Computational and Systematic Analysis of Zosurabalpin (RG6006) against Cancerous and Pathogenic Microbial Proteins

Sadia Afrin¹*, Rezwan Ahmed Mahedi^1,2, Mustafa Jawad Kadham³,

Mohammad Chand Jamali⁴, Swapnil Das⁵, Hrishik Iqbal⁶, Raed Fanoukh Aboqader Al-Aouadi⁷,

Djumaniyazova Mukhayya Xusinovna⁸, Abdul Kareem J. Al-Azzawi⁹, Nikolaus Syrmos¹⁰,

Akayed Hasan¹¹, Mustafa Mudhafar¹²

¹Department of Pharmacy, Comilla University, Comilla, Bangladesh.

^1,2Chief Researcher, Benzene Research Center, Dhaka, Bangladesh.

³College of Medical Techniques, Al-Farahidi University, Baghdad, Iraq.

^4*Assistant Professor, Faculty of Medical and Health Sciences,

Liwa College, Al Ain, Abu Dhabi, United Arab Emirates.

⁵Department of Pharmacy, University of Science and Technology Chittagong.

⁶Department of Mathematics and Natural Sciences, Brac University, Bangladesh.

⁷College of Medicine, Al-Ayen Iraqi University, Thi-Qar, Iraq.

⁸Pedagogy and Psychology Department, Urgench State University, Uzbekistan.

⁹Dentistry Department, Al-Turath University, Baghdad, Iraq.

¹⁰Aristotle University of Thessaloniki, Thesaaloniki, Macedonia, Greece.

¹¹Division of Medicinal Chemistry, Graduate School of Pharmaceutical Science, Duquesne University.

¹²Department of Medical Physics, Faculty of Medical Applied Sciences,

University of Kerbala, 56001, Karbala, Iraq.

¹²Department of Anesthesia Techniques and Intensive Care, Al Taff university college, 56001, Kerbala, Iraq.

*Corresponding Author E-mail: pcafrin7@gmail.com, mjamali68@gmail.com

ABSTRACT:

Introduction. Zosurabalpin (ZAB) is a new antibiotic that shows significant promise against drug-resistant bacteria, specifically Acinetobacter baumannii, a pathogen notorious for its resistance to many existing antibiotics. It works by blocking the lipid transport mechanism within the bacteria, which is crucial for their survival. Objective. This study aims to systematically analyze the mechanism of action of Zosurabalpin and to perform computational analysis to identify target selection and binding sites of cancerous and pathogenic microbial proteins. Method. A comprehensive literature review was conducted using PubMed, Google Scholar, and Cochrane Library databases to understand the mechanism of Zosurabalpin against A. baumannii. Computational molecular screening tools such as Swiss ADME, Swiss Target Prediction, Swiss Param, Mcule, PASS Online, and others were utilized to analyze the effectiveness of Zosurabalpin, determine its binding sites, and evaluate its pharmacokinetic and toxicological properties. Result. Zosurabalpin targets the lipopolysaccharide (LPS) transport machinery in A. baumannii, inhibiting LPS transport and destabilizing the bacterial outer membrane. Computational analysis indicated that Zosurabalpin could be useful in cancer treatment, showing potential activity as a fibroblast growth factor agonist and interleukin-2 agonist, among others. The compound demonstrated a balanced profile in terms of physicochemical properties, pharmacokinetics, and safety, though improvements in absorption might be needed. Discussion. The novel mechanism of action of Zosurabalpin, involving the inhibition of LPS transport in A. baumannii, highlights its potential to address the urgent need for effective treatments against drug-resistant infections. Computational predictions also suggest its potential application in cancer therapy, with favorable pharmacokinetic and safety profiles. However, challenges remain in optimizing its absorption properties for clinical use.

KEYWORDS: Zosurabalpin (ZAB), Swiss drug design, Lipopolysaccharide (LPS), A. baumannii, Mcule, etc.

INTRODUCTION:

A new class of tethered macrocyclic peptide antibiotics, led by Zosurabalpin (RG6006), is effective against Acinetobacter spp., including Acinetobacter baumannii-calcoaceticus complex (ABC) bacteria that are resistant to carbapenems.¹ The silent pandemic that is the development of germs that are resistant to antibiotics is threatening the efficacy of these lifesaving treatments and is a leading cause of death on a global scale. There is an alarming increase in antibiotic resistance among certain Gram-negative bacteria. The World Health Organization (WHO) and the US Centers for Disease Control and Prevention (CDC) have classified the most dangerous and urgently needed antibiotic-resistant microorganisms in order to coordinate worldwide efforts to combat them^2-4. Nosocomial pneumonia and bloodstream infections are the most prevalent invasive infections in hospitalized and critically sick patients caused by opportunistic bacterial pathogens, the most common of which are A. baumannii and the A. baumannii-calcoaceticus complex (ABC)^5,6.This favored antibiotic class is now outdated due to the fast development of resistance mechanisms to various classes of antibiotics and the worldwide expansion of Carbapenem-resistant Acinetobacter baumannii (CRAB)⁷. Evidence of the rise of Acinetobacter baumannii that is resistant to all major classes of antibiotics is mounting. New treatment options for infections caused by ABC have been made possible with the recent approval of the siderophore-conjugated β-lactam cefiderocol and the β-lactamase inhibitor durlobactam combined with sulbactam.^8-14 The current gold standard, however, is defined by outdated or repurposed drugs (such the polymyxin class) that have questionable safety and effectiveness records. The absence of effective treatment options contributes to the high mortality rates associated with invasive CRAB infections, which range from 40 to 60%.^15-17 Experimental mixtures of bacteriophages have also been used to treat patients when no effective antibiotic therapy options have been found. In this study, we detail how Zosurabalpin works and how computational analysis can be used to find carcinogenic and pathogenic microbial protein binding sites and target selection criteria.^18-22

MATERIAL AND METHOD:

For literature screening, we used google scholar, pubmed and cochrane database to understand the mechanism of Zosurabalpin (ZAB) against A. baumannii. On the other hand, we used online based Computational molecular screening tools e.g., SwissTargetPridiction (http://www.swisstargetprediction.ch/), SwissADME (http://www.swissadme.ch/), SwissParam (http://swissparam.ch/), Mcule (https://mcule.com/), PassTarget, PassOnline (https://www.way2drug.com/passonline/) to extract the binding sites for proteins, toxicology, pharmacokinetics, physical properties of Zosurabalpin (RG6006).

Figure 1: Prisma flow chart model 2009 for literature review.

RESULT:

Mechanism of Zosurabalpin (ZAB) against CRAB:

The emergence of antibiotic-resistant bacterial infections poses a critical threat to global health, with a particularly severe impact on modern medical practices such as surgery, transplantation, and cancer chemotherapy due to the rise of multidrug-resistant Gram-negative pathogens. Notably, Acinetobacter baumannii has been classified as a priority one and critical pathogen by the WHO and an urgent threat by the CDC, frequently causing invasive infections like nosocomial pneumonia and bloodstream infections in hospitalized patients. Traditional antibiotics have become increasingly ineffective against A. baumannii due to the bacteria's rapid acquisition of resistance mechanisms. Recently, the identification and optimization of a new antibiotic class, tethered MCPs, led to the selection of zosurabalpin, which targets the lipopolysaccharide (LPS) transport machinery in A. baumannii. Resistance development studies revealed mutations primarily in genes encoding components of the LptB2FG (C) complex, critical for LPS transport. Biochemical assays and cryo-EM structural analyses demonstrated that zosurabalpin binds to a composite site on the Lpt transporter and LPS, inhibiting LPS transport by trapping the transporter in a substrate-bound conformation, thereby modulating ATPase activity and stalling the LPS transport machinery. As a result, the transport of LPS is stalled, preventing it from being properly incorporated into the outer membrane. Without proper LPS transport, the outer membrane becomes destabilized and compromised and get membrane disruption. This novel mechanism highlights Zosurabalpin's potential to address the urgent need for effective treatments against drug-resistant A. baumannii infections.

Figure 1: Zosurabalpin binds to the LptB2FG(C) transporter to block LPS transport from the inner to the outer bacterial membrane in Acinetobacter baumannii. Thus, it modulates the ATPase activity of LPS transporter to alter the energy dynamics of LPS to destabilize the outer membrane for disruption.

Computational Analysis of Zosurabalpin (ZAB):

The possibility of activity and possibility of inhibition were generated by an online tool (www.way2drug.com/passonline/) using the Canonical SMILES of Zosurabalpin (RG6006). On the basis of passonline we can predict that ZAB can be useful to the treatment of cancer. The Canonical SMILES was derived from the online portal named Pubchem (https://pubchem.ncbi.nlm.nih.gov/). Now for protein or target selection of virtual screening, we used Passproteintarget (https://www.way2drug.com/passtargets/) and Swisstarget (http://www.swisstargetprediction.ch/) online tool to choose the suitable proteins. By this, we can say that mostly ZAB can bind to the Family A G-protein couple receptor. For molecule filtering, we need to use the SwissADME and ADMETLab 2.0 to know the pharmacokinetic and toxicological pattern of ZAB.

Table 1: Possibilities of activity and inhibition of ZAB extracted by passonline.

Pa	Pi	Activity
0,379	0,022	Cancer associated disorders treatment
0,345	0,095	Fibroblast growth factor agonist
0,291	0,147	Interleukin 2 agonist
0,209	0,127	Fibroblast growth factor 1 agonist
0,198	0,129	p21-activated kinase 1 agonist
0,214	0,161	Antineoplastic (pancreatic cancer)
0,176	0,130	Antineoplastic enhancer
0,179	0,125	Antineoplastic alkaloid
0,100	0,099	Fibrosis treatment

From passonline we can understand that Pa indicates the probability that Zosurabalpin exhibits a particular activity. Higher values suggest a greater likelihood of the compound being active in the specified role. Pi value represents the probability that Zosurabalpin does not exhibit the specified activity. Lower values are more favorable, indicating less likelihood of inactivity. The high Pa value (0.379) and low Pi value (0.022) suggest that Zosurabalpin is likely to be effective in treating cancer-related disorders. For Cancer Associated Disorders Treatment, A relatively high Pa (0.345) indicates potential agonist activity towards fibroblast growth factors, which are involved in wound healing and development processes. A relatively high Pa (0.345) indicates potential agonist activity towards fibroblast growth factors, which are involved in wound healing and development processes. Pa (0.291) suggests a moderate probability that Zosurabalpin can act as an agonist for Interleukin-2, an important cytokine in the immune response. Several entries under antineoplastic (cancer-fighting) roles (e.g., pancreatic cancer, enhancer, alkaloid) show moderate probabilities, indicating potential use in cancer therapy, especially against pancreatic cancer. This describes the specific biological activity or therapeutic potential predicted for Zosurabalpin.

Figure 2 provides a detailed summary of the physicochemical properties of Zosurabalpin. It includes parameters such as molecular weight, hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), and octanol-water partition coefficient (LogP). Zosurabalpin's molecular weight is listed as 790.360 g/mol, which is within the acceptable range for good drug-like properties, suggesting it is not too large to be effectively absorbed or permeate cellular membranes. The LogP value of 3.230 indicates moderate lipophilicity, balancing solubility and membrane permeability. With nine hydrogen bond donors and thirteen hydrogen bond acceptors, Zosurabalpin is capable of forming a sufficient number of hydrogen bonds, which is favorable for its interaction with biological targets and maintaining solubility in the biological environment. These properties collectively suggest that Zosurabalpin has a balanced profile suitable for effective drug action, supporting its potential as a therapeutic agent.

Table 2: ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) evaluation of ZAB by ADMETLab 2.0

Absorption
Property	Value	Comment
Caco-2 Permeability	-6.212	Optimal: > -5.15 Log unit
MOCK Permeability	10⁻⁶	Low: <2×10⁻⁶ cm/s; Medium: 2–20×10⁻⁶ cm/s; High: >20×10⁻⁶ cm/s
Pgp-inhibitor	0.004	Category 1: Inhibitor; Category 0: Non-inhibitor
Pgp-substrate	0.989	Category 1: Substrate; Category 0: Non-substrate
HIA (Human Intestinal Abs.)	0.991	Category 1: HIA+ (≥30%); Category 0: HIA− (<30%)
F (20% Bioavailability)	0.852	Category 1: F (<20%); Category 0: F (≥20%)
F (30% Bioavailability)	0.993	Category 1: F (<30%); Category 0: F (≥30%)
Distribution
PPB (Plasma Protein Binding)	71.49	Optimal: ≤90%. High binding may indicate low therapeutic index
VD (Volume of Distribution)	1.555	Optimal: 0.04–20 L/kg
BBB Penetration	0.145	Category 1: BBB+; Category 0: BBB−
Fu (Fraction Unbound)	28.29	Low: <5%; Middle: 5–20%; High: >20%
Metabolism
CYP1A2 Inhibitor	0.046	Category 1: Inhibitor; Category 0: Non-inhibitor
CYP1A2 Substrate	0.104	Category 1: Substrate; Category 0: Non-substrate
CYP2C19 Inhibitor	0.208	Category 1: Inhibitor; Category 0: Non-inhibitor
CYP2C19 Substrate	0.041	Category 1: Substrate; Category 0: Non-substrate
CYP2C9 Inhibitor	0.303	Category 1: Inhibitor; Category 0: Non-inhibitor
CYP2C9 Substrate	0.066	Category 1: Substrate; Category 0: Non-substrate
CYP2D6 Inhibitor	0.347	Category 1: Inhibitor; Category 0: Non-inhibitor
CYP2D6 Substrate	0.429	Category 1: Substrate; Category 0: Non-substrate
CYP3A4 Inhibitor	0.760	Category 1: Inhibitor; Category 0: Non-inhibitor
CYP3A4 Substrate	0.054	Category 1: Substrate; Category 0: Non-substrate
Excretion
Clearance (CL)	2.185	High: >15 mL/min/kg; Moderate: 5–15 mL/min/kg; Low: <5 mL/min/kg
Half-life (T½)	0.738	Category 1: Long (>3h); Category 0: Short (<3h)
Toxicity
AMES Toxicity	0.014	Category 1: Toxic (+); Category 0: Non-toxic (−)
Skin Sensitization	0.048	Category 1: Sensitizer; Category 0: Non-sensitizer
Carcinogenicity	0.018	Category 1: Carcinogen; Category 0: Non-carcinogen

Table 2 evaluates the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties of Zosurabalpin using ADMETLab 2.0 (https://admetmesh.scbdd.com/). For absorption, Zosurabalpin shows suboptimal Caco-2 permeability (-6.212 log units) and low MDCK permeability (1e-06 cm/s), but high human intestinal absorption (0.991 probability). In distribution, it has moderate plasma protein binding (71.49%), low volume distribution (1.555 L/kg), and moderate blood-brain barrier penetration (0.145 probability). Regarding metabolism, Zosurabalpin is not a significant inhibitor or substrate for most CYP enzymes except CYP3A4 (0.76 inhibitor probability). Its excretion profile includes moderate clearance (2.185 mL/min/kg) and a long half-life (0.738 probability). For toxicity, Zosurabalpin is unlikely to be mutagenic (0.014 probability for AMES toxicity) or carcinogenic (0.018 probability), and it has a low probability of causing skin sensitization (0.048). This comprehensive analysis suggests Zosurabalpin has favorable pharmacokinetic and safety profiles, although improvements in absorption might be needed.

Table 3: Medicinal properties of ZAB extracted by ADMETLab 2.0

Property	Value	Comment
QED	0.093	A measure of drug-likeness based on desirability. Attractive: > 0.67; Unattractive: 0.49–0.67; Too complex: < 0.34
SAscore	4.942	Synthetic accessibility score. < 6 = easy to synthesize; ≥ 6 = difficult to synthesize
Fsp³	0.326	Fraction of sp³-hybridized carbons. Correlates with melting point and solubility. Fsp³ ≈ 0.42 considered ideal
MCE-18	114.316	Medicinal Chemistry Evolution score. No specific cutoff, but higher scores generally reflect greater complexity
NPscore	0.39	Natural product-likeness score (Range: -5 to +5). Higher = more natural product-like
Lipinski Rule	Rejected	Violated one or more of: MW ≤ 500, logP ≤ 5, Hacc ≤ 10, Hdon ≤ 5
Pfizer Rule	Accepted	Acceptable if only one property is out of range; ≥2 may lead to poor absorption/permeability
GSK Rule	Rejected	logP > 3 and TPSA < 75; such compounds are more likely to be toxic
Golden Triangle	Rejected	Ideal: MW 200–500 and -2 ≤ logD ≤ 5; compounds within this range may have better ADMET properties
PAINS	0 alerts	No Pan Assay Interference Compounds (frequent hitters or artifacts)
ALARM NMR	1 alert	One thiol-reactive compound alert
BMS	0 alerts	No undesirable or reactive compound alerts as per Bristol-Myers Squibb criteria
Chelator Rule	0 alerts	No chelating compound alerts

Medicinal chemistry properties of a compound provide insights into its drug-likeness, ease of synthesis, structural features, and potential biological activity. These properties include the Quantitative Estimate of Drug-likeness (QED) which measures overall desirability with a score of 0.093 indicating low desirability. The Synthetic Accessibility score (SAscore) of 4.942 suggests moderate ease of synthesis. The fraction of sp3 hybridized carbons (Fsp3) is 0.326, below the preferred 0.42 threshold, indicating lower solubility and melting point. The Medicinal Chemistry Evolution (MCE-18) value of 114.316 is well above the 45 thresholds, showing favorable medicinal chemistry properties. The Natural Product-likeness score (NPscore) of 0.39 suggests moderate resemblance to natural products. Lipinski's Rule, GSK Rule, and Golden Triangle are rejected due to the compound not meeting some criteria for molecular weight, lipophilicity, or other key properties, potentially indicating challenges in absorption or permeability. However, it meets Pfizer's rule with a high logP (>3) and low TPSA (<75), suggesting potential toxicity. The compound has no PAINS alerts (indicating it is not a frequent hitter in assays), but has one ALARM NMR alert (thiol reactivity), and no BMS or chelator alerts, which indicates it is free from undesirable reactive groups except for thiol reactivity.

Figure 3 provides a summary of molecular docking results for Zosurabalpin with various protein targets. PKCδ is involved in various cellular processes including apoptosis, proliferation, and differentiation. The docking results indicate that Zosurabalpin has a moderate confidence score for inhibiting PKCδ, suggesting that it may bind to and inhibit this kinase, potentially influencing pathways associated with cell survival and apoptosis. Lactaldehyde Reductase is not explicitly listed in the provided data, so there is no direct information available for this enzyme in the context of Zosurabalpin’s activity from the uploaded slide. Generally, lactaldehyde reductase participates in metabolic pathways by reducing lactaldehyde to propanediol. CDK5 plays a crucial role in neuronal development and function. The very low confidence score for CDK5 suggests that Zosurabalpin is unlikely to significantly interact with or inhibit this kinase. This low binding affinity implies that Zosurabalpin might not affect CDK5-regulated pathways prominently. PKCθ is involved in the regulation of T-cell function and is critical in immune responses. Zosurabalpin shows a low confidence score for inhibition of PKCθ, indicating a weak potential to inhibit this kinase. Although it might bind to PKCθ, the effect is likely minimal, and thus Zosurabalpin may not substantially impact T-cell activity through this pathway.

DISCUSSION:

The medicinal chemistry properties of Zosurabalpin (ZAB) reveal a comprehensive profile that indicates both potential and challenges for its development as a therapeutic agent. The Quantitative Estimate of Drug-likeness (QED) score of 0.093 suggests that ZAB is not highly desirable based on traditional drug-likeness metrics. The Synthetic Accessibility score (SAscore) of 4.942 indicates that ZAB is moderately easy to synthesize, which is beneficial for large-scale production. However, the fraction of sp3 hybridized carbons (Fsp3) is 0.326, below the optimal threshold of 0.42, which might affect its solubility and melting point. The Medicinal Chemistry Evolution (MCE-18) score of 114.316 is notably high, suggesting favorable medicinal chemistry properties. The Natural Product-likeness score (NPscore) of 0.39 indicates a moderate resemblance to natural products, which can be advantageous for biological activity^27-30.

Zosurabalpin does not conform to several key rules of drug-likeness, such as Lipinski’s Rule of Five, the GSK Rule, and the Golden Triangle rule, indicating potential issues with absorption, permeability, or molecular weight. However, it meets the Pfizer Rule with a high logP (>3) and low topological polar surface area (TPSA < 75), though this also suggests a potential for toxicity. The absence of PAINS alerts is positive, indicating that ZAB is not likely to be a frequent hitter in biological assays, but the presence of one ALARM NMR alert points to some reactivity, particularly thiol reactivity^31,32. The ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis further complements the medicinal chemistry profile. ZAB shows suboptimal absorption properties with poor Caco-2 and MDCK permeability but high human intestinal absorption. It has moderate plasma protein binding and blood-brain barrier penetration, suggesting a balance in distribution. Metabolically, ZAB is a moderate inhibitor of CYP3A4 but not a significant substrate or inhibitor for other CYP enzymes, which is favorable for minimizing drug-drug interactions^33,34. The toxicity profile indicates a low probability of mutagenicity, carcinogenicity, and skin sensitization, underscoring its safety potential. The systematic in silico analysis, including molecular docking, indicates that Zosurabalpin has a moderate binding affinity for Protein Kinase C delta (PKCδ), suggesting potential involvement in apoptosis and cell survival pathways. However, it shows low confidence scores for Cyclin-dependent kinase 5 (CDK5) and Protein kinase C theta (PKCθ), implying limited effects on these kinases^35,36. This selective activity profile supports the notion that ZAB could be specifically tailored for certain therapeutic pathways while minimizing off-target effects.

CONCLUSION:

Zosurabalpin exhibits a complex yet promising medicinal chemistry and ADMET profile. While it shows some limitations in traditional drug-likeness metrics and absorption properties, its ease of synthesis, moderate toxicity, and specific kinase interactions highlight its potential as a therapeutic candidate, particularly against cancerous and pathogenic microbial proteins. Future development should focus on optimizing its solubility and absorption while leveraging its favorable synthetic and safety profiles.

AUTHOR CONTRIBUTION:

SA, RAM, MCJ: Conceptualization, Investigation, Writing—original draft, Writing—review and editing, Data Analysis, Validation.

MJK, HI, SD: Conceptualization, Investigation, Writing—original draft, Writing—review and editing, Data Analysis.

RFAA: Conceptualization, Writing—original draft, Writing—review and editing.

DMX: Critical assessment.

AKJA: Critical assessment, Writing—original draft, Writing—review and editing, Data Analysis.

AH: Critical assessment, Writing— review and editing, Validation.

NS: Writing—review and editing.

All authors have read and approved the submitted version

REFERENCE:

1. Hawser S, Kothari N, Valmont T, Louvel S, Zampaloni C. 2131. Activity of the Novel Antibiotic Zosurabalpin (RG6006) against Clinical Acinetobacter Isolates from China. Open Forum Infect Dis. 2023; Nov 27; 10(Suppl 2): ofad500.1754. https://doi.org/10.1093/ofid/ofad500.1754.

2. Rabeea AAH, Jarallah EM. Detection of AmpC gene and Some OXA β-lactamase class among Carbapenem Resistant Acinetobacter baumannii (CRAB) isolates in Hilla, Iraq. Research J. Pharm. and Tech. 2018; 11(2): 777-784. https://doi.org/10.5958/0974-360X.2018.00147.6

3. Guenther A, Millar L, Messer A, Giraudon M, Patel K, Deurloo EJ, Lobritz M, Gloge A. 2126. Safety, Tolerability, and Pharmacokinetics (PK) in Healthy Participants Following Single Dose Administration of Zosurabalpin, a Novel Pathogen-Specific Antibiotic for the Treatment of Serious Acinetobacter Infections. Open Forum Infect Dis. 2023 Nov 27;10(Suppl 2):ofad500.1749. https://doi.org/10.1093/ofid/ofad500.1749.

4. Centers for Disease Control and Prevention. 2019 AR Threats Report. CDC. 2019. https://www.cdc.gov/DrugResistance/Biggest-Threats.html (2019).

5. Roope, L. S. J. et al. The challenge of antimicrobial resistance: what economics can contribute. Science 364, eaau4679 (2019).

6. AL-Harmoosh RA, Jarallah EM, AL-Shamari AM, AL-Khafaji HM. Detection of Efflux Pumps Genes in Clinical Isolates of Acinetobacter baumannii . Research J. Pharm. and Tech. 2017; 10(12): 4231-4236. https://doi.org/10.5958/0974-360X.2017.00775.2

7. Homenta H, Julyadharma, Saharman YR, Kuntaman K, Susianti H, Santosaningsih D, Noorhamdani. Molecular characterization of Clinical carbapenem-resistant Acinetobacter baumannii isolates from two tertiary care hospitals in Indonesia. Research Journal of Pharmacy and Technology. 2022; 15(7): 2917-2. https://doi.org/10.52711/0974-360X.2022.00486

8. Aboqader RF, Jassim SM, Al-Hasnawy MH. Increase il-17 α and reduced ifn-γ/il-4 ratio are novel responsible factors for persistence of entamoeba histolytica infection. Biochemical and Cellular Archives, 2019, 19(2), 3883.

9. Tacconelli, E. et al. Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis. Lancet Infect. Dis. 18, 318–327 (2018).

10. Peleg, AY, Seifert H. and Paterson DL. Acinetobacter baumannii: emergence of a successful pathogen. Clin. Microbiol. Rev. 21, 538–582 (2008).

11. Bhavani G., Gopinath P. Detection of Biofilm among Clinical isolates of Acinetobacter baumannii by Tissue Culture Plate Method (TCP). Research J. Pharm. and Tech 2016; 9(10): 1635-1637. https://doi.org/10.5958/0974-360X.2016.00327.9

12. Nasr P. Genetics, epidemiology and clinical manifestations of multidrug-resistant Acinetobacter baumannii. J. Hosp. Infect. 104, 4–11 (2019).

13. Higgins PG, Dammhayn C, Hackel M and Seifert H. Global spread of carbapenem-resistant Acinetobacter baumannii. J. Antimicrob. Chemother. 65, 233–238 (2010).

14. Nowak J. et al. High incidence of pandrug-resistant Acinetobacter baumannii isolates collected from patients with ventilator-associated pneumonia in Greece, Italy and Spain as part of the MagicBullet clinical trial. J. Antimicrob. Chemother. 72, 3277–3282 (2017).

15. Al-Aouadi RF, Jassim S, Al-Aouadi RF. Study of Immunological Response to Early and Late Stages of Hydatid Cyst Formation. Journal of Babylon University. 2016, 24(5): 1433-1446.

16. Kareem MH, Hasan AY. Inhibition of Biofilm formation of Imipenem-resistant Acinetobacter baumannii using Curcuma longa extracts, silver nanoparticles and Azithromycin. Research J. Pharm. and Tech. 2019; 12(9): 4463-4470. https://doi.org/10.5958/0974-360X.2019.00769.8

17. Food and Drug Administration. FDA approves new treatment for pneumonia caused by certain difficult-to-treat bacteria. FDA. 2023. https://www.fda.gov/news-events/press-announcements/fda-approves-new-treatment-pneumonia-caused-certain-difficult-treat-bacteria (2023).

18. Mahedi M.R.A. et al. Cefiderocol (CFDC): A Spy Antibiotic Future Replacement of Carbapenem. Research Journal of Pharmacy and Technology. 2023; 16(11): 5492-6. https://doi.org/10.52711/0974-360X.2023.00888

19. Nabilah N. et al. Examining the Interplay of Psychological Factors in Chronic Skin Disease: A Review on Depression, Anxiety, and Stress. Research Journal of Pharmacy and Technology. 2024; 17(4): 1902-8. https://doi.org/10.52711/0974-360X.2024.00302

20. Shields RK, Paterson DL and Tamma PD. Navigating available treatment options for carbapenem-resistant Acinetobacter baumannii–calcoaceticus complex infections. Clin. Infect. Dis. 76, S179–S193 (2023).

21. Afrin S., et al. Eltrombopag Olamine in Dengue Fever: Systematic Review of Clinical Trials and Beyond. Research Journal of Pharmacy and Technology. 2024; 17(6): 2778-2. https://doi.org/10.52711/0974-360X.2024.00436

22. Piperaki ET, Tzouvelekis LS, Miriagou V. and Daikos GL. Carbapenem-resistant Acinetobacter baumannii: in pursuit of an effective treatment. Clin. Microbiol. Infect. 25, 951–957 (2019).

23. Tamma PD. et al. Infectious Diseases Society of America Guidance on the treatment of AmpC β-lactamase-producing Enterobacterales, carbapenem-resistant Acinetobacter baumannii, and Stenotrophomonas maltophilia infections. Clin. Infect. Dis. 74, 2089–2114 (2021).

24. Paul M. et al. European Society of Clinical Microbiology and Infectious Diseases (ESCMID) guidelines for the treatment of infections caused by multidrug-resistant Gram-negative bacilli (endorsed by ESICM –European Society of intensive care Medicine). Clin. Microbiol. Infect. 28, 521–547 (2021).

25. Paul M. et al. Colistin alone versus colistin plus meropenem for treatment of severe infections caused by carbapenem-resistant Gram-negative bacteria: an open-label, randomised controlled trial. Lancet Infect. Dis. 18, 391–400 (2018).

26. Chusri S. et al. Clinical characteristics and outcomes of community and hospital-acquired Acinetobacter baumannii bacteremia. J. Microbiol. Immunol. Infect. 52, 796–806 (2019).

27. Du X. et al. Predictors of mortality in patients infected with carbapenem-resistant Acinetobacter baumannii: a systematic review and meta-analysis. Am. J. Infect. Control. 47, 1140–1145 (2019).

28. Schooley RT. et al. Development and use of personalized bacteriophage-based therapeutic cocktails to treat a patient with a disseminated resistant Acinetobacter baumannii infection. Antimicrob. Agents Chemother. 61, e00954-17 (2017).

29. Mahedi M.R.A. et al. Understanding the Global Transmission and Demographic Distribution of Nipah Virus (NiV). Research Journal of Pharmacy and Technology 2023; 16(8): 3588-4. https://doi.org/10.52711/0974-360X.2023.00592

30. Uyttebroek S. et al. Safety and efficacy of phage therapy in difficult-to-treat infections: a systematic review. Lancet Infect. Dis. 22, e208–e220 (2022)

31. Zoete, V., Daina, A., Bovigny, C., and Michielin, O. SwissSimilarity: A Web Tool for Low to Ultra High Throughput Ligand-Based Virtual Screening., J. Chem. Inf. Model., 2016; 56(8): 1399-1404.

32. Bugnon M, Goullieux M, Röhrig UF, Perez MAS, Daina A, Michielin O, Zoete V. SwissParam 2023: a modern web-based tool for efficient small molecule parameterization. J. Chem. Inf. Model., 2023; 63(21): 6469-75.

33. Zoete V, Cuendet MA, Grosdidier A, Michielin O. SwissParam: a fast force field generation tool for small organic molecules. J. Comput. Chem., 2011; 32(11): 2359-68.

34. Yesselman JD, Price DJ, Knight JL, Brooks CL 3rd. MATCH: An atom-typing toolset for molecular mechanics force fields.J. Comput. Chem., 2011; 33(2): 189-202.

35. Hussein MJ, Mohammed Al-Alwany SH. Molecular Highlighting Analysis of Mutational CDK41, CDK6 and P27 in association with Human Mammary Tumor Virus Infection in Tissues from Iraqi Female with Ovarian Tumors. Research J. Pharm. and Tech 2018; 11(10): 4699-4706. https://doi.org/10.5958/0974-360X.2018.00858.2

36. Pai A, Jayashree BS. Computational Approach for the Design of Flavone based CDK2/CyclinA Inhibitors: A Simulation Study Employing Pharmacophore based 3D QSAR. Research J. Pharm. and Tech. 2019; 12(5): 2299-2303. https://doi.org/10.5958/0974-360X.2019.00383.4

Received on 02.07.2024 Revised on 15.11.2024

Accepted on 17.01.2025 Published on 02.08.2025

Available online from August 08, 2025

Research J. Pharmacy and Technology. 2025;18(8):3541-3548.

DOI: 10.52711/0974-360X.2025.00510

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Creative Commons License.