Approaches to Backbone Flexibility in Protein-Protein Docking.

Proteins are the fundamental organic macromolecules in living systems that play a key role in a variety of biological functions including immunological detection, intracellular trafficking, and signal transduction. The docking of proteins has greatly advanced during recent decades and has become a crucial complement to experimental methods. Protein-protein docking is a helpful method for simulating protein complexes whose structures have not yet been solved experimentally. This chapter focuses on major search tactics along with various docking programs used in protein-protein docking algorithms, which include: direct search, exhaustive global search, local shape feature matching, randomized search, and broad category of post-docking approaches. As backbone flexibility predictions and interactions in high-resolution protein-protein docking remain important issues in the overall optimization context, we have put forward several methods and solutions used to handle backbone flexibility. In addition, various docking methods that are utilized for flexible backbone docking, including ATTRACT, FlexDock, FLIPDock, HADDOCK, RosettaDock, FiberDock, etc., along with their scoring functions, algorithms, advantages, and limitations are discussed. Moreover, what progress in search technology is expected, including not only the creation of new search algorithms but also the enhancement of existing ones, has been debated. As conformational flexibility is one of the most crucial factors affecting docking success, more work should be put into evaluating the conformational flexibility upon binding for a particular case in addition to developing new algorithms to replace the rigid body docking and scoring approach.

Challenges of Protein-Protein Docking of the Membrane Proteins.

Despite the recent advances in the determination of high-resolution membrane protein (MP) structures, the structural and functional characterization of MPs remains extremely challenging, mainly due to the hydrophobic nature, low abundance, poor expression, purification, and crystallization difficulties associated with MPs. Whereby the major challenges/hurdles for MP structure determination are associated with the expression, purification, and crystallization procedures. Although there have been significant advances in the experimental determination of MP structures, only a limited number of MP structures (approximately less than 1% of all) are available in the Protein Data Bank (PDB). Therefore, the structures of a large number of MPs still remain unresolved, which leads to the availability of widely unplumbed structural and functional information related to MPs. As a result, recent developments in the drug discovery realm and the significant biological contemplation have led to the development of several novel, low-cost, and time-efficient computational methods that overcome the limitations of experimental approaches, supplement experiments, and provide alternatives for the characterization of MPs. Whereby the fine tuning and optimizations of these computational approaches remains an ongoing endeavor.Computational methods offer a potential way for the elucidation of structural features and the augmentation of currently available MP information. However, the use of computational modeling can be extremely challenging for MPs mainly due to insufficient knowledge of (or gaps in) atomic structures of MPs. Despite the availability of numerous in silico methods for 3D structure determination the applicability of these methods to MPs remains relatively low since all methods are not well-suited or adequate for MPs. However, sophisticated methods for MP structure predictions are constantly being developed and updated to integrate the modifications required for MPs. Currently, different computational methods for (1) MP structure prediction, (2) stability analysis of MPs through molecular dynamics simulations, (3) modeling of MP complexes through docking, (4) prediction of interactions between MPs, and (5) MP interactions with its soluble partner are extensively used. Towards this end, MP docking is widely used. It is notable that the MP docking methods yet few in number might show greater potential in terms of filling the knowledge gap. In this chapter, MP docking methods and associated challenges have been reviewed to improve the applicability, accuracy, and the ability to model macromolecular complexes.

Mycoplasma mycoides subspecies capri, an uncommon mastitis and respiratory pathogen isolated in a German flock of goats.

Mycoplasma mycoides ssp. capri (Mmc) is one of the etiological microorganisms of contagious agalactia, which is among the diseases causing the highest economical losses in small ruminants. We report a disease outbreak in a German flock that led to significant suffering of goats characterized by mastitis, arthritis, pleuropneumonia and sudden deaths. Mmc was persistently isolated from many animals both from milk, and from a number of different swab and tissue samples. A number of closely related Mycoplasma spp. have to be taken into consideration to rule out important animal epizootics listed by European Animal Health Law and the World Organisation for Animal Health (WOAH). Some goats developed cross-reacting antibodies against Mycoplasma mycoides ssp. mycoides. Although Mmc is believed to be an uncommon microorganism in Germany, this study highlights that veterinarians should consider this pathogen in their work during herd health monitoring in Central Europe. Although eradication was not fully achieved, autogenous vaccination significantly seemed to improve animal health and welfare.

A significance score for protein-protein interaction models through random docking.

Comparing accuracies of structural protein-protein interaction (PPI) models for different complexes on an absolute scale is a challenge, requiring normalization of scores across structures of different sizes and shapes. To help address this challenge, we have developed a statistical significance metric for docking models, called random-docking (RD) p-value. This score evaluates a PPI model based on how likely a random docking process is to produce a model of better or equal accuracy. The binding partners are randomly docked against each other a large number of times, and the probability of sampling a model of equal or greater accuracy from this reference distribution is the RD p-value. Using a subset of top predicted models from CAPRI (Critical Assessment of PRediction of Interactions) rounds over 2017-2020, we find that the ease of achieving a given root mean squared deviation or DOCKQ score varies considerably by target; achieving the same relative metric can be thousands of times easier for one complex compared to another. In contrast, RD p-values inherently normalize scores for models of different complexes, making them globally comparable. Furthermore, one can calculate RD p-values after generating a reference distribution that accounts for prior information about the interface geometry, such as residues involved in binding, by giving the random-docking process access the same information. Thus, one can decouple improvements in prediction accuracy that arise solely from basic modeling constraints from those due to the rest of the method. We provide efficient code for computing RD p-values at https://github.com/Grigoryanlab/RDP.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

G protein-coupled receptor-mediated membrane targeting of PLCγ2 is essential for neutrophil chemotaxis.

The current dogma is that chemoattractants G protein-coupled receptors activate ß phospholipase C while receptor tyrosine kinases activate γ phospholipase C. Here, we show that chemoattractant/G protein-coupled receptor-mediated membrane recruitment of γ2 phospholipase C constitutes G protein-coupled receptor-mediated phospholipase C signaling and is essential for neutrophil polarization and migration during chemotaxis. In response to a chemoattractant stimulation, cells lacking γ2 phospholipase C (plcg2kd) displayed altered dynamics of diacylglycerol production and calcium response, increased Ras/PI3K/Akt activation, elevated GSK3 phosphorylation and cofilin activation, impaired dynamics of actin polymerization, and, consequently, defects in cell polarization and migration during chemotaxis. The study reveals a molecular mechanism of membrane targeting of γ2 phospholipase C and the signaling pathways by which γ2 phospholipase C plays an essential role in neutrophil chemotaxis.

Critical Assessment of Methods for Predicting the 3D Structure of Proteins and Protein Complexes.

Advances in a scientific discipline are often measured by small, incremental steps. In this review, we report on two intertwined disciplines in the protein structure prediction field, modeling of single chains and modeling of complexes, that have over decades emulated this pattern, as monitored by the community-wide blind prediction experiments CASP and CAPRI. However, over the past few years, dramatic advances were observed for the accurate prediction of single protein chains, driven by a surge of deep learning methodologies entering the prediction field. We review the mainscientific developments that enabled these recent breakthroughs and feature the important role of blind prediction experiments in building up and nurturing the structure prediction field. We discuss how the new wave of artificial intelligence-based methods is impacting the fields of computational and experimental structural biology and highlight areas in which deep learning methods are likely to lead to future developments, provided that major challenges are overcome.

Evaluating GPCR modeling and docking strategies in the era of deep learning-based protein structure prediction.

While deep learning (DL) has brought a revolution in the protein structure prediction field, still an important question remains how the revolution can be transferred to advances in structure-based drug discovery. Because the lessons from the recent GPCR dock challenge were inconclusive primarily due to the size of the dataset, in this work we further elaborated on 70 diverse GPCR complexes bound to either small molecules or peptides to investigate the best-practice modeling and docking strategies for GPCR drug discovery. From our quantitative analysis, it is shown that substantial improvements in docking and virtual screening have been possible by the advance in DL-based protein structure predictions with respect to the expected results from the combination of best pre-DL tools. The success rate of docking on DL-based model structures approaches that of cross-docking on experimental structures, showing over 30% improvement from the best pre-DL protocols. This amount of performance could be achieved only when two modeling points were considered properly: 1) correct functional-state modeling of receptors and 2) receptor-flexible docking. Best-practice modeling strategies and the model confidence estimation metric suggested in this work may serve as a guideline for future computer-aided GPCR drug discovery scenarios.

Multiscale modelling of claudin-based assemblies: A magnifying glass for novel structures of biological interfaces.

Claudins (Cldns) define a family of transmembrane proteins that are the major determinants of the tight junction integrity and tissue selectivity. They promote the formation of either barriers or ion-selective channels at the interface between two facing cells, across the paracellular space. Multiple Cldn subunits form complexes that include cis- (intracellular) interactions along the membrane of a single cell and trans- (intercellular) interactions across adjacent cells. The first description of Cldn assemblies was provided by electron microscopy, while electrophysiology, mutagenesis and cell biology experiments addressed the functional role of different Cldn homologs. However, the investigation of the molecular details of Cldn subunits and complexes are hampered by the lack of experimental native structures, currently limited to Cldn15. The recent implementation of computer-based techniques greatly contributed to the elucidation of Cldn properties. Molecular dynamics simulations and docking calculations were extensively used to refine the first Cldn multimeric model postulated from the crystal structure of Cldn15, and contributed to the introduction of a novel, alternative, arrangement. While both these multimeric assemblies were found to account for the physiological properties of some family members, they gave conflicting results for others. In this review, we illustrate the major findings on Cldn-based systems that were achieved by using state-of-the-art computational methodologies. The information provided by these results could be useful to improve the characterization of the Cldn properties and help the design of new efficient strategies to control the paracellular transport of drugs or other molecules.

First Report and Comparative Genomic Analysis of a Mycoplasma mycoides Subspecies capri HN-A in Hainan Island.

Mycoplasma mycoides subspecies capri (Mmc) is one of the six Mycoplasma mycoides cluster (Mm cluster) members, which can cause "MAKePS" (Mastitis, Arthritis, Keratoconjunctivitis, Pneumonia, Septicemia) syndrome in ruminants. These symptoms can occur alone or together in individuals or flocks of goats. However, little is known about the epidemic Mmc strains in Hainan Island, China. We aimed to isolate the endemic Mmc strains in Hainan Island and reveal their molecular characteristics by genomic sequencing and comparative genomics to mitigate the impact of Mmc on local ruminant farming. Here, the Mmc HN-A strain was isolated and identified for the first time in Hainan Island, China. The genome of Mmc HN-A was sequenced. It contains a 1,084,691 bp-long circular chromosome and 848 coding genes. The genomic analysis of Mmc HN-A revealed 16 virulence factors, 2 gene islands, and a bacterial type IV secretion system protein VirD4. Comparative genomics showed that the core genome of the five Mycoplasma mycoides contained 611 genes that could be exploited to develop drugs and endemic vaccines. Additionally, 36 specific genes were included in the Mmc HN-A genome, which could provide the possibility for the further control and prevention of the Mmc effects on local ruminants and enrich the information on Mmc strains.

Transgressions of innate moral codes - transgressions in service of the Self.

Beginning with a discussion of transgressions against innate, archetypal moral codes, I also present those transgressions carried out in service of the Self. While both represent an affront to a universal moral code, the latter often furthers an individual's relationship to the Self. These themes are illustrated through the stories of Pontius Pilate, Jephthah, Il Padrino - the Godfather, then coupled with clinical vignettes. An important theme throughout this paper concerns humanity's ongoing hunger to expiate guilt through the practices of scapegoating, sin-eating and confession. While these practices promise redemption, each seriously fails through their reluctance to address the unconscious recognition and consequences of transgressions.

Commençant par une discussion sur les transgressions des codes moraux innés et archétypaux, je présente aussi les transgressions effectuées au service du Soi. Alors que ces deux formes représentent une offense au code moral universel, la deuxième forme fait souvent avancer la relation d'un individu avec le Soi. Ces thèmes sont illustrés par les histoires de Ponce Pilate, de Jephté, d'Il Padrino - le Parrain, puis couplés à des vignettes cliniques. Un thème important tout au long de cet article concerne l'appétit constant de l'humanité pour expier sa culpabilité à travers l'utilisation du bouc-émissaire, du mangeur de péchés, ou de la confession. Alors que ces pratiques promettent la rédemption, chacune d'elle est sérieusement défaillante de par sa répugnance à s'occuper de la reconnaissance inconsciente et des conséquences des transgressions.

Comienzo con una discusión acerca de las transgresiones de los códigos morales, innatos, arquetípales. También presento aquellas transgresiones realizadas al servicio del Self. Mientras ambas representan una afrenta a un código moral universal, la última a menudo favorece la relación individual con el Self. Estos temas son ilustrados a través de historias de Poncio Pilato, Jephthah, el Padrino II, articulándolas con viñetas clínicas. Un tema importante a través del artículo concierne el constante anhelo de la humanidad de expiar la culpa a través de prácticas del chivo expiatorio, el pecado y la confesión. Mientras estas prácticas prometen la redención, cada una fracasa seriamente debido a la reluctancia a reconocer el inconsciente y las consecuencias de las transgresiones.

Começando com uma discussão sobre transgressões contra códigos morais inatos e arquetípicos, também apresento essas transgressões realizadas a serviço do Si Mesmo. Embora ambos representem uma afronta a um código moral universal, este último muitas vezes promove a relação de um indivíduo com o Si Mesmo. Esses temas são ilustrados através das histórias de Pôncio Pilatos, Jefté, Il Padrino - o Poderoso Chefão, então juntamente com vinhetas clínicas. Um tema importante ao longo deste artigo diz respeito à fome contínua da humanidade de expiar culpa através das práticas de bode expiatório, pecado e confissão. Embora essas práticas prometam redenção, cada uma falha seriamente por sua relutância em abordar o reconhecimento do inconsciente e as consequências das transgressões.

Benchmarking of structure refinement methods for protein complex models.

Protein structure docking is the process in which the quaternary structure of a protein complex is predicted from individual tertiary structures of the protein subunits. Protein docking is typically performed in two main steps. The subunits are first docked while keeping them rigid to form the complex, which is then followed by structure refinement. Structure refinement is crucial for a practical use of computational protein docking models, as it is aimed for correcting conformations of interacting residues and atoms at the interface. Here, we benchmarked the performance of eight existing protein structure refinement methods in refinement of protein complex models. We show that the fraction of native contacts between subunits is by far the most straightforward metric to improve. However, backbone dependent metrics, based on the Root Mean Square Deviation proved more difficult to improve via refinement.

Ras inhibitor CAPRI enables neutrophil-like cells to chemotax through a higher-concentration range of gradients.

Neutrophils sense and migrate through an enormous range of chemoattractant gradients through adaptation. Here, we reveal that in human neutrophils, calcium-promoted Ras inactivator (CAPRI) locally controls the GPCR-stimulated Ras adaptation. Human neutrophils lacking CAPRI (caprikd ) exhibit chemoattractant-induced, nonadaptive Ras activation; significantly increased phosphorylation of AKT, GSK-3α/3ß, and cofilin; and excessive actin polymerization. caprikd cells display defective chemotaxis in response to high-concentration gradients but exhibit improved chemotaxis in low- or subsensitive-concentration gradients of various chemoattractants, as a result of their enhanced sensitivity. Taken together, our data reveal that CAPRI controls GPCR activation-mediated Ras adaptation and lowers the sensitivity of human neutrophils so that they are able to chemotax through a higher-concentration range of chemoattractant gradients.

Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70-75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70-80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands.

Water-Food Nexus Assessment in Agriculture: A Systematic Review.

The Water-Food Nexus (WF) has been proposed to reach equitable, balanced, and sustainable access to water and food resources in the face of the growing population demand. Therefore, developing models to assess them has become more relevant. This work systematically reviews the literature on the tools used to evaluate water and food resources between 2002 and 2020. Furthermore, it reports a critical analysis of the software used to assess the WF Nexus quantitatively. The models analyzed were Life Cycle Assessment (LCA), Common Agricultural Policy Regional Impact (CAPRI), Global Food and Water System (GFWS), Soil and Water Assessment Tool (SWAT), Water Evaluation And Planning system (WEAP), and Soil Water Atmosphere Plant (SWAP). We deduced that the following are necessary in evaluating the WF Nexus: (1) the capacity to generate future scenarios, (2) a global application, and (3) the application in case studies. The present paper is the first review to provide an overview of the software applied to evaluate WF Nexus, including the advantages and disadvantages of the tools found. They can help build sustainability criteria when designing policies that reduce water and food security risks and promote efficient water and food use.

Reuse of treated water in European agriculture: Potential to address water scarcity under climate change.

The use of reclaimed or treated water from urban wastewater treatment plants for irrigation has been proposed as an alternative water source to address water scarcity issues in Europe. In this paper using agro-economic modelling, we analyse if treated water available for agriculture has the potential to reduce freshwater abstraction and, consequently, water stress. Implementing exogenous treated water quantities as an additional water supply at NUTS 2 level in the CAPRI model, we found that treated water reuse is a possible alternative supply source to address water shortages with a very negligible effect on farmers' income and food production in the EU. However, the actual water reuse and water stress reduction is very limited due to high costs. Even climate change effects on water availability and precipitation failed to induce higher use. The one-size-fits-all approach modelled via a flat rate water price only encourages the reuse of treated water in a limited number of EU member states. Thus, in order to maximise the potential of reused water to address water scarcity, different rates should be used so as to ensure higher treated water volumes at lower costs.

Exploring effectiveness of ab-initio protein-protein docking methods on a novel antibacterial protein complex dataset.

Diseases caused by bacterial infections become a critical problem in public heath. Antibiotic, the traditional treatment, gradually loses their effectiveness due to the resistance. Meanwhile, antibacterial proteins attract more attention because of broad spectrum and little harm to host cells. Therefore, exploring new effective antibacterial proteins is urgent and necessary. In this paper, we are committed to evaluating the effectiveness of ab-initio docking methods in antibacterial protein-protein docking. For this purpose, we constructed a three-dimensional (3D) structure dataset of antibacterial protein complex, called APCset, which contained $19$ protein complexes whose receptors or ligands are homologous to antibacterial peptides from Antimicrobial Peptide Database. Then we selected five representative ab-initio protein-protein docking tools including ZDOCK3.0.2, FRODOCK3.0, ATTRACT, PatchDock and Rosetta to identify these complexes' structure, whose performance differences were obtained by analyzing from five aspects, including top/best pose, first hit, success rate, average hit count and running time. Finally, according to different requirements, we assessed and recommended relatively efficient protein-protein docking tools. In terms of computational efficiency and performance, ZDOCK was more suitable as preferred computational tool, with average running time of $6.144$ minutes, average Fnat of best pose of $0.953$ and average rank of best pose of $4.158$. Meanwhile, ZDOCK still yielded better performance on Benchmark 5.0, which proved ZDOCK was effective in performing docking on large-scale dataset. Our survey can offer insights into the research on the treatment of bacterial infections by utilizing the appropriate docking methods.

Open-access data: A cornerstone for artificial intelligence approaches to protein structure prediction.

The Protein Data Bank (PDB) was established in 1971 to archive three-dimensional (3D) structures of biological macromolecules as a public good. Fifty years later, the PDB is providing millions of data consumers around the world with open access to more than 175,000 experimentally determined structures of proteins and nucleic acids (DNA, RNA) and their complexes with one another and small-molecule ligands. PDB data users are working, teaching, and learning in fundamental biology, biomedicine, bioengineering, biotechnology, and energy sciences. They also represent the fields of agriculture, chemistry, physics and materials science, mathematics, statistics, computer science, and zoology, and even the social sciences. The enormous wealth of 3D structure data stored in the PDB has underpinned significant advances in our understanding of protein architecture, culminating in recent breakthroughs in protein structure prediction accelerated by artificial intelligence approaches and deep or machine learning methods.

Establishment of caprine airway epithelial cells grown in an air-liquid interface system to study caprine respiratory viruses and bacteria.

Respiratory diseases negatively impact the global goat industry, but are understudied. There is a shortage of established and biological relevant in vitro or ex vivo assays to study caprine respiratory infections. Here, we describe the establishment of an in vitro system based on well-differentiated caprine airway epithelial cell (AEC) cultures grown under air liquid interface conditions as an experimental platform to study caprine respiratory pathogens. The functional differentiation of the AEC cultures was monitored and confirmed by light and immunofluorescence microscopy, scanning electron microscopy and examination of histological sections. We validated the functionality of the platform by studying Influenza D Virus (IDV) infection and Mycoplasma mycoides subsp. capri (Mmc) colonization over 5 days, including monitoring of infectious agents by titration and qPCR as well as colour changing units, respectively. The inoculation of caprine AEC cultures with IDV showed that efficient viral replication takes place, and revealed that IDV has a marked cell tropism for ciliated cells. Furthermore, AEC cultures were successfully infected with Mmc using a multiplicity of infection of 0.1 and colonization was monitored over several days. Altogether, these results demonstrate that our newly-established caprine AEC cultures can be used to investigate host-pathogen interactions of caprine respiratory pathogens.

Multilocus sequence typing of pathogenic Mycoplasma mycoides subsp. capri reveals the predominance of a novel clonal complex among isolates from goats in India.

Mycoplasma mycoides subsp. capri (Mmc) typically causes pneumonia, mastitis, arthritis, keratitis and septicaemia in goats. Mortality associated with Mmc in goat flocks is lower compared to Mycoplasma capricolum subsp. capripneumoniae-associated respiratory infections. Case fatality rates associated with Mmc ranged from 9.8 to 26.8% among several states in India. Molecular epidemiology approaches aimed at genotyping help to identify the diversity of isolates involved in a disease. Ten clinical pathogenic Mmc isolates were analysed by multilocus sequence typing (MLST) for studying genotypic relationships with 50 isolates available from public databases. The MLST analysis indicates high genetic diversity among Mmc isolates. From a total number of 60 isolates, 43 six sequence types (STs) were recognized comprising of six STs from India and 37 STs from other geographical regions. MLST profiles of isolates revealed none of the STs observed in Indian isolates were shared with global isolates. Some of the STs representing Indian isolates (four STs) were clustered into a novel clonal complex 1 (CC1). Maintenance of genetically related STs forming CCs among the goat population in India for longer periods indicates disease causing potentiality of these isolates. Based on various recombination analysis, weak clonal relationship among Mmc isolates were identified. The present study has enlightened further steps in disease investigations and to design future control measures by employing prevalent genotypes as vaccine candidates against Mmc infections.