scholarly journals Disjoint combinations profiling (DCP): a new method for the prediction of antibody CDR conformation from sequence

2014 ◽  
Author(s):  
Dimitris Nikoloudis ◽  
Jim E. Pitts ◽  
José W. Saldanha
Keyword(s):  
Protein Engineering ◽  
Prediction Accuracy ◽  
Variable Region ◽  
New Method ◽  
Engineering Applications ◽  
Variable Regions ◽  
Blind Prediction ◽  
Novel Method ◽  
Complementarity Determining Regions ◽  
Sequence Rules

The accurate prediction of the conformation of Complementarity-Determining Regions (CDRs) is important in modelling antibodies for protein engineering applications. Specifically, the Canonical paradigm has proved successful in predicting the CDR conformation in antibody variable regions. It relies on canonical templates which detail allowed residues at key positions in the variable region framework or in the CDR itself for 5 of the 6 CDRs. While no templates have as yet been defined for the hypervariable CDR-H3, instead, reliable sequence rules have been devised for predicting the base of the CDR-H3 loop. Here a new method termed Disjoint Combinations Profiling (DCP) is presented, which contributes a considerable advance in the prediction of CDR conformations. This novel method is explained and compared with canonical templates and sequence rules in a 3-way blind prediction. DCP achieved 93% accuracy over 951 blind predictions and showed an improvement in cumulative accuracy compared to predictions with canonical templates or sequence-rules. In addition to its overall improvement in prediction accuracy, it is suggested that DCP is open to better implementations in the future and that it can improve as more antibody structures are deposited in the databank. In contrast, it is argued that canonical templates and sequence rules may have reached their peak.

scholarly journals Disjoint combinations profiling (DCP): a new method for the prediction of antibody CDR conformation from sequence.

2014 ◽  
Author(s):  
Dimitris Nikoloudis ◽  
Jim E. Pitts ◽  
José W. Saldanha
Keyword(s):  
Protein Engineering ◽  
Prediction Accuracy ◽  
Variable Region ◽  
New Method ◽  
Engineering Applications ◽  
Variable Regions ◽  
Blind Prediction ◽  
Novel Method ◽  
Complementarity Determining Regions ◽  
Sequence Rules

The accurate prediction of the conformation of Complementarity-Determining Regions (CDRs) is important in modelling antibodies for protein engineering applications. Specifically, the Canonical paradigm has proved successful in predicting the CDR conformation in antibody variable regions. It relies on canonical templates which detail allowed residues at key positions in the variable region framework or in the CDR itself for 5 of the 6 CDRs. While no templates have as yet been defined for the hypervariable CDR-H3, instead, reliable sequence rules have been devised for predicting the base of the CDR-H3 loop. Here a new method termed Disjoint Combinations Profiling (DCP) is presented, which contributes a considerable advance in the prediction of CDR conformations. This novel method is explained and compared with canonical templates and sequence rules in a 3-way blind prediction. DCP achieved 93% accuracy over 951 blind predictions and showed an improvement in cumulative accuracy compared to predictions with canonical templates or sequence-rules. In addition to its overall improvement in prediction accuracy, it is suggested that DCP is open to better implementations in the future and that it can improve as more antibody structures are deposited in the databank. In contrast, it is argued that canonical templates and sequence rules may have reached their peak.

scholarly journals Disjoint combinations profiling (DCP): a new method for the prediction of antibody CDR conformation from sequence.

2014 ◽  
Author(s):  
Dimitris Nikoloudis ◽  
Jim E. Pitts ◽  
José W. Saldanha
Keyword(s):  
Protein Engineering ◽  
Prediction Accuracy ◽  
Variable Region ◽  
New Method ◽  
Engineering Applications ◽  
Variable Regions ◽  
Blind Prediction ◽  
Novel Method ◽  
Complementarity Determining Regions ◽  
Sequence Rules

The accurate prediction of the conformation of Complementarity-Determining Regions (CDRs) is important in modelling antibodies for protein engineering applications. Specifically, the Canonical paradigm has proved successful in predicting the CDR conformation in antibody variable regions. It relies on canonical templates which detail allowed residues at key positions in the variable region framework or in the CDR itself for 5 of the 6 CDRs. While no templates have as yet been defined for the hypervariable CDR-H3, instead, reliable sequence rules have been devised for predicting the base of the CDR-H3 loop. Here a new method termed Disjoint Combinations Profiling (DCP) is presented, which contributes a considerable advance in the prediction of CDR conformations. This novel method is explained and compared with canonical templates and sequence rules in a 3-way blind prediction. DCP achieved 93% accuracy over 951 blind predictions and showed an improvement in cumulative accuracy compared to predictions with canonical templates or sequence-rules. In addition to its overall improvement in prediction accuracy, it is suggested that DCP is open to better implementations in the future and that it can improve as more antibody structures are deposited in the databank. In contrast, it is argued that canonical templates and sequence rules may have reached their peak.

scholarly journals Disjoint combinations profiling (DCP): a new method for the prediction of antibody CDR conformation from sequence

2014 ◽  
Author(s):  
Dimitris Nikoloudis ◽  
Jim E. Pitts ◽  
José W. Saldanha
Keyword(s):  
Protein Engineering ◽  
Prediction Accuracy ◽  
Variable Region ◽  
New Method ◽  
Engineering Applications ◽  
Variable Regions ◽  
Blind Prediction ◽  
Novel Method ◽  
Complementarity Determining Regions ◽  
Sequence Rules

The accurate prediction of the conformation of Complementarity-Determining Regions (CDRs) is important in modelling antibodies for protein engineering applications. Specifically, the Canonical paradigm has proved successful in predicting the CDR conformation in antibody variable regions. It relies on canonical templates which detail allowed residues at key positions in the variable region framework or in the CDR itself for 5 of the 6 CDRs. While no templates have as yet been defined for the hypervariable CDR-H3, instead, reliable sequence rules have been devised for predicting the base of the CDR-H3 loop. Here a new method termed Disjoint Combinations Profiling (DCP) is presented, which contributes a considerable advance in the prediction of CDR conformations. This novel method is explained and compared with canonical templates and sequence rules in a 3-way blind prediction. DCP achieved 93% accuracy over 951 blind predictions and showed an improvement in cumulative accuracy compared to predictions with canonical templates or sequence-rules. In addition to its overall improvement in prediction accuracy, it is suggested that DCP is open to better implementations in the future and that it can improve as more antibody structures are deposited in the databank. In contrast, it is argued that canonical templates and sequence rules may have reached their peak.

scholarly journals Evidence supporting somatic assembly of the DNA segments (minigenes), coding for the framework, and complementarity-determining segments of immunoglobulin variable regions.

1979 ◽  
Vol 149 (6) ◽  
pp. 1299-1313 ◽  
Author(s):  
E A Kabat ◽  
T T Wu ◽  
H Bilofsky
Keyword(s):  
Adult Mouse ◽  
Germ Line ◽  
Variable Region ◽  
Single Copy ◽  
Variable Regions ◽  
X Ray ◽  
V Genes ◽  
V Region ◽  
Complementarity Determining Regions ◽  
The One

Two sets of apparently conflicting data on the genes coding for the variable region are being accumulated. One suggests that the sets of nucleotides coding for the framework segments of immunoglobulin light and heavy (VL and VH) chains assort independently and are therefore germ-line minigenes which, together with sets of nucleotides coding for the complementarity-determining regions (CDR) or segments assemble to form complete variable (V)-region genes (15, 16, 33). The other, based on the findings with clones from 12-d-old embryo and adult mouse coding for V-regions, infer that the first three frameworks and the three complementarity-determining segments are already assembled as germ-line V-genes (17-21). It is now generally accepted that the J segment, which in the one instance sequenced (21) is made up of nucleotides coding for framework (FR)4 plus two residues of CDR3, is a minigene. An examination of sequences of human, mouse, and rabbit V-regions, assuming the latter hypothesis, indicates that individual framework sets would have to be present in many copies. The FR2 segment found in one human, 20 mice, and 13 rabbits would have to be present in at least 10/14 copies in the NZB, and 5/6 in the BALB/c mouse, and 12/13 in the rabbit. The X-ray crystallographic data show this region to be a loop, projecting out from the V-domain, capable of accommodating many substiutions and 12 and 8 alternative sequences for this FR2 segment have been found in mouse and rabbit VK chains with substitutions possible at 13 of the 15 positions. These alternative sequences occur much less frequently than the preserved FR2 segment. Thus, there is no basis in the protein structure to account for evolutionary stability of this FR2 segment if it occurs in so many copies in germ-line genes coding for residues 1-96, but its stability is easily explained if it were coded for by a separate germ-line minigene present as a single copy; the alternative forms could then have arisen by duplication and mutation of this minigene. Somatic assembly of the minigene segments for the three framework and three complementarity-determining segments during differentiation would account completely for our assortment data from which FR4 was inferred to be a minigene.

scholarly journals Sequence intrinsic somatic mutation mechanisms contribute to affinity maturation of VRC01-class HIV-1 broadly neutralizing antibodies

2017 ◽  
Vol 114 (32) ◽  
pp. 8614-8619 ◽  
Author(s):  
Joyce K. Hwang ◽  
Chong Wang ◽  
Zhou Du ◽  
Robin M. Meyers ◽  
Thomas B. Kepler ◽  
...  
Keyword(s):  
B Cells ◽  
Neutralizing Antibodies ◽  
Somatic Hypermutation ◽  
Human Subjects ◽  
Variable Region ◽  
Affinity Maturation ◽  
Broadly Neutralizing Antibodies ◽  
Variable Regions ◽  
Complementarity Determining Regions ◽  
Hiv 1

Variable regions of Ig chains provide the antigen recognition portion of B-cell receptors and derivative antibodies. Ig heavy-chain variable region exons are assembled developmentally from V, D, J gene segments. Each variable region contains three antigen-contacting complementarity-determining regions (CDRs), with CDR1 and CDR2 encoded by the V segment and CDR3 encoded by the V(D)J junction region. Antigen-stimulated germinal center (GC) B cells undergo somatic hypermutation (SHM) of V(D)J exons followed by selection for SHMs that increase antigen-binding affinity. Some HIV-1–infected human subjects develop broadly neutralizing antibodies (bnAbs), such as the potent VRC01-class bnAbs, that neutralize diverse HIV-1 strains. Mature VRC01-class bnAbs, including VRC-PG04, accumulate very high SHM levels, a property that hinders development of vaccine strategies to elicit them. Because many VRC01-class bnAb SHMs are not required for broad neutralization, high overall SHM may be required to achieve certain functional SHMs. To elucidate such requirements, we used a V(D)J passenger allele system to assay, in mouse GC B cells, sequence-intrinsic SHM-targeting rates of nucleotides across substrates representing maturation stages of human VRC-PG04. We identify rate-limiting SHM positions for VRC-PG04 maturation, as well as SHM hotspots and intrinsically frequent deletions associated with SHM. We find that mature VRC-PG04 has low SHM capability due to hotspot saturation but also demonstrate that generation of new SHM hotspots and saturation of existing hotspot regions (e.g., CDR3) does not majorly influence intrinsic SHM in unmutated portions of VRC-PG04 progenitor sequences. We discuss implications of our findings for bnAb affinity maturation mechanisms.

scholarly journals Prospective Characterization of Full-Length Hepatitis C Virus NS5A Quasispecies during Induction and Combination Antiviral Therapy

2000 ◽  
Vol 74 (19) ◽  
pp. 9028-9038 ◽  
Author(s):  
J.-B. Nousbaum ◽  
S. J. Polyak ◽  
S. C. Ray ◽  
D. G. Sullivan ◽  
A. M. Larson ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Amino Acid ◽  
Antiviral Therapy ◽  
Variable Region ◽  
Response To Therapy ◽  
Full Length ◽  
Variable Regions ◽  
C Terminus

ABSTRACT The hepatitis C virus (HCV) nonstructural 5A (NS5A) protein has been controversially implicated in the inherent resistance of HCV to interferon (IFN) antiviral therapy in clinical studies. In this study, the relationship between NS5A mutations and selection pressures before and during antiviral therapy and virologic response to therapy were investigated. Full-length NS5A clones were sequenced from 20 HCV genotype 1-infected patients in a prospective, randomized clinical trial of IFN induction (daily) therapy and IFN plus ribavirin combination therapy. Pretreatment NS5A nucleotide and amino acid phylogenies did not correlate with clinical IFN responses and domains involved in NS5A functions in vitro were all well conserved before and during treatment. A consensus IFN sensitivity-determining region (ISDR237–276) sequence associated with IFN resistance was not found, although the presence of Ala245 within the ISDR was associated with nonresponse to treatment in genotype 1a-infected patients (P < 0.01). There were more mutations in the 26 amino acids downstream of the ISDR required for PKR binding in pretreatment isolates from responders versus nonresponders in both HCV-1a- and HCV-1b-infected patients (P < 0.05). In HCV-1a patients, more amino acid changes were observed in isolates from IFN-sensitive patients (P < 0.001), and the mutations appeared to be concentrated in two variable regions in the C terminus of NS5A, that corresponded to the previously described V3 region and a new variable region, 310 to 330. Selection of pretreatment minor V3 quasispecies was observed within the first 2 to 6 weeks of therapy in responders but not nonresponders, whereas the ISDR and PKR binding domains did not change in either patient response group. These data suggest that host-mediated selective pressures act primarily on the C terminus of NS5A and that NS5A can perturb or evade the IFN-induced antiviral response using sequences outside of the putative ISDR. Mechanistic studies are needed to address the role of the C terminus of NS5A in HCV replication and antiviral resistance.

scholarly journals Characterization of Neutralizing Antibody Responses Elicited by Clade A Envelope Immunogens Derived from Early Transmitted Viruses

2008 ◽  
Vol 82 (12) ◽  
pp. 5912-5921 ◽  
Author(s):  
Zane Kraft ◽  
Katharine Strouss ◽  
William F. Sutton ◽  
Brad Cleveland ◽  
For Yue Tso ◽  
...  
Keyword(s):  
Chronic Infection ◽  
Neutralizing Antibodies ◽  
Acute Infection ◽  
Variable Region ◽  
Neutralizing Antibody ◽  
Antibody Responses ◽  
Virus Envelope ◽  
Variable Regions ◽  
Clade B ◽  
Region Length

ABSTRACT The vast majority of studies with candidate immunogens based on the human immunodeficiency virus envelope (Env) have been conducted with Env proteins derived from clade B viruses isolated during chronic infection. Whether non-clade B Env protein immunogens will elicit antibodies with epitope specificities that are similar to those of antibodies elicited by clade B Envs and whether the antibodies elicited by Envs derived from early transmitted viruses will be similar to those elicited by Envs derived from viruses isolated during chronic infection are currently unknown. Here we performed immunizations with four clade A Envs, cloned directly from the peripheral blood of infected individuals during acute infection, which differed in lengths and extents of glycosylation. The antibody responses elicited by these four Envs were compared to each other and to those elicited by a well-characterized clade B Env immunogen derived from the SF162 virus, which was isolated during chronic infection. Only one clade A Env, the one with the fewer glycosylation sites, elicited homologous neutralizing antibodies (NAbs); these did not target the V1, V2, or V3 regions. In contrast, all four clade A Envs elicited anti-V3 NAbs against “easy-to-neutralize” clade B and clade A isolates, irrespective of the variable region length and extent of glycosylation of the Env used as an immunogen. These anti-V3 NAbs did not access their epitopes on homologous and heterologous clade A, or B, neutralization-resistant viruses. The length and extent of glycosylation of the variable regions on the clade A Env immunogens tested did not affect the breadth of the elicited NAbs. Our data also indicate that the development of cross-reactive NAbs against clade A viruses faces similar hurdles to the development of cross-reactive anti-clade B NAbs.

scholarly journals Investigation of major amino acid residues of anti-norfloxacin monoclonal antibodies responsible for binding with fluoroquinolones

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Patamalai Boonserm ◽  
Songchan Puthong ◽  
Thanaporn Wichai ◽  
Sajee Noitang ◽  
Pongsak Khunrae ◽  
...  
Keyword(s):  
Monoclonal Antibodies ◽  
Amino Acid ◽  
3D Structure ◽  
Cross Reactivity ◽  
Enzyme Linked Immunosorbent Assay ◽  
Amino Acid Residues ◽  
Variable Regions ◽  
Complementarity Determining Regions ◽  
Crucial Part ◽  
Major Amino Acid

AbstractIt is important to understand the amino acid residues that govern the properties of the binding between antibodies and ligands. We studied the binding of two anti-norfloxacins, anti-nor 132 and anti-nor 155, and the fluoroquinolones norfloxacin, enrofloxacin, ciprofloxacin, and ofloxacin. Binding cross-reactivities tested by an indirect competitive enzyme-linked immunosorbent assay indicated that anti-nor 132 (22–100%) had a broader range of cross-reactivity than anti-nor 155 (62–100%). These cross-reactivities correlated with variations in the numbers of interacting amino acid residues and their positions. Molecular docking was employed to investigate the molecular interactions between the fluoroquinolones and the monoclonal antibodies. Homology models of the heavy chain and light chain variable regions of each mAb 3D structure were docked with the fluoroquinolones targeting the crucial part of the complementarity-determining regions. The fluoroquinolone binding site of anti-nor 155 was a region of the HCDR3 and LCDR3 loops in which hydrogen bonds were formed with TYR (H:35), ASN (H:101), LYS (H:106), ASN (L:92), and ASN (L:93). These regions were further away in anti-nor 132 and could not contact the fluoroquinolones. Another binding region consisting of HIS (L:38) and ASP (H:100) was found for norfloxacin, enrofloxacin, and ciprofloxacin, whereas only ASP (H:100) was found for ofloxacin.

scholarly journals Strategic Team AI Path Plans: Probabilistic Pathfinding

2008 ◽  
Vol 2008 ◽  
pp. 1-6 ◽  
Author(s):  
Tng C. H. John ◽  
Edmond C. Prakash ◽  
Narendra S. Chaudhari
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computer Games ◽  
Fitness Function ◽  
New Method ◽  
High Quality ◽  
Plan Generation ◽  
Novel Method ◽  
Games And Simulations

This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002), in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006). We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

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