You are here

PhD position available in the Biochemistry Group

Top Stories

Seminar Announcement

Please join us on Friday, October 13th, at 1:05 pm, as we continue our series of research seminars this semester.

Read More ➝

Seminar Announcement

Please join us this Friday, October 1st, at 1:05 PM (Montgomery 103) as Dr.

Read More ➝

Seminar Announcement

Please join us this Friday, September 17th, at 1:05 PM (Montgomery 103) as Dr.

Read More ➝

One Open Ph.D. Studentship at University of Louisiana at Lafayette, USA (duration four to five years)

Job description:

Research project: development of a new algorithm for studying drug and target interactions.

Objectives:

Protein and drug 3-D structures play a pivotal role in drug design and discovery. Our project adds to the existing knowledge base with a new TSR (Triangular Spatial Relationship)-based representation of protein 3-D structures using Cα atoms. Triangles are constructed with the Cα atoms of a protein as vertices. Every triangle is represented by an integer, which we denote as "key". A key is computed using the length, angle and vertex labels based on a rule-based formula, which ensures assignment of the same key to identical TSRs across proteins (https://www.frontiersin.org/articles/10.3389/fchem.2020.602291/full, https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.26215, https://www.sciencedirect.com/science/article/pii/S1476927121000463). Since the keys are constructed among three residues, they are considered inter-residue keys. Our results clearly demonstrate successful clustering of proteins that matches their functional classifications in most cases and successful identification of known and new structural motifs. Although we have been successful using Cα, two facts inspired us to continue developing intra-residue keys to represent structures of side chains. The first fact, which emerged when we studied triad of serine proteases, is that we found a key that represents two different triads of chymotrypsin. However, only one of them is the true triad, when the interactions between the side chains are considered. The second fact is that drugs often have close interactions with side chains of proteins. Thus, the overall objectives of this project are to develop an effective method for representing 3-D structures of proteins and drugs that is customized for the study of drug and protein interactions. The ways to represent protein and drug structures, and to predict drug and protein interactions, are innovative. We have made our computational tools available for the scientific community and will continue to do so. The central hypothesis is that complex 3-D structures can be divided into a set of triangles, the simplest primitives to capture the shape. Each triangle is converted to an integer that uniquely captures its essential characteristics. It means that a 3-D structure can be represented by a multiset of integers. The rationale of this proposal is derived from the results of our studies that used inter-residue keys to obtain TSR-based representation of protein structures. The method built based on this TSR idea has important advantages over the existing methods. Five specific Aims will be pursued: development of TSR-based key representation of amino acids and corresponding representation mechanism for drugs, integration of inter- and intra-residue keys for identifying drug-binding sites, predicting drug – target interactions, and integration of computational calculations with experimental data. The proposed research is funded by NIH and will have significant impacts on research in the fields of comparing protein 3-D structures and accelerating drug development for pharmaceutical industries.

Requirements:

I am looking for talented, creative and highly motivated students. A suitable background for this open position must have BS or MS (preferred) degree in computer science or bioinformatics or cheminformatics. Fluent written and spoken English and solid programming (C/C++/Python/R/Matlab) skills are required. Excellent skills in statistics, applied mathematics and data science are essential. Skills in computational chemistry/biology are acknowledged. If English is not native language, TOEFL is required (http://gradschool.louisiana.edu/node/103). The candidate must take GRE and meet the requirement of the Graduate School (http://gradschool.louisiana.edu/node/101). The recruited candidate is expected to enroll as a Ph.D. student at University of Louisiana at Lafayette.

Support:

The accepted students will receive stipend and full tuition support.

Expected starting date:

The expected start date is January 2022 or as mutually agreed upon by both parties.

For further information, please contact:

Dr. Wu Xu
Professor of Biochemistry
Department of Chemistry
Telephone: 337-482-5684
Email: wxx6941@louisiana.edu

How to Apply:
Applications must be submitted via electronic application system through the graduate school website (http://gradschool.louisiana.edu/node/87). You are encouraged to contact Dr. Xu before you submit your application.

SHARE THIS |