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Enzyme discovery is always a hot topic for industry and biochemists, since there is huge commercial benefit and advancement in current knowledge-base. Unlike, early days where enzyme discovery relied upon assays, now it is a bioinformatics approach to speed up the process.

Lytic polysaccharide monooxygenases (LPMO) are the latest family of enzymes that have affected the biofuel industry, specifically cellulosic bioethanol industry. These enzymes, previously thought to bind to polymers of carbohydrates, are now understood to boost the enzymatic process of degrading recalcitrant crystalline polysaccharides. LPMOs are probably one of the enzymes that bind to crystalline surfaces of polymers and thus hopefully reducing the cost and time in the pre-processing step of biomass to bioethanol conversion.

As of now, there are 4 families that CAZy identifies to consist of LPMOs (AA9, AA10, AA11, and AA13), where they are now called as Auxillary Activity enzymes. However, there is the possibility that newer families of LPMOs may exist and it depends on how or when we identify them. Voshol et al in their recent paper discuss a bionnformatics based approach and validation using expression data for discovery of novel LPMO families, and report the existence of “LPMO14” family that are active on sugars such as beat-1,3-glucans.

In short, they took 14 known LPMOs from the four families and generated a HMM profile, using which they scanned six genomes and identified 7 LPMO14 genes. They were also able to find LPMO genes in other organisms (such as Drosophila, Bivalves, corals, etc) where the function of LPMO is not known.

While, this data sounds promising, further identification and characterization using standard assays would ensure that this is indeed a new family of LPMOs. Also, the authors do not mention as to why they stuck to 14 known LPMO structures to generate the HMM profile, while there are nearly 50 structures currently deposited in PDB.

Reference: G. Voshol, E. Vijgenboom and P. Punt, “The discovery of novel LPMO families with a new Hidden Markov model“, BMC Research Notes, vol. 10, no. 1, 2017.

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The area of protein-protein interactions (PPI) is always exciting as proteins can be either monogamous or promiscuous with their interaction partners. Also, a hot topic these days in computational biology is multiscale modelling. It refers to the method of analyzing a system from atomistic and at a global scale and other scales, in between. Few years ago, a new method of co-evolutionary analysis of residues made news and has been used for gaining insights in other systems. Read the blog by Bosco Ho about the groundbreaking work here about Direct Coupling Analysis (DCA).

1dfj_RNAseInhibitor-RNAse_complex

Example of a protein-protein interaction. By Dcrjsr – Own work, CC BY 3.0, https://commons.wikimedia.org/w/index.php?curid=10510713

So, when two orthogonal approaches are used to understand a PPI system, it obviously becomes an interesting work. A recent paper in eLife reports exactly that. Malinverni et al report the use of coarse-grained simulation coupled with atomistic molecular dynamics simulation and data from DCA to identify the evolutionarily conserved residues that cause the specific interaction between Hsp70 and Hsp40.

ResearchBlogging.orgAs these two proteins are part of the chaperone machinery, any insight on the Hsp70’s ability to bind to proteins along with Hsp40 is crucial to understand the short-lived interaction. As mentioned in the article, vast amount of data (in terms of NMR, mutagenesis, etc.) is present that can be incorporated in this multiscale modelling.

The impact of the predicted interaction model is not only statistically significant, but also correlates well with the known experimental data.

Malinverni D, Jost Lopez A, De Los Rios P, Hummer G, Barducci A: Modeling Hsp70/Hsp40 interaction by multi-scale molecular simulations and coevolutionary sequence analysis. eLife 2017, 6. DOI: https://doi.org/10.7554/eLife.23471

PDB_2fft_EBI.jpg

Cartoon representation of the molecular structure of protein registered with 2fft code. By Jawahar Swaminathan and MSD staff at the European Bioinformatics Institute – Public Domain, https://commons.wikimedia.org/w/index.php?curid=5877319

Intrinsically disordered proteins are thought to be fully functional, yet do not confirm to a single conformation, thereby identifying their structure via crystallography becomes problematic. Many intrinsically disordered proteins have been studied and analyzed using NMR methods, however the question as to why proteins are intrinsically disordered is still debatable.

While, viewing X-ray diffraction data some residues do not have an electron density region, thus they are marked as missing residues. These regions are highly mobile and are considered as intrinsically disordered. For some proteins, the entire sequence is considered intrinsically disordered.

ResearchBlogging.orgIt is a widely accepted fact that sequence dictates structure, and structure in turn dictates function. So, is the “disordered-ness” encoded in the genome, if so to what extent? This and related questions have led Basile et al at the Stockholm University, Sweden to delve deeper and have narrowed it down to GC content. Their work has been published in latest issue of PLoS Computational Biology.

Using computational methods they analyzed 400 eukaryotic genomes and looked into the so-called orphan genes, specifically. They categorized the age of the proteins using ProteinHistorian tool and looked into the old and young proteins. They found that the

…selective pressure to change amino acids in a protein is stronger than the one to change the GC content. At low GC ancient proteins are more disordered than expected for random sequence while at high GC they are less.

The three disorder promoting amino acids (Ala, Pro, and Gly) are high in GC content w.r.t to their codons. However,

At high GC the youngest proteins become more disordered and contain less secondary structure elements, while at low GC the reverse is observed. We show that these properties can be explained by changes in amino acid frequencies caused by the different amount of GC in different codons.

References:

  1.  Basile, W., Sachenkova, O., Light, S., & Elofsson, A. (2017). High GC content causes orphan proteins to be intrinsically disordered PLOS Computational Biology, 13 (3) DOI: 10.1371/journal.pcbi.1005375

With increasing computational power (aka GPU) that can be accessed these days, it is no wonder that performing all-atom molecular dynamics simulation for a longer time, with duplicates and/or triplicates, has become easier.

ResearchBlogging.org
Two publications report all-atom MD data that have significant implication in two diverse areas. The first one is the popular CRISPR-Cas9 system and the second one is Dengue virus.

With these data it should pave way for more insights.

CRISPR-Cas9 all atom simulation (total of 400-600ns data)
Zuo Z, & Liu J (2016). Cas9-catalyzed DNA Cleavage Generates Staggered Ends: Evidence from Molecular Dynamics Simulations. Scientific reports, 5 PMID: 27874072

Entire Dengue viral envelope complex simluation (1 microsecond data)
Marzinek JK, Holdbrook DA, Huber RG, Verma C, & Bond PJ (2016). Pushing the Envelope: Dengue Viral Membrane Coaxed into Shape by Molecular Simulations. Structure (London, England : 1993), 24 (8), 1410-20 PMID: 27396828

References:

  1. https://www.sciencedaily.com/releases/2017/01/170111131105.htm
  2. http://www.research.a-star.edu.sg/research/7645/molecular-movie-reels-viral-envelope-into-shape

Reading one paper in a decent way takes a lot of time, which I realized in the past few months where I am strapped for time! Hopefully the dry phase ends sooner.

Came across this “Science blogging” article/podcast in Nature newsletter and thought of sharing it here. Enjoy!

The challenges of science blogging for established professors and young PhD students.

Whether you’re a PhD student or an established professor, being able to communicate your research is an important part of your career development. You will, at some point, have to persuade that funding body to give you some money, or that supervisory committee to grant you that PhD. Other times, you might have to work with politicians and the media to help them access your research. All these conversations, whether oral or in writing, require good communication skills.

Many of these will be done in a written format and blogging can be a great way to practice those writing skills.

Suzi Gage is writing up her PhD thesis. Three years ago, this was a gargantuan challenge that she was unsure of how to tackle. To prepare, she started blogging. “I really feel like the blogging has helped so much. When I sit down at a blank page, I know that I can write 1000 words. They might not be good words, but I know that I can turn them into something better.” Now she’s a well-established, award-winning science blogger, writing about epidemiology on Sifting the evidence, hosted by the Guardian.

Professor Jon Butterworth is an established experimental physicist, splitting his time between the Large Hadron Collider in Geneva and teaching at UCL. He blogs at Life and physics, also hosted by the Guardian. “We wanted to share the excitement of the thing [LHC].”

Science blogging challenges for young scientists

Audience

Your audience could include fellow students, potential employers and your supervisors. Therefore, think carefully about how you portray and express yourself, “particularly if you’re blogging under your own name,” says Suzi. There is a fine line between voicing your opinion and becoming a trouble maker, so it’s worth understanding where that line is. Our advice: don’t cross it.

Evidence

“My blogs came under a lot of attention from those who disagreed with what I was saying… everything I said I had to back up,” says Suzi. This is the case for anyone who is blogging about science, really, but it’s especially true for young scientists as they don’t have a decade-long research career and reputation to back them up. Do your research, interview scientists in the field and be 100% positive that what you are saying is correct, or can be backed up if it is opinion.

Bosses

Suzi is fortunate in that she has had supportive bosses who understand and agree with what she is doing. “But I don’t take the micky,” she says. As a young scientist, your priority should be your research, so don’t let your hobby take over. Suzi suggests combining the two: if you have to read a paper for your literature review, why not write up a lay summary for it at the same time? This is a good test to see if you have really understood it: if your audiences understand what you’ve written, you’re off to a flying start.

Goals

Are your science communication efforts a hobby, or are they something more? “This is a question that might come up in a job interview,” says Jon, and one that you should be prepared to answer. If you’re interviewing for a postdoc position, make sure that your potential employer understands that this is a hobby, that you’re organised and that your blogging won’t interfere with your work. If it isn’t a hobby, and you’re considering becoming a journalist, think carefully about applying for a postdoc, it might not be the right thing for you.

Sounding boards

“Two heads are better than one.” Wise words that apply to science blogging (as well as many other things!) When you run dry on ideas, or you’re not sure if one will work, use a friend or colleague as a sounding board. They’ll be able to help you think through your ideas, or maybe even give you new ones. It’s always useful to get another set of eyes on your work, just to check for grammatical and spelling errors.

Networks

“If you don’t think you have time to do a blog entirely by yourself….” approach a network that is already on the go, says Suzi. “That’s a great way to practice writing and see if it’s the kind of thing that you want to do,” she says. Setting up a blog for your lab can also be an option. “You don’t just have to cover the science, you can also talk about the PhD life.” Some good examples are The Mental Elf (mental health research, policy and guidance), Speakers of Science (science communication), Naturejobs (science careers), Climate Snack (environmental science) and others.

Science blogging challenges for an established scientist

Audience

The audience of an established researcher will be mixed. It might include your students and others that work for you, colleagues or “directors of labs in the US and Switzerland, leaders in the field and within government departments,” says Jon. They will each be judging your written words with their role in mind. You can never keep everyone happy, but try not to upset the same group of people two posts in a row!

Impact

What you say not only affects you, but it could also impact on your colleagues, policy, funding bodies and research decisions. Consider what you write, and how you write it, very carefully. “It does cramp your style a little bit,” says Jon, but don’t let that take all the enjoyment out of it.

Trust

Maintain the trust of your colleagues. As a senior scientist, you’ll be privy to meetings and experimental results that are not to be shared with the media. So don’t share them. Simple. If you do, you’ll risk being blacklisted from those meetings. Jon, as a researcher at the LHC, was part of several meetings that discussed confidential results, and he had to make sure that his colleagues trusted him not to spill the beans. “I don’t want to be shut out of the room for those [meetings],” says Jon.

Location

Don’t write a corporate blog, that’s Jon’s advice. Jon feels that a blog is a space where you can express your own personality and views (in a sensible way). If you have to walk a corporate tight-rope, he says it might not be worth it.

Responsibility

“You have a position of influence that you have to be conscious of when you’re writing,” says Jon. Accept your responsibility as a professor and a blogger: be polite, considerate of colleagues and your science, and a nice person!

Register and join us next week for a seminar on protein design using the Biologics Suite! This seminar is free of charge and our speaker, Dr. David Pearlman, will take questions from the audience in a Q&A session.


Recent Advances in Protein Design using the Biologics Suite – Featuring BioLuminate 

Tuesday, June 24

10 am and 1 pm EDT 

Schrödinger’s structure-based design platform for biologics – the Biologics Suite, featuring BioLuminate – includes a number of important tools for modeling biologics, antibodies, and proteins. In this presentation, we discuss recent applications of the Suite to protein and antibody design, including:  

Disulfide

  • Alanine scanning to identify mutational hot spots
  • A new approach to identify residue mutations favorable for forming a cysteine disulfide
  • Dramatic success using Prime de novo loop prediction to model antibody H3 loop structures, including first-place performance in the Second Blinded Antibody Modeling Assessment (AMA-II)
  • Incorporating residue mutation affinity calculations into workflows to facilitate enzyme design

    Register

Today, I saw this blogpost by Dr.Adam Ruben in social media via a researcher. It was very funny, yet nailed the truth quite strong. Reading through the long list, I kept saying “Yes, that true!”. So, here I am sharing the list with you, those highlighted in bold are mine. Those in italics are not completely true to me. Mea Culpa! 🙂

I don’t sit at home reading journals on the weekend.

I have skipped talks at scientific conferences for social purposes.

I remember about 1% of the organic chemistry I learned in college. Multivariable calculus? Even less.

I have felt certain that the 22-year-old intern knows more about certain subjects than I do.

I have avoided eye contact with eager grad students while walking past their poster sessions.

When someone describes research as “exciting,” I often don’t agree. Interesting, maybe, but it’s a big jump from interest to excitement.

Sometimes I see sunshine on the lawn outside the lab window and realize that I’d rather be outside in the sun. [TOTALLY!!!]

I have gone home at 5 p.m.

I have asked questions at seminars not because I wanted to know the answers but because I wanted to demonstrate that I was paying attention.

I have never fabricated data or intentionally misled, but I have endeavored to present data more compellingly rather than more accurately.

I have pretended to know what I’m talking about.

I sometimes make superstitious choices but disguise them as tradition or unassailable preference.

I like the liberal arts. [No, I LOVE them!]

When a visiting scientist gives a colloquium, more often than not I don’t understand what he or she is saying. This even happens sometimes with research I really should be familiar with.

I have enjoyed the fruits of grade inflation.

I have called myself “doctor” because it sounds impressive.

I dread applying for grants. I resent the fact that scientists need to bow and scrape for funding in the first place, but even more than that, I hate seeking the balance of cherry-picked data, baseless boasts, and exaggerations of real-world applications that funding sources seem to require.

I have performed research I didn’t think was important.

In grad school, I once stopped writing in my lab notebook for a month. I told myself I could easily recreate the missing data from Post-it notes, paper scraps, and half-dry protein gels, but I never did.

I do not believe every scientific consensus.

I do not fully trust peer review.

When I ask scientists to tell me about their research, I nod and tell them it’s interesting even if I don’t understand it at all.

I never was never interested in Star Wars. [I don’t know why Scientists = Star Wars Fan!]

I have openly lamented my ignorance of certain scientific subtopics, yet I have not remedied this.

I have identified steps in lab protocols that can be optimized, yet I have not optimized them.

I have worried more about accolades than about content.

If I could hand over my lab work to a robot, I’d do it in a second. Then I’d resent having to maintain the robot.

During my graduate-board oral exam, I blanked on a question I would have found easy in high school.

I can’t name four papers my grad-school lab published, but I can describe the details of our entry every year into the Biology Department Holiday Party Dessert Competition.

I have feigned familiarity with scientific publications I haven’t read.

I have told other people my convictions, with certainty, then later reversed those convictions.

I have killed 261 lab mice, including one by accident. In doing so, I have learned nothing that would save a human life. [No, not 261. About 20 in high school.]

I can’t get excited about the research to which some of my friends and colleagues have devoted their lives.

I can’t read most scientific papers unless I devote my full attention, usually with a browser window open to look up terms on Wikipedia.

I allow the Internet to distract me.

I have read multiple Michael Crichton novels.

I have taken food from events I did not attend and mooched swag from vendors I did not talk to.

I have used big science words to sound important to colleagues.

I have used big science words to sound important to students.

I have used big science words to sound important to my 3-year-old daughter.

I sometimes avoid foods containing ingredients science has proved harmless, just because the label for an alternative has a drawing of a tree.

I have miserably failed exams in the exact field I chose to study.

I own large science textbooks I have scarcely used. I have kept them “for reference” even though I know I’ll never use them again. I intend to keep them “for reference” until I die.

I have abandoned experiments because they did not yield results right away.

I own no wacky science ties.

I want everyone to like me.

I have known professors who celebrate milestone birthdays by organizing daylong seminars about their field of study. To me, no way of spending a birthday sounds less appealing.

Sometimes science feels like it’s made of the same politics, pettiness, and ridiculousness that underlie any other job. [Absolutely!]

I decry the portrayal of scientists in films, then pay money to go see more films with scientists in them.

I have worked as a teaching assistant for classes in which I did not understand the material.

I have taught facts and techniques to students that I only myself learned the day before.

I find science difficult.

I have delusions that people will read this confession and applaud my bravery for identifying a universal fear.

I am afraid that people will read this confession and angrily oust me from science, which I love. [Yes, Maybe.]

27 confessions!!!! So, what about you? 🙂