Determining the unbinding events and conserved motions associated with the pyrazinamide release due to resistance mutations of Mycobacterium tuberculosis pyrazinamidase

Amamuddy, Olivier Sheik; Musyoka, Thommas M.; Boateng, Rita Afriyie; Zabo, Sophakama; Bishop, Özlem Tastan

doi:10.1016/j.csbj.2020.05.009

Cited by 16 publications

(21 citation statements)

References 66 publications

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“…The short bond length might be attributed to the comparatively smaller atom radius of oxygen in Gln to that of sulfur in Cys [1,2]. These values coincided with those obtained from previous related studies concerning Fe 2+ and Cys [36,37,39,57,58]. However, there is limited literature in Fe 2+ and Gln force field interactions which has been sufficiently addressed in this study.…”

Section: Geometry Optimizationsupporting

confidence: 89%

“…Despite the slight differences, the value of force constant from both systems (Model 1 and 2) were within the same range, and consistent with those obtained from previous studies [36,59]. Commonly, force field parameter values of a model conducted under different systems are not exact but fall within expected range [36,37,56]. In generating new parameters, the state of structure geometry optimization is thought to be a contributing factor to the varied observation [60].…”

Section: Geometry Optimizationsupporting

confidence: 85%

“…Contrastingly, the bonded model utilizes defined harmonic energy terms, which have been introduced into possible energy function to account for the bond formation between atoms and metal centers [28,34,35]. The approaches mentioned above have extensively been used in studies to characterize Fe 2+ centers in a range of metalloproteins [36][37][38][39]. Among other Fe 2+ clusters, Carvalho and colleagues [36] satisfactorily generated AMBER force field parameters for Fe 2+ 4S 2-4 clusters coordinated by cysteine residues.…”

Section: The Studymentioning

confidence: 99%

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Force field parameters for Fe²⁺₄S^2-₄ clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies

Tendwa¹,

Chebon²,

Lobb³

et al. 2021

Preprint

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The dimeric dihydropyrimidine dehydrogenase (DPD) metalloenzyme, an adjunct anti-cancer drug target contains highly specialized 4 x Fe2+4S2-4 clusters per chain. These clusters facilitate the catalysis of the rate-limiting step in the pyrimidine degradation pathway through a harmonized electron transfer cascade that triggers a redox catabolic reaction. In the process, majority of administered 5-fluorouracil (5-FU) cancer drug is inactivated while a small proportion is activated to nucleic acid antimetabolites. The occurrence of missense mutations in DPD protein within the general population, including those of African descent, has adverse toxicity effects due to altered 5-FU metabolism. Thus, deciphering mutation effects on protein structure and function is vital, especially for precision medicine purposes. We previously proposed combined molecular dynamics (MD) and dynamic residue network (DRN) analysis to decipher the molecular mechanisms of missense mutations in other proteins. However, the presence of Fe2+4S2-4 clusters in DPD poses a challenge for such in silico studies. The existing AMBER force field parameters cannot accurately describe the Fe2+ center coordination exhibited by this enzyme. Therefore, this study aimed to derive AMBER force field parameters for DPD enzyme Fe2+ centers, using the original Seminario method and collation features Visual Force Field Derivation Toolkit as a supportive approach. All-atom MD simulations were performed to validate the results. Both approaches generated similar force field parameters which accurately described the human DPD protein Fe2+4S2-4 clusters architecture. This information is crucial and opens new avenues for in silico cancer pharmacogenomics and drug discovery related research on 5-FU drug efficacy and toxicity issues.

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Section: Geometry Optimizationsupporting

confidence: 89%

Section: Geometry Optimizationsupporting

confidence: 85%

Section: The Studymentioning

confidence: 99%

See 1 more Smart Citation

Force field parameters for Fe²⁺₄S^2-₄ clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies

Tendwa¹,

Chebon²,

Lobb³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Since the presence of variants causes a substantial effect in the NBD1, as evidenced from the above analysis, to analyze more closely, we used a graph theory technique to describe the effect of variants in residual communication, which is directly correlated with protein function [ 55 , 56 , 57 , 58 ]. The results are presented as average betweenness centrality (BC) and average shortest path (L), where BC indicates major residue involved in inter-domain communication, while L denotes residue reachability [ 57 , 58 ]. Average ΔBC analysis showed that the residue 942, 1085, and 1108 are essential for communication, as they obtained high value in the wild-type ( Figure 6 A).…”

Section: Resultsmentioning

confidence: 99%

Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

Dash

Ali

Rana

et al. 2020

IJMS

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The ATP-binding cassette transporter A1 (ABCA1) is a membrane-bound exporter protein involved in regulating serum HDL level by exporting cholesterol and phospholipids to load up in lipid-poor ApoA-I and ApoE, which allows the formation of nascent HDL. Mutations in the ABCA1 gene, when presents in both alleles, disrupt the canonical function of ABCA1, which associates with many disorders related to lipid transport. Although many studies have reported the phenotypic effects of a large number of ABCA1 variants, the pathological effect of non-synonymous polymorphisms (nsSNPs) in ABCA1 remains elusive. Therefore, aiming at exploring the structural and functional consequences of nsSNPs in ABCA1, in this study, we employed an integrated computational approach consisting of nine well-known in silico tools to identify damaging SNPs and molecular dynamics (MD) simulation to get insights into the magnitudes of the damaging effects. In silico tools revealed four nsSNPs as being most deleterious, where the two SNPs (G1050V and S1067C) are identified as the highly conserved and functional disrupting mutations located in the NBD1 domain. MD simulation suggested that both SNPs, G1050V and S1067C, changed the overall structural flexibility and dynamics of NBD1, and induced substantial alteration in the structural organization of ATP binding site. Taken together, these findings direct future studies to get more insights into the role of these variants in the loss of the ABCA1 function.

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“…Likewise, conserved motions and unbinding events of 82 point mutations in Mtb pncA, linked to PZA resistance, were also discerned through MD simulations. Coupled expansions and contractions of the pncA lid and the side flap were observed in the unbinding of PZA in some mutants, while destabilisation of the “hinge” or nearby residues facilitated lid opening and PZA release from the active site [129] .…”

Section: Computational Tools Measuring the Effect Of Mutationsmentioning

confidence: 99%

Combining structure and genomics to understand antimicrobial resistance

Tunstall

Portelli

Phelan

et al. 2020

Computational and Structural Biotechnology Journal

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Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis . Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

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Determining the unbinding events and conserved motions associated with the pyrazinamide release due to resistance mutations of Mycobacterium tuberculosis pyrazinamidase

Cited by 16 publications

References 66 publications

Force field parameters for Fe²⁺₄S^2-₄ clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies

Force field parameters for Fe²⁺₄S^2-₄ clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies

Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

Combining structure and genomics to understand antimicrobial resistance

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Determining the unbinding events and conserved motions associated with the pyrazinamide release due to resistance mutations of Mycobacterium tuberculosis pyrazinamidase

Cited by 16 publications

References 66 publications

Force field parameters for Fe2+4S2-4 clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies

Force field parameters for Fe2+4S2-4 clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies

Computational SNP Analysis and Molecular Simulation Revealed the Most Deleterious Missense Variants in the NBD1 Domain of Human ABCA1 Transporter

Combining structure and genomics to understand antimicrobial resistance

Contact Info

Product

Resources

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Force field parameters for Fe²⁺₄S^2-₄ clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies

Force field parameters for Fe²⁺₄S^2-₄ clusters of dihydropyrimidine dehydrogenase, the 5-fluorouracil cancer drug deactivation protein: a step towards in silico pharmacogenomics studies