Identifying functionally important cis‐peptide containing segments in proteins and their utility in molecular function annotation

Abstract

Cis-peptide embedded segments are rare in proteins but often highlight their important role in molecular function when they do occur. The high evolutionary conservation of these segments illustrates this observation almost universally, although no attempt has been made to systematically use this information for the purpose of function annotation. In the present study, we demonstrate how geometric clustering and level-specific Gene Ontology molecular-function terms (also known as annotations) can be used in a statistically significant manner to identify cis-embedded segments in a protein linked to its molecular function. The present study identifies novel cis-peptide fragments, which are subsequently used for fragmentbased function annotation. Annotation recall benchmarks interpreted using the receiver-operator characteristic plot returned an area-under-curve > 0.9, corroborating the utility of the annotation method. In addition, we identified cis-peptide fragments occurring in conjunction with functionally important trans-peptide fragments, providing additional insights into molecular function. We further illustrate the applicability of our method in function annotation where homology-based annotation transfer is not possible. The findings of the present study add to the repertoire of function annotation approaches and also facilitate engineering, design and allied studies around the cis-peptide neighborhood of proteins.

Development of a structure-based computational simulation to optimize the blocking efficacy of pro-antibodies

“…To avoid d -amino acids and cis peptide bonds in pro-Ab, these structures were validated by VMD software. 26–29 These initial structures were then simulated using the software package AMBER 18 with the all-hydrogen amino acid AMBER FF14SB force field and generalized Born solvent model (igb = 5). 30–32 All MD simulations were performed in the NVT ensembles with a simulation temperature of 310 K, unless otherwise stated, using the Langevin integrator with an integration time step of 2 fs and SHAKE constraints 33 for all covalent bonds involving hydrogen atoms.…”

“…The 3D pro-Ab structures were built using Discovery Studio Software (San Diego, CA, USA). To avoid D-amino acids and cis peptide bonds in pro-Ab, these structures were validated by VMD software [26][27][28][29]. These initial structures were then simulated using the software package AMBER 18 with the all-hydrogen amino acid AMBER FF14SB force field and generalized Born solvent model (igb=5) [30][31][32].…”

Molecular Dynamics Information Improves cis-Peptide-Based Function Annotation of Proteins

“…All GO terms with p value ≤0.05 and propensities ≥20 were accepted to conform to statistically significant enrichment, similar to our previous studies. 9,22 The fragments associated with these enriched GO terms were inferred to have functional relevance to their corresponding proteins and inducted into a library of functionally important fragments (F0 data set). Our analyses yielded 2095 Xaa-cisPro and 369 Xaa-cisXnp (Xaa: any amino acid, Xnp: non-Pro amino acid) functionally important FL6 fragments composed of unique 848 Pro and 124 non-Pro cis-peptides.…”

“…The p value of a GO term 'X' occurring k times in a cluster was calculated as Fragments with propensity ≥20 were considered functionally important, while p value ≤0.05 was used to confirm their statistically significance (F0 data set), similar to our previous studies. 9,22 Information Content Calculation…”

“…Preparing the Functionally Important Fragment Library (F0 Data Set) Clustered fragments exhibit an enrichment of GO MF terms that can be utilized to detect fragments relevant to the molecular function of the corresponding protein. 9,22 Hence, the GO MF terms of the PDB entries were assigned to the clustered FL6 and FL8 fragments and subsequently mapped to the parent GO MF at levels 3−5 using the GO graph (Supplementary Figure S1). Some of the GO MFs can be at multiple levels depending on the path used to trace it to the root of the graph and can, therefore, have multiple parent terms at a given level.…”