Manmohan Sharma’s scientific contributions

A phylogenetic tree commonly represents evolutionary relationships within a set of protein sequences. Various methods and strategies have been used to improve the accuracy of phylogenetic trees, but their capacity to derive a biologically credible relationship appears to be overestimated. Although the quality of the protein sequence alignment and the choice of substitution matrix are preliminary constraints to define the biological accuracy of the overlapped residues, the alignment is not iteratively optimized through the statistical testing of residue-substitution models. The exact alignment protocol and substitution model information are by default used for every sequence set by a server to construct an often-irrelevant phylogenetic tree, and no sequence-based tailoring of phylogenetic strategy is implemented by any server. Rigorously constructing 270 evolutionary trees, constructed using IQ-TREE based on 13 different alignments (Clustal-Omega, Kalign, MAFFT, MUSCLE, TCoffee, and Promals3D, as well as their HHPred-based hidden Markov model [HMM] alignments using HHPred) and nine substitution models (Dayhoff, JJT, block substitution matrix62, WAG, probability matrix from blocks [PMB], direct computation with mutability [DCMUT], JTTDCmut, LG, and variable time), the present study highlights the failure of the current methods and emphasizes the need for a more accurate scrutiny of the entire phylogenetic methodology. MUSCLE alignment and the LG and Dayhoff matrices yield more accurate phylogenetic results for sequences shorter than 500 residues for the log-likelihood measure. Moreover, Kalign 1 HMM alignment yields the top-ranked tree with the lowest tree length score with only the PMB matrix, making this substitution model more accurate in terms of total tree length score. The suggested strategy would be beneficial for understanding the potential pitfalls of phylogenetic inference and would aid us in deriving a more accurate evolutionary relationship for a sequence dataset.

Introduction With more than 70,000 unique compounds indexed in the Dictionary of Natural Products database, terpenes and their various derivatives are one of the largest and structurally most diverse categories of natural chemicals [1]. These molecules serve a variety of functions, ranging from protein prenylation, mediating antagonistic/symbiotic interactions between organisms to electron transfer or contribution to membrane fluidity [2-4]. Due to their vast fictional and structural variability, terpenoids can be used for a variety of applications, including pharmaceuticals, biofuels, tastes, and scents [5-9]. Although there are still many of these compounds that are taken from their natural sources, which are usually plants, this method frequently suffers from seasonal and geographic changes in supply and quality. The strong anticancer agent Taxol (paclitaxel), which had been discovered in the bark of adult pacific yew trees, serves as a great example of low yields or even a lack of sufficient plant material [10]. A lot of interest has been shown in the biotechnological production of chemical products in general and terpenoids in particular, along with an increasing demand for sustainable manufacturing. From the last two decades, the interest in biosynthesizing terpenoids from the microbial hosts has dramatically increased [11-14]. The study has been mostly focused on using the most genetically traceable and tractable microbial host E. coli [15, 16], because certain aspects, including genetic engineering, characterisation, reliability, and independence of biological modules, are still fraught with uncertainty [17]. Several other microbial hosts, both from prokaryotic and eukaryotic communities, have been explored in recent years to overcome such limitations. The eukaryotic host, Saccharomyces cerevisiae, has been explored and contributed well towards the production of higher-order terepenoids [18]; however, Bacillus subtilis has been actively favoured for biosynthesizing the lower-order terpenoids [19,20]. The earlier path breaking studies showed that the terpenoid precursors, isopentenyl diphosphate (IPP) and dimethyallyl diphosphate (DMAPP), are endogenously biosynthesized by the mevalonate pathway [21-24] and this mechanism, which is present in Eukarya, Archaea, and some bacteria, has been extensively studied [25]. Research studies in past two decades unravel the existence of a mevalonate-independent pathway, known as methylerythritol phosphate pathway (MEP), for the biosynthesis of C5-molecules IPP and DMAPP in the cell organelles of plants, like plastids and in majority of eubacteria [26,27]. Condensation of two or more of these molecules leads to the formation of the larger prenyl diphosphate compounds geranyl diphosphate (GPP), farnesyl diphosphate (FPP), and geranylgeranyl diphosphate (GGPP). To This preprint research paper has not been peer reviewed. Electronic copy available at: https://ssrn.com/abstract=4585173 P r e p r i n t n o t p e e r r e v i e w e d