Molecular Characterization And In-Silicon Drug Designing For Antibiotic Resistant Genes of Beta Lactamases Producing Coli From Clinical Isolates Of Khyber Teaching Hospital, District Peshawar

Abstract

The antibiotics resistance is increasing rapidly in Escherichia coli, develops resistance to broad spectrum antibiotics and challenge for clinicians to eradicate the resistance bacteria worldwide. The use of these drugs is also under threat due to the emergence of beta-lactamases, mainly the class B metallo-β-lactamases. To overcome the problem of resistance, novel inhibitors with multi inhibition potential are required to block the β-lactamases resistant genes and having the good Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) than the reported antibiotics. In the current study, an effort was made to identify the resistance genes from of β-lactamases producing E. coli using 573 clinical isolates and single inhibitor was designed having the potential to block all the resistant proteins. The current study was aimed to determine the antibiotic resistance pattern, molecular characterization and in-silico drug designing for antibiotic resistant genes of beta lactamases producing E. coli from clinical isolates (urine, blood, body fluid, sputum, CSF, pus and HVS). The clinical E. coli isolates were identified by API 10S and marker gene (uidA). Out of 3278 clinical samples, 573(17.5%) clinical isolates of E. coli were obtained. The most effective antibiotics against E. coli were; TGC and CO(100%), MEM(85.9%), FOS(86.4%), AK(73.5%), SCF(73.3%), C(66.3%) and TZP(63.7%). The current study reported high resistance against AMP(93.3%), SXT(89.35%), CIP(76.1%), LEV(73.8%) and CTX(62.0%). Of the isolates, 246 isolates were found ESBLs-Ec. Genetic analysis identified different ESBLs genes; CTX-M(69.9%), TEM(63.4%), SHV(34.5%) and CTX M(17.5%). All the ESBLs-Ec isolates tested against MEM, TGC, and CO showed 100% susceptibility. The ESBLs-Ec isolates were highly resistant not only to β-lactam drugs like CTX, CAZ, FEP, ATM, AMP and AMC but were also resistant to non-β- Abstract xli | P a g e lactam drugs like SXT(93.1%), CIP(90.7%), LEV(86.6) DO(65%) and CN(56.9%). The MICs of cephalosporins for resistant isolates ranged from 64 to >256μg/ml. In our study, 81(14.1%) isolates were found MBLs-Ec. NDM-1gene was the most prevalent MBLs gene observed in 27.2% isolates followed by VIM(13.6%) and OXA-48 like carbapenemases(9.9%). All the isolates were completely resistant to MEM, IMP, AMP, AMC, FEP, CTX, ATM and CAZ. The high resistance was also observed in isolates against SXT(95.1%), CIP(93.9%), LEV(92.6%), TOB(88.9%), CN(85.2%) and C(75.3%). All the isolates were sensitive to TGC and CO while FOS(56.8%), DO(38.3%) and AK(34.6%) were also effective against MBLs-Ec isolates. MICs of carbapenems for resistant isolates ranged from 4 to >32μg/ml. Of the isolates, the AmpC production was detected in 208 (36.3%) isolates. The high prevalence of AmpC gene was detected in 85% isolates amongst AmpC-β lactamase producing isolates, followed by CMY(15.8%), CIT(15.8%) and DHA(12.0%). All the AmpC producing isolates tested against MEM, TGC, and CO showed 100% susceptibility while resistant to AMP, AMC, FEP, FOX, CTX and CAZ. The highest resistance was also observed in isolates tested against SXT(91.3%), CIP(87.1%), LEV(83.2%), TOB(65.4%), DO(63.9%), CN(56.3%), TZP(56.3%), C(53.4%) while FOS(80.8%), SCF(65.4%) and AK(58.7%) showed good results. MICs of cephalosporins for resistant isolates ranged from 64 to >256μg/ml. There is a great need for new ways to kill bacteria that tolerate or resist standard antibiotics, and to that end in the current study we did in-silico approach to find new and potent inhibitors for ESBLs; Bla-TEM, Bla-CTX-M-14, Bla-CTX-M-15 and Bla SHV-1, MBLs; Bla-NDM-1, Bla-VIM and Bla-OXA-48 and AmpC-β-lactamases, Bla-AMPC, Bla-CMY and Bla-DHA-1 resistant proteins. Using integrated computational techniques, including homology modeling and RECAP Analysis and Abstract xlii | P a g e Synthesis to perform the synthesis of commercially available antibiotics. To find out the significant inhibitors for each resistant protein, crystal structures were retrieved from the protein data band (RCSB-PDB) database. The crystal structures were refined using the MOE2019 autocorrect algorithm. Proteins having no crystal structure reported yet in the protein data bank were modeled using MODELLER software. The template structures were selected from the protein data bank having the highest identity and coverage to the sequence and the final model was selected on the bases of DOPE score reported by MODELLER. The Electrostatic Maps were computed to identify neutral, positive and negative features in binding site of protein and ligand using Poisson-Boltzmann electrostatics. The 21 reported antibiotics for the beta lactamases proteins 3D structure were fetched from pubchem database and were selected for the de-novo discovery methodology RECAP Analysis and Synthesis. Every molecule in the subset was fragmented according to simple retrosynthetic analysis rules and collect statistics on the resulting fragments by the RECAP Analysis. The RECAP Analysis fragments were randomly recombined by RECAP synthesis to generate synthetically reasonable novel chemical structures. 1000 new compounds were generated by RECAP synthesis; hydrogens were added to them and were energy minimized prior to docking. Lipinski’s rules of five were applied on all compounds to identify that whether the retrieved hits retain drug-like properties. Before docking the new compounds in the active sites of the proteins, the docking protocols were validated by redocking the present ligand in each protein and RMSDs were calculated to observe the difference. The 1000 compounds were docked in the binding pocket of ESBLs, MBLs and AmpC β-lactamases proteins binding pockets using the Fast Fourier Transforms (FFT) method to generate tens of thousands of poses of ligand around the restraints to confine binding site region. Top 10 poses with Abstract xliii | P a g e R-Field electrostatics and the final refine (rigid body) top pose with full GB/VI solvation model was generated. After docking of these hit compounds in the binding pockets of ESBLs, MBLs and AmpC-β-lactamases proteins simultaneously, 15% compounds were kept on the bases of best fit in the binding pocket for each ESBLs, MBLs and AmpC-β-lactamases proteins.10 confirmations were selected for each protein using the proxy triangle algorithm, followed by London dG scoring methodology. Before calculating the binding affinity, the binding pocket energy minimization has been achieved. Generalized Born/Volume Integral (GB/VI) algorithm was applied in the MOE2019 to calculate the binding affinities of each protein and ligand to find out most potential ligand for each beta lactamases protein. The overall 10 hits for each protein with various scaffolds have best ADMET properties, interactions, binding energy and binding affinity than the reported ligand of each protein and were considered as lead compounds. These reported compounds for each protein have unique scaffolds and strong likelihood to act as further starting points in the development of novel and potent inhibitors for ESBLs, MBLs and AmpC-β-lactamases proteins to overcome the resistance. Top 10 compounds based on docking score, binding energy and binding affinity were selected which can inhibit the selected proteins. These hits compounds have unique scaffolds and predicted to be a starting point for the development of novel and potent inhibitors for 10 antibiotic resistant proteins. Final reported inhibitors can be subjected to further experimental assays