Computer modeling of new drugs

Automatic Summary

Computer Discovery of Novel Drugs: Paving the Future of the Pharmaceutical Industry

Good afternoon, I'm Hannah Karanka, and I'm thrilled to unveil our latest advancements in computer-aided drug discovery. This cutting-edge technology has the potential to revolutionize the drug design market and accelerate the development of innovative treatments.

Global Drug Discovery Service Market Outlook

A recent study predicts that the global drug discovery service market is set to soar to $21 billion by 2025, from $11.1 billion in 2020 – that's a compound annual growth rate (CAGR) of 14%. This surge in growth is largely attributed to increasing investment in the biopharmaceutical industry, growing demand for analytical testing and clinical trials, and a heightened focus on researching rare diseases.

To meet these demands, we've assembled a highly skilled team of professionals spanning various scientific disciplines, including chemistry, computer science, biology, mathematics, and physics.

Our Team's Expertise

Our multidisciplinary team is adept at using molecular modeling tools such as molecular docking and molecular searching. In recent years, we have identified several potential HIV inhibitors, as well as small drug compounds that could inhibit SARS-CoV-2 – the virus that causes COVID-19.

Success in COVID-19 Research

Our initial findings on COVID-19 were published in the highly-regarded Journal of Pharmacometrics and Computational Biology. Impressively, our study was cited over 2000 times and downloaded more than 600 times.

Our Work Process: A Glimpse at the Future of Drug Discovery

Our work is a systematic, tiered process:

  • Constructing a pharmacological model and executing a virtual screening
  • Sorting identified compounds efficiently using molecular docking tools
  • Generating more potential active compounds using the results as a training data set for our neural network
  • Evaluating top compounds using molecular dynamics and quantum chemistry tools

The Results

The end product of our work is a list of potential inhibitors to certain biological targets, ready to be synthesized and tested. What makes our approach unique is our reliance on neural network technology at each step of the process. Compared to classical methods, our approach is more cost-effective and expedient, proving to be at least two times faster and six times cheaper.

We're open to pursuing joint research and project collaboration, joint publications in international journals, and joint patents.

Our Offer

We're equipped to manage the full cycle of computer drug discovery, as well as offer specialized expertise in specific methods. Any diseases for which the biological trigger is on the Protein Data Bank are within our reach. In turn, we can provide lists of potential inhibitors to certain biological targets, producing ready-to-test drug candidates.

If you have any questions or would like further information, please don't hesitate to get in contact via email or LinkedIn, or visit our website. Your input and inquiries are much appreciated. Thank you!


Video Transcription

So good afternoon everyone. My name is Hannah Karanka. And today I would like to present to you in my project computer discovery of novel drugs. The technologies use it as a project are progressive and use it worldwide. Recent research showed the drug design market is activity development.

The global drug discovery service market size is projected to reach $21 billion by 2025 by 11 and $1 billion in 2020 cigr of 14% during the forecast period. Growing area expenditure in the pharmaceutical and biopharmaceutical industry. This necessitates an increasing demand of certain analysis, test and clinical trial diseases. Initiatives for research on rare diseases are often drugs and focus on the drug discovery are driving the growth of the global drug discovery market. There is the industry growing in biology, patent experience and image and economics is expected to provide a wide range of growth opportunity to players in the market. Uh As you can see, I and my team are professional from various benches of science such as the chemistry, computer science, biology, mathematics and physics. That is why we are capable of working this multidisciplinary projects such as computer added drug design. Our team has extensive experience in using such molecular modeling tools as molecular docking molecular for searching and so on. In recent years, our team has identified a series of no HIV and inhibitors K foods mimicking HIV neti antibodies. Number of bits are built to resin as potential inhibitors and so on. Moreover, recently, we have discovered small drugs compound as potential incubators of SARS COV two main projects.

What is the more important we develop a future of approach in order to identify potential featured incubators to new biological target. We already had a successful project with the Fudan University joint developing initiatives and the Academy of Science. Our key publications were published in high cited international journals.

The first results of our work on COVID-19 issue were published in the journal of the from Metics and Computing Biology. This impact factor higher than three. This is the present day. The article issued about more than 2000 times and downloaded more than 600 times. We consider presentation and popularization of our result is an extremely important part of our work. Our team members actively participated in the conference and scientific competition. This drives and maintain of our competence of international level as a result. Our team is among the finals of the International JD COVID-19 challenge and the final I expected in August. So here I would like to tell you about our main work scheme on the first step which is the target is that to reconstruct the pharmaco model and carry out virtual screening on the basis of it. Then we sort identified compounds in the order then efficiently by the means of molecular dogging tools. On the next step, we obtain result as a teaching data set for our neural network and generate more potential active compounds. The last step in the evaluation of the best compounds is molecular dynamics as well as quantum chemistry tools. Since that method gives the most reliable results. Additionally, they provide a comprehensive description of binding prophy and under met properties for the best compounds in a night show.

The result of our work is a list of potential incubators to the certain biological target that are to be synthesized and tested extremely accompanied with a detailed information about their activity. I have to tell that nowadays we can use as a neural network on all steps uh which you can see from our area. The green part is that what we are doing. The um the blue part is what we expect since our approach is a theoretical, one is at much less cost and time demanding at least two times faster and six times cheaper in comprehension to the classical approach. As you can see from the table of the slide, every step of which structure to discovery is significantly accelerated by the needs of molecular model and common fors uh the type of cooper operation. What we are looking for is a join research and project joint publication, international journal and join patent. So what we can offer, they offer a full cycle of computer drug discovery cycle as well as some particular expertise in any of the film methods. Above of any diseases for the biological trigger is no longer posted in the protein data bank to sum up as a result of our work is a lead of potential individuals to certain biological targets.

This is the drug candidates are ready for laboratory expertise for the future in individual and invivo modification. So thank you for your attention. We'll be glad to listen and to get your questions here or by mail link it in or if you would like to visit our website.