Argument against “DIY computational drug-discovery” trend in Bangladesh

I’m seeing a trend that bioscience students from Bangladesh (South Asia in general) are increasingly interested in publishing papers on computational drug design. Many bright students, undergrad or freshly graduated, are actually publishing drug designing related papers in good journals.

I have also done similar projects. But now, I think it is a bad trend.

While it is completely sound to do computational simulations for drug discovery, however, most of the published articles I’m seeing seem to motivated to get a “publication”, with a hope that these “publication” will help to get opportunities for higher studies abroad.

It is understandable that since our universities in Bangladesh do not provide enough good opportunities to have research experience under supervision of good mentor, many bright students are leaning to jump in such “do it yourself drug design and publish it” endeavors.

I have few arguments to make against this trend.

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What is the alternative to the ‘junk DNA’ hypothesis?

After completing the human genome sequencing in the 2000s, much of our DNA, even more than half, was considered unnecessary. It was called “junk DNA,” “broken genes” trapped in the genome’s prison, and the DNA fossils of viruses that have been silenced. It was thought these destroyed DNA elements had no purpose and were unrelated to changes.

However, in the past decade, research has shown that some of this “junk DNA” is not entirely useless. Compared to the entire genome, the amount of functional genes is minimal, only 2 percent, which can produce various proteins. It is now known that certain so-called “non-coding” DNA helps regulate the expression of different genes. However, whether these DNA controllers are essential or potentially harmful to the body is still debated among scientists.

In 2013, research from the ENCODE project revealed that non-coding DNA, which was previously considered junk, actually performs important functions, leading to controversy and discussions. Since then, there has been further research on non-coding DNA. In this article, we will learn about some of the new research that does not support the concept of “junk DNA.”

Junk DNA can be essential in mammalian development

Researchers from the University of California, Berkeley, and Washington University have worked on the transposons. Transposons involves the selfish DNA elements that integrate into various parts of the genome. A specific family of transposons is derived from the DNA of different ancient viruses. When these viruses infect a host, their DNA elements become integrated into the genome of certain individuals. During the long evolution of the host’s genome and the viral genome, these “foreign” elements underwent evolution as transposons. This research suggests that transposons from viruses are inevitable for the survival of certain hosts. When researchers removed these transpositions from the genomes of mice, more than half of them died before birth.

Figure: Only 1.5-2% of human genome are protein coding genes. So what are the rest?

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Clad-shift consistency of Dengue in Bangladesh

Last year I collaborated with cross-institution researchers from Bangladesh led by BCSIR on the severe Dengue outbreak in 2021. The study has been published in the BMC Virology Journal recently.

Dengue remains a dangerous endemic disease causing many deaths and suffering in Bangladesh.

My contribution was to analyze the phylodynamics of the Dengue virus (DENV). The DENV3 serotype dominated the 2021 outbreak. We confirmed a previously reported genotype shift (DENV3-II to DENV3-I).

Right after the 2006–2009 DENV3 outbreak, the genotype shift presumably happened in Bangladesh (tMRCA from genotype I DENV3 sequences from Bangladesh was 2013).

Another interesting fact. The 2021 epidemic isolates, which share strong similarities, are well separated from the 2017 epidemic isolates in Bangladesh but interleaved by two DENV3 isolates sampled in 2019. Interestingly, these two isolates, 19XN13542 and 19XN14065, were sampled in China from travelers returning from Bangladesh.

Figure: Phylodynamic analysis showed a clad shift in the DENV3 in Bangladesh. Source: Original paper.

So what is going on? A transboundary movement of the virus? Only further research can tell. But this highlights the importance of genomic surveillance for these infectious diseases.

This year’s cases are showing a high prevalence of DENV3, too (>60%) followed by the other strains, according to IEDCR.

Check out the article for detail:

Sarkar, M.M.H., Rahman, M.S., Islam, M.R. et al. Comparative phylogenetic analysis and transcriptomic profiling of Dengue (DENV-3 genotype I) outbreak in 2021 in Bangladesh. Virol J 20, 127 (2023).

How to resolve conflict in Science: On FMDV classification problem

How a scholarly conflict on FMD virus classification between Bangladeshi and Chinese research-groups was resolved.

Scientists form hypothesis, formulate experiments and publish their results. But not all researchers agree to the same conclusion. Hence, comes scientific-conflict. How to resolve that? Publish and exchange opinions!

Recently, scientific debate and exchange of opinions came to my attention. Back in Bangladesh during and after my MS study in Microbiology at the University of Dhaka, I was affiliated with Dr. M Anwar Hossain’s FMDV research project (Microbial Genetics and Bioinformatics Lab). In that project, Dr. Hossain lead the research on Foot-and-Mouth disease virus detection and vaccine development. Briefly speaking, this is a very dangerous viral disease of cattle and cause several million dollar loss in agro-veterinary economy in Bangladesh.

Figere 3 from Siddique et al. 2018 shows that proposed sub-lineage Ind2001BD1 and BD2 do not fall into established genotypes. Source:

The FMD is an RNA-virus and it evolves very fast due to higher mutational rate. Classifying newly emerged FMD virus can be a complex task. I co-authored a paper (Siddique et al. 2018) on which the research group detected two novel sub-lineage of FMDV virus, namely Ind2001BD1 and BD2. We have used distance-based clustering method (multi-dimensional clustering: novel in this field but widely used for classification) as well as more traditional phylogenetic method to establish and propose this. In this point, I should mention that there is a world reference laboratory for FMDV characterization (WRLFMD), but FMDV strains isolated by Siddique et al. 2018 did not fall into the classification maintained by them.

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