta, Yash / Nicolaescu, Vlad / Gula, Haley / Caulfield, Thomas R / Durvasula, Ravi / Kempaiah, Prakasha / Kwofie, Samuel K / Wilson, Michael D

International journal of molecular sciences

2023 Volume 24, Issue 8

Abstract: We have previously shown computationally that Mycolactone (MLN), a toxin produced ... ...

Abstract	We have previously shown computationally that Mycolactone (MLN), a toxin produced by
MeSH term(s)	Humans ; COVID-19 ; SARS-CoV-2 ; Antiviral Agents/pharmacology ; HEK293 Cells
Chemical Substances	mycolactone ; Antiviral Agents
Language	English
Publishing date	2023-04-12
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2019364-6
ISSN	1422-0067 ; 1422-0067 ; 1661-6596
ISSN (online)	1422-0067
ISSN	1422-0067 ; 1661-6596
DOI	10.3390/ijms24087151
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Article ; Online: EBOLApred: A machine learning-based web application for predicting cell entry inhibitors of the Ebola virus.

Adams, Joseph / Agyenkwa-Mawuli, Kwasi / Agyapong, Odame / Wilson, Michael D / Kwofie, Samuel K

Computational biology and chemistry

2022 Volume 101, Page(s) 107766

Abstract: ... support vector machine (SVM), naïve Bayes (NB), k-nearest neighbor (kNN), and logistic regression (LR). The models were ...

Abstract	Ebola virus disease (EVD) is a highly virulent and often lethal illness that affects humans through contact with the body fluid of infected persons. Glycoprotein and matrix protein VP40 play essential roles in the virus life cycle within the host. Whilst glycoprotein mediates the entry and fusion of the virus with the host cell membrane, VP40 is also responsible for viral particle assembly and budding. This study aimed at developing machine learning models to predict small molecules as possible anti-Ebola virus compounds capable of inhibiting the activities of GP and VP40 using Ebola virus (EBOV) cell entry inhibitors from the PubChem database as training data. Predictive models were developed using five algorithms comprising random forest (RF), support vector machine (SVM), naïve Bayes (NB), k-nearest neighbor (kNN), and logistic regression (LR). The models were evaluated using a 10-fold cross-validation technique and the algorithm with the best performance was the random forest model with an accuracy of 89 %, an F1 score of 0.9, and a receiver operating characteristic curve (ROC curve) showing the area under the curve (AUC) score of 0.95. LR and SVM models also showed plausible performances with overall accuracy values of 0.84 and 0.86, respectively. The models, RF, LR, and SVM were deployed as a web server known as EBOLApred accessible via http://197.255.126.13:8000/.
MeSH term(s)	Humans ; Ebolavirus ; Bayes Theorem ; Virus Internalization ; Machine Learning ; Glycoproteins
Chemical Substances	Glycoproteins
Language	English
Publishing date	2022-09-02
Publishing country	England
Document type	Journal Article
ISSN	1476-928X
ISSN (online)	1476-928X
DOI	10.1016/j.compbiolchem.2022.107766
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Article ; Online: Development of a proteochemometric-based support vector machine model for predicting bioactive molecules of tubulin receptors.

Agyapong, Odame / Miller, Whelton A / Wilson, Michael D / Kwofie, Samuel K

Molecular diversity

2021 Volume 26, Issue 4, Page(s) 2231–2242

Abstract: Microtubules are receiving enormous interest in drug discovery due to the important roles they play in cellular functions. Targeting tubulin polymerization presents an excellent opportunity for the development of anti-tubulin drugs. Drug resistance and ... ...

Abstract	Microtubules are receiving enormous interest in drug discovery due to the important roles they play in cellular functions. Targeting tubulin polymerization presents an excellent opportunity for the development of anti-tubulin drugs. Drug resistance and high toxicity of currently used tubulin-binding agents have necessitated the pursuit of novel drug candidates with increased therapeutic potency. The design of novel drug candidates can be achieved using efficient computational techniques to support existing efforts. Proteochemometric (PCM) modeling is a computational technique that can be employed to elucidate the bioactivity relations between related targets and multiple ligands. We have developed a PCM-based Support Vector Machine (SVM) approach for predicting the bioactivity between tubulin receptors and small, drug-like molecules. The bioactivity datasets used for training the SVM algorithm were obtained from the Binding DB database. The SVM-based PCM model yielded a good overall predictive performance with an area under the curve (AUC) of 87%, Matthews correlation coefficient (MCC) of 72%, overall accuracy of 93%, and a classification error of 7%. The algorithm allows the prediction of the likelihood of new interactions based on confidence scores between the query datasets, comprising ligands in SMILES format and protein sequences of tubulin targets. The algorithm has been implemented as a web server known as TubPred, accessible via http://35.167.90.225:5000/ .
MeSH term(s)	Algorithms ; Amino Acid Sequence ; Ligands ; Support Vector Machine ; Tubulin
Chemical Substances	Ligands ; Tubulin
Language	English
Publishing date	2021-10-09
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1376507-3
ISSN	1573-501X ; 1381-1991
ISSN (online)	1573-501X
ISSN	1381-1991
DOI	10.1007/s11030-021-10329-w
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Zs.A 4946: Show issues

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Article ; Online: Therapeutic potential of HIV-1 entry inhibitor peptidomimetics.

Korie, Nneka Pu / Tandoh, Kwesi Z / Kwofie, Samuel K / Quaye, Osbourne

Experimental biology and medicine (Maywood, N.J.)

2021 Volume 246, Issue 9, Page(s) 1060–1068

Abstract: Human immunodeficiency virus 1 (HIV-1) infection remains a public health concern globally. Although great strides in the management of HIV-1 have been achieved, current highly active antiretroviral therapy is limited by multidrug resistance, prolonged ... ...

Abstract	Human immunodeficiency virus 1 (HIV-1) infection remains a public health concern globally. Although great strides in the management of HIV-1 have been achieved, current highly active antiretroviral therapy is limited by multidrug resistance, prolonged use-related effects, and inability to purge the HIV-1 latent pool. Even though novel therapeutic options with HIV-1 broadly neutralizing antibodies (bNAbs) are being explored, the scalability of bNAbs is limited by economic cost of production and obligatory requirement for parenteral administration. However, these limitations can be addressed by antibody mimetics/peptidomimetics of HIV-1 bNAbs. In this review we discuss the limitations of HIV-1 bNAbs as HIV-1 entry inhibitors and explore the potential therapeutic use of antibody mimetics/peptidomimetics of HIV-1 entry inhibitors as an alternative for HIV-1 bNAbs. We highlight the reduced cost of production, high specificity, and oral bioavailability of peptidomimetics compared to bNAbs to demonstrate their suitability as candidates for novel HIV-1 therapy and conclude with some perspectives on future research toward HIV-1 novel drug discovery.
MeSH term(s)	Anti-HIV Agents/pharmacology ; Broadly Neutralizing Antibodies ; Drug Discovery ; HIV Antibodies ; HIV Infections/drug therapy ; HIV-1 ; Humans ; Peptidomimetics/pharmacology ; Virus Internalization/drug effects
Chemical Substances	Anti-HIV Agents ; Broadly Neutralizing Antibodies ; HIV Antibodies ; Peptidomimetics
Language	English
Publishing date	2021-02-17
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	4015-0
ISSN	1535-3699 ; 1525-1373 ; 0037-9727
ISSN (online)	1535-3699 ; 1525-1373
ISSN	0037-9727
DOI	10.1177/1535370221990870
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Article ; Online: Targeting the

Enninful, Kweku S / Kwofie, Samuel K / Tetteh-Tsifoanya, Mark / Lamptey, Amanda N L / Djameh, Georgina / Nyarko, Samuel / Ghansah, Anita / Wilson, Michael D

Frontiers in cellular and infection microbiology

2022 Volume 12, Page(s) 868529

Abstract: Recent reports of resistance to artemisinin-based combination drugs necessitate the need to discover novel antimalarial compounds. The present study was aimed at identifying novel antimalarial compounds from natural product libraries using computational ... ...

Abstract	Recent reports of resistance to artemisinin-based combination drugs necessitate the need to discover novel antimalarial compounds. The present study was aimed at identifying novel antimalarial compounds from natural product libraries using computational methods.
MeSH term(s)	Antimalarials/pharmacology ; Artemisinins/pharmacology ; Humans ; Malaria, Falciparum/drug therapy ; Nucleoside-Phosphate Kinase/pharmacology ; Plasmodium falciparum
Chemical Substances	Antimalarials ; Artemisinins ; Nucleoside-Phosphate Kinase (EC 2.7.4.4) ; dTMP kinase (EC 2.7.4.9)
Language	English
Publishing date	2022-05-25
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2619676-1
ISSN	2235-2988 ; 2235-2988
ISSN (online)	2235-2988
ISSN	2235-2988
DOI	10.3389/fcimb.2022.868529
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Article ; Online: Computational Identification of Potential Anti-Inflammatory Natural Compounds Targeting the p38 Mitogen-Activated Protein Kinase (MAPK): Implications for COVID-19-Induced Cytokine Storm.

Asiedu, Seth O / Kwofie, Samuel K / Broni, Emmanuel / Wilson, Michael D

Biomolecules

2021 Volume 11, Issue 5

Abstract: Severely ill coronavirus disease 2019 (COVID-19) patients show elevated concentrations of pro-inflammatory cytokines, a situation commonly known as a cytokine storm. The p38 MAPK receptor is considered a plausible therapeutic target because of its ... ...

Abstract	Severely ill coronavirus disease 2019 (COVID-19) patients show elevated concentrations of pro-inflammatory cytokines, a situation commonly known as a cytokine storm. The p38 MAPK receptor is considered a plausible therapeutic target because of its involvement in the platelet activation processes leading to inflammation. This study aimed to identify potential natural product-derived inhibitory molecules against the p38α MAPK receptor to mitigate the eliciting of pro-inflammatory cytokines using computational techniques. The 3D X-ray structure of the receptor with PDB ID 3ZS5 was energy minimized using GROMACS and used for molecular docking via AutoDock Vina. The molecular docking was validated with an acceptable area under the curve (AUC) of 0.704, which was computed from the receiver operating characteristic (ROC) curve. A compendium of 38,271 natural products originating from Africa and China together with eleven known p38 MAPK inhibitors were screened against the receptor. Four potential lead compounds ZINC1691180, ZINC5519433, ZINC4520996 and ZINC5733756 were identified. The compounds formed strong intermolecular bonds with critical residues Val38, Ala51, Lys53, Thr106, Leu108, Met109 and Phe169. Additionally, they exhibited appreciably low binding energies which were corroborated via molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. The compounds were also predicted to have plausible pharmacological profiles with insignificant toxicity. The molecules were also predicted to be anti-inflammatory, kinase inhibitors, antiviral, platelet aggregation inhibitors, and immunosuppressive, with probable activity (Pa) greater than probable inactivity (Pi). ZINC5733756 is structurally similar to estradiol with a Tanimoto coefficient value of 0.73, which exhibits anti-inflammatory activity by targeting the activation of Nrf2. Similarly, ZINC1691180 has been reported to elicit anti-inflammatory activity in vitro. The compounds may serve as scaffolds for the design of potential biotherapeutic molecules against the cytokine storm associated with COVID-19.
MeSH term(s)	Animals ; Biological Products/metabolism ; COVID-19/metabolism ; Coronavirus/pathogenicity ; Cytokines/metabolism ; Humans ; Inflammation/metabolism ; Molecular Docking Simulation ; ROC Curve ; p38 Mitogen-Activated Protein Kinases/metabolism
Chemical Substances	Biological Products ; Cytokines ; p38 Mitogen-Activated Protein Kinases (EC 2.7.11.24)
Language	English
Publishing date	2021-04-29
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2701262-1
ISSN	2218-273X ; 2218-273X
ISSN (online)	2218-273X
ISSN	2218-273X
DOI	10.3390/biom11050653
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Article ; Online: Density Functional Theory-Based Studies Predict Carbon Nanotubes as Effective Mycolactone Inhibitors.

Suleiman, Nafiu / Yaya, Abu / Wilson, Michael D / Aryee, Solomon / Kwofie, Samuel K

Molecules (Basel, Switzerland)

2022 Volume 27, Issue 14

Abstract: Fullerenes, boron nitride nanotubes (BNNTs), and carbon nanotubes (CNTs) have all been extensively explored for biomedical purposes. This work describes the use of BNNTs and CNTs as mycolactone inhibitors. Density functional theory (DFT) has been used to ...

Abstract	Fullerenes, boron nitride nanotubes (BNNTs), and carbon nanotubes (CNTs) have all been extensively explored for biomedical purposes. This work describes the use of BNNTs and CNTs as mycolactone inhibitors. Density functional theory (DFT) has been used to investigate the chemical properties and interaction mechanisms of mycolactone with armchair BNNTs (5,5) and armchair CNTs (5,5). By examining the optimized structure and interaction energy, the intermolecular interactions between mycolactone and nanotubes were investigated. The findings indicate that mycolactone can be physically adsorbed on armchair CNTs in a stable condition, implying that armchair CNTs can be potential inhibitors of mycolactone. According to DOS plots and HOMO-LUMO orbital studies, the electronic characteristics of pure CNTs are not modified following mycolactone adsorption on the nanotubes. Because of mycolactone's large π-π interactions with CNTs, the estimated interaction energies indicate that mycolactone adsorption on CNTs is preferable to that on BNNTs. CNTs can be explored as potentially excellent inhibitors of mycolactone toxins in biological systems.
MeSH term(s)	Adsorption ; Density Functional Theory ; Macrolides ; Nanotubes/chemistry ; Nanotubes, Carbon/chemistry
Chemical Substances	Macrolides ; Nanotubes, Carbon ; mycolactone
Language	English
Publishing date	2022-07-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules27144440
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Article ; Online: Dual-Inhibition of Human N-Myristoyltransferase Subtypes Halts Common Cold Pathogenesis: Atomistic Perspectives from the Case of IMP-1088.

Agoni, Clement / Salifu, Elliasu Y / Enslin, Gill / Kwofie, Samuel K / Soliman, Mahmoud E

Chemistry & biodiversity

2022 Volume 19, Issue 2, Page(s) e202100748

Abstract: The pharmacological inhibition of human N-myristoyltransferase (HsNMT) has emerged as an efficient strategy to completely prevent the replication process of rhinoviruses, a potential treatment for the common cold. This was corroborated by the recent ... ...

Abstract	The pharmacological inhibition of human N-myristoyltransferase (HsNMT) has emerged as an efficient strategy to completely prevent the replication process of rhinoviruses, a potential treatment for the common cold. This was corroborated by the recent discovery of compound IMP-1088, a novel inhibitor that demonstrated a dual-inhibitory activity against the two HsNMT subtypes 1 and 2 without inducing cytotoxicity. However, the molecular and structural basis for the dual-inhibitory potential of IMP-1088 has not been investigated. As such, we employ molecular modelling techniques to resolve the structural mechanisms that account for the dual-inhibitory prowess of IMP-1088. Sequence and nanosecond-based analyses identified Tyr296, Phe190, Tyr420, Leu453, Gln496, Val181, Leu474, Glu182, and Asn246 as residues common within the binding pockets of both HsNMT1 and HsNMT2 subtypes whose consistent interactions with IMP-1088 underpin the basis for its dual inhibitory potency. Nano-second-based assessment of interaction dynamics revealed that Tyr296 consistently elicited high-affinity π-π stacked interaction with IMP-1088, thus further highlighting its cruciality corroborating previous report. An exploration of resulting structural changes upon IMP-1088 binding further revealed a characteristic impeding of residue fluctuations, structural compactness, and a consequential burial of crucial hydrophobic residues, features required for HsNMT1/2 functionality. Findings present essential structural perspectives that augment previous experimental efforts and could also advance drug development for treating respiratory tract infections, especially those mediated by rhinoviruses.
MeSH term(s)	Acyltransferases/antagonists & inhibitors ; Common Cold/drug therapy ; Humans ; Inosine Monophosphate/metabolism ; Models, Molecular
Chemical Substances	Inosine Monophosphate (131-99-7) ; Acyltransferases (EC 2.3.-) ; glycylpeptide N-tetradecanoyltransferase (EC 2.3.1.97)
Language	English
Publishing date	2022-01-11
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2139001-0
ISSN	1612-1880 ; 1612-1872
ISSN (online)	1612-1880
ISSN	1612-1872
DOI	10.1002/cbdv.202100748
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