The evolutionary approach to drug development: a resistance perspective | Adamas University

The evolutionary approach to drug development: a resistance perspective


The evolutionary approach to drug development: a resistance perspective

Student contributor: Akash Mitra, PG-IV Microbiology

The tussle between pathogens and antimicrobial therapy is essentially in the evolutionary arms race. The specific mutation for stabilizing the drug-tolerant property and horizontal gene transfer, offering selection advantage against antimicrobials, are the common modes for resistance acquisition as observed for antibiotic-resistant bacteria. Often the rate of mutation acquisition is enhanced from a transient hypermutation phenotype, with loss of maintenance of fidelity for genome duplication owing to dysfunctional mismatch repair or by error-prone translation repair mechanism. However, for obligate parasites including viruses, the evolutionary landscape is somewhat multidimensional in terms of dynamic intra-host drug concentrations resulting in differential selection pressure. Mutations induct considerable fitness cost for basic processes associated with parasitism. Antiviral resistance often accompanies less robust therapeutic regimens insufficient to diminish viral replication, thereby imposing selection pressure and eventuates rapid adaptation leading to resistance. With the high replication rate for large population size, the resistance-conferring polymorphisms emerge promptly in the viral genome (Irwin et al., 2016).

While strategizing drug designing, a key factor to consider is sustainability. Genetic barrier, i.e. number of genetic changes required for building resistance is the cornerstone in determining the period for optimum applicability of an antimicrobial. For some of the older drugs like the first generation reverse transcriptase inhibitors, the genetic barrier was indeed feeble and mere one or two variations impart resistance. The genetic barrier should not be perceived as a mere number (of mutation) but the type of genetic variation that would result in resistance also influences the magnitude of the barrier. Transition mutations are often common compared to transversions. Drugs requiring to transversions (for resistance) should impose greater impediments compared to a transition. Additionally, a higher genetic barrier requires building an integrated mutation network to attain a stable and substantial level of resistance. Such a situation imposes deleterious trade-offs like reduced replication rate and deregulation of gene expression which often surge beyond error threshold causing deleterious mutations (and lethal) to occur.Such situations cause depletion of faithful replication and eventual extinction. However often compensatory mutations emerge to decrease the fitness cost imposed by such trade-offs (Gotte 2012). Therefore, a clear understanding of resistance emergence from an evolutionary perspective is imperative for strategizing antiviral regiments including developing novel, repurposed, or combinatorial therapy.

RNA viruses replicate close to error threshold and are prone to ‘error catastrophe’. Although this might appear an inherently unstable evolutionary strategy, provided that viral population sizes are sufficiently large, life at the error threshold does allow RNA viruses to produce effective mutations within a few replication cycles. So a prospective rational for next-generation drug development can be aiming at exceeding an error threshold. Favipiravir is one such drug that targets RNA dependent RNA polymerase of RNA viruses including Coronaviridae and enhances wrong base incorporation.Although targeting RNA dependent RNA polymerases (RdRp) might be considered as a strategy to induce “error catastrophe”, mechanistic understanding of components of replication for the virus shed light on various other factors that can be targeted. Like many other RNA virus, coronavirus (CoV) RNA-dependent RNA polymerases (RdRp) lack co- and post-replicative proof-reading pathways as reflected by the incorporation of mutations at a considerably elevated rate.  RdRps have been exploited as a favored node for intervention as being prone to incorporate nucleotide analogs like ribavirin into nascent viral RNA during genome amplification (Crotty et al., 2000). For CoV, resistance inducing mutation against3C-Like protease Inhibitor displayed considerable fitness cost indicative of low genetic barrier (Deng et al., 2014).  Interestingly, in this group of the virus, nsp14 protein with 3′-5′ exoribonuclease (ExoN) in the amino (N) terminus (Eckerle et al., 2010) mediates mismatch correction. Inactivation of nsp14-ExoN of SARS-CoV results in ~20-fold more mutations in genomes than for wild-type (wt) viruses in infected cells (Eckerle et al., 2010). The ExoN domain (amino acids 1–287) with a DEEDh catalytic motif and the N7-MTase domain (amino acids 288–527) and a DxGxPxG/A SAM-binding/catalytic domain of nsp14 are distinct in structure among other members of the same enzyme family. The N7cap-MTase domain is also linked to RNA processing as it generates Cap0 of mRNA and this reaction is particularly crucial for recognition by the host ribosome (Chen et al., 2016). Inhibiting NSP14 mediated mismatch correction might be a viable strategy to induce ‘error catastrophe’ during replication. With the ongoing effort to screen specific inhibitor against NSP14 (Fig.1) and deciphering the evolutionary impact of such inhibition on mutational dynamics can accentuate the development of a sustainable drug against SARS-CoV-2.


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Fig1. Putative inhibitor for nsp14.Molecular docking analysis depicting potential interaction between the ExoN domain of SARS-CoV-2 nsp14 and a candidate molecule annotated as ExoI.5 (unpublished data).


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