Comparative modelling of protein structure and its impact on microbial cell factories

Whole genome sequencing of Clarireedia aff. paspali reveals potential pathogenesis factors in Clarireedia species, causal agents of dollar spot in turfgrass

Dollar spot is one of the most damaging diseases in turfgrass, reducing its quality and playability. Two species, Clarireedia monteithiana and C. jacksonii (formerly Sclerotinia homoeocarpa) have been reported so far in the United States To study the Clarireedia genome, two isolates H2 and H3, sampled from seashore paspalum in Hawaii in 2019 were sequenced via Illumina paired-end sequencing by synthesis technology and PacBio SMRT sequencing. Both isolates were identified as C. aff. paspali, a novel species in the United States Using short and long reads, C. aff. paspali H3 contained 193 contigs with 48.6 Mbp and presented the most completed assembly and annotation among Clarireedia species. Out of the 13,428 protein models from AUGUSTUS, 349 cytoplasmic effectors and 13 apoplastic effectors were identified by EffectorP. To further decipher Clarireedia pathogenicity, C. aff. paspali genomes (H2 and H3), as well as available C. jacksonii (LWC-10 and HRI11), C. monteithiana (DRR09 and RB-19) genomes were screened for fifty-four pathogenesis determinants, previously identified in S. sclerotiorum. Seventeen orthologs of pathogenicity genes have been identified in Clarireedia species involved in oxalic acid production (pac1, nox1), mitogen-activated protein kinase cascade (pka1, smk3, ste12), appressorium formation (caf1, pks13, ams2, rgb1, rhs1) and glycolytic pathway (gpd). Within these genes, 366 species-specific SNPs were recorded between Clarireedia species; twenty-eight were non-synonymous and non-conservative. The predicted protein structure of six of these genes showed superimposition of the models among Clarireedia spp. The genomic variations revealed here could potentially lead to differences in pathogenesis and other physiological functions among Clarireedia species.

Deep learning-based molecular dynamics simulation for structure-based drug design against SARS-CoV-2

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), has led to a global pandemic. Deep learning (DL) technology and molecular dynamics (MD) simulation are two mainstream computational approaches to investigate the geometric, chemical and structural features of protein and guide the relevant drug design. Despite a large amount of research papers focusing on drug design for SARS-COV-2 using DL architectures, it remains unclear how the binding energy of the protein-protein/ligand complex dynamically evolves which is also vital for drug development. In addition, traditional deep neural networks usually have obvious deficiencies in predicting the interaction sites as protein conformation changes. In this review, we introduce the latest progresses of the DL and DL-based MD simulation approaches in structure-based drug design (SBDD) for SARS-CoV-2 which could address the problems of protein structure and binding prediction, drug virtual screening, molecular docking and complex evolution. Furthermore, the current challenges and future directions of DL-based MD simulation for SBDD are also discussed.

Genome sequencing and in silico analysis of isoprene degrading monooxygenase enzymes of Sphingobium sp. BHU LFT2

The whole genome sequencing of a novel isoprene degrading strain of Sphingobium sp. BHU LFT2, its in silico analysis for identifying and characterizing enzymes, especially isoprene monooxygenases (IsoMO), which initiate the degradation process, and in vitro validation with cell extract of optimal temperature and pH and analysis for utilizing isoprene as the preferential substrate, were conducted. The most efficient monooxygenase was identified through comparative analyses using molecular docking followed by molecular dynamics simulation approach. The in silico results revealed high thermostability for most of the monooxygenases. Most potent monooxygenase with locus ID JQK15_20300 exhibiting high sequence similarity with known monooxygenases of isoprene-degrading Rhodococcus sp. LB1 and SC4 strains was identified. Interaction energy of -17.25 kJ/mol for JQK15_20300 with isoprene, was almost similar as that analysed for above-mentioned similar known counterparts, was exhibited by the molecular docking. Molecular dynamic simulation of 100 ns and free energy analysis of JQK15_20300 in the complex with isoprene gave persistent interaction of isoprene with JQK15_20300 during the simulation with high average binding energy of -47.13 kJ/mol thus proving higher affinity of JQK15_20300 for isoprene. The study revealed that the highly efficient isoprene degrading strain of Sphingobium sp. BHU LFT2 having effective monooxygenase could be utilized for large-scale applications including detoxification of air contaminated with isoprene in closed working systems.Communicated by Ramaswamy H. Sarma.

Parallel evolution of non-homologous isofunctional enzymes in methionine biosynthesis

Experimental validation of enzyme function is crucial for genome interpretation, but it remains challenging because it cannot be scaled up to accommodate the constant accumulation of genome sequences. We tackled this issue for the MetA and MetX enzyme families, phylogenetically unrelated families of acyl-L-homoserine transferases involved in L-methionine biosynthesis. Members of these families are prone to incorrect annotation because MetX and MetA enzymes are assumed to always use acetyl-CoA and succinyl-CoA, respectively. We determined the enzymatic activities of 100 enzymes from diverse species, and interpreted the results by structural classification of active sites based on protein structure modeling. We predict that >60% of the 10,000 sequences from these families currently present in databases are incorrectly annotated, and suggest that acetyl-CoA was originally the sole substrate of these isofunctional enzymes, which evolved to use exclusively succinyl-CoA in the most recent bacteria. We also uncovered a divergent subgroup of MetX enzymes in fungi that participate only in L-cysteine biosynthesis as O-succinyl-L-serine transferases.

Modelface: an Application Programming Interface (API) for Homology Modeling Studies Using Modeller Software

An interactive application, Modelface, was presented for Modeller software based on windows platform. The application is able to run all steps of homology modeling including pdb to fasta generation, running clustal, model building and loop refinement. Other modules of modeler including energy calculation, energy minimization and the ability to make single point mutations in the PDB structures are also implemented inside Modelface. The API is a simple batch based application with no memory occupation and is free of charge for academic use. The application is also able to repair missing atom types in the PDB structures making it suitable for many molecular modeling studies such as docking and molecular dynamic simulation. Some successful instances of modeling studies using Modelface are also reported.

Strategies and molecular tools to fight antimicrobial resistance: resistome, transcriptome, and antimicrobial peptides

The increasing number of antibiotic resistant bacteria motivates prospective research toward discovery of new antimicrobial active substances. There are, however, controversies concerning the cost-effectiveness of such research with regards to the description of new substances with novel cellular interactions, or description of new uses of existing substances to overcome resistance. Although examination of bacteria isolated from remote locations with limited exposure to humans has revealed an absence of antibiotic resistance genes, it is accepted that these genes were both abundant and diverse in ancient living organisms, as detected in DNA recovered from Pleistocene deposits (30,000 years ago). Indeed, even before the first clinical use of antibiotics more than 60 years ago, resistant organisms had been isolated. Bacteria can exhibit different strategies for resistance against antibiotics. New genetic information may lead to the modification of protein structure affecting the antibiotic carriage into the cell, enzymatic inactivation of drugs, or even modification of cellular structure interfering in the drug-bacteria interaction. There are still plenty of new genes out there in the environment that can be appropriated by putative pathogenic bacteria to resist antimicrobial agents. On the other hand, there are several natural compounds with antibiotic activity that may be used to oppose them. Antimicrobial peptides (AMPs) are molecules which are wide-spread in all forms of life, from multi-cellular organisms to bacterial cells used to interfere with microbial growth. Several AMPs have been shown to be effective against multi-drug resistant bacteria and have low propensity to resistance development, probably due to their unique mode of action, different from well-known antimicrobial drugs. These substances may interact in different ways with bacterial cell membrane, protein synthesis, protein modulation, and protein folding. The analysis of bacterial transcriptome may contribute to the understanding of microbial strategies under different environmental stresses and allows the understanding of their interaction with novel AMPs.

Proposed Bioactive Conformations of Opiorphin, an Endogenous Dual APN/NEP Inhibitor

The conformational profiles for the endogenous peptide Opiorphin and a set of seven analogues exhibiting different inhibitory activities toward human aminopeptidase N (hAPN) and human neprilysin (hNEP) were independently computed to deduce a bioactive conformation that Opiorphin may adopt when binding these two enzymes. The conformational space was thoroughly sampled using an iterative simulated annealing protocol, and a library of low-energy conformers was generated for each peptide. Bioactive Opiorphin conformations fitting our experimental structure-activity relationship data were identified for hAPN and hNEP using computational pairwise comparisons between each of the unique low-energy conformations of Opiorphin and its analogues. The obtained results provide a structural explanation for the dual hAPN and hNEP inhibitory activity of Opiorphin and show that the inborn flexibility of Opiorphin is essential for its analgesic activity.